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.
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DOI:
10.1371/journal.pone.0122170
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发表时间:
2015
期刊:
影响因子:
3.7
通讯作者:
Wang C
Wang C
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Zhang S;Shi Y;Cheng N;Du H;Fan W;Wang C

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苜蓿(Medicago sativa L.)是世界上种植最广泛的多年生饲草豆科植物之一。秋季休眠是苜蓿的一种适应性性状,关系到苜蓿的生物量生产和冬季生存。引起秋季休眠的生理、生化和分子机制及其相关基因尚未得到很好的研究。在这项研究中,我们在两个时间点对两个标准的苜蓿品种(休眠和非休眠)进行了测序,并使用合成测序(SBS)技术产生了大约1.6亿个高质量的对端序列reads。从头转录组组装产生了192,875个转录本,平均长度为856 bp,代表了苜蓿叶转录组的约165.1 Mb。组装后,在NCBI非冗余数据库中对111,062份(57.6%)转录本进行了注释。共有30,165个转录本(15.6%)被定位到京都基因和基因组百科全书的323条通路上。我们还鉴定出41,973个简单序列重复序列,可用于生成苜蓿标记,并在1,350个转录本中鉴定出1,541个转录因子。在不同的时间点进行了休眠和非休眠苜蓿的基因表达,我们发现了几个可能与秋季休眠相关的差异表达基因。确定了基因本体和通路信息。我们对紫花苜蓿秋季休眠相关的叶片转录组进行了测序和组装,并鉴定了一些与秋季休眠机制相关的基因。因此,我们的研究重点是通过转录组测序研究苜蓿的秋季休眠。本研究获得的测序和基因表达数据可用于进一步阐明紫花苜蓿秋季休眠的完整机制。
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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