Next-generation sequencing technologies for gene expression profiling in plants

被引:120
作者
Jain, Mukesh [1 ]
机构
[1] Natl Inst Plant Genome Res, New Delhi 110067, India
关键词
gene expression profiling; next-generation sequencing; RNA-seq; transcriptome; RNA-SEQ DATA; DIFFERENTIAL EXPRESSION; SPLICE JUNCTIONS; GLYCINE-MAX; TRANSCRIPTOME; QUANTIFICATION; COMPLEXITY; RESOLUTION; ANNOTATION; LANDSCAPE;
D O I
10.1093/bfgp/elr038
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
Next-generation sequencing (NGS) provides a better approach to gene expression profiling with several advantages. The power of NGS along with novel molecular techniques and computational tools allow the researchers to perform the gene expression profiling to reveal transcriptional complexity of an organism and answering several biological questions. Although many studies for gene expression profiling related to various aspects have been performed in animal systems revealing unprecedented levels of complexity of transcriptomes, their use is still limited in plant biology. This review describes the use of NGS technologies with respect to gene expression profiling, bioinformatics challenges associated with data analysis and advances made so far in the plant biology research. We anticipate many more studies in recent future, which will surely advance our understanding of the complexity of plant genomes.
引用
收藏
页码:63 / 70
页数:8
相关论文
共 78 条
[1]   Differential expression analysis for sequence count data [J].
Anders, Simon ;
Huber, Wolfgang .
GENOME BIOLOGY, 2010, 11 (10)
[2]   Detection of splice junctions from paired-end RNA-seq data by SpliceMap [J].
Au, Kin Fai ;
Jiang, Hui ;
Lin, Lan ;
Xing, Yi ;
Wong, Wing Hung .
NUCLEIC ACIDS RESEARCH, 2010, 38 (14) :4570-4578
[3]   Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays [J].
Bloom, Joshua S. ;
Khan, Zia ;
Kruglyak, Leonid ;
Singh, Mona ;
Caudy, Amy A. .
BMC GENOMICS, 2009, 10
[4]   rQuant.web: a tool for RNA-Seq-based transcript quantitation [J].
Bohnert, Regina ;
Raetsch, Gunnar .
NUCLEIC ACIDS RESEARCH, 2010, 38 :W348-W351
[5]   Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays [J].
Brenner, S ;
Johnson, M ;
Bridgham, J ;
Golda, G ;
Lloyd, DH ;
Johnson, D ;
Luo, SJ ;
McCurdy, S ;
Foy, M ;
Ewan, M ;
Roth, R ;
George, D ;
Eletr, S ;
Albrecht, G ;
Vermaas, E ;
Williams, SR ;
Moon, K ;
Burcham, T ;
Pallas, M ;
DuBridge, RB ;
Kirchner, J ;
Fearon, K ;
Mao, J ;
Corcoran, K .
NATURE BIOTECHNOLOGY, 2000, 18 (06) :630-634
[6]   Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments [J].
Bullard, James H. ;
Purdom, Elizabeth ;
Hansen, Kasper D. ;
Dudoit, Sandrine .
BMC BIOINFORMATICS, 2010, 11
[7]   Comprehensive analysis of alternative splicing in rice and comparative analyses with Arabidopsis [J].
Campbell, Matthew A. ;
Haas, Brian J. ;
Hamilton, John P. ;
Mount, Stephen M. ;
Buell, C. Robin .
BMC GENOMICS, 2006, 7 (1)
[8]   Meiosis-specific gene discovery in plants: RNA-Seq applied to isolated Arabidopsis male meiocytes [J].
Chen, Changbin ;
Farmer, Andrew D. ;
Langley, Raymond J. ;
Mudge, Joann ;
Crow, John A. ;
May, Gregory D. ;
Huntley, James ;
Smith, Alan G. ;
Retzel, Ernest F. .
BMC PLANT BIOLOGY, 2010, 10
[9]   RNA-MATE: a recursive mapping strategy for high-throughput RNA-sequencing data [J].
Cloonan, Nicole ;
Xu, Qinying ;
Faulkner, Geoffrey J. ;
Taylor, Darrin F. ;
Tang, Dave T. P. ;
Kolle, Gabriel ;
Grimmond, Sean M. .
BIOINFORMATICS, 2009, 25 (19) :2615-2616
[10]   Transcriptome content and dynamics at single-nucleotide resolution [J].
Cloonan, Nicole ;
Grimmond, Sean M. .
GENOME BIOLOGY, 2008, 9 (09) :234