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  • De novo characterization of fall dormant and nondormant alfalfa (Medicago sativa L.) leaf transcriptome and identification of candidate genes related to fall dormancy.

De novo characterization of fall dormant and nondormant alfalfa (Medicago sativa L.) leaf transcriptome and identification of candidate genes related to fall dormancy.

PloS one (2015-03-24)
Senhao Zhang, Yinghua Shi, Ningning Cheng, Hongqi Du, Wenna Fan, Chengzhang Wang
ABSTRACT

Alfalfa (Medicago sativa L.) is one of the most widely cultivated perennial forage legumes worldwide. Fall dormancy is an adaptive character related to the biomass production and winter survival in alfalfa. The physiological, biochemical and molecular mechanisms causing fall dormancy and the related genes have not been well studied. In this study, we sequenced two standard varieties of alfalfa (dormant and non-dormant) at two time points and generated approximately 160 million high quality paired-end sequence reads using sequencing by synthesis (SBS) technology. The de novo transcriptome assembly generated a set of 192,875 transcripts with an average length of 856 bp representing about 165.1 Mb of the alfalfa leaf transcriptome. After assembly, 111,062 (57.6%) transcripts were annotated against the NCBI non-redundant database. A total of 30,165 (15.6%) transcripts were mapped to 323 Kyoto Encyclopedia of Genes and Genomes pathways. We also identified 41,973 simple sequence repeats, which can be used to generate markers for alfalfa, and 1,541 transcription factors were identified across 1,350 transcripts. Gene expression between dormant and non-dormant alfalfa at different time points were performed, and we identified several differentially expressed genes potentially related to fall dormancy. The Gene Ontology and pathways information were also identified. We sequenced and assembled the leaf transcriptome of alfalfa related to fall dormancy, and also identified some genes of interest involved in the fall dormancy mechanism. Thus, our research focused on studying fall dormancy in alfalfa through transcriptome sequencing. The sequencing and gene expression data generated in this study may be used further to elucidate the complete mechanisms governing fall dormancy in alfalfa.

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