BACKGROUND
soybeans  contain complete protein and oil, providing all the essential amino acids necessary for the human diet  <cit> .
hence, a great effort has been made to increase soybean yield, while maintaining a high level of quality characteristics  <cit> .
yield and quality-related traits of soybean are quantitative traits that are controlled by a combination of genetic and environmental factors  <cit> .
the genetic maps with traditional molecular markers including restriction fragment length polymorphism , simple sequence repeats  and amplified fragment length polymorphism  have been traditionally used to identify the genetic basis of complex traits in plants .
however, conventional molecular markers often display a low density and are unevenly distributed throughout the whole genome.
therefore, the genetic maps developed using these molecular markers have limited both the efficiency and accuracy of qtl positioning.
recently, with the rapid development of high-throughput sequencing technology, single nucleotide polymorphism  markers have emerged as new molecular markers of choice because of their high-density and relatively even distribution across plant genomes.
further, they have resolved many of the problems associated with the efficiency and accuracy of qtl mapping .
several new technologies for snp genotyping have been developed over the last few years.
a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing to construct a dense genetic map using recombination bins as markers was developed by huang et al.
<cit> .
restriction-site associated dna sequencing , was one of the next generation sequencing  methods, has been effectively applied in high-throughput snp marker discovery and quantitative trait loci  analysis including the mapping of quality and agronomic trait loci in soybean  <cit> .
based on these new technologies for snp genotyping, numerous qtls associated with yield or quality traits have been identified in soybean .
for example, kim et al.
evaluated two populations for seed yield and other agronomic traits using  <dig> snp markers.
in total,  <dig> qtls for plant height and  <dig> qtls for seed yield were identified  <cit> .
in another study, two qtls for protein content and six oil content qtls were identified by akond and colleagues using a ril population derived from a cross of pi43848913 × hamilton  <cit> .
further, a high density map was developed using the  <dig> snp markers from the illumina infinium beadchip array.
in addition, one protein and  <dig> oil content qtls were detected in the md96– <dig> by ‘spencer’ rils population  <cit> .
hwang et al.
detected  <dig> snps associated with seed protein content and  <dig> snps associated with seed oil content.
among these markers,  <dig> snps were found to be significantly associated with both protein and oil content  <cit> .
the objectives of this research reported here were  to develop a high-density soybean molecular genetic bin map with the rad-seq method, and  to map qtls for yield and quality-related traits in the ril population and compare these data with previous research ,  to determine if any qtls were identified in both years and were co-localized with any other trait-related qtls,  to select candidate genes that may influence both yield and quality using gene ontology  enrichment analysis.
methods
plant materials and field trials
a ril population was developed from a cross between zhonghuang  <dig>  and huaxia  <dig>  using a modified single seed method  <cit> .
zhonghuang  <dig> is a variety with high-oil content adaptive to huang-huai-hai region.
huaxia  <dig> was derived from a cross between ‘guizao 1’ and ‘brsmg <dig> ’ that is a high-yielding soybean cultivar.
the 164 f <dig> rils were grown together with both parents at the zengcheng experimental station  following a randomized complete block planting with three replications in the summer of  <dig>  each plot contained  <dig> plants per row, with  <dig>  m between rows and  <dig>  m between plants.
the 146 f <dig> rils were grown using the same methods in the same location in  <dig>  field management followed normal soybean production practices for the area.
measurement of yield-related and two quality traits
the five plants in the middle of each row were individually harvested to score the following traits: plant height , number of nodes , number of branches , number of effective pods , number of invalid pods , 100-seed weight , seed protein content  and seed oil content .
ph was measured in mature plants as the distance  from the cotyledonary node to the top node of the main stem.
nn was measured by counting the number of nodes from the cotyledonary node to the top of the main stem.
bn was determined by counting the number of branches with podding on the main stem.
ep were obtained by counting the number of pods with more than one filled seed per pod.
ip were obtained by counting number of pods that did not contain seed.
sw was measured by weighing  <dig> random filled seeds.
50 g of seed from each line were used for protein and oil determination by an infratec  <dig> grain analyzer based on 10% moisture.
frequency distribution and correlation analysis for the parental and ril population were analyzed with the spss statistics  <dig>  and microsoft excel  <dig>
genetic map and qtl detection
snp genotyping
all the genotyping work was conducted at the beijing genome institute  tech, shenzhen, china.
the soybean reference genome from williams  <dig> was used for read mapping with soap software  <cit> .
input data for snp calling with realsfs was prepared by samtools  <cit> .
according to site frequency at every site, population snp calling was performed with realsfs.
the likelihoods of genotypes for each individual were integrated and extracted as candidate snps and then filtering these snps using the following criteria: 40 ≤ depth ≤  <dig> sites with a probability ≥ 95%.
the homozygous genotype of parents and their populations were obtained based on the high fidelity-snps.
according to the sliding window approach, we chose to include  <dig> snps per window, identifying the genotype for each window and the exchange sites for each individual when sliding a snp every time, and then using the genotype for each individual to generate bin information  <cit> .
qtl analysis
a high-density genetic map was constructed using mst software .
the composite interval mapping  method was employed to scan qtls.
the lod thresholds for qtl significance were determined by a test  with a genome-wide at the 5% level of significance to judge whether there exist qtl.
the location of a qtl was described according to its lod peak location and the surrounding region with 95% confidence interval calculated using winqtlcart software  <cit> .
running result of software can show additive effects of qtls and phenotypic variation.
the lod values were shown in additional file  <dig>  qtl mapping results were comprehensively compared to soybase .
method for naming qtls
all qtls were named according to cui et al.
as follows  <cit> : initial ‘q’ denotes ‘qtl’; the letters following it are the abbreviation of the corresponding traits; the next number is the soybean chromosomes on which the corresponding qtl is distributed; then, ‘a’ and ‘b’ represent whether the qtl was identified in  <dig> and  <dig>  respectively; if more than one qtl for a certain trait was dispersed along a certain chromosome, a serial number, viz.- <dig>   <dig>  etc., is used after ‘a’ or ‘b’ to describe their order.
RESULTS
phenotypic analysis of the ril population
most of the traits of huaxia  <dig> showed higher values compared with those of zhonghuang  <dig>  providing ideal material for population construction and qtl analysis, with the exception of oil .
figure  <dig> shows the frequency distribution for eight traits in 2 years.
phenotypic values were found to be continuous with normal or skew normal distributions.
transgressive segregation in the rils was shown for eight traits, suggesting that alleles with positive effects on the measured traits are distributed among the parents.fig.
<dig> frequency distribution for eight traits in  <dig>  and  <dig>
the correlation analysis showed that most of the yield-related traits were correlated with each other in both years .
ph was positively correlated with nn, bn, ep, ip and sw, except for ep and ip in  <dig> and sw in  <dig> where it was not significant.
nn also showed significant positive correlations with bn and ep in both years, but no correlation was detected with sw. significant negative correlations were found for sw with bn and ep, ranging from r = − <dig> ** to r = − <dig> **in both years, but have a significant positive correlation with protein  in  <dig>  most previous studies reported that there is a strong negative correlation between seed protein and seed oil content  <cit> .
in our study, a highly significant negative correlation  was observed between protein and oil in both years.table  <dig> phenotypic correlations between yield-related traits and quality traits in  <dig> and 2015
abbreviations: ph plant height, nn number of nodes, bn number of branches, ep number of effective pods, ip number of invalid pods, sw 100-seed weight, pro seed protein content, oil seed oil content
**means significant correlation at p <  <dig> ;* means significant correlation at p <  <dig>
athe data used was generated in summer 2012
bthe data used was generated in summer 2015
high-density snp linkage map construction
based on  <dig> × rad-seq  of the zhonghuang  <dig> and huaxia  <dig> ril population,  <dig> g sequence reads were obtained and the average read number was  <dig>  m. half of them have more than 200 m reads.
according to this data, a total of  <dig>  high-quality polymorphic snp sites were detected for the rils.
all of the snp sites in the rils were integrated into a recombination bin unit, and  <dig> recombinant bins were obtained.
the average physical length of the bins was  <dig>  kb, ranging from  <dig>  kb to  <dig>  mb.
a total of  <dig> bins’ length were less than 100 kb,  <dig> bins ranging from 100 kb to 200 kb,  <dig> bins from 200 kb to 300 kb,  <dig> bins from 300 kb to 400 kb and  <dig> bins above 400 kb.
based on the genotypes of  <dig> bins, a high-density bin linkage map was constructed covering  <dig>  cm, with an average distance of  <dig>  cm between adjacent markers.
for each chromosome, the average genetic distance between adjacent bins ranged from  <dig>  to  <dig>  cm .
therefore, the linkage map constructed with recombination bins resulted in well-distributed linkage distances and has higher resolution than conventional maps.table  <dig> description of characteristics of  <dig> chromosomes in the high-density genetic map
achr indicates chromosome
qtl analysis for yield-related traits
forty-seven qtls associated with yield-related traits including ph, nn, bn, ep, ip and sw, were identified on  <dig> chromosomes  .
a single qtl explained  <dig> % - <dig> %  of phenotypic variance.
among the qtls,  <dig> were identified on ten chromosomes in  <dig>  the most prominent qtl with the highest lod score  was identified in a 56 kb region, which we designated qnn19a, explained  <dig> % of phenotypic variation and displayed a negative additive effect, mainly with the positive allele from the male parent huaxia  <dig>  nineteen qtls on nine chromosomes were detected in  <dig>  and qph19b- <dig> has the most significant lod score , explaining  <dig> % of phenotypic variation and showed negative additive alleles from the male parent huaxia  <dig>  of these qtls,  <dig> were in agreement with earlier reports and  <dig> qtls were found to be novel .
eight qtl clusters responsible for more than two traits were detected on four different chromosomes .
a total of  <dig> qtls were stable across both years.
thirty-four of these qtls had a positive additive effect, which were contributed from the female parent zhonghuang  <dig>  whereas  <dig> qtls had a negative effect, with additive alleles from the male parent huaxia  <dig> fig.
<dig> the positions of qtls for eight traits.
<dig> qtls for eight traits identified across 2 years are depicted in different shapes on the right side of each linkage group.
<dig> qtls identified in  <dig> are colored in blue and  <dig> qtl identified in  <dig> are highlighted in red
qph04ad
qph04bd
qnn04a-1d
qnn19ad
qnn04bd
qnn19bd
qep11ad
qep11bd
qip17ad
qip17bd
achr indicates chromosome
blod indicates the logarithm of odds score
cpercentage of phenotypic variation explained
dmarked by qtl name indicates a new, stable qtl that was detected in both years
qtl analysis for quality traits
a total of  <dig> qtls were associated with quality traits on ten different chromosomes  in both growing seasons .
three qtls for protein content were identified on chr <dig>  chr <dig> and chr <dig> in  <dig>  respectively.
five qtls for oil content were identified on chr <dig>  chr <dig>  chr <dig>  chr <dig> and chr <dig>  with the phenotypic variance effect ranging from  <dig> %  to  <dig> % .
four qtls  showed positive additive effects ranging from  <dig>   to  <dig>  , while the other four qtls  showed negative additive effects that were from − <dig>  to − <dig> .
a qtl  for protein content was detected in a 52 kb region on chr <dig>  explaining  <dig> % of phenotypic variation in  <dig>  in addition, four qtls on chr <dig> and chr <dig> were identified for oil content, which individually explained  <dig> %  and  <dig> %  of the phenotypic variation.
within these qtls, three of them had positive additive effects, indicating that the female parent, zhonghuang  <dig>  contributed the trait for increased oil content.
a total of ten qtls were reported in prior studies, and three new qtls were identified for the first time in the present study.
the gene ontology enrichment analysis base on qtl hotpot
it was noteworthy that an important qtl hotspot was mapped in a physical position between  <dig> , <dig> and  <dig> ,371 bp on chr <dig>  seven qtls associated with five traits that explained up to  <dig> % of phenotypic variation, were all detected within this genomic region that was previously reported to be associate with seed weight, protein and oil in several different studies.
in order to gain an in- depth understanding of which genes/qtls were related to yield and quality in this region, we retrieved gene calls and annotations using glyma.wm <dig> a <dig> v <dig>  gene model from soybase .
a total of  <dig> genes were found within this region using gene ontology enrichment analysis, and among them,  <dig> annotated genes were closely related to yield or quality, which could be classified into five groups .
the first group contains  <dig> genes associated with phytohormone regulation, including hormones such as auxin, abscisic acid and ethylene, which play an essential role in coordination of in vitro and in vivo regulation mechanisms to simultaneously improve yield and quality  <cit> .
the second group is comprised of  <dig> genes that are associated with metabolic processes, including carbohydrate metabolism, lipid metabolism, fatty acid catabolism and brassinosteroid metabolism, which are known to have an effect on the growth and development of soybean.
the third group contains  <dig> genes associated with protein phosphorylation, which could be related to functional properties of food protein.
next, the fourth group is made up of  <dig> genes that are associated with cellular processes, including cell differentiation, cell proliferation, multicellular organism reproduction, and cell growth, which may have positive consequences for grain yield and quality in plants  <cit> .
the fifth group consists of  <dig> genes associated with organ morphogenesis, including the development of root, stamen, leaf and seedling, etc., even directly influence on soybean yield and quality.
discussion
main effect factors for qtl mapping
the utility of qtl mapping is to obtain valuable alleles and understand genetic mechanisms, thus promoting genetic improvement of soybean by molecular methods, which is one of the main objectives in soybean breeding.
parental genetic diversity, environmental effects, and marker density are the main factors affecting qtl mapping  <cit> .
in this study, the parents of the ril population are derived from geographically distinct locations.
zhonghuang  <dig> is a main variety grown in central china, while male parent, huaxia  <dig>  is derived from brazilian soybean germplasm that have high yield and become the main variety grown in southern china.
our data indicated that there were more differences in yield and quality-related traits between zhonghuang  <dig> and huaxia  <dig>  relative to other similarly performed studies.
thus, the detected qtls of these traits could be more useful for soybean improvement.
in addition, quantitative traits can be strongly affected by environment factors  <cit> .
in order to find qtls that are stably expressed across environments, we chose two non-consecutive years including  <dig> that was determined to be a suitable climate and  <dig>  which experienced greater than rainfall throughout all growth stages.
according to guangzhou meteorological service , the total rainfall from july to october was 433 mm in  <dig>  while 1023 mm for the same period in  <dig>  under these conditions, the qtls identified in both years can be considered robust and environmentally stable.
furthermore, qtl mapping based on the resequencing genotyping method resulted in the integration of a total of  <dig>  snps into  <dig> recombination bin units.
this was used to construct a high-density bin linkage map with an average distance of  <dig>  cm between adjacent markers.
the map has well-distributed linkage distances and higher resolution than the conventional map, making qtl mapping more accurate and reliable.
comparison of the present study with previous research
in the present study,  <dig> qtls were identified for ph, explaining  <dig>  to  <dig> % of phenotypic variation across the two growth seasons, of which, qph19a was major qtl associated with ph and was detected in both years.
this qtl has been previously reported by lee et al.
and specht et al.
<cit> .
it is worth noting the importance of the novel qtls  on chr <dig> identified in this study, because they expressed across both years and accounted for  <dig>  and  <dig> % of phenotypic variation, respectively.
three qtls  were identified on chr <dig>  which were in similar regions of those previously reported by wang et al.
and gai et al.
<cit> , respectively.
four novel qtls  were identified on chr <dig>  chr <dig> and chr <dig> for ph.
nn was found to be influenced by nine distinct qtls distributed across four chromosomes.
the qtl detected on chr <dig> in  <dig>  with an interval of  <dig> ,934– <dig> ,822 bp, was in a similar region  to another one identified in  <dig>  and it is likely that they are the same.
two qtls were identified on chr <dig>  qnn19a and qnn19b, which were consistent in both years and explained up to  <dig> % of phenotypic variation.
interestingly, no similar positions were found for nn in prior studies.
bn, a key constituent of soybean yield, has been studied extensively.
some researchers think that increasing production could be achieved through adjusting the branching number, and was confirmed by panthee et al.
<cit> .
in their study, sd yld24– <dig> was mapped for yield traits with satt <dig> on chr <dig>  interestingly, qbn19a which controls the number of branches in our study falls within this interval.
moreover, sd wt4– <dig> and sd wt11– <dig> for seed weight were identified by maughan and lee  <cit> , which was located at the same position as qbn11a, qep11a, and qep11b on chr <dig> in this study.
three other novel qtls  for bn were detected on chr <dig>  chr <dig>  and chr <dig>  accounting for  <dig>  to  <dig> % of phenotypic variation.
pod number and 100-seed weight are important parameters in measuring soybean yield and controlled by multiple genes.
two qtls, qep19a and qip19b, on chr <dig> were found to be associated with pod number during both years, and were located in the same region as those previously reported by zhang et al.
<cit> .
moreover, qsw19a- <dig> was shown to be associated with 100-seed weight, and is also mapped on chr <dig> near this interval.
orf et al.
reported a fine-mapped, 100-seed weight qtl located on chr <dig>  which just overlapped the intervals of the qtl for sw detected in both years in the present study  <cit> .
in our study, a total of  <dig> protein content qtls and  <dig> seed oil content qtls were identified in 2 years.
three qtls  were found to be novel, and no similar position has been identified previously for protein content.
ten of the  <dig> qtls relevant to protein or oil content detected in the present study were consistent with previous research, and some of them shortened the interval.
for example, a qtl associated with oil content, qoil06a, was found on chr <dig> .
palomeque et al.
also reported that a qtl for oil content fell within the same interval, and a similar locus regarding seed oil and ‘oil plus protein’ related traits was also published by other researchers  <cit> , which indicated that this qtl is stable and may have pleiotropic effects.
meanwhile, three other qtls  for yield-related traits were mapped to a similar region identified in our study, which explained  <dig>  to  <dig> % of phenotypic variation, respectively.
qoil20a was mapped in a 39 kb region to bin  <dig> on chr <dig> , which falls within the same region identified by both qi et al.
and reinprecht et al.
<cit> .
moreover, qsw20b- <dig>  for yield was also located near this position, suggesting that these two aforementioned regions should be of great value for genetic improvement of both soybean yield and quality.
the remaining qtls associated with protein or oil content in agreement with those of previous studies are presented in additional file  <dig> .
the coincidence of qtl across different genetic backgrounds not only reveals the stability and reliability of the qtl detected herein but also highlights the significance of these regions in marker breeding works designed to develop higher protein or oil soybean cultivars.
important qtl hotspots
most of the qtls were clustered in eight genomic regions, particularly on chr <dig>  chr <dig>  chr <dig> and chr <dig> .
these qtls hotspots included at least two traits such as ph, nn and sw, and was previously reported to be associated with some other traits in different genetic sources.
four qtls for yield-related traits were mapped in two intervals of  <dig> ,048– <dig> ,822 bp on chr <dig>  which explained  <dig> – <dig> % of phenotypic variation.
these qtls have not been published and add to the growing knowledge on the genetic control of these traits.
three other qtls were also detected on chr <dig>  explaining the range of phenotypic variation .
however, this region was reported to be associated with seed protein and seed weight in some earlier studies  <cit> .
seven qtls for ph, nn, bn, and oil were identified in two regions  that were separated by a distance of more than 7 cm on chr <dig>  and accounted for  <dig> – <dig> % of phenotypic variation.
previously, sun et al.
located two qtls for pod number on chr <dig> near these two regions  <cit> .
the first region on chr <dig> in the present study has been shown to be associated with different traits by other researches  <cit> .
moreover, chen et al.
found that two qtls for pod number and seed oil plus protein were consistent with the second region on chr <dig> in our study  <cit> .
more seed weight, protein and oil content qtls were mapped to this locus in previous studies  <cit> .
three qtls for bn and ep were identified on chr <dig> that explained  <dig> – <dig> % of phenotypic variation.
of these, two qtls for ep were expressed over 2 years.
three previously reported qtls for protein content and seed weight were located in this region  <cit> .
seven qtls were located in a physical position  on chr <dig>  of which qph19a, qnn19a and qph19b- <dig> have large effect  on phenotypic variation in comparison to the others.
mansur et al.
found two qtls associated with protein and oil were close to this region  <cit> .
orf et al.
also reported that this locus as associated with seed weight  <cit> .
in addition, three qtls  were detected on chr <dig>  in this study.
similar loci have been previously reported for seed weight, protein and oil content  <cit> .
another two qtls  on chr <dig> were mapped to the interval of  <dig> ,067– <dig> ,449 bp.
some of the seed weight qtls were detected near this position in past studies  <cit> .
moreover, qtls for protein and oil content were also previously identified in this region by both orf et al.
and qi er al.
<cit> .
interestingly, in this study, highly significant correlations were observed among ph, nn, bn, ep and sw. qtl mapping analysis showed that these traits were all linked to same region on three chromosomes , which is consistent with the conclusion of phenotypic correlation analysis, and provided a genetic explanation for these associations.
these qtl clusters may be cause of the pleiotropism or associations between the traits related.
every single cluster may function as an independent gene or closely linked genes  <cit> .
more importantly, some of those qtls on chr <dig>  chr <dig>  chr <dig>  and chr <dig> were identified in both years.
these chromosome regions can be considered robust and environmentally stable, which could be helpful for further studies aimed at simultaneously altering soybean yield and quality in a predictable manner.
three candidate genes on chr19
based on the predicted function of the five groups, three predicted genes  were selected as the best candidate genes that may affect both yield and quality because they are involved in various biological process .
glyma19g <dig> encodes a member of the basic leucine zipper transcription factor family, involved in arabidopsis abscisic acid signalling during seed maturation and germination.
go analysis showed that this gene participated in more than ten biological process, which include seed development, lipid storage, gibberellin biosynthesis, and vegetative to reproductive phase transition of the meristem, etc.
glyma19g <dig> gene has a domain predicted to encode a serine/threonine protein kinase that could influence cells in various ways.
this gene is related to the process of stem cell division, protein phosphorylation, gibberellin biosynthesis and timing of the transition from vegetative to reproductive development.
glyma19g <dig> encodes a plastidic triose phosphate isomerase, and go analysis revealed that this gene participates in three catabolic process  and four biosynthetic process .
moreover, it also plays a key role in multicellular organism reproduction and primary root development, which may have an effect on the yield and quality of crops.
in general, these three candidates should be investigated in more detail in further studies to increase our understanding regarding the factors involved in the process of improving quality and productivity in soybean.table  <dig> the information of three candidates’ annotations
the three candidate genes were selected in a physical position between  <dig> , <dig> and  <dig> ,371 bp on chr <dig>  seven qtls  associated with five traits were all detected within this genomic region
CONCLUSIONS
in this study, we genotyped a recombinant inbred line  population  using a restriction-site associated dna sequencing  approach.
a high-density soybean genetic map with  <dig> recombination bins was constructed and used to identify qtls that were shown to influence six yield-related and two quality traits.
a total of  <dig> qtls for six yield-related traits and  <dig> qtls for two quality traits were identified.
of these,  <dig> qtls detected herein were coincident with those of previous research .
eighteen qtls were stable qtls that were identified in 2 years.
twenty-six qtls were shown for the first time in this research, of which  <dig> were novel and stable qtls.
in addition, eight qtl hotspots on four chromosomes were identified for the correlated traits.
three predicted genes were selected as candidate genes that may directly or indirectly influence both yield and quality in soybean.
additional files
additional file 1: the distribution of lod values for eight traits.
maximum lod score of each major qtl is indicated next to the peak.
red lines indicated data was collected in  <dig>  blue lines indicated data was collected in  <dig>  different line colors indicate data collected in different years .
additional file 2: difference in agronomic traits between the parents and their recombinant inbred lines.
a the data used was generated in summer 2012; b the data used was generated in summer  <dig>
additional file 3: qtls detected in rils population that reported by previously studies.
**marked by qtl name indicates a new, stable qtl that was detected in both years; achr indicates chromosome; blod indicates the logarithm of odds score; c percentage of phenotypic variation explained; d related qtls have been reported in the previous studies of the region which was identified in the zhonghuang  <dig> and huaxi  <dig> rils population.
additional file 4:  <dig> qtl hotspots detected in zhonghuang24 × huaxia <dig> ril population in 2 years.
**marked by qtl name indicates a new, stable qtl that was detected in both years; achr indicates chromosome; blod indicates the logarithm of odds score; cpercentage of phenotypic variation explained.
additional file 5: annotation description of five gene groups based on go analysis.
abbreviations
bnnumber of branches on main stem
chrchromosome
cimcomposite interval mapping
epnumber of effective pod
gogene ontology
ipnumber of invalid pod
lodlogarithm of the odds
nnnumber of nodes on main stem
phplant height
qtlquantitative trait loci
snpsingle nucleotide polymorphisms
sw100-seed weight
r2phenotypic variance
rad-seqrestriction-site associated dna sequencing
rilrecombinant inbred line
electronic supplementary material
the online version of this article  contains supplementary material, which is available to authorized users.

 soybeans contain complete protein and oil, providing all the essential amino acids necessary for the human diet. hence, a great effort has been made to increase soybean yield, while maintaining a high level of quality characteristics. yield and quality-related traits of soybean are quantitative traits that are controlled by a combination of genetic and environmental factors. the genetic maps with traditional molecular markers including restriction fragment length polymorphism, simple sequence repeats and amplified fragment length polymorphism have been traditionally used to identify the genetic basis of complex traits in plants. however, conventional molecular markers often display a low density and are unevenly distributed throughout the whole genome. therefore, the genetic maps developed using these molecular markers have limited both the efficiency and accuracy of qtl positioning. recently, with the rapid development of high-throughput sequencing technology, single nucleotide polymorphism markers have emerged as new molecular markers of choice because of their high-density and relatively even distribution across plant genomes. further, they have resolved many of the problems associated with the efficiency and accuracy of qtl mapping. several new technologies for snp genotyping have been developed over the last few years. a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing to construct a dense genetic map using recombination bins as markers was developed by huang et al.. restriction-site associated dna sequencing, was one of the next generation sequencing methods, has been effectively applied in high-throughput snp marker discovery and quantitative trait loci analysis including the mapping of quality and agronomic trait loci in soybean. based on these new technologies for snp genotyping, numerous qtls associated with yield or quality traits have been identified in soybean. for example, kim et al. evaluated two populations for seed yield and other agronomic traits using snp markers. in total, qtls for plant height and qtls for seed yield were identified. in another study, two qtls for protein content and six oil content qtls were identified by akond and colleagues using a ril population derived from a cross of pi43848913 × hamilton. further, a high density map was developed using the snp markers from the illumina infinium beadchip array. in addition, one protein and oil content qtls were detected in the md96– by ‘spencer’ rils population. hwang et al. detected snps associated with seed protein content and snps associated with seed oil content. among these markers, snps were found to be significantly associated with both protein and oil content. the objectives of this research reported here were to develop a high-density soybean molecular genetic bin map with the rad-seq method, and to map qtls for yield and quality-related traits in the ril population and compare these data with previous research, to determine if any qtls were identified in both years and were co-localized with any other trait-related qtls, to select candidate genes that may influence both yield and quality using gene ontology enrichment analysis. methods plant materials and field trials a ril population was developed from a cross between zhonghuang and huaxia using a modified single seed method. zhonghuang is a variety with high-oil content adaptive to huang-huai-hai region. huaxia was derived from a cross between ‘guizao 1’ and ‘brsmg ’ that is a high-yielding soybean cultivar. the 164 f rils were grown together with both parents at the zengcheng experimental station following a randomized complete block planting with three replications in the summer of each plot contained plants per row, with  m between rows and  m between plants. the 146 f rils were grown using the same methods in the same location in field management followed normal soybean production practices for the area. measurement of yield-related and two quality traits the five plants in the middle of each row were individually harvested to score the following traits: plant height, number of nodes, number of branches, number of effective pods, number of invalid pods, 100-seed weight, seed protein content and seed oil content. ph was measured in mature plants as the distance from the cotyledonary node to the top node of the main stem. nn was measured by counting the number of nodes from the cotyledonary node to the top of the main stem. bn was determined by counting the number of branches with podding on the main stem. ep were obtained by counting the number of pods with more than one filled seed per pod. ip were obtained by counting number of pods that did not contain seed. sw was measured by weighing random filled seeds. 50 g of seed from each line were used for protein and oil determination by an infratec grain analyzer based on 10% moisture. frequency distribution and correlation analysis for the parental and ril population were analyzed with the spss statistics and microsoft excel genetic map and qtl detection snp genotyping all the genotyping work was conducted at the beijing genome institute tech, shenzhen, china. the soybean reference genome from williams was used for read mapping with soap software. input data for snp calling with realsfs was prepared by samtools. according to site frequency at every site, population snp calling was performed with realsfs. the likelihoods of genotypes for each individual were integrated and extracted as candidate snps and then filtering these snps using the following criteria: 40 ≤ depth ≤  sites with a probability ≥ 95%. the homozygous genotype of parents and their populations were obtained based on the high fidelity-snps. according to the sliding window approach, we chose to include snps per window, identifying the genotype for each window and the exchange sites for each individual when sliding a snp every time, and then using the genotype for each individual to generate bin information. qtl analysis a high-density genetic map was constructed using mst software. the composite interval mapping method was employed to scan qtls. the lod thresholds for qtl significance were determined by a test with a genome-wide at the 5% level of significance to judge whether there exist qtl. the location of a qtl was described according to its lod peak location and the surrounding region with 95% confidence interval calculated using winqtlcart software. running result of software can show additive effects of qtls and phenotypic variation. the lod values were shown in additional file qtl mapping results were comprehensively compared to soybase. method for naming qtls all qtls were named according to cui et al. as follows: initial ‘q’ denotes ‘qtl’; the letters following it are the abbreviation of the corresponding traits; the next number is the soybean chromosomes on which the corresponding qtl is distributed; then, ‘a’ and ‘b’ represent whether the qtl was identified in and respectively; if more than one qtl for a certain trait was dispersed along a certain chromosome, a serial number, viz.- etc., is used after ‘a’ or ‘b’ to describe their order.  phenotypic analysis of the ril population most of the traits of huaxia showed higher values compared with those of zhonghuang providing ideal material for population construction and qtl analysis, with the exception of oil. figure shows the frequency distribution for eight traits in 2 years. phenotypic values were found to be continuous with normal or skew normal distributions. transgressive segregation in the rils was shown for eight traits, suggesting that alleles with positive effects on the measured traits are distributed among the parents.fig. frequency distribution for eight traits in and the correlation analysis showed that most of the yield-related traits were correlated with each other in both years. ph was positively correlated with nn, bn, ep, ip and sw, except for ep and ip in and sw in where it was not significant. nn also showed significant positive correlations with bn and ep in both years, but no correlation was detected with sw. significant negative correlations were found for sw with bn and ep, ranging from r = − ** to r = − **in both years, but have a significant positive correlation with protein in most previous studies reported that there is a strong negative correlation between seed protein and seed oil content. in our study, a highly significant negative correlation was observed between protein and oil in both years.table phenotypic correlations between yield-related traits and quality traits in and 2015 abbreviations: ph plant height, nn number of nodes, bn number of branches, ep number of effective pods, ip number of invalid pods, sw 100-seed weight, pro seed protein content, oil seed oil content **means significant correlation at p < ;* means significant correlation at p <  athe data used was generated in summer 2012 bthe data used was generated in summer 2015 high-density snp linkage map construction based on × rad-seq of the zhonghuang and huaxia ril population, g sequence reads were obtained and the average read number was  m. half of them have more than 200 m reads. according to this data, a total of high-quality polymorphic snp sites were detected for the rils. all of the snp sites in the rils were integrated into a recombination bin unit, and recombinant bins were obtained. the average physical length of the bins was  kb, ranging from  kb to  mb. a total of bins’ length were less than 100 kb, bins ranging from 100 kb to 200 kb, bins from 200 kb to 300 kb, bins from 300 kb to 400 kb and bins above 400 kb. based on the genotypes of bins, a high-density bin linkage map was constructed covering  cm, with an average distance of  cm between adjacent markers. for each chromosome, the average genetic distance between adjacent bins ranged from to  cm. therefore, the linkage map constructed with recombination bins resulted in well-distributed linkage distances and has higher resolution than conventional maps.table description of characteristics of chromosomes in the high-density genetic map achr indicates chromosome qtl analysis for yield-related traits forty-seven qtls associated with yield-related traits including ph, nn, bn, ep, ip and sw, were identified on chromosomes. a single qtl explained % - % of phenotypic variance. among the qtls, were identified on ten chromosomes in the most prominent qtl with the highest lod score was identified in a 56 kb region, which we designated qnn19a, explained % of phenotypic variation and displayed a negative additive effect, mainly with the positive allele from the male parent huaxia nineteen qtls on nine chromosomes were detected in and qph19b- has the most significant lod score, explaining % of phenotypic variation and showed negative additive alleles from the male parent huaxia of these qtls, were in agreement with earlier reports and qtls were found to be novel. eight qtl clusters responsible for more than two traits were detected on four different chromosomes. a total of qtls were stable across both years. thirty-four of these qtls had a positive additive effect, which were contributed from the female parent zhonghuang whereas qtls had a negative effect, with additive alleles from the male parent huaxia fig. the positions of qtls for eight traits. qtls for eight traits identified across 2 years are depicted in different shapes on the right side of each linkage group. qtls identified in are colored in blue and qtl identified in are highlighted in red qph04ad qph04bd qnn04a-1d qnn19ad qnn04bd qnn19bd qep11ad qep11bd qip17ad qip17bd achr indicates chromosome blod indicates the logarithm of odds score cpercentage of phenotypic variation explained dmarked by qtl name indicates a new, stable qtl that was detected in both years qtl analysis for quality traits a total of qtls were associated with quality traits on ten different chromosomes in both growing seasons. three qtls for protein content were identified on chr chr and chr in respectively. five qtls for oil content were identified on chr chr chr chr and chr with the phenotypic variance effect ranging from % to %. four qtls showed positive additive effects ranging from to, while the other four qtls showed negative additive effects that were from − to −. a qtl for protein content was detected in a 52 kb region on chr explaining % of phenotypic variation in in addition, four qtls on chr and chr were identified for oil content, which individually explained % and % of the phenotypic variation. within these qtls, three of them had positive additive effects, indicating that the female parent, zhonghuang contributed the trait for increased oil content. a total of ten qtls were reported in prior studies, and three new qtls were identified for the first time in the present study. the gene ontology enrichment analysis base on qtl hotpot it was noteworthy that an important qtl hotspot was mapped in a physical position between, and,371 bp on chr seven qtls associated with five traits that explained up to % of phenotypic variation, were all detected within this genomic region that was previously reported to be associate with seed weight, protein and oil in several different studies. in order to gain an in- depth understanding of which genes/qtls were related to yield and quality in this region, we retrieved gene calls and annotations using glyma.wm a v gene model from soybase. a total of genes were found within this region using gene ontology enrichment analysis, and among them, annotated genes were closely related to yield or quality, which could be classified into five groups. the first group contains genes associated with phytohormone regulation, including hormones such as auxin, abscisic acid and ethylene, which play an essential role in coordination of in vitro and in vivo regulation mechanisms to simultaneously improve yield and quality. the second group is comprised of genes that are associated with metabolic processes, including carbohydrate metabolism, lipid metabolism, fatty acid catabolism and brassinosteroid metabolism, which are known to have an effect on the growth and development of soybean. the third group contains genes associated with protein phosphorylation, which could be related to functional properties of food protein. next, the fourth group is made up of genes that are associated with cellular processes, including cell differentiation, cell proliferation, multicellular organism reproduction, and cell growth, which may have positive consequences for grain yield and quality in plants. the fifth group consists of genes associated with organ morphogenesis, including the development of root, stamen, leaf and seedling, etc., even directly influence on soybean yield and quality. discussion main effect factors for qtl mapping the utility of qtl mapping is to obtain valuable alleles and understand genetic mechanisms, thus promoting genetic improvement of soybean by molecular methods, which is one of the main objectives in soybean breeding. parental genetic diversity, environmental effects, and marker density are the main factors affecting qtl mapping. in this study, the parents of the ril population are derived from geographically distinct locations. zhonghuang is a main variety grown in central china, while male parent, huaxia is derived from brazilian soybean germplasm that have high yield and become the main variety grown in southern china. our data indicated that there were more differences in yield and quality-related traits between zhonghuang and huaxia relative to other similarly performed studies. thus, the detected qtls of these traits could be more useful for soybean improvement. in addition, quantitative traits can be strongly affected by environment factors. in order to find qtls that are stably expressed across environments, we chose two non-consecutive years including that was determined to be a suitable climate and which experienced greater than rainfall throughout all growth stages. according to guangzhou meteorological service, the total rainfall from july to october was 433 mm in while 1023 mm for the same period in under these conditions, the qtls identified in both years can be considered robust and environmentally stable. furthermore, qtl mapping based on the resequencing genotyping method resulted in the integration of a total of snps into recombination bin units. this was used to construct a high-density bin linkage map with an average distance of  cm between adjacent markers. the map has well-distributed linkage distances and higher resolution than the conventional map, making qtl mapping more accurate and reliable. comparison of the present study with previous research in the present study, qtls were identified for ph, explaining to % of phenotypic variation across the two growth seasons, of which, qph19a was major qtl associated with ph and was detected in both years. this qtl has been previously reported by lee et al. and specht et al.. it is worth noting the importance of the novel qtls on chr identified in this study, because they expressed across both years and accounted for and % of phenotypic variation, respectively. three qtls were identified on chr which were in similar regions of those previously reported by wang et al. and gai et al., respectively. four novel qtls were identified on chr chr and chr for ph. nn was found to be influenced by nine distinct qtls distributed across four chromosomes. the qtl detected on chr in with an interval of,934–,822 bp, was in a similar region to another one identified in and it is likely that they are the same. two qtls were identified on chr qnn19a and qnn19b, which were consistent in both years and explained up to % of phenotypic variation. interestingly, no similar positions were found for nn in prior studies. bn, a key constituent of soybean yield, has been studied extensively. some researchers think that increasing production could be achieved through adjusting the branching number, and was confirmed by panthee et al.. in their study, sd yld24– was mapped for yield traits with satt on chr interestingly, qbn19a which controls the number of branches in our study falls within this interval. moreover, sd wt4– and sd wt11– for seed weight were identified by maughan and lee, which was located at the same position as qbn11a, qep11a, and qep11b on chr in this study. three other novel qtls for bn were detected on chr chr and chr accounting for to % of phenotypic variation. pod number and 100-seed weight are important parameters in measuring soybean yield and controlled by multiple genes. two qtls, qep19a and qip19b, on chr were found to be associated with pod number during both years, and were located in the same region as those previously reported by zhang et al.. moreover, qsw19a- was shown to be associated with 100-seed weight, and is also mapped on chr near this interval. orf et al. reported a fine-mapped, 100-seed weight qtl located on chr which just overlapped the intervals of the qtl for sw detected in both years in the present study. in our study, a total of protein content qtls and seed oil content qtls were identified in 2 years. three qtls were found to be novel, and no similar position has been identified previously for protein content. ten of the qtls relevant to protein or oil content detected in the present study were consistent with previous research, and some of them shortened the interval. for example, a qtl associated with oil content, qoil06a, was found on chr. palomeque et al. also reported that a qtl for oil content fell within the same interval, and a similar locus regarding seed oil and ‘oil plus protein’ related traits was also published by other researchers, which indicated that this qtl is stable and may have pleiotropic effects. meanwhile, three other qtls for yield-related traits were mapped to a similar region identified in our study, which explained to % of phenotypic variation, respectively. qoil20a was mapped in a 39 kb region to bin on chr, which falls within the same region identified by both qi et al. and reinprecht et al.. moreover, qsw20b- for yield was also located near this position, suggesting that these two aforementioned regions should be of great value for genetic improvement of both soybean yield and quality. the remaining qtls associated with protein or oil content in agreement with those of previous studies are presented in additional file. the coincidence of qtl across different genetic backgrounds not only reveals the stability and reliability of the qtl detected herein but also highlights the significance of these regions in marker breeding works designed to develop higher protein or oil soybean cultivars. important qtl hotspots most of the qtls were clustered in eight genomic regions, particularly on chr chr chr and chr. these qtls hotspots included at least two traits such as ph, nn and sw, and was previously reported to be associated with some other traits in different genetic sources. four qtls for yield-related traits were mapped in two intervals of,048–,822 bp on chr which explained – % of phenotypic variation. these qtls have not been published and add to the growing knowledge on the genetic control of these traits. three other qtls were also detected on chr explaining the range of phenotypic variation. however, this region was reported to be associated with seed protein and seed weight in some earlier studies. seven qtls for ph, nn, bn, and oil were identified in two regions that were separated by a distance of more than 7 cm on chr and accounted for – % of phenotypic variation. previously, sun et al. located two qtls for pod number on chr near these two regions. the first region on chr in the present study has been shown to be associated with different traits by other researches. moreover, chen et al. found that two qtls for pod number and seed oil plus protein were consistent with the second region on chr in our study. more seed weight, protein and oil content qtls were mapped to this locus in previous studies. three qtls for bn and ep were identified on chr that explained – % of phenotypic variation. of these, two qtls for ep were expressed over 2 years. three previously reported qtls for protein content and seed weight were located in this region. seven qtls were located in a physical position on chr of which qph19a, qnn19a and qph19b- have large effect on phenotypic variation in comparison to the others. mansur et al. found two qtls associated with protein and oil were close to this region. orf et al. also reported that this locus as associated with seed weight. in addition, three qtls were detected on chr in this study. similar loci have been previously reported for seed weight, protein and oil content. another two qtls on chr were mapped to the interval of,067–,449 bp. some of the seed weight qtls were detected near this position in past studies. moreover, qtls for protein and oil content were also previously identified in this region by both orf et al. and qi er al.. interestingly, in this study, highly significant correlations were observed among ph, nn, bn, ep and sw. qtl mapping analysis showed that these traits were all linked to same region on three chromosomes, which is consistent with the conclusion of phenotypic correlation analysis, and provided a genetic explanation for these associations. these qtl clusters may be cause of the pleiotropism or associations between the traits related. every single cluster may function as an independent gene or closely linked genes. more importantly, some of those qtls on chr chr chr and chr were identified in both years. these chromosome regions can be considered robust and environmentally stable, which could be helpful for further studies aimed at simultaneously altering soybean yield and quality in a predictable manner. three candidate genes on chr19 based on the predicted function of the five groups, three predicted genes were selected as the best candidate genes that may affect both yield and quality because they are involved in various biological process. glyma19g encodes a member of the basic leucine zipper transcription factor family, involved in arabidopsis abscisic acid signalling during seed maturation and germination. go analysis showed that this gene participated in more than ten biological process, which include seed development, lipid storage, gibberellin biosynthesis, and vegetative to reproductive phase transition of the meristem, etc. glyma19g gene has a domain predicted to encode a serine/threonine protein kinase that could influence cells in various ways. this gene is related to the process of stem cell division, protein phosphorylation, gibberellin biosynthesis and timing of the transition from vegetative to reproductive development. glyma19g encodes a plastidic triose phosphate isomerase, and go analysis revealed that this gene participates in three catabolic process and four biosynthetic process. moreover, it also plays a key role in multicellular organism reproduction and primary root development, which may have an effect on the yield and quality of crops. in general, these three candidates should be investigated in more detail in further studies to increase our understanding regarding the factors involved in the process of improving quality and productivity in soybean.table the information of three candidates’ annotations the three candidate genes were selected in a physical position between, and,371 bp on chr seven qtls associated with five traits were all detected within this genomic region  in this study, we genotyped a recombinant inbred line population using a restriction-site associated dna sequencing approach. a high-density soybean genetic map with recombination bins was constructed and used to identify qtls that were shown to influence six yield-related and two quality traits. a total of qtls for six yield-related traits and qtls for two quality traits were identified. of these, qtls detected herein were coincident with those of previous research. eighteen qtls were stable qtls that were identified in 2 years. twenty-six qtls were shown for the first time in this research, of which were novel and stable qtls. in addition, eight qtl hotspots on four chromosomes were identified for the correlated traits. three predicted genes were selected as candidate genes that may directly or indirectly influence both yield and quality in soybean. additional files additional file 1: the distribution of lod values for eight traits. maximum lod score of each major qtl is indicated next to the peak. red lines indicated data was collected in blue lines indicated data was collected in different line colors indicate data collected in different years. additional file 2: difference in agronomic traits between the parents and their recombinant inbred lines. a the data used was generated in summer 2012; b the data used was generated in summer additional file 3: qtls detected in rils population that reported by previously studies. **marked by qtl name indicates a new, stable qtl that was detected in both years; achr indicates chromosome; blod indicates the logarithm of odds score; c percentage of phenotypic variation explained; d related qtls have been reported in the previous studies of the region which was identified in the zhonghuang and huaxi rils population. additional file 4: qtl hotspots detected in zhonghuang24 × huaxia ril population in 2 years. **marked by qtl name indicates a new, stable qtl that was detected in both years; achr indicates chromosome; blod indicates the logarithm of odds score; cpercentage of phenotypic variation explained. additional file 5: annotation description of five gene groups based on go analysis. abbreviations bnnumber of branches on main stem chrchromosome cimcomposite interval mapping epnumber of effective pod gogene ontology ipnumber of invalid pod lodlogarithm of the odds nnnumber of nodes on main stem phplant height qtlquantitative trait loci snpsingle nucleotide polymorphisms sw100-seed weight r2phenotypic variance rad-seqrestriction-site associated dna sequencing rilrecombinant inbred line electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. 
a high-density soybean genetic map was constructed and used to identify several qtls that were shown to influence six yield-related and two quality traits. the online version of this article contains supplementary material, which is available to authorized users. with rad-sequencing, some novel qtls and important qtl clusters for both yield-related and quality traits were identified based on a new, high-density bin linkage map. a total of single-nucleotide polymorphisms were detected for the rils that were integrated into recombination bin units, with an average distance of  cm between adjacent markers. twenty six qtls were identified for the first time, with a single qtl in a 56 kb region explaining % of phenotypic variation, and an additional of these were novel, stable qtls. forty seven qtls for yield-related traits and qtls for grain quality traits were found to be distributed on chromosomes in the 2 year studies. qtlyield-related traitsquality traitsrad-sequencingsoybeanchina agricultural research systemcars-04-ps09nian hai major projects of new varieties cultivation of genetically modified organisms 2014zx08004-002nian hai issue-copyright-statement© the author 2017 moreover, qtl hotpots on four different chromosomes were identified for the correlated traits.
 one of the overarching goals of soybean breeding is to develop lines that combine increased yield with improved quality characteristics. high-density-marker qtl mapping can serve as an effective strategy to identify novel genomic information to facilitate crop improvement. in this study, we genotyped a recombinant inbred line population using a restriction-site associated dna sequencing approach. a high-density soybean genetic map was constructed and used to identify several qtls that were shown to influence six yield-related and two quality traits.  a total of single-nucleotide polymorphisms were detected for the rils that were integrated into recombination bin units, with an average distance of  cm between adjacent markers. forty seven qtls for yield-related traits and qtls for grain quality traits were found to be distributed on chromosomes in the 2 year studies. among them, qtls were stable, and were identified in both analyses. twenty six qtls were identified for the first time, with a single qtl in a 56 kb region explaining % of phenotypic variation, and an additional of these were novel, stable qtls. moreover, qtl hotpots on four different chromosomes were identified for the correlated traits.  with rad-sequencing, some novel qtls and important qtl clusters for both yield-related and quality traits were identified based on a new, high-density bin linkage map. three predicted genes were selected as candidates that likely have a direct or indirect influence on both yield and quality in soybean. our findings will be helpful for understanding common genetic control mechanisms of co-localized traits and to select cultivars for further analysis to predictably modulate soybean yield and quality simultaneously. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords qtlyield-related traitsquality traitsrad-sequencingsoybeanchina agricultural research systemcars-04-ps09nian hai major projects of new varieties cultivation of genetically modified organisms 2014zx08004-002nian hai issue-copyright-statement© the author 2017 