An RNA-Seq based gene expression atlas of the common bean

被引:114
|
作者
O'Rourke, Jamie A. [1 ]
Iniguez, Luis P. [2 ]
Fu, Fengli [1 ]
Bucciarelli, Bruna [1 ,3 ]
Miller, Susan S. [1 ]
Jackson, Scott A. [4 ]
McClean, Philip E. [5 ]
Li, Jun [6 ]
Dai, Xinbin [6 ]
Zhao, Patrick X. [6 ]
Hernandez, Georgina [2 ]
Vance, Carroll P. [1 ]
机构
[1] Univ Minnesota, Dept Agron & Plant Genet, St Paul, MN 55108 USA
[2] Univ Nacl Autonoma Mexico, Ctr Ciencias Genom, Cuernavaca 66210, Morelos, Mexico
[3] USDA ARS, Plant Sci Res Unit, St Paul, MN 55108 USA
[4] Univ Georgia, Ctr Appl Genet Technol, Athens, GA 30602 USA
[5] N Dakota State Univ, Dept Plant Sci, Fargo, ND 58105 USA
[6] Samuel Roberts Noble Fdn Inc, Div Plant Biol, Ardmore, OK 73401 USA
来源
BMC GENOMICS | 2014年 / 15卷
基金
美国国家科学基金会;
关键词
Phaseolus vulgaris cv Negro jamapa; Common bean; RNA-Seq; Symbiotic nitrogen fixation; Expression atlas; SRP046307; GENOME-WIDE IDENTIFICATION; MEDICAGO-TRUNCATULA; GLYCINE-MAX; TRANSCRIPTION FACTORS; NODULE DEVELOPMENT; NITROGEN-FIXATION; RHIZOBIAL INFECTION; MOLECULAR-CLONING; ARABIDOPSIS SEEDS; NITRATE TRANSPORT;
D O I
10.1186/1471-2164-15-866
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. Results: Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change >= 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/. Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. Conclusions: These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] COMPREHENSIVE EFFECTS OF IBUPROFEN ON GENE EXPRESSION IN CHONDROCYTES AS DETERMINED BY RNA-SEQ
    Pemmari, A.
    Tuure, L.
    Hamalainen, M.
    Leppanen, T.
    Vuolteenaho, K.
    Moilanen, T.
    Moilanen, E.
    [J]. OSTEOARTHRITIS AND CARTILAGE, 2019, 27 : S378 - S378
  • [42] RNA-Seq analysis of high NaCl-induced gene expression
    Izumi, Yuichiro
    Yang, Wenjing
    Zhu, Jun
    Burg, Maurice B.
    Ferraris, Joan D.
    [J]. PHYSIOLOGICAL GENOMICS, 2015, 47 (10) : 500 - 513
  • [43] DEB: A web interface for RNA-seq digital gene expression analysis
    Yao, Ji Qiang
    Yu, Fahong
    [J]. BIOINFORMATION, 2011, 7 (01) : 44 - 45
  • [44] Principles of transcriptome analysis and gene expression quantification: an RNA-seq tutorial
    Wolf, Jochen B. W.
    [J]. MOLECULAR ECOLOGY RESOURCES, 2013, 13 (04) : 559 - 572
  • [45] MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps
    Bohdan B. Khomtchouk
    James R. Hennessy
    Claes Wahlestedt
    [J]. BMC Bioinformatics, 17
  • [46] ExpressionPlot: a web-based framework for analysis of RNA-Seq and microarray gene expression data
    Brad A Friedman
    Tom Maniatis
    [J]. Genome Biology, 12
  • [47] The Physcomitrella patens gene atlas project: large-scale RNA-seq based expression data (vol 95, pg 168, 2018)
    Perroud, P. -F
    Haas, F. B.
    Hiss, M.
    [J]. PLANT JOURNAL, 2019, 98 (04): : 759 - 759
  • [48] Bootstrap-based differential gene expression analysis for RNA-Seq data with and without replicates
    Sahar Al Seesi
    Yvette Temate Tiagueu
    Alexander Zelikovsky
    Ion I Măndoiu
    [J]. BMC Genomics, 15
  • [49] Bootstrap-based differential gene expression analysis for RNA-Seq data with and without replicates
    Al Seesi, Sahar
    Tiagueu, Yvette Temate
    Zelikovsky, Alexander
    Mandoiu, Ion I.
    [J]. BMC GENOMICS, 2014, 15
  • [50] Transcriptome Analysis of the Gene Expression Profiles Associated with Fungal Keratitis in Mice Based on RNA-Seq
    Zhang, Qing
    Zhang, Jian
    Gong, Mengting
    Pan, Ruolan
    Liu, Yanchang
    Tao, Liming
    He, Kan
    [J]. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2020, 61 (06)