Project description:Advances in alfalfa [Medicago sativa (L.) subsp. sativa] breeding, molecular genetics and genomics have been slow because this crop is an allogamous autotetraploid (2n = 4x = 32) with complex polysomic inheritance. Increasing cellulose and decreasing lignin in alfalfa stem cell walls would improve this crop as a cellulosic ethanol feedstock. We selected two alfalfa genotypes (252, 1283) that differ in cellulose and Klason lignin concentration in stem cell walls. Analysis of GeneChip expression data files of alfalfa stem internodes of genotypes 252 and 1283 at two growth stages (elongating, post-elongation) revealed 10,887 SFPs in 8,230 probe sets. Validation analysis by PCR-sequencing of a random sample of SFPs indicated a 12% false discovery rate. Functional classification and over-representation analysis showed that both genotypes were highly enriched in SFP-harboring cell wall genes. We mapped 5,833 of the 8,230 SFP-harboring genes onto putative orthologous loci on Medicago truncatula chromosomes. Clustering and over-representation of SFP-harboring genes within the same functional class (e.g. cell wall genes) was observed on some chromosomes. Prior to analysis of expression data for the two alfalfa genotypes, SFP probes were masked to reduce false positives and false negatives. The combination of SFP and gene expression analysis provide a list of candidate cell wall genes that can be used as molecular markers in a breeding program to improve alfalfa as a cellulosic feedstock. The results of this study will also be useful in advancing understanding of genome organization in alfalfa and for comparative genomics research with other legume species. SUBMITTER_CITATION: Mesfin Tesfaye, S.S. Yang, J.F. Lamb, H.J. Jung, D.A. Samac, J. Gronwald, C.P. Vance and K.A. VandenBosch (2009). Medicago truncatula as a model for dicot cell wall development. BioEnergy Research 2: 59-76 Experiment Overall Design: The alfalfa clonal lines 252 and 1283 were propagated from cuttings and grown in the greenhouse. The greenhouse experiments consisted of three replicates arranged in a randomized complete block design. There were eight plants of each clone, in individual pots, in each replicate. Plant material for analysis was composited within each replicate at harvest. Stem internode tissues were harvested at full bloom. Based on tissue pliability and coloration, the internode in transition from elongation to post-elongation cambial growth was identified. The internodes immediately above (elongating internodes) and below this transition internode (post-elongation internodes) were collected for RNA extraction.

Project description:Alfalfa, [Medicago sativa (L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. The application of genomic approaches would advance development of alfalfa as a cellulosic feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling. Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. These ESTs were de novo assembled into 132,153 unique sequences. By combining the de novo assembled ESTs (132,153 sequences) with our previously identified EST sequences (341,984 sequences, unpublished data), and the ESTs available from GenBank (12,371 sequences), we built the first Alfalfa Gene Index (MSGI 1.0). MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1, 294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Transcript profiling of stem internodes of genotypes 708 and 773 was conducted by quantifying the number of Illumina EST reads that were mapped to sequences in MSGI 1.0. We identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes. Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index (MSGI 1.0) assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a cellulosic feedstock. Examination of 2 different tissue types at different developmental stages (Elongating vs. post-elongation stem internodes) in two alfalfa genotypes (708 and 773) with divergent cell wall composition in stems.

Project description:Alfalfa, [Medicago sativa (L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. The application of genomic approaches would advance development of alfalfa as a cellulosic feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling. Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. These ESTs were de novo assembled into 132,153 unique sequences. By combining the de novo assembled ESTs (132,153 sequences) with our previously identified EST sequences (341,984 sequences, unpublished data), and the ESTs available from GenBank (12,371 sequences), we built the first Alfalfa Gene Index (MSGI 1.0). MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1, 294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Transcript profiling of stem internodes of genotypes 708 and 773 was conducted by quantifying the number of Illumina EST reads that were mapped to sequences in MSGI 1.0. We identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes. Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index (MSGI 1.0) assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a cellulosic feedstock.

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An improved protocol to study the plant cell wall proteome

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