# Recent Advances in Cotton Genomics

Authors: Hong-Bin Zhang; Yaning Li; Baohua Wang; Peng W. Chee
Journal: International Journal of Plant Genomics
 (2008)

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## Abstract

Genome research promises to promote continued and enhanced plant genetic improvement. As a world's leading crop and a model system for studies of many biological processes, genomics research of cottons has advanced rapidly in the past few years. This article presents a comprehensive review on the recent advances of cotton genomics research. The reviewed areas include DNA markers, genetic maps, mapped genes and QTLs, ESTs, microarrays, gene expression profiling, BAC and BIBAC libraries, physical mapping, genome sequencing, and applications of genomic tools in cotton breeding. Analysis of the current status of each of the genome research areas suggests that the areas of physical mapping, QTL fine mapping, genome sequencing, nonfiber and nonovule EST development, gene expression profiling, and association studies between gene expression and fiber trait performance should be emphasized currently and in near future to accelerate utilization of the genomics research achievements for enhancing cotton genetic improvement.


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## Body

## 1. Introduction

Cottons (Gossypium spp.)  belong to the genus Gossypium of the family Malvaceae. Gossypium consists of 45–50
species, with 40–45 being diploids (2n=26) and 5 being allotetraploids (2n=52). The species are grouped into eight genome groups, designated A through G
and K, on the basis of chromosome pairing affinities [1]. At the tetraploid level, there are five
species, designated (AD)1 through (AD)5 for their genome
constitutions. Phylogenetic analyses clustered the diploid species of Gossypium into two major lineages,
including the 13 D-genome species lineage and the 30∼32 A-, B-, E-, F-, C-, G-, and K-genome species lineage, and the polyploid species into one
lineage, that is, the 5 AD-genome species lineage (Figure 1; [2]).Figure 1
Phylogeny and evolution ofGossypium species. The phylogenetic data is from Wendel and Cronn
[2], the genome sizes are from Hendrix and Stewart [3], and genomic designations follow Endrizzi et al. [4] and Percival [5]. The species in bold face are
cultivated. MYA: million years ago.Of theGossypium species, four are cultivated in agriculture, including two allotetraploids (G.
hirsutum and G. barbadense) and two diploids (G. herbaceum and G. arboreum). Gossypium hirsutum, also known as Upland cotton, Long Staple Cotton, or Mexican Cotton,
produces over 90% of the world’s cotton; G. barbadense, also known as Sea Island Cotton, Extra Long Staple Cotton, American Pima,
or Egyptian Cotton, contributes
8% of the world’s cotton; and G. herbaceum, also known as Levant Cotton,
and G. arboreum, also
known as Tree Cotton, together provide 2% of the world’s cotton.Cottons are not only a world’s leading textile fiber and
oilseed crop, but also a crop that is of significance for foil energy and
bioengergy production.  Although cottons
are native to tropics and subtropics naturally, including the Americas, Africa
and Asia, they are cultivated in nearly 100 countries. India, China, USA, and
Pakistan are the top four cotton growing countries, accounting for
approximately 2/3 of the world’s cotton (http://www.ers.usda.gov/Briefing/Cotton/trade.htm).
According to the Food and Agriculture Organization (FAO) of the United Nations
(http://www.fao.org),
the cotton planting area reached about 35 million hectares and the total
world’s cotton production had a record of about 23 million metric tones in
2004/2005. Cotton products include fibers and seeds that have a variety of
uses. Cotton fibers sustain one of the world’s largest industries, the textile
industry, for wearing apparel, home furnishings, and medical supplies, whereas
cottonseeds are widely used for food oil, animal feeds, and industrial
materials (such as soap). Cottonseed oil is ranked fifth in production and
consumption volume among all vegetable oils in the past decades, accounting for
8% of the world’s vegetable oil consumption. The business stimulated by cotton
is hundreds of billion dollars in the world. In the USA alone, for instance,
the annual cotton business revenue exceeds $120 billion (Agricultural
Statistics Board 1999; National Cotton Council of America, http://www.cotton.org/news/releases/2003/cotton-trade.cfm).
Moreover, nearly a billion barrels of petroleum worldwide are used in every
year to synthesize artificial “synthetic” fibers. Further improvement of cotton
fibers in yield and quality will replace or significantly reduce the
consumption of fossil oil for synthetic fiber production, thus being saved for
energy production. Finally, cottonseed oil, the main by-product of cotton fiber
production, could be potentially used as biofuel.In
addition to their economic importance, cottons are an excellent model system
for several important biological studies,
including plant genome size evolution, plant polyploidization and single-celled
biological processes. The genomes of angiosperm plants vary over
1000 folds in size, ranging from 100 to>100,000 Mb/1C (haploid) [6]. It has long been recognized that polyploidy is a
common, prominent, ongoing, and dynamic process of genome organization,
function diversification, and evolution in angiosperms [7]. The genomes of most angiosperms are thought to have incurred one or more
polyploidization events during evolution [8]. Studies have
demonstrated that genome doubling has also been significant in the evolutionary
history of all vertebrates and in many other eukaryotes [9–12]. It is estimated
that about 70% of the flowering plant species are polyploids. For instance, of
the world-leading field, forage, horticultural, and environmental crops, many
are contributed by polyploid species, such as cotton, wheat, soybean, potatoes,
canola, sugarcane, Brassica, oats,
peanut, tobacco, rose, coffee, and banana. Therefore, studies of both genome size evolution and polyploidization have
long attracted the interests of scientists in different disciplines.
Nevertheless, much remains to be learned. Examples include impacts of
polyploidization on genome size, genome organization, gene duplication and
function, and gene family evolution; the role of transposable elements in
structural and regulatory gene evolution and gene functions; and mechanisms and
functional significance of rapid genome changes.Cottons have several advantages over other polyploid
complexes for plant genome size and polyploidization studies. First, the genome
sizes of 37 of the 45∼50 Gossypium species, including all eight genomes and polyploidy species, have been
determined and shown to vary extremely significantly ([3];
Figure 1). At the diploid level, the genome sizes vary by three folds, ranging
from 885 Mb/1C in the D-genome species to 2,572 Mb/1C in the K-genome species.
Within each lineage, the genome sizes vary most in the A+F+B+E+C+G+K lineage,
ranging from 1,311 to 2,778 Mb/1C with a difference of 1,467 Mb (110.2%);
second in the D-genome lineage, ranging from 841 to 934 Mb/1C with a difference
of 93 Mb (10.5%); and least in the polyploidy lineage, ranging from 2,347 to
2,489 Mb/1C with a difference of 142 Mb (5.9%). Variations were also observed
within a species.  For instance, within
G. hirsutum, the variation (n=5) was from 2,347 to
2,489 Mb/1C, differing by 142 Mb (5.9%) while within G. arboreum, the variation (n=5) was from
1,677 to 1,746 Mb/1C, differing by 69 Mb (4.0%).Second, the evolutionary history of the allotetraploid
species ofGossypium has been
established (Figure 1),
especially for the two cultivated AD-genome cottons, G. hirsutum and G.
barbadense, and their closely related diploid progenitors, G. herbaceum (A1), G. arboreum (A2), G. raimondii (D5),
and G. gossypioides (D6). The A-genome species are
African-Asian in origin, whereas the D-genome species are endemic to the New
World subtropics, primarily Mexico. Following the transoceanic
dispersal of an A-genome taxon to the New World, hybridization between the
immigrant A-genome taxon and a local D-genome taxon led to the origin and
evolution of the New World allopolyploids (AD-genome) [13, 14]. Subsequent to
the polyploidization event, the allopolyploids radiated into three sublineages
[15], among which
included are the world’s commercially most important species, G. hirsutum and G. barbadense. Studies showed that the A subgenome of the AD-genome-cultivated
cottons is the most closely related to the genome of the extant diploid G.
herbaceum (A1) [16]; the D subgenome of the AD-genome-cultivated cottons is the most
closely related to the genome of the extant diploid, G. raimondii (D5)
or G. gossypioides (D6) [13]; and the cytoplasm of the AD-genome-cultivated cottons
is the most closely related to that of the extant diploids G. herbaceum (A1) and G. arboreum (A2) [14, 17]. Sequence analysis and
paleontological record suggest that the A-genome and the D-genome groups
diverged from a common ancestor 5–10 million years ago, and that the two
diverged diploid genomes became reunited in a common nucleus to form the
polyploid cottons, via allopolyploidization, in the mid-Pleistocene, or 1-2 million years ago [14, 15, 18, 19].Finally, as in the wheat polyploid complex, cottons have a
long history of research at the cytological level. A wealth of cytogenetic
stocks has been developed, including artificially synthesized AD-genome
polyploids between the A-genome and D-genome diploid species [20] as
well as individual chromosome addition and substitution lines [21].
These cytogenetic stocks are unique and valuable not only for cotton genetics
research, but also for deciphering the ramifications of polyploidization on
genome organization, function, and evolution.Cotton fiber is an excellent single-celled model
system for studies of many single-celled biological processes, particularly
cell expansion and cellulose biosynthesis. Cotton fibers are unicellular,
unbranched, simple trichomes that differentiate from the protoderm of developing
seeds. There are probably over one-half million quasi-synchronously elongating
fibers in each boll or ovary. Although all plant cells extend to some degree
during development and differentiation, cotton fibers can reach up to 5.0 cm in
length in some genotypes, being among the longest cells. Therefore, they offer
a unique opportunity to study cell expansion at the single cell level.  Cellulose is a major component of the cell
walls of all higher plants, constituting perhaps the largest component of plant
biomass, with an estimated annual world production of 100 million metric tons.
The fiber cell wall of cottons consists of>90% cellulose. Therefore,
cotton fiber cells have long been used as a model system to study cellulose
biosynthesis [22] that is the basis for biomass-based
bioenergy production.


## 2. Advances in Cotton Genomics Research

Genome research has
been demonstrated to be promising for continued and enhanced crop plant genetic
improvement. Therefore, efforts have been made in cotton genome research,
especially development of genomic resources and tools for basic and applied
genetics, genomics, and breeding research. These resources and tools include
different types of DNA markers such as restriction fragment length polymorphism
(RFLP), randomly amplified polymorphic DNA (RAPD), amplified fragment length
polymorphism (AFLP), resistance gene analogs (RGA), sequence-related amplified
polymorphism (SRAP), simple sequence repeat (SSR) or microsatellites, DNA
marker-based genetic linkage maps, QTLs and genes for the traits important to
agriculture, expressed sequence tags (ESTs), arrayed large-insert bacterial
artificial chromosome (BAC) and plant-transformation-competent binary BAC
(BIBAC) libraries, and genome-wide, cDNA-, or unigene EST-based microarrays.
Efforts are also being made to develop the genome-wide, BAC/BIBAC-based
integrated physical and genetic maps, and sequence the genomes of the key
cotton species. However, compared with other major crops, such as rice, maize,
and soybean, the genome research of cottons is far behind, mainly due to the
limited funds allocated to the species. Summarized below are the major advances
achieved recently in cotton genomics research.


### 2.1. DNA Markers and Molecular Linkage Maps

Genetic maps constructed in theGossypium species and the types of
markers used are listed in Table 1. As in most plant species, the early
application of DNA markers in cotton genomic research has been in the form of
RFLPs. It is, therefore, not surprising that the first molecular linkage map of
the Gossypium species was constructed
from an interspecific G. hirsutum×G. barbadense F2 population
based on RFLPs [23]. The map contained 705 loci that were assembled into 41 linkage groups and
spanned 4,675 cM. This map later was further advanced by Rong et al. [24] that comprised 2,584 loci
at 1.74-cM intervals and covered all 13 homeologous chromosomes of the
allotetraploid cottons, representing the most complete genetic map of the Gossypium to date. Many of the DNA
probes of the map were also mapped in crosses of the D-genome diploid species G. trilobum×G. raimondii [24] and the A-genome diploid species G.
arboreum×G. herbaceum [16]. Detailed comparative
analysis of the relationship of gene orders between the tetraploid
AD-subgenomes with the maps of the A and D diploid genomes has revealed
intriguing insights on the organization, transmission and evolution of the Gossypium genomes.Table 1
Genetic maps constructed forGossypium species.
Marker typeTotal lociMap distancePopulation(a)Cross type(b)ReferencesAFLP176773 cMF2GN × GAU[26]AFLP213931 cMF2GN × GAU[26]AFLP, SSR, and RFLP3923,287 cMF2GH × GB[27]AFLP, SSR, and RFLP8884,400 cMBC1GH × GB[28]AFLP, SSR, and RFLP1,1605,519 cMBC1GH × GB[29]RFLP2751,147 cMF2GAR × GHE[16]RFLP2841,503 cMF2 and F3GH × GH[30]RFLP5894,259 cMF2GH × GTO[31]RFLP7054,675 cMF2GH × GB[23]RFLP7631,493 cMF2GT × GR[24]RFLP2,5844,448 cMF2GH × GB[24]RFLP and RAPD3554,766 cMF2GH × GB[25]SRAP2373,031 cMF2GH × GB[32]SRAP, SSR, and RAPD5665,142 cMF2GH × GB[33]SRAP, SSR, RAPD, and REMAP1,0295,472 cMF2GH × GB[34]SSR1931,277 cMRILGH × GB[35]SSR4332,126 cMRILGH × GB[36]SSR4424,331 cMBC1GH × GB[37]SSR4443,263 cMDHGH × GB[37]SSR6245,644 cMBC1GH × GB[38]SSR9075,060 cMBC1GH × GB[39]SSR1,7903,426 cMBC1GH × GB[40]SSR and RAPD4893,315 cMDHGH × GB[41](a) RIL = recombinant inbred line, and DH = doubled haploid.(b) GH = G. hirsutum, GB = G. barbadense, GTO = G. tomentosum, GR = G. raimondii, GAR = G. arboretum, GHE = G. herbaceum,
GN = G. nelsonii, and GAU = G. australe.Because RFLPs are labor-intensive and require large
amounts of DNA, tedious blot hybridization and autoradiographic methods,
polymerase chain reaction (PCR)-based DNA marker methods have come into vogue.
Several types of PCR-based DNA markers have been utilized in cotton genome
research. Methods, such as RAPD, AFLP, RGA, and SRAP, offer an excellent
opportunity to scan enormous numbers of DNA loci rapidly, often targeting the
DNA elements that are rapidly-evolving and therefore, are more likely to
contain loci differing among genotypes. Kohel et al. [25] constructed a genetic map based on a population
derived from an interspecific cross between Texas Marker-1 (TM-1) (G. hirsutum) and 3–79 (G. barbadense) in which a total of 355
DNA markers (216 RFLPs and 139 RAPDs) were assembled into 50 linkage groups,
covering 4,766 cM. Brubaker and Brown [26] presented the first AFLP genetic
linkage map for the Gossypium G-genome
that was constructed from an interspecific G.
nelsonii×G. australe population. The AFLP genetic linkage maps were used to identify G-genome
chromosome-specific molecular markers, which, in turn, were used to track the
fidelity and frequency of G. australe chromosome transmission in a G. hirsutum×G. australe hexaploid bridging
family.Advent of SSR or
microsatellite markers has brought a new, user-friendly, and highly polymorphic
class of genetic markers for cotton. The latter feature is especially useful to
the cultivated Upland cotton due to its low intraspecific polymorphism. SSRs
are PCR-based markers, usually codominant, well dispersed throughout the
genome, easily shared between labs via flanking primer sequences, and well
portable from one population to another [84]. Reddy et al. [85] suggested that the total pool of SSRs present in the cotton genome is
sufficiently abundant to satisfy the requirements of extensive genome mapping
and marker-assisted selection (MAS). Liu et al. [86] reported the assignment of SSRs to cotton chromosomes by making
use of aneuploid stocks. SSRs have been widely employed in genetic diversity
analyses of cotton [87–90] and several genetic linkage maps
based mostly on SSRs have now been developed [37–41].Several methods
have been pursued to develop SSR markers in cottons, including analysis of
SSR-enriched small-insert genomic DNA libraries [29, 85, 86, 91], SSR mining from ESTs (see
below; [35, 38, 39, 92], and large-insert BAC derivation by end sequence
analysis [36]
or SSR-containing BAC subcloning as described by Lichtenzveig et al. [93]. Currently, a total of
approximately 5,484 SSRs have been developed in cotton ([94]; http://www.cottonmarker.org).The development of
a large number of ESTs (see below) provides a good source of PCR-based primers
for targeting SSRs [92, 95, 96]. Taliercio et al. [97] sequenced ESTs
representing a variety of tissues and treatments with SSRs identified among the
ESTs. Their results indicated that these SSRs could potentially map the genes
represented by the ESTs. Guo et al. [98] examined the transferability of 207 G.
arboreum-derived EST-SSR primer pairs among 25 different diploid accessions
from 23 species representing 7 Gossypium genomes. Their results demonstrated that the transferability of EST-SSR markers
among these diploid species could assist the introgression of genes into
cultivated cotton species especially by molecular tagging of the important
genes existing in these diploid species. Guo et al. [40] also developed 2,218 EST-SSRs, with 1,554 from G. raimondii-derived ESTs and 754 from G. hirsutum-derived ESTs. By integrating
these new EST-SSRs to enhance the genetic map constructed by Han et al. [39], the present SSR-based
genetic map consists of 1,790 loci in 26 linkage groups and covers 3,425.8 cM
with an average distance between markers of 1.91 cM. This SSR-based high-density
map contains 71.96% functional marker loci, of which 87.11% are EST-SSR loci.DNA sequences
derived from clone end sequencing of BAC libraries provide yet another resource
for SSR marker development. In addition to the uses as genetic markers, SSRs
developed from BAC-end sequences provide the possibility to efficiently
integrate the genetic and physical maps of cotton. Frelichowski et al. [36] developed 1,316 PCR primer
pairs to flank SSR motif sequences from 2,603 new BAC-end genomic sequences
developed from G. hirsutum Acala
“Maxxa.” An interspecific recombinant inbred population was used to map 433
marker loci in 46 linkage groups with a total genetic distance of 2,126.3 cM
and an average distance between loci of 4.9 cM which covered approximately 45%
of the cotton genome.To overcome the paucity of a
particular type of DNA markers, genetic maps were developed by incorporating
different classes of markers. For example, Lacape et al. [28] constructed a combined RFLP-SSR-AFLP map based on an
interspecific G. hirsutum×G. barbadense backcross population of 75
BC1 plants. The map consists of 888 loci that ordered into 37
linkage groups and spanning 4,400 cM. This map was updated, mostly with new SSR
markers, to contain 1,160 loci that spanned 5,519 cM with an average distance
between loci of 4.8 cM [29]. Mei et al. [27] developed a genetic map using an interspecific G. hirsutum and G. barbadense F2 population that contained 392 genetic
loci, including AFLPs, SSRs, and RFLPs, and mapped into 42 linkage groups that
spanned 3,287 cM, thus covering approximately 70% of the cotton genome. Lin et al. [33] constructed a linkage map of tetraploid cotton using SRAPs, SSRs,
and RAPDs to screen an interspecific G.
hirsutum×G. barbadense F2 population.
A total of 566 loci were assembled into 41 linkages that covered 5,141.8 cM
with a mean interlocus space of 9.08 cM. He et al. [34] constructed a more detailed
cotton map with this same F2 population [33] using SSRs, SRAP, RAPD, and
retrotransposon-microsatellite amplified polymorphisms (REMAPs). One thousand
twenty nine loci were mapped to 26 linkage groups that extended for 5,472.3 cM
with an average distance between loci of 5.32 cM.  The linkage groups of the
genetic maps have been assigned to their corresponding chromosomes by using the
available cotton aneuploid stocks [21, 23] and fluorescent in
situ hybridization using mapped genetic marker-containing BACs as probes
[99].


### 2.2. Gene and QTL Mapping

Although molecular linkage maps
have contributed greatly to our understanding of the evolution and organization
of the cotton genomes, a primary purpose of the map construction is to provide
a common point of reference for locating the genes affecting qualitative and
quantitative traits. DNA markers that are associated with genes conferring
important agronomic traits that are costly or laborious to measure will provide
a less costly and yet more dependable means of selection for identifying
desirable progenies in breeding programs.Mapping qualitative traits
Qualitative or simple Mendelian inherited traits are traits of individuals that
differ as to kind and not of degree, typically controlled by single genes and
the phenotypic variation falls into discrete classes in the segregating
progenies. Over 200 qualitative traits have been identified in either the
diploid (G. arboreum and G. herbaceum) or tetraploid (mostly in G.
hirsutum and G. barbadense) species [1]. Examples of such traits include leaf shape, pollen color, leaf color, lint color, pubescent, bract shape, and so on. Because many
qualitative traits are either morphological mutants that have arisen through
spontaneous mutation, irradiation, or from natural variation between species in
interspecific hybrids, they have little utility in crop improvement.
Consequently, there have been little efforts in mapping qualitative traits onto
the molecular genetic map. Qualitative traits that have been mapped using
molecular markers were recently summarized in [105]. Many of these traits were mapped not as the main
objective but as a tool for aligning the various linkage groups to chromosomes
assigned by the classical map. Noteworthy exceptions include those that are
related to agricultural productivity and quality of cotton and can be broadly
grouped into four categories: genes for leaf shape, fiber development,
resistant to disease and insect pests, and fertility restoration [105].Mapping quantitative traits
Quantitative traits are traits of individuals that differ as to degree and not
of kind, typically considered as interactions of multiple loci, tend to exhibit
continuous variation in a segregating population, and are readily subjected to
variation of environments. With the increased availability of DNA markers for
use in cotton genetic map construction in the last ten years, activities in
identifying and locating quantitative trait loci (QTLs) have blossomed. QTLs
that have been identified in cotton include yield and yield components, fiber
quality, plant architecture, resistance to diseases such as bacterial blight
andVerticillium wilt, resistance to
pests like root-knot nematode, and flowering date. A list of QTLs mapped in
cotton is presented in Table 2.
Several  noteworthy
findings have come out of QTL mapping in cotton.  First, in tetraploid cottons,
although the D-subgenome was derived from an ancestor that does not produce
spinnable fibers, many QTLs influencing fiber quality traits were detected on
the D-subgenome [106].
For example, Jiang et al. [45]
pointed out that D-subgenome QTLs may partly explain the fact that
domestication and breeding of tetraploid cottons has resulted in fiber with a
higher quality than those achieved by parallel improvement of the A-genome
diploid cottons which produce spinnable fibers. The merger of the A- and
D-genomes in tetraploid cottons, where each genome has a different evolutionary
history, may have offered unique avenues for phenotypic response to selection.
Second, numerous studies have shown that QTLs occur in clusters genetically in
the cotton genome [27, 46, 55, 56, 76, 106]. Ulloa et al. [56] suggested the possible existence of highly recombined regions in the
cotton genome with abundant putative genes. QTL clusters might exert their
multiple functions to compensate for a numerical deficiency, expanding their
roles in cotton growth and development [76]. Finally, the position and effect of QTLs for fiber
quality are not comparable in different populations and environments evaluated
[60, 106]. This suggests that QTL
studies conducted thus far have detected only a small number of loci for fiber
growth and development and that additional QTLs remain to be discovered [58, 59]. Furthermore, because
quantitative traits are readily subjected to variation of environments, mapping
efforts of these traits need to be pursued in multiple environments including
years and locations.Table 2
QTLs or genes identified for various traits in cottons.
Traits/genesParental materialsReferenceResistance to the bacterial blight pathogenEmpire B2/B3/B2b6, S295 and Pima S-7*[42]Resistance to the bacterial blight pathogenCS50 and Pima S-7*[43]Density of leaf and stem trichomesPima S-7 and Empire B2b6*[44]Fiber quality and yieldCAMD-E and Sea Island Seaberry*[45]Agronomic and fiber traitsMARCABUCAG8US-1-88 and HS46[46]Cotton leaf morphology and other traitsSeaberry and Deltapine 61 with morphological mutants*[47]Productivity and qualitySiv’on and F-177*[48]Physiological variables and crop productivitySiv’on and F-177*[49]Fiber qualityTM-1 and 3-79*[25]Yield components, fiber, flowering date, et al.TM-1 and 3-79*[50]Rf1 fertility-restoring geneCMS and the restoring lines[51]Fiber qualitySiv’on and F-177*[52]Fiber strength7235 and TM-1[53]Rf1 fertility-restoring geneXiangyuanA, ZMS12A, Sumian16A and 0-613-2R[54]Fiber-related traitsAcala-44 and Pima S-7*[27]Agronomic and fiber quality traitsMD5678ne and Prema[55]Fiber and yield traitsMARCABUCAG8US-1-88, HS46, MD5678ne et al.[56]Resistance to Verticillium wiltPima S-7 and Acala 44*[57]Fiber elongationTamcot 2111 and Pima S6*[58]Fiber length, length uniformity, and short fiber contentTamcot 2111 and Pima S6*[59]Fiber fineness and micronaire (MIC)Tamcot 2111 and Pima S6*[60]Li1, Li2, N1, Fbl, n2, sma-4(ha), and sma-4(fz)Pima S-7, Li1, Li2, N1, Fbl,n2, SMA4, A1-97*[61]Leaf morphologyTMS-22 and WT936*[31]Leaf morphological traits and chlorophyll contentTM-1 and Hai 7124[62]Fiber quality traitsTM1 and Pima 3-79*[35]Leaf and stem pubescenceGuazuncho 2 and VH8-4602*[63]Fiber qualityGuazuncho 2 and VH8*[64]Lint percentage and fiber quality traitsYumian 1 and T586[65]Fiber traitsHandan208 and Pima90*[33]Fiber yield and yield componentsHandan 208 and Pima 90*[66]Fiber quality and yield componentHandan 208 and Pima 90*[34]Fiber traits7235, TM-1, HS427-10, PD6992 and SM3[67]Root-knot nematode resistance geneM-120 RNR and Pima S-6*[68]Fiber and yield component traits7235 and TM-1[69]Fiber quality and yield components7235 and TM-1[70]Root-knot nematode resistance gene(rkn1)Acala SJ-2, Acala NemX, and Pima S-7*[71]Root-knot nematode resistance gene(rkn1)Acala SJ-2 and Acala NemX[72]Root-knot nematode resistance geneResistant near isoline and susceptible near isoline[73]Lint percentage and morphological marker genesTM-1 and T586[74]Fiber-related traitsTM-1 and 3-79*[36]Yield, yield component and fiber qualityNear-isogenicBC5S1 chromosome substitution lines, TM-1[75]Plant architecture traitsZhongmiansuo12 and 8891[76]Fiber quality traitsZhongmiansuo12 and 8891[77]Yield and yield-component traitsZhongmiansuo12 and 8891[78]* Interspecific cross.


### 2.3. BAC and BIBAC Resources

Large-insert BAC and BIBAC libraries have been demonstrated
essential and desirable for advanced genomics and genetics research [107–111].  Because of their low-level
chimerism, readily amenability to high-throughput purification of cloned insert
DNA, and high stability in the host cell [83, 112, 113], BACs and BIBACs have quickly assumed a central
position in genome research. BAC and BIBAC libraries have widely been
used in many research areas of genomics and molecular biology, including
whole-genome or chromosome physical mapping [110, 114–128], large-scale
genome sequencing [129–133], positional cloning of
genes and QTLs (for review, see [134]), isolation and characterization of
structural and regulatory genes [135, 136],
long-range genome analysis [135, 136],
organization and evolution of multigene families [136], and cytologically physical mapping [137].BAC libraries have
been developed for a number of species, including plants, animals, insects, and
microbes and made available to the public (http://hpc.tamu.edu;
http://bacpac.chori.org;
http://www.genome.clemson.edu). To
facilitate cotton genome research, BAC and BIBAC libraries have been developed
for several genotypes of Upland cotton,  G. hirsutum (Table 3). As of May 1, 2007, at
least six BAC and BIBAC libraries have been developed and made available to the
public. These libraries were constructed from five genotypes of Upland cotton,
including Tamcot HQ95, Auburn 623, TM-1, Maxxa, and 0-613-2R, in four BAC vectors
and one Agrobacterum-mediated, plant-transformation-competent BIBAC vector with three restriction enzymes. The
libraries have average insert sizes ranging from 93 to 175 kb and each have a
genome coverage ranging from 2.3 to 8.3x genome equivalents, collectively
covering >21x haploid genomes of the polyploid cotton (Figure 2). Moreover, BAC libraries have also been constructed for several other Gossypium species, including G. barbadense (Pima S6), G. arboreum (AKA8401), G. raimindii, and G. longicalyx (A.H. Paterson, pers. communication). These BAC and
BIBAC libraries provide resources essential for advanced genomics and genetics
research of cottons.Table 3
Upland cotton BAC and BIBAC libraries that have been published or are accessible to the public (as of May 2007).
GenotypeMean insert size (kb)No. of clonesGenome equivalentsVector(a)Cloning siteReferences/locations where libraries are availableTamcot HQ959351,3532.3xpBeloBAC11HindIIIhttp://hbz7.tamu.eduAuburn 62314044,1602.7xpBeloBAC11BamHIhttp://hbz7.tamu.eduTexas Marker-113076,8004.4xpCLD04541BamHIhttp://hbz7.tamu.eduTexas Marker-117576,8006.0xpECBAC1EcoRIhttp://hbz7.tamu.eduMaxxa137129,0248.3xpCUGI-1HindIII[79]0-613-2R13097,8255.7xpIndigoBAC-5HindIII[80](a) The vectors, pBeloBAC11 (Kim et al. [81]), pECBAC1 (Frijters et al. [82]), pCUGI-1 [79],
and pIndigoBAC-5 (http://www.epibio.com/item.asp?ID=328), are BAC vectors whereas pCLD04541 is plant-transformation-competent BIBAC vector (http://www.jic.bbsrc.ac.uk/staff/ian-bancroft/vectorspage.htm; [83]) that can be directly transformed into cotton plants via Agrobacterium.Figure 2
BACs randomly selected from the TM-1/Eco RI BAC library (see Table 3; C. Scheuring and H.-B. Zhang, unpublished). BAC DNA was isolated, digested with NotI, and run on a pulsed-field gel.


### 2.4. ESTs, Microarrays, and Gene Expression Profiling

ESTs
Cloning and sequencing of
expressed gene sequence tags (ESTs) by single sequencing pass from
one or both ends of cDNA clones have been widely used to rapidly discover and
characterize genes in a large-scale and high-throughput manner. As have been
done in many other plant and animal species of biological and/or economical
importance, significant efforts have been made to generate ESTs in
cottons.  As of April 27, 2007, 281,233
ESTs have been available for theGossypium species in GenBank (Table 4; http://www.ncbi.nlm.nih.gov/dbEST). Of
these ESTs, 178,177 were from the polyploid cultivated cottons with 177,154
(63.0%) from G. hirsutum and 1,023
(<1.0%) from G. barbadnese while
103,056 were from the related diploid species with 39,232 (13.9%) from G. arboreum (A2), 63,577
(22.6%) from G. raimondii (D5),
and 247 (<1.0%) from G. herbaceum (A1).  This number of cotton
ESTs, compared with that of five years ago, has been significantly increased,
due to several large EST projects funded [100–104]. Nevertheless, when compared with those of other major
crop species such as rice, maize, wheat, and soybean, the number of the cotton
ESTs is very low, only being about one-forth of those of rice, maize, or wheat
(Table 4).Table 4
Summary of ESTs of major crops available in GenBank (as of April 27, 2007).
SpeciesGenome(a)No. of ESTsCotton and related species (Gossypium species):G. hirsutum (Upland cotton)(AADD)1177,154G. raimondiiD5D563,577G. arboreumA2A239,232G. barbadense (Sea Island)(AADD)21,023G. herbaceum var. africanumA1A1247Total:281,233Rice and Related Species (Oryza species):O. sativa (rice)AA1,211,447O. minutaBBCC5,760O. grandiglumisCCDD128Total:1,217,335Maize and Related Species (Zea species):Z. mays (maize)1,161,241Total:1,161,241Wheat and Related Species (Triticum and Aegilops species):T. aestivum (wheat)AABBDD1,050,131T. monococcumAA10,139T. turgidum ssp. durumAABB8,924T. turgidumAABB1,938Ae. speltoidesBB4,315Ae. tauschiiDD116Total:1,075,563Soybean and Related Species (Glycine species):G. max (soybean)GG371,817G. sojaGG18,511G. clandestinaA1A1931Total:391,259(a) There is no relationship in the genome letter designation between genera, but there is a
relationship in the genome letter designation between species within a genus, the species
with the same genome letter being closely related.Table5 summaries 247,979
ESTs of cottons published [100, 102–104]. These ESTs were collectively generated from 32 cDNA
libraries constructed from mRNA isolated from 18 genotypes of three species, G. hirsutum, G. arboreum, and G raimondii, by one-pass sequencing of cDNA clones from one (3′ or 5′ end) or both
ends.  They were generated from 12
different organs, including developing fibers, seedlings, buds, bolls, ovules,
roots, hypocotyls, immature embryos, leaves, stems, and cotyledons. Some of the
ESTs were generated from plants growing under biotic or abiotic stress
conditions such as drought, chilling, and pathogens. By analyzing approximately
185,000 ESTs from both fibers/ovules (124,299 ESTs) and nonfiber/ovule tissues
(60,899 ESTs) of G. hirsutum, G. arboreum and G. raimondii, Udall et al. [102] obtained 51,107 unigenes.  A few
months later, Yang et al. [103]
analyzed their 32,789 ESTs generated from −3- to +3-dpa fibers of Upland cotton
cv. TM-1, along with 211,397 cotton ESTs downloaded from GenBank (as of April
2006), resulting in 55,673 unigenes and updating The Institute of Genomic
Research Cotton Gene Index version 6 (CGI6) into CGI7 (http://www.tigr.org).  The unigene EST number may provide a
reasonable estimation about the number of expressed genes in the cotton
genomes. Of the unigene set, those derived from fibers or fiber-bearing ovules
suggest the number of genes potentially involved in fiber development and
genetic complexity of fiber traits.Table 5
Summary of cotton ESTs (as of May 2007).
GenotypesLibrary nameTissues usedNo. of ESTsNo. of unigenesAuthorsReferencesGossypium arboreum (A2):[100]AKA8401GA-Ea7- to 10-dpa fibers46,603Wing et al.(normalized)Arpat et al.Subtotal46,60313,947G. Raimondii (D5):GN34GR_EaWhole seedlings33,671Udall et al.with 1st true leavesGN34GR-Eb−3-dpa buds to33,061Udall et al.+3-dpa bollsSubtotal68,732G. hirsutum (AD1):Coker 312GH_MD8- to 10-dpa boll1,144Allen[101](irrigated)Coker 312GH_MDDS8- to 10-dpa boll1,238Allen(drought stressed)Coker 312GH_LDI15- to 20-dpa boll1,799Allen & Payton(irrigated)Coker 312GH_LDDI15- to 20-dpa boll1,409Allen & Payton(drought stressed)Acala MaxxaGH_BNL5-dpa fibers8,022Blewitt & BurrXu-142GH_FOX0- to 5-dpa ovule and7,997Gou & Chen1- to 22-dpa fibersDeltapine 90GH_SCW2nd versus 1st primary7,385Haigler &fibersWilkersonZhongmian 12GH_SUO0-dpa ovules1,240Suo & XueDeltapine 16GH-CHX−3- to 0-dpa ovules7,631Wu & DennisDeltapine 16GH_OCF0-dpa ovules867Wu and DennisDeltapine 16GH_ON0-dpa ovules5,903Wu & Dennis(normalized)Stv 7A glGH_ECT18 h etiolated seedlings2,880ChapmanDelta emeraldGH_CRHRoot and hypocotyls1,464Dowd & McFaddenDelta emeraldGH_CFUSRH tissues infected with820Dowd &Fusarium oxysporumMcFaddenSicotGH_LSLS9i leaves, late season1,810Faivre-Nitschke& DennisCoker 312GH_SDLSeedlings (control)1,918Klueva et al.Coker 312GH_SDLDSeedlings (drought1,142Klueva & Nguyenstressed)Coker 312GH_SDCHSeedling (chilling576Klueva & Nguyenstressed)Deltapine 16GH_IMEImmature embryo1,536Liu & DennisIm216GH_IMXLeaf 8, 14, 20, 30, 45,1,134Patil et al.60 hpiXanthomonasAcB4Blnb7GH_ACXELeaf8+14 hpi647Phillips et al.XanthomonasAcB4Blnb7GH_ACXMLeaf20+30 hpi1,328Phillips et al.XanthomonasAcB4Blnb7GH_ACXLLeaf45+60 hpi862Phillips et al.XanthomonasT25GH_pARLeaves1,230TrolinderDES119GH_STEMMature stem8,643TaliercioDP62GH_ECOTEtiolated cotyledon2,772Ni & Trelease91-D-92GH_CBAZBall abscission zone1,306Wan & Wing185,198(a)51,107[102]Texas Marker-1GH_TMO−3- to 3-dpa ovules32,7898,540Chen[103]−1 (TM-1)Not available5- to 10-dpa fibers29,99212,992ZhuXuzhou 142[104](Xu-142)Subtotal132,644Total247,979(a) The number was the sum of numbers of all ESTs above the line including those of G. arboreum, G. raimondii and G.
hirsutum [102]. Of the 247,979 cotton ESTs, 187,014 (75.4%) were from developing fibers or ovules
whereas 160,965 (24.6%) from nonfiber or nonovule organs.A predominant feature of the cotton EST set is the significant preference of
their tissue sources for fiber or fiber-bearing ovules than other organs. Of
the 247,979 ESTs listed in Table5, 187,080 (75.4%) were from developing fibers
or fiber-bearing ovules while only
60,899 (24.6%) were from nonfiber and
nonovule organs. Within each of the two categories, fiber/fiber-bearing ovules
and nonfiber/ovule organs, there is also a significant bias in the number of
ESTs. Cotton fiber development is classified into four clearly characterized,
but overlapping stages, including fiber initiation (−3 to 5 dpa), elongation (5–25 dpa), secondary cell wall deposition (15–45 dpa), and maturation/dehydration (45–70 dpa) (see Figure 3). All of the 187,080
fiber ESTs were generated from the fibers or fiber-bearing ovules collected
from the first three stages with 43.6% from the initiation stage, 46.5% from
the elongation stage, and 5.7% from the secondary cell wall deposition stage.
It is apparent that the number of fiber ESTs from the secondary cell wall
deposition stage is much smaller than that of either initiation or elongation
stage. Although the initiation and elongation stages are of significance for
the number of fibers per seed and fiber length, the secondary cell wall
deposition stage is crucial to fiber strength.
Of the 60,899 nonfiber/nonovule ESTs, 66.0% were from seedlings, 14.2%
from stems, and 2.4% from roots.Figure 3
Cotton fiber development and corresponding morphogenesis stages (according to [138, 139]). The initiation stage is characterized by the enlargement and protrusion of epidermal cells from the ovular surface; during the elongation stage the cells expend in polar directions with a rate of >2 mm/day; during the secondary cell wall deposition stage celluloses are synthesized rapidly until the fibers contain ∼90% of cellulose; and at the maturation stages minerals accumulate in the fibers and the fibers dehydrate.The
cotton ESTs have been used in several aspects, including development of
genome-wide cotton microarrays (see below), mining of SSRs (see above) and
study of polyploidization. The development of the significant numbers of ESTs
from the cultivated tetraploid cotton,G. hirsutum [(AADD)1], and its closely related
diploid species, G. arboreum (A1A1)
and G. raimondii (D5D5)
(see Table 5) made it possible to compare the transcriptomes among the three
species.  Udall et al. [102] comparatively analyzed 31,424, 68,732, and 69,853 ESTs
derived from G. arboreum, G. raimondii, and G. hirsutum, respectively. Although the comparison was
significantly affected by the tissue sources and developmental status, they
identified the putative homoeologs among the four genomes, A, D, A1,
and D5. This information is useful for our understanding of how the
cotton genomes function and evolve during the courses of speciation,
domestication, plant breeding, and polyploidization.Microarray
Microarray has been a technology that
is widely used in many aspects of genomics research, including gene discovery,
gene expression profiling, mutation assay, high-throughput genetic mapping,
gene expression mapping (eQTL mapping), and comparative genome analysis. It
involves robotically printing tens of thousands of cDNA amplicons or
gene-specific long (70 mers) oligonucleotides as array elements on a
chemically-coated glass slide, followed by hybridizing the array with one or more
fluorescent-labeled cDNA or cRNA targets derived from mRNA isolated from
particular tissues, organs, or cells. Therefore, it allows the simultaneous
monitoring of the expression/activities of all genes arrayed on the array in a
single hybridization experiment. To facilitate cotton genomics research,
microarrays have been developed from the cotton ESTs (Table5) in several
laboratories worldwide.
The
first batch of cotton microarrays was fabricated from 70-mers oligos designed
from the 7–10 dpa fiber nonredundant (NR) or unigene ESTs ofG. arboreum (Table 5) ([100]; http://cottongenomecenter.ucdavis.edu/microarrays.asp).
Each microarray consists of 12,227 elements corresponding to 12,227 NR fiber
ESTs, with a duplicate of each element. Using the microarrays, Arpat et al. [100] compared the expression of
the genes between 10-dpa fibers at elongation or primary cell wall synthesis
stage and 24-dpa fibers at secondary cell wall disposition stage (see Figure 3).
The expression of fiber genes was found to change dynamically from elongation
or primary cell wall to secondary cell wall biogenesis, with 2,553 of the fiber
genes being significantly downregulated and 81 being significantly upregulated.
This result suggests that the expression of fiber genes is stage-specific or
cell expansion-associated. Annotation of the genes upregulated in the secondary
cell wall synthesis relative to the primary cell wall biogenesis showed that
most of the genes felt in three major functional categories, energy/metabolism,
cell structure, organization and biogenesis, and cytoskeleton. This finding is
consistent with the fact of massive cellulose synthesis and cell wall
biogenesis during this stage. The fiber gene microarrays have been updated
recently by incorporating nearly 10,000 gene elements designed from the fiber
and ovary ESTs of the tetraploid cultivated cotton, G. hirsutum (Table 5; T.A. Wilkins, pers. communication). The
current fiber microarrays each slide consist of four duplicated arrays with
22,406 60-mers oligo elements per array and a duplicate of each element (see, e.g., Figure 4).  The new version of
fiber gene arrays covers 100% of the fiber ESTs of diploid cotton and 65% of
the fiber ESTs of the tetraploid cultivated cotton, G. hirsutum that are available in GenBank, thus representing the
most comprehensive coverage of the cotton fiber genes. The elements are printed
on a slide in a randomized manner instead of the conventional ordered manner.
The fabrication of four duplicated arrays per slide and randomized printing
design have significantly minimized the systematic problems that are frequently
encountered in the conventional array design (one array per slide and ordered
printing), thus further enhancing the reproducibility and accuracy of the
microarray analysis results.
Recently,
several additional batches of EST- or cDNA-based microarrays with different
formats and elements have been reported in cotton [102, 104, 140]. Shi et al. [104] reported the fabrication
of microarrays from unigene ESTs derived from 5–10 dpa ovules of the Upland cotton cv. Xuzhou
142 and using the amplicons of the EST clones as the array elements. The
microarrays each consist of 11,962 uniEST elements. Using the microarrays, Shi et al. [104] comparatively studied the
wild-type Xuzhou 142 versus its fuzzless-lintless (fl) mutation using the RNAs isolated
from the ovules at stages of 0-, 3-, 5-, 10-, 15-, and 20-dpa. It was found
that ethylene biosynthesis is one of the most significantly upregulated
biochemical pathways during fiber elongation. Similarly, Wu et al. [140] also fabricated a set of
microarrays from amplicons of 10,410 cDNA clones derived from −3- to 0-dpa
ovules of the Upland cotton cv. DP16 (see Table 5, Wu & Dennis).
The arrays were analyzed with RNAs isolated from 0-dpa whole ovules,
outer integument, and inner integument/nucellus of five lintless mutation lines
against the wild-type DP16. Of the 10,410 gene elements on the array, 60 to 243
were found to significantly differentially express between each pair of the
wild type and mutant when the array was hybridized with the RNAs isolated from
the 0-dpa whole ovules.  Of these
differentially expressed genes, 70.6% were upregulated and 29.4% downregulated
in the fiber mutant, suggesting that the mutation caused not only gene downregulation,
but also gene upregulation. However, when the whole ovule was dissected into
three layers, outer integument, inner integument, and nucellus, of which cotton
fibers develop from the epidermal cells of the outer integument, and analyzed
with the outer integument against the inner integument and the nucellus, the
number of the genes downregulated in the mutants was reduced to 13. These
include an Myb transcription factor,
a putative homeodomain protein, a cyclin D gene, and some fiber-expressed
structural and metabolic genes, suggesting that these genes may be involved in
the process of fiber initiation.
In summary, three batches of
EST- or cDNA-based cotton microarrays were fabricated from fiber genes of
either cultivated tetraploid cotton,G.
hirsutum [104, 140], or cultivated diploid
cotton, G. arboreum [100].  Using the microarrays, the expression of the
fiber genes was profiled and comparatively analyzed at fiber initiation stage
[140], elongation stage
[100, 104], and secondary cell wall
deposition stage [100].
However, the expression of other cotton genes such as those from nonfiber and
nonovary tissues remains to profile. To fill this gap, another two batches of
long oligo-based microarrays have been developed. The first batch contains approximately
21,000 gene elements per array  (http://cotton.agtec.uga.edu/CottonFiber/pages/mcriarray/Array.aspx).
These genes were from 52 cDNA libraries constructed from a variety of tissues
and organs in a range of conditions, including drought stress and pathogen
challenges, and represents tetraploid (G.
hirsutum) and its diploid relatives (G.
arboreum and G. raimondii).  Of the 21,000 genes, approximately one-forth
were from fiber genes and three-forth were from nonfiber and nonovary tissues
(J. A. Udall, pers. communication). The second batch contains 38,716 gene
elements per array. Of the gene elements, 22,409 are designed from fiber ESTs
and 16,307 from nonfiber ESTs (T.A. Wilkins, pers. communication). There is no
doubt that these versions of cotton microarrays will provide new tools for
comprehensive functional and comparative genomics research of cottons.Figure 4
Comparative analysis of the expression of fiber genes in 10-dpa fibers betweenG. hirsutum and  G. barbadense (M. Goebel, M. Alabady, C.W. Smith, T. A. Wilkins and H.-B. Zhang, unpublished). The cotton fiber microarrays are available in the laboratory of T. A. Wilkins, Texas Tech University (Texas, USA). One of the four arrays printed on a single slide is shown.


### 2.5. Physical Mapping

Whole-genome,
BAC- and/or BIBAC-based, integrated physical/genetic maps have played a central
role in genomics research of humans, plants, animals, and microbes [110, 123, 127]. This is because they provide central platforms for many areas, if not
all, of modern genomics research, including large-scale transcript or gene
mapping, region-targeted marker development for fine mapping and MAS of genes
and QTLs, map-based gene/QTL cloning, local- and whole-genome comparative
analysis, genome sequencing, and functional analysis of DNA sequences and
component network.  Therefore,
whole-genome, BAC/BIBAC-based, integrated physical/genetic maps have been
developed for a number of plant and animal species. In plants, whole-genome BAC
physical maps have been developed for several species, including Arabidopsis [114, 118], indica rice [121],
japonica rice [117],
soybean [124], and maize
[141]. However,
whole-genome physical maps of cottons have only been initiated in several
laboratories. One is the laboratory of H.-B. Zhang, Texas A&M University,
College Station (Texas, USA). This laboratory is developing a whole-genome
BAC/BIBAC physical map of the Upland cotton cv. TM-1 by using the latest
physical mapping technology [123, 126]. The project
was a collaborative effort among the laboratories of H.-B. Zhang, R. J. Kohel,
USDA/ARS, College Station (Texas, USA) (who provided a part of the fund for the
project), and D. M. Stelly, Texas A&M University (Texas, USA). Nearly 120,000
(∼7.3x) BIBACs and BACs selected from the TM-1 BIBAC and BAC libraries (see
Table 3) have been fingerprinted and a draft BAC/BIBAC contig map has been
constructed. The draft physical map consists of 5,088 contigs collectively
spanning approximately 2,300 Mb of the 2,400 Mb Upland genome (unpublished).
Currently, additional clones (to reach about 10x genome coverage clones) are
being analyzed. Furthermore, because the Upland cotton is an allotetraploid
which makes the physical map construction more complicated, several approaches
are being used to sort the map contigs according to their origin of subgenomes.
The laboratory of A. H. Paterson, University of Georgia (Athens, Georgia) is
also working toward development of a whole-genome BAC-based physical map of the
diploid species, G. raimondii (A. H.
Paterson, pers. communication). Given the importance of physical maps for
modern genome research, there is no doubt that development of a robust
integrated physical/genetic map will greatly promote advanced genomics research
of cottons and related species (also see below).


### 2.6. Genome Sequencing

Sequence
maps represent the most-fine physical maps of genomes [108]. They provide not only physical positions of and
distances between genes and other components constituting a genome [142], but also their sequences
and putative functions inferred from the sequences. Therefore, development of a
complete genome sequence map of a species will significantly promote genomics
research of the species in a variety of aspects. Because of this reason, the
whole genomes of several plant and animal species have been sequenced. In
plants, the genomes of two model species, Arabidopsis [130] and rice [132], have been completely sequenced and the genomes
of several other species, including Medicago
truncatula (http://www.medicago.org), Lotus
japonicus (http://www.kazusa.or.jp/lotus), tomato (http://www.sgn.cornell.edu/about/tomato_sequencing.pl),
maize (http://www.maizegenome.org),
and soybean (http://genome.purdue.edu/isgc/Tsukuba07/ISGC_report_Apr2007.htm),
are currently being sequenced.However,
there is only a limited amount of genomic sequences available for cotton and
related species in GenBank.  A major
source of the genomic sequences ofGossypium species was from Hawkins et al. [143]. To understand the underlying genome size variation and evolution of Gossypium species, Hawkins et al. [143] constructed whole-genome
shotgun libraries for G. raimondii (D5D5), G. herbaceum (A1A1), G. exiguum (KK), and the species that
was used as the outgroup species for phylogenetic analysis of the Gossypium species, Gossypioideskirkii, with
each species library containing 1920–10,368 clones. From each of the four shotgun
libraries, 1,464–6,747 clones were sequenced, together covering
a total length of 11.4 Mb. Annotation of these clone sequences and estimation
of the copy number of each type of the sequences suggested that differential
lineage-specific amplification of transposable elements is responsible for
genome size variation in the Gossypium species. Moreover, G. raimondii has
been selected recently by the DOE Joint Genome Institute, U.S. Department of
Energy to be sequenced for genomic study of cotton and related species (http://www.jgi.doe.gov/sequencing/cspseqplans2007.html).
At the first phase of the sequencing project, a whole-genome shotgun library
covering about 1x of the G. raimondii genome will be sequenced.  While this
number is far from the genome coverage of clones (>6x) that is needed to
assemble the sequence map of the genome, it will provide the first glimpse into
the cotton genome and useful information for sequencing the entire genomes of
this and other cotton key species efficiently.


## 2.1. DNA Markers and Molecular Linkage Maps

Genetic maps constructed in theGossypium species and the types of
markers used are listed in Table 1. As in most plant species, the early
application of DNA markers in cotton genomic research has been in the form of
RFLPs. It is, therefore, not surprising that the first molecular linkage map of
the Gossypium species was constructed
from an interspecific G. hirsutum×G. barbadense F2 population
based on RFLPs [23]. The map contained 705 loci that were assembled into 41 linkage groups and
spanned 4,675 cM. This map later was further advanced by Rong et al. [24] that comprised 2,584 loci
at 1.74-cM intervals and covered all 13 homeologous chromosomes of the
allotetraploid cottons, representing the most complete genetic map of the Gossypium to date. Many of the DNA
probes of the map were also mapped in crosses of the D-genome diploid species G. trilobum×G. raimondii [24] and the A-genome diploid species G.
arboreum×G. herbaceum [16]. Detailed comparative
analysis of the relationship of gene orders between the tetraploid
AD-subgenomes with the maps of the A and D diploid genomes has revealed
intriguing insights on the organization, transmission and evolution of the Gossypium genomes.Table 1
Genetic maps constructed forGossypium species.
Marker typeTotal lociMap distancePopulation(a)Cross type(b)ReferencesAFLP176773 cMF2GN × GAU[26]AFLP213931 cMF2GN × GAU[26]AFLP, SSR, and RFLP3923,287 cMF2GH × GB[27]AFLP, SSR, and RFLP8884,400 cMBC1GH × GB[28]AFLP, SSR, and RFLP1,1605,519 cMBC1GH × GB[29]RFLP2751,147 cMF2GAR × GHE[16]RFLP2841,503 cMF2 and F3GH × GH[30]RFLP5894,259 cMF2GH × GTO[31]RFLP7054,675 cMF2GH × GB[23]RFLP7631,493 cMF2GT × GR[24]RFLP2,5844,448 cMF2GH × GB[24]RFLP and RAPD3554,766 cMF2GH × GB[25]SRAP2373,031 cMF2GH × GB[32]SRAP, SSR, and RAPD5665,142 cMF2GH × GB[33]SRAP, SSR, RAPD, and REMAP1,0295,472 cMF2GH × GB[34]SSR1931,277 cMRILGH × GB[35]SSR4332,126 cMRILGH × GB[36]SSR4424,331 cMBC1GH × GB[37]SSR4443,263 cMDHGH × GB[37]SSR6245,644 cMBC1GH × GB[38]SSR9075,060 cMBC1GH × GB[39]SSR1,7903,426 cMBC1GH × GB[40]SSR and RAPD4893,315 cMDHGH × GB[41](a) RIL = recombinant inbred line, and DH = doubled haploid.(b) GH = G. hirsutum, GB = G. barbadense, GTO = G. tomentosum, GR = G. raimondii, GAR = G. arboretum, GHE = G. herbaceum,
GN = G. nelsonii, and GAU = G. australe.Because RFLPs are labor-intensive and require large
amounts of DNA, tedious blot hybridization and autoradiographic methods,
polymerase chain reaction (PCR)-based DNA marker methods have come into vogue.
Several types of PCR-based DNA markers have been utilized in cotton genome
research. Methods, such as RAPD, AFLP, RGA, and SRAP, offer an excellent
opportunity to scan enormous numbers of DNA loci rapidly, often targeting the
DNA elements that are rapidly-evolving and therefore, are more likely to
contain loci differing among genotypes. Kohel et al. [25] constructed a genetic map based on a population
derived from an interspecific cross between Texas Marker-1 (TM-1) (G. hirsutum) and 3–79 (G. barbadense) in which a total of 355
DNA markers (216 RFLPs and 139 RAPDs) were assembled into 50 linkage groups,
covering 4,766 cM. Brubaker and Brown [26] presented the first AFLP genetic
linkage map for the Gossypium G-genome
that was constructed from an interspecific G.
nelsonii×G. australe population. The AFLP genetic linkage maps were used to identify G-genome
chromosome-specific molecular markers, which, in turn, were used to track the
fidelity and frequency of G. australe chromosome transmission in a G. hirsutum×G. australe hexaploid bridging
family.Advent of SSR or
microsatellite markers has brought a new, user-friendly, and highly polymorphic
class of genetic markers for cotton. The latter feature is especially useful to
the cultivated Upland cotton due to its low intraspecific polymorphism. SSRs
are PCR-based markers, usually codominant, well dispersed throughout the
genome, easily shared between labs via flanking primer sequences, and well
portable from one population to another [84]. Reddy et al. [85] suggested that the total pool of SSRs present in the cotton genome is
sufficiently abundant to satisfy the requirements of extensive genome mapping
and marker-assisted selection (MAS). Liu et al. [86] reported the assignment of SSRs to cotton chromosomes by making
use of aneuploid stocks. SSRs have been widely employed in genetic diversity
analyses of cotton [87–90] and several genetic linkage maps
based mostly on SSRs have now been developed [37–41].Several methods
have been pursued to develop SSR markers in cottons, including analysis of
SSR-enriched small-insert genomic DNA libraries [29, 85, 86, 91], SSR mining from ESTs (see
below; [35, 38, 39, 92], and large-insert BAC derivation by end sequence
analysis [36]
or SSR-containing BAC subcloning as described by Lichtenzveig et al. [93]. Currently, a total of
approximately 5,484 SSRs have been developed in cotton ([94]; http://www.cottonmarker.org).The development of
a large number of ESTs (see below) provides a good source of PCR-based primers
for targeting SSRs [92, 95, 96]. Taliercio et al. [97] sequenced ESTs
representing a variety of tissues and treatments with SSRs identified among the
ESTs. Their results indicated that these SSRs could potentially map the genes
represented by the ESTs. Guo et al. [98] examined the transferability of 207 G.
arboreum-derived EST-SSR primer pairs among 25 different diploid accessions
from 23 species representing 7 Gossypium genomes. Their results demonstrated that the transferability of EST-SSR markers
among these diploid species could assist the introgression of genes into
cultivated cotton species especially by molecular tagging of the important
genes existing in these diploid species. Guo et al. [40] also developed 2,218 EST-SSRs, with 1,554 from G. raimondii-derived ESTs and 754 from G. hirsutum-derived ESTs. By integrating
these new EST-SSRs to enhance the genetic map constructed by Han et al. [39], the present SSR-based
genetic map consists of 1,790 loci in 26 linkage groups and covers 3,425.8 cM
with an average distance between markers of 1.91 cM. This SSR-based high-density
map contains 71.96% functional marker loci, of which 87.11% are EST-SSR loci.DNA sequences
derived from clone end sequencing of BAC libraries provide yet another resource
for SSR marker development. In addition to the uses as genetic markers, SSRs
developed from BAC-end sequences provide the possibility to efficiently
integrate the genetic and physical maps of cotton. Frelichowski et al. [36] developed 1,316 PCR primer
pairs to flank SSR motif sequences from 2,603 new BAC-end genomic sequences
developed from G. hirsutum Acala
“Maxxa.” An interspecific recombinant inbred population was used to map 433
marker loci in 46 linkage groups with a total genetic distance of 2,126.3 cM
and an average distance between loci of 4.9 cM which covered approximately 45%
of the cotton genome.To overcome the paucity of a
particular type of DNA markers, genetic maps were developed by incorporating
different classes of markers. For example, Lacape et al. [28] constructed a combined RFLP-SSR-AFLP map based on an
interspecific G. hirsutum×G. barbadense backcross population of 75
BC1 plants. The map consists of 888 loci that ordered into 37
linkage groups and spanning 4,400 cM. This map was updated, mostly with new SSR
markers, to contain 1,160 loci that spanned 5,519 cM with an average distance
between loci of 4.8 cM [29]. Mei et al. [27] developed a genetic map using an interspecific G. hirsutum and G. barbadense F2 population that contained 392 genetic
loci, including AFLPs, SSRs, and RFLPs, and mapped into 42 linkage groups that
spanned 3,287 cM, thus covering approximately 70% of the cotton genome. Lin et al. [33] constructed a linkage map of tetraploid cotton using SRAPs, SSRs,
and RAPDs to screen an interspecific G.
hirsutum×G. barbadense F2 population.
A total of 566 loci were assembled into 41 linkages that covered 5,141.8 cM
with a mean interlocus space of 9.08 cM. He et al. [34] constructed a more detailed
cotton map with this same F2 population [33] using SSRs, SRAP, RAPD, and
retrotransposon-microsatellite amplified polymorphisms (REMAPs). One thousand
twenty nine loci were mapped to 26 linkage groups that extended for 5,472.3 cM
with an average distance between loci of 5.32 cM.  The linkage groups of the
genetic maps have been assigned to their corresponding chromosomes by using the
available cotton aneuploid stocks [21, 23] and fluorescent in
situ hybridization using mapped genetic marker-containing BACs as probes
[99].


## 2.2. Gene and QTL Mapping

Although molecular linkage maps
have contributed greatly to our understanding of the evolution and organization
of the cotton genomes, a primary purpose of the map construction is to provide
a common point of reference for locating the genes affecting qualitative and
quantitative traits. DNA markers that are associated with genes conferring
important agronomic traits that are costly or laborious to measure will provide
a less costly and yet more dependable means of selection for identifying
desirable progenies in breeding programs.Mapping qualitative traits
Qualitative or simple Mendelian inherited traits are traits of individuals that
differ as to kind and not of degree, typically controlled by single genes and
the phenotypic variation falls into discrete classes in the segregating
progenies. Over 200 qualitative traits have been identified in either the
diploid (G. arboreum and G. herbaceum) or tetraploid (mostly in G.
hirsutum and G. barbadense) species [1]. Examples of such traits include leaf shape, pollen color, leaf color, lint color, pubescent, bract shape, and so on. Because many
qualitative traits are either morphological mutants that have arisen through
spontaneous mutation, irradiation, or from natural variation between species in
interspecific hybrids, they have little utility in crop improvement.
Consequently, there have been little efforts in mapping qualitative traits onto
the molecular genetic map. Qualitative traits that have been mapped using
molecular markers were recently summarized in [105]. Many of these traits were mapped not as the main
objective but as a tool for aligning the various linkage groups to chromosomes
assigned by the classical map. Noteworthy exceptions include those that are
related to agricultural productivity and quality of cotton and can be broadly
grouped into four categories: genes for leaf shape, fiber development,
resistant to disease and insect pests, and fertility restoration [105].Mapping quantitative traits
Quantitative traits are traits of individuals that differ as to degree and not
of kind, typically considered as interactions of multiple loci, tend to exhibit
continuous variation in a segregating population, and are readily subjected to
variation of environments. With the increased availability of DNA markers for
use in cotton genetic map construction in the last ten years, activities in
identifying and locating quantitative trait loci (QTLs) have blossomed. QTLs
that have been identified in cotton include yield and yield components, fiber
quality, plant architecture, resistance to diseases such as bacterial blight
andVerticillium wilt, resistance to
pests like root-knot nematode, and flowering date. A list of QTLs mapped in
cotton is presented in Table 2.
Several  noteworthy
findings have come out of QTL mapping in cotton.  First, in tetraploid cottons,
although the D-subgenome was derived from an ancestor that does not produce
spinnable fibers, many QTLs influencing fiber quality traits were detected on
the D-subgenome [106].
For example, Jiang et al. [45]
pointed out that D-subgenome QTLs may partly explain the fact that
domestication and breeding of tetraploid cottons has resulted in fiber with a
higher quality than those achieved by parallel improvement of the A-genome
diploid cottons which produce spinnable fibers. The merger of the A- and
D-genomes in tetraploid cottons, where each genome has a different evolutionary
history, may have offered unique avenues for phenotypic response to selection.
Second, numerous studies have shown that QTLs occur in clusters genetically in
the cotton genome [27, 46, 55, 56, 76, 106]. Ulloa et al. [56] suggested the possible existence of highly recombined regions in the
cotton genome with abundant putative genes. QTL clusters might exert their
multiple functions to compensate for a numerical deficiency, expanding their
roles in cotton growth and development [76]. Finally, the position and effect of QTLs for fiber
quality are not comparable in different populations and environments evaluated
[60, 106]. This suggests that QTL
studies conducted thus far have detected only a small number of loci for fiber
growth and development and that additional QTLs remain to be discovered [58, 59]. Furthermore, because
quantitative traits are readily subjected to variation of environments, mapping
efforts of these traits need to be pursued in multiple environments including
years and locations.Table 2
QTLs or genes identified for various traits in cottons.
Traits/genesParental materialsReferenceResistance to the bacterial blight pathogenEmpire B2/B3/B2b6, S295 and Pima S-7*[42]Resistance to the bacterial blight pathogenCS50 and Pima S-7*[43]Density of leaf and stem trichomesPima S-7 and Empire B2b6*[44]Fiber quality and yieldCAMD-E and Sea Island Seaberry*[45]Agronomic and fiber traitsMARCABUCAG8US-1-88 and HS46[46]Cotton leaf morphology and other traitsSeaberry and Deltapine 61 with morphological mutants*[47]Productivity and qualitySiv’on and F-177*[48]Physiological variables and crop productivitySiv’on and F-177*[49]Fiber qualityTM-1 and 3-79*[25]Yield components, fiber, flowering date, et al.TM-1 and 3-79*[50]Rf1 fertility-restoring geneCMS and the restoring lines[51]Fiber qualitySiv’on and F-177*[52]Fiber strength7235 and TM-1[53]Rf1 fertility-restoring geneXiangyuanA, ZMS12A, Sumian16A and 0-613-2R[54]Fiber-related traitsAcala-44 and Pima S-7*[27]Agronomic and fiber quality traitsMD5678ne and Prema[55]Fiber and yield traitsMARCABUCAG8US-1-88, HS46, MD5678ne et al.[56]Resistance to Verticillium wiltPima S-7 and Acala 44*[57]Fiber elongationTamcot 2111 and Pima S6*[58]Fiber length, length uniformity, and short fiber contentTamcot 2111 and Pima S6*[59]Fiber fineness and micronaire (MIC)Tamcot 2111 and Pima S6*[60]Li1, Li2, N1, Fbl, n2, sma-4(ha), and sma-4(fz)Pima S-7, Li1, Li2, N1, Fbl,n2, SMA4, A1-97*[61]Leaf morphologyTMS-22 and WT936*[31]Leaf morphological traits and chlorophyll contentTM-1 and Hai 7124[62]Fiber quality traitsTM1 and Pima 3-79*[35]Leaf and stem pubescenceGuazuncho 2 and VH8-4602*[63]Fiber qualityGuazuncho 2 and VH8*[64]Lint percentage and fiber quality traitsYumian 1 and T586[65]Fiber traitsHandan208 and Pima90*[33]Fiber yield and yield componentsHandan 208 and Pima 90*[66]Fiber quality and yield componentHandan 208 and Pima 90*[34]Fiber traits7235, TM-1, HS427-10, PD6992 and SM3[67]Root-knot nematode resistance geneM-120 RNR and Pima S-6*[68]Fiber and yield component traits7235 and TM-1[69]Fiber quality and yield components7235 and TM-1[70]Root-knot nematode resistance gene(rkn1)Acala SJ-2, Acala NemX, and Pima S-7*[71]Root-knot nematode resistance gene(rkn1)Acala SJ-2 and Acala NemX[72]Root-knot nematode resistance geneResistant near isoline and susceptible near isoline[73]Lint percentage and morphological marker genesTM-1 and T586[74]Fiber-related traitsTM-1 and 3-79*[36]Yield, yield component and fiber qualityNear-isogenicBC5S1 chromosome substitution lines, TM-1[75]Plant architecture traitsZhongmiansuo12 and 8891[76]Fiber quality traitsZhongmiansuo12 and 8891[77]Yield and yield-component traitsZhongmiansuo12 and 8891[78]* Interspecific cross.


## 2.3. BAC and BIBAC Resources

Large-insert BAC and BIBAC libraries have been demonstrated
essential and desirable for advanced genomics and genetics research [107–111].  Because of their low-level
chimerism, readily amenability to high-throughput purification of cloned insert
DNA, and high stability in the host cell [83, 112, 113], BACs and BIBACs have quickly assumed a central
position in genome research. BAC and BIBAC libraries have widely been
used in many research areas of genomics and molecular biology, including
whole-genome or chromosome physical mapping [110, 114–128], large-scale
genome sequencing [129–133], positional cloning of
genes and QTLs (for review, see [134]), isolation and characterization of
structural and regulatory genes [135, 136],
long-range genome analysis [135, 136],
organization and evolution of multigene families [136], and cytologically physical mapping [137].BAC libraries have
been developed for a number of species, including plants, animals, insects, and
microbes and made available to the public (http://hpc.tamu.edu;
http://bacpac.chori.org;
http://www.genome.clemson.edu). To
facilitate cotton genome research, BAC and BIBAC libraries have been developed
for several genotypes of Upland cotton,  G. hirsutum (Table 3). As of May 1, 2007, at
least six BAC and BIBAC libraries have been developed and made available to the
public. These libraries were constructed from five genotypes of Upland cotton,
including Tamcot HQ95, Auburn 623, TM-1, Maxxa, and 0-613-2R, in four BAC vectors
and one Agrobacterum-mediated, plant-transformation-competent BIBAC vector with three restriction enzymes. The
libraries have average insert sizes ranging from 93 to 175 kb and each have a
genome coverage ranging from 2.3 to 8.3x genome equivalents, collectively
covering >21x haploid genomes of the polyploid cotton (Figure 2). Moreover, BAC libraries have also been constructed for several other Gossypium species, including G. barbadense (Pima S6), G. arboreum (AKA8401), G. raimindii, and G. longicalyx (A.H. Paterson, pers. communication). These BAC and
BIBAC libraries provide resources essential for advanced genomics and genetics
research of cottons.Table 3
Upland cotton BAC and BIBAC libraries that have been published or are accessible to the public (as of May 2007).
GenotypeMean insert size (kb)No. of clonesGenome equivalentsVector(a)Cloning siteReferences/locations where libraries are availableTamcot HQ959351,3532.3xpBeloBAC11HindIIIhttp://hbz7.tamu.eduAuburn 62314044,1602.7xpBeloBAC11BamHIhttp://hbz7.tamu.eduTexas Marker-113076,8004.4xpCLD04541BamHIhttp://hbz7.tamu.eduTexas Marker-117576,8006.0xpECBAC1EcoRIhttp://hbz7.tamu.eduMaxxa137129,0248.3xpCUGI-1HindIII[79]0-613-2R13097,8255.7xpIndigoBAC-5HindIII[80](a) The vectors, pBeloBAC11 (Kim et al. [81]), pECBAC1 (Frijters et al. [82]), pCUGI-1 [79],
and pIndigoBAC-5 (http://www.epibio.com/item.asp?ID=328), are BAC vectors whereas pCLD04541 is plant-transformation-competent BIBAC vector (http://www.jic.bbsrc.ac.uk/staff/ian-bancroft/vectorspage.htm; [83]) that can be directly transformed into cotton plants via Agrobacterium.Figure 2
BACs randomly selected from the TM-1/Eco RI BAC library (see Table 3; C. Scheuring and H.-B. Zhang, unpublished). BAC DNA was isolated, digested with NotI, and run on a pulsed-field gel.


## 2.4. ESTs, Microarrays, and Gene Expression Profiling

ESTs
Cloning and sequencing of
expressed gene sequence tags (ESTs) by single sequencing pass from
one or both ends of cDNA clones have been widely used to rapidly discover and
characterize genes in a large-scale and high-throughput manner. As have been
done in many other plant and animal species of biological and/or economical
importance, significant efforts have been made to generate ESTs in
cottons.  As of April 27, 2007, 281,233
ESTs have been available for theGossypium species in GenBank (Table 4; http://www.ncbi.nlm.nih.gov/dbEST). Of
these ESTs, 178,177 were from the polyploid cultivated cottons with 177,154
(63.0%) from G. hirsutum and 1,023
(<1.0%) from G. barbadnese while
103,056 were from the related diploid species with 39,232 (13.9%) from G. arboreum (A2), 63,577
(22.6%) from G. raimondii (D5),
and 247 (<1.0%) from G. herbaceum (A1).  This number of cotton
ESTs, compared with that of five years ago, has been significantly increased,
due to several large EST projects funded [100–104]. Nevertheless, when compared with those of other major
crop species such as rice, maize, wheat, and soybean, the number of the cotton
ESTs is very low, only being about one-forth of those of rice, maize, or wheat
(Table 4).Table 4
Summary of ESTs of major crops available in GenBank (as of April 27, 2007).
SpeciesGenome(a)No. of ESTsCotton and related species (Gossypium species):G. hirsutum (Upland cotton)(AADD)1177,154G. raimondiiD5D563,577G. arboreumA2A239,232G. barbadense (Sea Island)(AADD)21,023G. herbaceum var. africanumA1A1247Total:281,233Rice and Related Species (Oryza species):O. sativa (rice)AA1,211,447O. minutaBBCC5,760O. grandiglumisCCDD128Total:1,217,335Maize and Related Species (Zea species):Z. mays (maize)1,161,241Total:1,161,241Wheat and Related Species (Triticum and Aegilops species):T. aestivum (wheat)AABBDD1,050,131T. monococcumAA10,139T. turgidum ssp. durumAABB8,924T. turgidumAABB1,938Ae. speltoidesBB4,315Ae. tauschiiDD116Total:1,075,563Soybean and Related Species (Glycine species):G. max (soybean)GG371,817G. sojaGG18,511G. clandestinaA1A1931Total:391,259(a) There is no relationship in the genome letter designation between genera, but there is a
relationship in the genome letter designation between species within a genus, the species
with the same genome letter being closely related.Table5 summaries 247,979
ESTs of cottons published [100, 102–104]. These ESTs were collectively generated from 32 cDNA
libraries constructed from mRNA isolated from 18 genotypes of three species, G. hirsutum, G. arboreum, and G raimondii, by one-pass sequencing of cDNA clones from one (3′ or 5′ end) or both
ends.  They were generated from 12
different organs, including developing fibers, seedlings, buds, bolls, ovules,
roots, hypocotyls, immature embryos, leaves, stems, and cotyledons. Some of the
ESTs were generated from plants growing under biotic or abiotic stress
conditions such as drought, chilling, and pathogens. By analyzing approximately
185,000 ESTs from both fibers/ovules (124,299 ESTs) and nonfiber/ovule tissues
(60,899 ESTs) of G. hirsutum, G. arboreum and G. raimondii, Udall et al. [102] obtained 51,107 unigenes.  A few
months later, Yang et al. [103]
analyzed their 32,789 ESTs generated from −3- to +3-dpa fibers of Upland cotton
cv. TM-1, along with 211,397 cotton ESTs downloaded from GenBank (as of April
2006), resulting in 55,673 unigenes and updating The Institute of Genomic
Research Cotton Gene Index version 6 (CGI6) into CGI7 (http://www.tigr.org).  The unigene EST number may provide a
reasonable estimation about the number of expressed genes in the cotton
genomes. Of the unigene set, those derived from fibers or fiber-bearing ovules
suggest the number of genes potentially involved in fiber development and
genetic complexity of fiber traits.Table 5
Summary of cotton ESTs (as of May 2007).
GenotypesLibrary nameTissues usedNo. of ESTsNo. of unigenesAuthorsReferencesGossypium arboreum (A2):[100]AKA8401GA-Ea7- to 10-dpa fibers46,603Wing et al.(normalized)Arpat et al.Subtotal46,60313,947G. Raimondii (D5):GN34GR_EaWhole seedlings33,671Udall et al.with 1st true leavesGN34GR-Eb−3-dpa buds to33,061Udall et al.+3-dpa bollsSubtotal68,732G. hirsutum (AD1):Coker 312GH_MD8- to 10-dpa boll1,144Allen[101](irrigated)Coker 312GH_MDDS8- to 10-dpa boll1,238Allen(drought stressed)Coker 312GH_LDI15- to 20-dpa boll1,799Allen & Payton(irrigated)Coker 312GH_LDDI15- to 20-dpa boll1,409Allen & Payton(drought stressed)Acala MaxxaGH_BNL5-dpa fibers8,022Blewitt & BurrXu-142GH_FOX0- to 5-dpa ovule and7,997Gou & Chen1- to 22-dpa fibersDeltapine 90GH_SCW2nd versus 1st primary7,385Haigler &fibersWilkersonZhongmian 12GH_SUO0-dpa ovules1,240Suo & XueDeltapine 16GH-CHX−3- to 0-dpa ovules7,631Wu & DennisDeltapine 16GH_OCF0-dpa ovules867Wu and DennisDeltapine 16GH_ON0-dpa ovules5,903Wu & Dennis(normalized)Stv 7A glGH_ECT18 h etiolated seedlings2,880ChapmanDelta emeraldGH_CRHRoot and hypocotyls1,464Dowd & McFaddenDelta emeraldGH_CFUSRH tissues infected with820Dowd &Fusarium oxysporumMcFaddenSicotGH_LSLS9i leaves, late season1,810Faivre-Nitschke& DennisCoker 312GH_SDLSeedlings (control)1,918Klueva et al.Coker 312GH_SDLDSeedlings (drought1,142Klueva & Nguyenstressed)Coker 312GH_SDCHSeedling (chilling576Klueva & Nguyenstressed)Deltapine 16GH_IMEImmature embryo1,536Liu & DennisIm216GH_IMXLeaf 8, 14, 20, 30, 45,1,134Patil et al.60 hpiXanthomonasAcB4Blnb7GH_ACXELeaf8+14 hpi647Phillips et al.XanthomonasAcB4Blnb7GH_ACXMLeaf20+30 hpi1,328Phillips et al.XanthomonasAcB4Blnb7GH_ACXLLeaf45+60 hpi862Phillips et al.XanthomonasT25GH_pARLeaves1,230TrolinderDES119GH_STEMMature stem8,643TaliercioDP62GH_ECOTEtiolated cotyledon2,772Ni & Trelease91-D-92GH_CBAZBall abscission zone1,306Wan & Wing185,198(a)51,107[102]Texas Marker-1GH_TMO−3- to 3-dpa ovules32,7898,540Chen[103]−1 (TM-1)Not available5- to 10-dpa fibers29,99212,992ZhuXuzhou 142[104](Xu-142)Subtotal132,644Total247,979(a) The number was the sum of numbers of all ESTs above the line including those of G. arboreum, G. raimondii and G.
hirsutum [102]. Of the 247,979 cotton ESTs, 187,014 (75.4%) were from developing fibers or ovules
whereas 160,965 (24.6%) from nonfiber or nonovule organs.A predominant feature of the cotton EST set is the significant preference of
their tissue sources for fiber or fiber-bearing ovules than other organs. Of
the 247,979 ESTs listed in Table5, 187,080 (75.4%) were from developing fibers
or fiber-bearing ovules while only
60,899 (24.6%) were from nonfiber and
nonovule organs. Within each of the two categories, fiber/fiber-bearing ovules
and nonfiber/ovule organs, there is also a significant bias in the number of
ESTs. Cotton fiber development is classified into four clearly characterized,
but overlapping stages, including fiber initiation (−3 to 5 dpa), elongation (5–25 dpa), secondary cell wall deposition (15–45 dpa), and maturation/dehydration (45–70 dpa) (see Figure 3). All of the 187,080
fiber ESTs were generated from the fibers or fiber-bearing ovules collected
from the first three stages with 43.6% from the initiation stage, 46.5% from
the elongation stage, and 5.7% from the secondary cell wall deposition stage.
It is apparent that the number of fiber ESTs from the secondary cell wall
deposition stage is much smaller than that of either initiation or elongation
stage. Although the initiation and elongation stages are of significance for
the number of fibers per seed and fiber length, the secondary cell wall
deposition stage is crucial to fiber strength.
Of the 60,899 nonfiber/nonovule ESTs, 66.0% were from seedlings, 14.2%
from stems, and 2.4% from roots.Figure 3
Cotton fiber development and corresponding morphogenesis stages (according to [138, 139]). The initiation stage is characterized by the enlargement and protrusion of epidermal cells from the ovular surface; during the elongation stage the cells expend in polar directions with a rate of >2 mm/day; during the secondary cell wall deposition stage celluloses are synthesized rapidly until the fibers contain ∼90% of cellulose; and at the maturation stages minerals accumulate in the fibers and the fibers dehydrate.The
cotton ESTs have been used in several aspects, including development of
genome-wide cotton microarrays (see below), mining of SSRs (see above) and
study of polyploidization. The development of the significant numbers of ESTs
from the cultivated tetraploid cotton,G. hirsutum [(AADD)1], and its closely related
diploid species, G. arboreum (A1A1)
and G. raimondii (D5D5)
(see Table 5) made it possible to compare the transcriptomes among the three
species.  Udall et al. [102] comparatively analyzed 31,424, 68,732, and 69,853 ESTs
derived from G. arboreum, G. raimondii, and G. hirsutum, respectively. Although the comparison was
significantly affected by the tissue sources and developmental status, they
identified the putative homoeologs among the four genomes, A, D, A1,
and D5. This information is useful for our understanding of how the
cotton genomes function and evolve during the courses of speciation,
domestication, plant breeding, and polyploidization.Microarray
Microarray has been a technology that
is widely used in many aspects of genomics research, including gene discovery,
gene expression profiling, mutation assay, high-throughput genetic mapping,
gene expression mapping (eQTL mapping), and comparative genome analysis. It
involves robotically printing tens of thousands of cDNA amplicons or
gene-specific long (70 mers) oligonucleotides as array elements on a
chemically-coated glass slide, followed by hybridizing the array with one or more
fluorescent-labeled cDNA or cRNA targets derived from mRNA isolated from
particular tissues, organs, or cells. Therefore, it allows the simultaneous
monitoring of the expression/activities of all genes arrayed on the array in a
single hybridization experiment. To facilitate cotton genomics research,
microarrays have been developed from the cotton ESTs (Table5) in several
laboratories worldwide.
The
first batch of cotton microarrays was fabricated from 70-mers oligos designed
from the 7–10 dpa fiber nonredundant (NR) or unigene ESTs ofG. arboreum (Table 5) ([100]; http://cottongenomecenter.ucdavis.edu/microarrays.asp).
Each microarray consists of 12,227 elements corresponding to 12,227 NR fiber
ESTs, with a duplicate of each element. Using the microarrays, Arpat et al. [100] compared the expression of
the genes between 10-dpa fibers at elongation or primary cell wall synthesis
stage and 24-dpa fibers at secondary cell wall disposition stage (see Figure 3).
The expression of fiber genes was found to change dynamically from elongation
or primary cell wall to secondary cell wall biogenesis, with 2,553 of the fiber
genes being significantly downregulated and 81 being significantly upregulated.
This result suggests that the expression of fiber genes is stage-specific or
cell expansion-associated. Annotation of the genes upregulated in the secondary
cell wall synthesis relative to the primary cell wall biogenesis showed that
most of the genes felt in three major functional categories, energy/metabolism,
cell structure, organization and biogenesis, and cytoskeleton. This finding is
consistent with the fact of massive cellulose synthesis and cell wall
biogenesis during this stage. The fiber gene microarrays have been updated
recently by incorporating nearly 10,000 gene elements designed from the fiber
and ovary ESTs of the tetraploid cultivated cotton, G. hirsutum (Table 5; T.A. Wilkins, pers. communication). The
current fiber microarrays each slide consist of four duplicated arrays with
22,406 60-mers oligo elements per array and a duplicate of each element (see, e.g., Figure 4).  The new version of
fiber gene arrays covers 100% of the fiber ESTs of diploid cotton and 65% of
the fiber ESTs of the tetraploid cultivated cotton, G. hirsutum that are available in GenBank, thus representing the
most comprehensive coverage of the cotton fiber genes. The elements are printed
on a slide in a randomized manner instead of the conventional ordered manner.
The fabrication of four duplicated arrays per slide and randomized printing
design have significantly minimized the systematic problems that are frequently
encountered in the conventional array design (one array per slide and ordered
printing), thus further enhancing the reproducibility and accuracy of the
microarray analysis results.
Recently,
several additional batches of EST- or cDNA-based microarrays with different
formats and elements have been reported in cotton [102, 104, 140]. Shi et al. [104] reported the fabrication
of microarrays from unigene ESTs derived from 5–10 dpa ovules of the Upland cotton cv. Xuzhou
142 and using the amplicons of the EST clones as the array elements. The
microarrays each consist of 11,962 uniEST elements. Using the microarrays, Shi et al. [104] comparatively studied the
wild-type Xuzhou 142 versus its fuzzless-lintless (fl) mutation using the RNAs isolated
from the ovules at stages of 0-, 3-, 5-, 10-, 15-, and 20-dpa. It was found
that ethylene biosynthesis is one of the most significantly upregulated
biochemical pathways during fiber elongation. Similarly, Wu et al. [140] also fabricated a set of
microarrays from amplicons of 10,410 cDNA clones derived from −3- to 0-dpa
ovules of the Upland cotton cv. DP16 (see Table 5, Wu & Dennis).
The arrays were analyzed with RNAs isolated from 0-dpa whole ovules,
outer integument, and inner integument/nucellus of five lintless mutation lines
against the wild-type DP16. Of the 10,410 gene elements on the array, 60 to 243
were found to significantly differentially express between each pair of the
wild type and mutant when the array was hybridized with the RNAs isolated from
the 0-dpa whole ovules.  Of these
differentially expressed genes, 70.6% were upregulated and 29.4% downregulated
in the fiber mutant, suggesting that the mutation caused not only gene downregulation,
but also gene upregulation. However, when the whole ovule was dissected into
three layers, outer integument, inner integument, and nucellus, of which cotton
fibers develop from the epidermal cells of the outer integument, and analyzed
with the outer integument against the inner integument and the nucellus, the
number of the genes downregulated in the mutants was reduced to 13. These
include an Myb transcription factor,
a putative homeodomain protein, a cyclin D gene, and some fiber-expressed
structural and metabolic genes, suggesting that these genes may be involved in
the process of fiber initiation.
In summary, three batches of
EST- or cDNA-based cotton microarrays were fabricated from fiber genes of
either cultivated tetraploid cotton,G.
hirsutum [104, 140], or cultivated diploid
cotton, G. arboreum [100].  Using the microarrays, the expression of the
fiber genes was profiled and comparatively analyzed at fiber initiation stage
[140], elongation stage
[100, 104], and secondary cell wall
deposition stage [100].
However, the expression of other cotton genes such as those from nonfiber and
nonovary tissues remains to profile. To fill this gap, another two batches of
long oligo-based microarrays have been developed. The first batch contains approximately
21,000 gene elements per array  (http://cotton.agtec.uga.edu/CottonFiber/pages/mcriarray/Array.aspx).
These genes were from 52 cDNA libraries constructed from a variety of tissues
and organs in a range of conditions, including drought stress and pathogen
challenges, and represents tetraploid (G.
hirsutum) and its diploid relatives (G.
arboreum and G. raimondii).  Of the 21,000 genes, approximately one-forth
were from fiber genes and three-forth were from nonfiber and nonovary tissues
(J. A. Udall, pers. communication). The second batch contains 38,716 gene
elements per array. Of the gene elements, 22,409 are designed from fiber ESTs
and 16,307 from nonfiber ESTs (T.A. Wilkins, pers. communication). There is no
doubt that these versions of cotton microarrays will provide new tools for
comprehensive functional and comparative genomics research of cottons.Figure 4
Comparative analysis of the expression of fiber genes in 10-dpa fibers betweenG. hirsutum and  G. barbadense (M. Goebel, M. Alabady, C.W. Smith, T. A. Wilkins and H.-B. Zhang, unpublished). The cotton fiber microarrays are available in the laboratory of T. A. Wilkins, Texas Tech University (Texas, USA). One of the four arrays printed on a single slide is shown.


## 2.5. Physical Mapping

Whole-genome,
BAC- and/or BIBAC-based, integrated physical/genetic maps have played a central
role in genomics research of humans, plants, animals, and microbes [110, 123, 127]. This is because they provide central platforms for many areas, if not
all, of modern genomics research, including large-scale transcript or gene
mapping, region-targeted marker development for fine mapping and MAS of genes
and QTLs, map-based gene/QTL cloning, local- and whole-genome comparative
analysis, genome sequencing, and functional analysis of DNA sequences and
component network.  Therefore,
whole-genome, BAC/BIBAC-based, integrated physical/genetic maps have been
developed for a number of plant and animal species. In plants, whole-genome BAC
physical maps have been developed for several species, including Arabidopsis [114, 118], indica rice [121],
japonica rice [117],
soybean [124], and maize
[141]. However,
whole-genome physical maps of cottons have only been initiated in several
laboratories. One is the laboratory of H.-B. Zhang, Texas A&M University,
College Station (Texas, USA). This laboratory is developing a whole-genome
BAC/BIBAC physical map of the Upland cotton cv. TM-1 by using the latest
physical mapping technology [123, 126]. The project
was a collaborative effort among the laboratories of H.-B. Zhang, R. J. Kohel,
USDA/ARS, College Station (Texas, USA) (who provided a part of the fund for the
project), and D. M. Stelly, Texas A&M University (Texas, USA). Nearly 120,000
(∼7.3x) BIBACs and BACs selected from the TM-1 BIBAC and BAC libraries (see
Table 3) have been fingerprinted and a draft BAC/BIBAC contig map has been
constructed. The draft physical map consists of 5,088 contigs collectively
spanning approximately 2,300 Mb of the 2,400 Mb Upland genome (unpublished).
Currently, additional clones (to reach about 10x genome coverage clones) are
being analyzed. Furthermore, because the Upland cotton is an allotetraploid
which makes the physical map construction more complicated, several approaches
are being used to sort the map contigs according to their origin of subgenomes.
The laboratory of A. H. Paterson, University of Georgia (Athens, Georgia) is
also working toward development of a whole-genome BAC-based physical map of the
diploid species, G. raimondii (A. H.
Paterson, pers. communication). Given the importance of physical maps for
modern genome research, there is no doubt that development of a robust
integrated physical/genetic map will greatly promote advanced genomics research
of cottons and related species (also see below).


## 2.6. Genome Sequencing

Sequence
maps represent the most-fine physical maps of genomes [108]. They provide not only physical positions of and
distances between genes and other components constituting a genome [142], but also their sequences
and putative functions inferred from the sequences. Therefore, development of a
complete genome sequence map of a species will significantly promote genomics
research of the species in a variety of aspects. Because of this reason, the
whole genomes of several plant and animal species have been sequenced. In
plants, the genomes of two model species, Arabidopsis [130] and rice [132], have been completely sequenced and the genomes
of several other species, including Medicago
truncatula (http://www.medicago.org), Lotus
japonicus (http://www.kazusa.or.jp/lotus), tomato (http://www.sgn.cornell.edu/about/tomato_sequencing.pl),
maize (http://www.maizegenome.org),
and soybean (http://genome.purdue.edu/isgc/Tsukuba07/ISGC_report_Apr2007.htm),
are currently being sequenced.However,
there is only a limited amount of genomic sequences available for cotton and
related species in GenBank.  A major
source of the genomic sequences ofGossypium species was from Hawkins et al. [143]. To understand the underlying genome size variation and evolution of Gossypium species, Hawkins et al. [143] constructed whole-genome
shotgun libraries for G. raimondii (D5D5), G. herbaceum (A1A1), G. exiguum (KK), and the species that
was used as the outgroup species for phylogenetic analysis of the Gossypium species, Gossypioideskirkii, with
each species library containing 1920–10,368 clones. From each of the four shotgun
libraries, 1,464–6,747 clones were sequenced, together covering
a total length of 11.4 Mb. Annotation of these clone sequences and estimation
of the copy number of each type of the sequences suggested that differential
lineage-specific amplification of transposable elements is responsible for
genome size variation in the Gossypium species. Moreover, G. raimondii has
been selected recently by the DOE Joint Genome Institute, U.S. Department of
Energy to be sequenced for genomic study of cotton and related species (http://www.jgi.doe.gov/sequencing/cspseqplans2007.html).
At the first phase of the sequencing project, a whole-genome shotgun library
covering about 1x of the G. raimondii genome will be sequenced.  While this
number is far from the genome coverage of clones (>6x) that is needed to
assemble the sequence map of the genome, it will provide the first glimpse into
the cotton genome and useful information for sequencing the entire genomes of
this and other cotton key species efficiently.


## 3. Applications of Genomic Tools in Cotton Genetic Improvement

One
of the major goals of genome research is to use the genomic tools developed to
promote or assist continued crop genetic improvement. In cottons, the
development of the genomic resources and tools has allowed addressing many
significantly scientific questions that are impossible to do so before. These
include, but not limited to, construction of genome-wide genetic maps (Table1), identification and mapping of genes and loci controlling traits underlying
qualitative and quantitative inheritance (Table 2), determination of mechanisms
of cotton genome evolution, and identification and determination of genes that
are involved in cotton fiber initiation, elongation, and secondary cell wall
biogenesis. The genomic resources and tools could be used to promote or
facilitate cotton genetic improvement in numerous ways.  Marker-assisted selection (MAS) is likely one
of the most important and practical applications at present time and in near
future. The MAS technology could offer many potential benefits to a breeding
program. For instance, DNA linked to a gene of interest could be utilized in
early generation of breeding cycle to improve the efficiency of selection. This
approach has a particular advantage when screening for phenotypes in which the
selection is expensive or difficult to perform, as is the case involving
recessive or multiple genes, seasonal or geographical considerations, and late
expression of the phenotype [144]. However, application of MAS in cotton breeding programs is still
in its infancy as the major effort of cotton genome research in the past has
been on the development of genomic resources and tools for the eventual goal of
enhanced cotton genetic improvement.Fiber quality
Zhang et al. [53] used a G. anomalum introgression line 7235 with good fiber quality properties to identify
molecular markers linked to fiber-strength QTLs. A major QTL, QTLFS1, was detected at the Nanjing and
Hainan field locations (China) and College Station, Texas, (USA). This QTL was
associated with eight markers and explained more than 30% of the phenotypic
variation. QTLFS1 was first thought
to be mapped to chromosome 10, however, further study showed that this QTL was
located on LGD03 [67].
Guo et al. [145] showed that the
specific SCAR4311920 marker could be applied to large-scale screening for the
presence or absence of this major fiber strength QTL in breeding populations.
The DNA markers tightly linked to this QTL could be useful for developing
commercial cultivars with enhanced fiber length properties [67].
Wang et al. [76] identified a stable fiber length QTL, qFL-D2-1, simultaneously in four environments in Xiangzamian 2. The
high degree of stability suggests this QTL might be particularly valuable for
use in MAS programs. Chee et al. [59] dissected the molecular basis of genetic variation governing 15
parameters that reflect fiber length by applying a detailed RFLP map to 3,662
BC3F2 plants from 24 independently derived BC3 families utilizing G. barbadense as
the donor parent. The discovery of many QTLs unique to each trait indicates
that maximum genetic gain will require breeding efforts that target each trait.
Lacape et al. [64] performed QTL
analysis of 11 fiber properties in BC1, BC2, and BC2S1 backcross generations derived from the cross between G. hirsutum “Guazuncho 2” and G.
barbadense “VH8.” They detected 15, 12, 21, and 16 QTLs for length,
strength, fineness, and color, respectively, in one or more populations. The
results showed that favorable alleles came from the G. barbadense parent for the majority of QTLs, and cases of
colocalization of QTLs for different traits were more frequent than isolated
positioning. Taking these QTL-rich chromosomal regions into consideration, they
identified 19 regions on 15 different chromosomes as target regions for the
marker-assisted introgression strategy. The availability of DNA markers linked
to G. barbadense QTLs promises to
assist breeders in transferring and maintaining valuable traits from exotic
sources during cultivar development.Cytoplasmic male sterility
In cotton, cytoplasmic male sterility conditioned by the D8 alloplasm (CMS-D8) is
independently restored to fertility by its specific D8 restorer (D8R) and by
the D2 restorer (D2R) that was developed for the D2 cytoplasmic male sterile
alloplasm (CMS-D2). Zhang and Stewart [146] concluded that the two restorer
loci are nonallelic, but are tightly linked with an average genetic distance of
0.93 cM. The D2 restorer gene is redesignated as Rf1, and Rf2 is assigned
to the D8 restorer gene. The identification of molecular markers closely linked
to restorer genes of the cytoplasmic male sterile could facilitate the
development of parental lines for hybrid cotton. Guo et al. [147] found that one RAPD marker fragment, designated
OPV-15(300), was closely linked with the fertility-restoring gene Rf1. Zhang and Stewart [148] identified
RAPD markers linked to the restorer gene and, furthermore, converted the three
RAPD markers into reliable and genome-specific sequence tagged site (STS)
markers. Liu et al. [51] determined
that the Rf1 locus is located on the
long arm of chromosome 4. Two RAPD and three SSR markers were identified to be
closely linked to the Rf1 gene. These
markers are restorer-specific and should be useful in MAS for developing
restorer parental lines. Yin et al. [54] further constructed a high-resolution genetic map of Rf1 containing 13 markers in a genetic
distance of 0.9 cM. They constructed a physical map for the Rf1 locus and enclosed the possible
location of the Rf1 gene to a minimum
of two BAC clones spanning an interval of approximately 100 kb between two
clones, designated as 081-05K and 052-01N. Work to isolate the Rf1 gene in cotton is now in progress.Resistance to diseases and insect pests
Breeding for disease resistance is of great importance in cotton breeding program. To facilitate
analysis, cloning, and manipulation of the genes conferring resistance to
different pathogens, including bacteria, fungi, viruses, and nematodes, He et al. [149] isolated and characterized
the family of nucleotide-banding site-leucine-rich repeat (NBS-LRR)-encoding
genes or resistance gene analogues (RGAs) in the Upland cotton cv. Auburn 634
genome. Genetic mapping of a sample (21 genes) of the RGAs indicated that the
gene family resides on a limited number of the cotton AD-genome chromosomes
with those from a single subfamily tending to cluster on the cotton genetic map
and more RGAs in the A subgenome than in the D subgenome. Of the 16 RGAs
mapped, two happened to be comapped with the cotton bacterial blight resistance
QTLs previously mapped by Wright et al. [42].  Since nearly 80% of the genes
(>40 genes) cloned to date that confer resistance to bacteria, fungi,
viruses, and nematodes are contributed by the NBS-LRR gene family, the cotton
RGAs of the NBS-LRR family have provided valuable tools for cloning,
characterization, and manipulation of the resistant genes to different
pathogens and pests in cottons.
Root-knot
nematodes (RKN),Meloidogyne incognita, can cause severe yield loss in cotton. Wang et al.  [71] identified one SSR marker CIR316 on the linkage group A03
tightly linked to a major RKN resistant gene (rkn1) in the resistant cultivar G.
hirsutum “Aacla NemX.” In a companion study, a bulked segregant analysis
(BSA) combined with AFLP was used to identify additional molecular markers
linked to rkn1 [72]. An AFLP marker linked to rkn1 designated as GHACC1 was converted to a cleaved amplified polymorphic sequence
(CAPS) marker. These two markers have potential for utilization in MAS. Shen et al. [68] identified RFLP markers
on chromosome 7 and chromosome 11 showing significant association with RKN
resistance from the Auburn 634 source, a different source of resistant
germplasm than Acala NemX. The association was further confirmed by detection
of a minor and a major dominant QTL on chromosomes 7 and 11, respectively,
using SSR markers. Ynturi et al. [73] identified two SSR markers which together accounted for 31% of the
variation in galling index. The marker BNL 3661 is mapped to the short arm of
chromosome 14 while BNL 1231 to the long arm of chromosome 11. The association
of two different chromosomes with RKN resistance suggests at least two genes
are involved in resistance to RKN.
Bacterial blight
caused by the pathogenXanthomonas campestris pv. malvacearum (Xcm) is another economically important disease in cotton. Wright et al. [42] and Rungi et al. [43] both used mapped RFLP
markers to investigate the chromosomal location of genes conferring resistance
to the bacterial blight pathogen. The mapping data suggest that the resistance
locus segregates with a marker on chromosome 14 known to be linked to the
broad-spectrum B12 resistance gene
originally from African cotton cultivars. AFLPs and SSRs were also used to
search for novel markers linked to the Xcm resistance locus to facilitate introgression of this trait into G. barbadense through MAS.


## 4. Concluding Remarks

A significant amount of genomic
resources and tools has been available in cottons though cotton genomics
research is far behind those of other major crops such as rice, maize, wheat,
and soybean. These resources and tools have allowed identifying and mapping many
genes and QTLs of importance to cotton fiber quality, fiber yield, and biotic
and abiotic stresses and addressing several significant questions to plant
biology in general and to cotton in particular.
Nevertheless, many efforts are needed to further develop the resources
and tools and to make the tools readily usable in applications in order to
fully and effectively use them in cotton genetic improvement and biology
research. In particular, the following areas of cotton genomics research should
be emphasized.(i)Development of whole-genome BAC/BIBAC-based, integrated physical maps
of cottons. There is no whole-genome, robust BAC/BIBAC-based, integrated
physical/genetic map that has been developed for cottons. The maps should be
developed for at least two species of Gossypium. One is the Upland cotton that produces >90% of the world’s cotton whereas
the other is G. raimondii, the
species having the smallest genome among all Gossypium species, thus likely having highest density of genes. This
research is emphasized because it has been proven in model and other species,
including Arabidopsis, rice, Drosophila, human, mouse, and chicken,
that whole-genome integrated physical/genetic maps provide powerful platforms
and “freeways” for many, if not all, modern genetics and genomics research
([110, 123, 127]; see above). These include not only genome sequencing (see below),
but also development of closely linked, user-friendly DNA markers for any
region or loci of the genome, fine QTL and gene mapping (see below), map-based
gene/QTL cloning, and high-throughput and high-resolution transcript (unigene
EST) mapping [150].
Development of the integrated physical maps will allow rapidly and efficiently
integrating all existing genetic maps, mapped genes and QTLs, and BAC and BIBAC
resources and cotton unigene ESTs, and accelerate the efficiency and reduce the
cost of research in all areas by manifold.(ii)QTL fine mapping. Many genes and QTLs that are important to cotton
fiber yield fiber quality, and biotic and abiotic stresses have been
genetically mapped, but two problems are apparent. The first one is that almost
all of the QTLs were mapped using F2, BC1, or early
segregating generations in a single or a limited number of environments (Table 2). Since quantitative traits are readily subjected to environmental variation,
the mapping results using the early generations in a single or a limited number
of environments would vary from experiments to experiments [59, 60, 106]. The other problem is that the genetic distances between DNA markers and
most of the QTLs are too far to be used for MAS. Therefore, it is of
significance to fine map the QTLs using large and advanced generation or
homozygous populations, such as RILs and DHs, in multiple environments, and
closely linked DNA markers, for which advantage of integrated physical maps
could be taken. In addition to accurate mapping of the QTLs and development of
DNA markers that are well-suited (closely linked and user-friendly) for MAS,
fine mapping is also an essential step toward the final isolation of the QTL
genes by map-based cloning [134]. The isolated genes are not only the
sources for molecular breeding via genetic transformation, but also the most
desirable for marker development for MAS because there is no recombination
between the gene and its derived marker.(iii)Sequencing of one or more key cotton genomes. While it is costly
using the current sequencing technology, whole-genome sequencing is a most-efficient
method to discover and decode all cotton genes and provides a most-desired and most-fine
integrated physical and genetic map of the cotton genome. Comparative genomics
studies demonstrated that the gene contents and orders are highly conserved
among the genomes of Gossypium species even they are significantly different in genome size [16, 24]. Based on this result, G. raimondii is an excellent choice to be sequenced because it has
the smallest genome among all Gossypium species though it is not cultivated. If an integrated physical map is available
for the major cultivated cotton, G.
hirsutum, that has a three-fold larger genome than G. raimondii, the sequence information of G. raimondii could be readily
transferred to the cultivated cotton by using the BAC end sequences of its
integrated physical map as anchors.(iv)ESTs from nonfiber and nonovary tissues and fibers at the secondary
cell wall deposition stage. As shown above, the number of cotton ESTs
available in GenBank has been increased significantly in the past few years;
however, the distribution of the ESTs among tissue sources are extremely
biased. The numbers of ESTs from both nonfiber/nonovary tissues and fibers at
the secondary cell wall deposition stage (15–45 dpa), particularly after 20 dpa, are
especially small. The former set of expressed genes, despite of not directly
contributing to fiber yield and quality, is of significance to fiber yield and
quality, whereas there is no doubt that the later set of expressed genes
directly contribute to the fiber strength.(v)Profiling and identification of genes involved in individual biological
processes and conditions with emphasis on those involved in fiber development. Development and availability of cDNA- or unigene EST-based microarrays have
provided unprecedented opportunities for research of molecular biology,
functional genomics, and evolutionary genomics, however, cotton research in
these regards are very limited. Identifying and characterizing genes that are
involved in the processes of fiber development, plant growth and development,
and biotic and abiotic stresses will greatly facilitate our understanding of
underlying molecular basis of these processes in cottons, and thus, enhance
breeders’ ability to cotton genetic improvement.(vi)Translating the gene activities or expressions at different tissues and
stages into fiber yield and fiber quality, thus assisting in cotton breeding. The
genes that are involved in fiber initiation [104, 140], elongation [100, 104], and secondary
cell wall deposition [100] have been identified from several genotypes of cottons, but it is unknown
about what the up- or downregulation, or active expression of fiber genes at a
developmental stage and organ means to final fiber yield and/or quality. For
instance, does the active expression of a gene at fiber elongation stage in
fiber suggest longer fibers? Studies in this regard are essential to use the
gene expression data in cotton germplasm analysis and breeding.



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*Source: 742304-2008-01-23.xml*