Jean-Michel Ane´ et al. Que´tier et al. at the Genoscope. A physical map grouping and ordering of BAC clones was developed by the labora- tory of Douglas R. Cook by combining HindIII digestion ﬁngerprints with BAC-end sequence data through the FPC software [52, 61, 62]. More than 1370 FPC contigs cover 466 Mbp (93% of the genome) and are used to determine the minimum tiling path of gene-rich regions for whole genome sequencing [52]. As of February 2007, 188 Mb of genome sequence from 1950 BAC clones are publicly available. About 10% of this in- formation is redundant due to the overlap of BAC clones nec- essary to create a tiling path and more than 300 gaps between contigs need to be ﬁlled. These gaps are sized by FISH and covered with contigs by long-range PCR or classical chromo- some walking [62]. Integration of genetic, cytogenetic, physical, and se- quence maps allowed the development of pseudochromo- somes and greatly facilitated comparative mapping [52, 58– 60]. Annotating pseudochromosome sequences is classically achieved through gene prediction programs and compari- son with EST databases (Figure 1). The IMGAG (Interna- tional Medicago Genome Annotation Group) has developed a unique automated pipeline to predict gene structures and functions [63]. More than 25 000 genes have been predicted so far and techniques to test these predictions need to be de- veloped. Oligonucleotides covering the entire sequence of pseu- dochromosomes can be printed on glass slides to generate tiling arrays. These arrays can be used for a wide range of applications from gene identiﬁcation and detection of alter- native splicing to comparative genome hybridization (CGH) and chromatin immunoprecipitation on chips (ChIP chips) [64–67]. 4. SYSTEMS ANALYSIS 4.1. Transcriptomics Large-scale EST sequencing is essential for functional ge- nomics studies, permitting the direct identiﬁcation of large gene collections and setting the stage for further analysis, such as those using DNA microarray technology. Several large EST projects have been completed [68–71]. The anal- ysis of the almost 200 000 ESTs isolated from many diﬀer- ent libraries constructed from diverse stages and treatments that came out of these projects is facilitated by searchable databases such as MtDB2 [72] and the TIGR Gene Index (http://www.tigr.org). Both microarray and macroarray analyses of gene ex- pression changes during symbiosis have been published [73–78]. These experiments ranged from analysis of a few thousand genes on ﬁlters during AM symbiosis [73] to almost 10 000 genes compared between wild type and nonn- odulating mutants [76, 77] or between ﬁx-mutants [79]. A dual symbiosis chip containing 10 000 M. truncatula genes and the entire S. meliloti prokaryotic genome allows side by side analysis of both partners in the symbiosis [80], and an Aﬀymetrix chip with bioinformatically optimized oligonu- cleotides representing 48 000 genes is available (http://www Genetic map (markers such as CAPS, SSRs, . . .) EST libraries Physical map (BAC clones, ﬁngerprint and BAC ends) Genome sequence (pseudo-chromosome) and comparative genomics Gene prediction Genome annotation 3 Cytogenetic map (FISH on metaphase or pachytene chromosomes) Repeats (centromeric repeats, rDNA, . . .) Tiling arrays Figure 1: Integration of diﬀerent maps and libraries to generate and annotate the genomic sequence of M. truncatula. Expressed sequence tags (EST) are used to generate genetic markers and to identify BAC clones in gene-rich regions as well as for gene iden- tiﬁcation. Repeats identiﬁed via genome sequencing and compar- ison with other species can be mapped via FISH on chromosome spreads. .aﬀymetrix.com/support/technical/datasheets/medicago da- tasheet.pdf). As genome sequencing continues, following the expression of all M. truncatula genes under varying conditions should soon be possible. Aﬀymetrix placed probe sets for 1850 M. sativa transcripts on these chips to facilitate the study of closely related species such as M. sativa. The use of M. truncatula arrays for analysis of M. sativa (crop alfalfa) gene expression has proven eﬀective [81, 82]. Other eﬀective genomic approaches to transcriptional analysis utilized to date in M. truncatula include suppres- sive subtractive hybridization (SSH) and serial analysis of gene expression (SAGE). In SSH, suppressive PCR is used to both normalize the abundance of transcripts in individ- ual libraries and enrich for transcripts unique to the library by subtracting sequences common to several libraries, with rare sequences being enriched up to 1000 folds [83]. This method has been used to identify AM speciﬁc transcripts [84] and transcripts speciﬁcally involved in the S. meliloti symbiosis [85]. SAGE is a method for comprehensive anal- ysis of gene expression patterns using short sequence tags obtained from a unique position within each transcript (10– 14 bp) to uniquely identify a transcript. The expression level of the corresponding transcript is determined by quanti- fying of the number of times a particular tag is observed [86]. Although no publications have arisen yet, a project applying SAGE to M. truncatula is underway at the Center for Medicago Genomics Research at the Nobel Foundation (http://www.noble.org/medicago/GEP.html). 4.2. Proteomics Another complementary approach to identify import gene products involved in interesting processes is to look at changes in the protein complement of a genome that vary by cell or treatment. In order for proteomic approaches to be useful in a system, a large sequence resource is necessary to match the sequences of peptides generated in tryptic digests