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Switchgrass (Panicum virgatum) has been identified as a promising cellulosic biofuel crop in the United States. Construction of a genetic linkage map is fundamental for switchgrass molecular breeding and the elucidation of its genetic mechanisms for economically important traits. In this study, a novel population consisting of 139 selfed progeny of a northern lowland genotype, NL 94 LYE 16X13, was used to construct a linkage map. A total of 2493 simple sequence repeat markers were screened for polymorphism. Of 506 polymorphic loci, 80.8% showed a goodness-of-fit of 1:2:1 segregation ratio. Among 469 linked loci on the framework map, 241 coupling vs. 228 repulsion phase linkages were detected that conformed to a 1:1 ratio, confirming disomic inheritance. A total of 499 loci were mapped to 18 linkage groups (LG), of which the cumulative length was 2085.2 cM, with an average marker interval of 4.2 cM. Nine homeologous LG pairs were identified based on multi-allele markers and comparative genomic analysis. Two clusters of segregation-distorted loci were identified on LG 5b and 9b, respectively. Comparative analysis indicated a one-to-one relationship between nine switchgrass homeologous groups and nine foxtail millet (Setaria italica) chromosomes, suggesting strong homology between the two species. The linkage map derived from selfing a heterozygous parent, instead of two separate maps usually constructed for a cross-fertilized species, provides a new genetic framework to facilitate genomics research, quantitative trait locus (QTL) mapping, and marker-assisted breeding.
Pubmed ID: 22413090
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A curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.
View all literature mentionsA comparative platform for green plant genomics. Families of orthologous and paralogous genes that represent the modern descendents of ancestral gene sets are constructed at key phylogenetic nodes. These families allow easy access to clade specific orthology / paralogy relationships as well as clade specific genes and gene expansions. As of release v9.1, Phytozome provides access to forty-one sequenced and annotated green plant genomes which have been clustered into gene families at 20 evolutionarily significant nodes. Where possible, each gene has been annotated with PFAM, KOG, KEGG, and PANTHER assignments, and publicly available annotations from RefSeq, UniProt, TAIR, JGI are hyper-linked and searchable.
View all literature mentionsThis portal takes you to the NCBI''s BLAST Assembled RefSeq Genomes. The Basic Local Alignment Search Tool (BLAST) finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches. BLAST can be used to infer functional and evolutionary relationships between sequences as well as help identify members of gene families. Sponsors: This resource is supported by the National Institutes of Health. Keywords: BLAST, Genome, Search engine, Sequence, Biological, Local, Alignment, Nucleotide, Protein, Program, Database, Stastical, Functional, Evolutionaary, Gene,
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