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.

Project description:Background:; Cowpea (Vigna unguiculata L. Walp) is an important food and fodder legume of the semiarid tropics and subtropics worldwide, especially in sub-Saharan Africa. High density genetic linkage maps are needed for marker assisted breeding but are not available for cowpea. A single feature polymorphism (SFP) is a microarray-based marker which can be used for high throughput genotyping and high density mapping. Results:; Here we report detection and validation of SFPs in cowpea using a readily available soybean (Glycine max) genome array. Robustified projection pursuit (RPP) was used for statistical analysis using RNA as a surrogate for DNA. Using a 15% outlying score cut-off, 1058 potential SFPs were enumerated between two parents of a recombinant inbred line (RIL) population segregating for several important traits including drought tolerance, Fusarium and brown blotch resistance, grain size and photoperiod sensitivity. Sequencing of 25 putative polymorphism-containing amplicons yielded a SFP probe set validation rate of 68%. Conclusions:; We conclude that the Affymetrix soybean genome array is a satisfactory platform for identification of some 1000âs of SFPs for cowpea. This study provides an example of extension of genomic resources from a well supported species to an orphan crop. Presumably, other legume systems are similarly tractable to SFP marker development using existing legume array resources. SUBMITTER_CITATION: Detection and validation of single feature polymorphisms in cowpea (Vigna unguiculata L. Walp) using a soybean genome array Sayan Das, Prasanna R. Bhat, Chinta Sudhakar, Jeffrey D. Ehlers, Steve Wanamaker, Philip A. Roberts, Xinping Cui, Timothy J. Close BMC Genomics 2008, 9:107 Experiment Overall Design: Expression data were generated by hybridizing cowpea cRNA to the soybean genome array. A statistical method called robustified projection pursuit (RPP) was used for Single Feature Polymorphism(SFP) analysis. Only the values from the PM probes were utilized. The use of RNA as a surrogate for genomic DNA eliminated interference from highly repetitive DNA as a technical impediment to SFP detection. An important aspect of the RPP method is that it first utilizes a probe set level analysis to identify SFP-containing probe sets and then chooses individual probes from within each SFP-containing probe set. The net result is the identification of probes that directly overlay polymorphic sequences. Experiment Overall Design: Separate comparisons were made between two genotypes (with two replicates each) for unstressed and drought stressed treatments, resulting in two SFP lists. In the context of SFPs, there is no necessity to have separate stress and control lists; in fact it would be simpler and less costly to have only one SFP list from highly complex RNA made by blending stressed and unstressed RNA. In our case, two separate lists were available as a consequence of another study not described here which compared gene expression patterns in stressed and control plants (data not shown). At 15% outlying score cut-off, we detected 488 SFP probes in stressed and 661 SFP probes in unstressed treatments. The union of these two lists contained 1058 SFP probes and the intersection contained 91. A total of 37 primer pairs targeting 37 putative SFP probe sets were initially tested, of which 25 yielded single amplicons of the expected sizes from both parents. These 25 amplicons targeted 14 probe sets selected from the intersection of the two SFP probe set lists and 11 from the remaining SFP probe sets. 9 of the 14 SFP probe sets (64%) from the intersection list were validated at the DNA sequence level and 8 of the other 11 (73%) were validated.

Project description:Seminal fluid contains some of the fastest evolving proteins currently known. These seminal fluid proteins (Sfps) play crucial roles in reproduction, such as supporting sperm function, and – particularly in insects – modifying female physiology and behaviour. Identification of Sfps in small animals is challenging, and often relies on samples taken from the female reproductive tract after mating. A key pitfall of this method is that it might miss Sfps that are of low abundance due to dilution in the female-derived sample or rapid processing in females. Here we present a new and complimentary method, which provides added sensitivity to Sfp identification. We applied label-free quantitative proteomics to Drosophila melanogaster male reproductive tissue – where Sfps are unprocessed, and highly abundant – and quantified Sfps before and immediately after mating, to infer those transferred during copulation. We also analysed female reproductive tracts immediately before and after copulation to confirm the presence and abundance of known and candidate Sfps, where possible. Results were cross-referenced with transcriptomic and sequence databases to improve confidence in Sfp detection. Our data was consistent with 124 previously reported Sfps. We found 8 high-confidence novel candidate Sfps, which were both depleted in mated versus unmated males and identified within the reproductive tract of mated but not virgin females. We also identified 31 more candidates that are likely Sfps based on their abundance, known expression and predicted characteristics, and revealed that four proteins previously identified as Sfps are at best minor contributors to the ejaculate. The estimated copy numbers for our candidate Sfps were lower than for previously identified Sfps, supporting the idea that our technique provides a deeper analysis of the Sfp proteome than previous studies. Our results demonstrate a novel, high-sensitivity approach to the analysis of seminal fluid proteomes, whose application will further our understanding of reproductive biology.

Project description:Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of Eucalyptus using Single Feature Polymorphism (SFP) markers. SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. In silico validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the Eucalyptus grandis genome. The Eucalyptus 1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on Eucalyptus maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species.

Project description:Advances in genomic technologies are rapidly filling the gap in genomic information available from non-model species that are economically and ecologically important. Reduction in costs and higher throughput of data acquisition will progressively increase the application of genomics in population and quantitative genetics. In molecular breeding, the ability to rapidly develop large numbers of genetic markers and generate high-density genetic maps at low cost is critical because they provide the framework for identification of elements that regulate trait variation, connecting genetics and genomics to phenotype. To generate the first high-density, gene-based genetic map for Eucalyptus, we genotyped a hybrid segregating population with microarray-based markers. The genus Eucalyptus includes the most economically important species used for bioenergy pulp and paper production worldwide. A custom 25-mers oligonucleotide array was designed based on 20,726 expressed sequence tags consensus, and RNA from 28 biologically-replicated individuals allowed clear-cut detection of putative single feature polymorphisms (SFPs) segregating 1:1 and 3:1. A genotyping array confirmed the segregation in a larger portion of the family and a genetic map with 1064 gene-related markers is made available with an average of one marker every 1.2 cM. Interestingly, reanalyzing the data from the 28 genotypes using a mixed-model approach resulted in most of the mapped genes among the significant probesets. We also demonstrate that designing more probes per gene increases the chance of mapping those genes. Finally, in silico validatation shows that 87% of the markers map to expected location on the draft genome, an important characteristic of SFP markers. Simultaneously detecting and genotyping SFP markers in a subset of the mapping population instead of only the genitors was more efficient for mapping genes in outcrossing species than previously reported approaches. Mapping SFP markers require low genomic resources and can be done at relatively low cost. We demonstrate the possibility of mapping hundreds to thousands of genes that can ultimately be used in generating further genomic resources, such as genome assembly, or for more direct applications, such as QTL analysis. Two biological replication of 28 genotypes were hybridized to the custom microarray, labeled with Cy3 and Cy5. Genotypes are fullsib progenies of the cross E. urophylla X E. grandis. A loop design was employed for the hybridization using xylem tissue. In total the microarray comprised 103,000 probes representing 20,726 unigenes with an average of five probes per unigene. Twenty-six negative control probes were also included in the microarray.

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Transcriptome Profiles of Medicago Stem Internodes

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