Transcriptome landscape of human primary monocytes at different sequencing depth

被引:7
作者
Mirsafian, Hoda [1 ]
Ripen, Adiratna Mat [2 ]
Leong, Wai-Mun [1 ]
Manaharan, Thamilvaani [3 ]
Bin Mohamad, Saharuddin [1 ,3 ]
Merican, Amir Feisal [1 ,3 ]
机构
[1] Univ Malaya, Inst Biol Sci, Fac Sci, Kuala Lumpur 50603, Malaysia
[2] Inst Med Res, Allergy & Immunol Res Ctr, Jalan Pahang, Kuala Lumpur 50588, Malaysia
[3] Univ Malaya, Ctr Res Computat Sci & Informat Biol Bioind Envir, Kuala Lumpur 50603, Malaysia
关键词
RNA sequencing; Transcriptome; Monocytes; Sequencing depth; RNA-SEQ; GENE-EXPRESSION; CELL; BIOLOGY; TISSUES; STEM;
D O I
10.1016/j.ygeno.2017.07.003
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
Differential gene and transcript expression pattern of human primary monocytes from healthy young subjects were profiled under different sequencing depths (50M, 100M, and 200M reads). The raw data consisted of 1.3 billion reads generated from RNA sequencing (RNA-Seq) experiments. A total of 17,657 genes and 75,392 transcripts were obtained at sequencing depth of 200M. Total splice junction reads showed an evenmore significant increase. Comparative analysis of the expression patterns of immune-related genes revealed a total of 217 differentially expressed (DE) protein-coding genes and 50 DE novel transcripts, in which 40 DE protein-coding genes were related to the immune system. At higher sequencing depth, more genes, known and novel transcriptswere identified and larger proportion of reads were allowed to map across splice junctions. The results also showed that increase in sequencing depth has no effect on the sequence alignment. (C) 2017 The Authors. Published by Elsevier Inc.
引用
收藏
页码:463 / 470
页数:8
相关论文
共 41 条
[1]   Transcriptional profiling reveals developmental relationship and distinct biological functions of CD16+and CD16-monocyte subsets [J].
Ancuta, Petronela ;
Liu, Kuang-Yu ;
Misra, Vikas ;
Wacleche, Vanessa Sue ;
Gosselin, Annie ;
Zhou, Xiaobo ;
Gabuzda, Dana .
BMC GENOMICS, 2009, 10 :403
[2]  
[Anonymous], 2016, GENOME BIOL
[3]  
[Anonymous], FASTQC QUALITY CONTR
[4]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[5]   RNA-seq transcriptome analysis of male and female zebra finch cell lines [J].
Balakrishnan, Christopher N. ;
Lin, Ya-Chi ;
London, Sarah E. ;
Clayton, David F. .
GENOMICS, 2012, 100 (06) :363-369
[6]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[7]   High-Resolution Transcriptome of Human Macrophages [J].
Beyer, Marc ;
Mallmann, Michael R. ;
Xue, Jia ;
Staratschek-Jox, Andrea ;
Vorholt, Daniela ;
Krebs, Wolfgang ;
Sommer, Daniel ;
Sander, Jil ;
Mertens, Christina ;
Nino-Castro, Andrea ;
Schmidt, Susanne V. ;
Schultze, Joachim L. .
PLOS ONE, 2012, 7 (09)
[8]   Trimmomatic: a flexible trimmer for Illumina sequence data [J].
Bolger, Anthony M. ;
Lohse, Marc ;
Usadel, Bjoern .
BIOINFORMATICS, 2014, 30 (15) :2114-2120
[9]   X chromosome regulation: diverse patterns in development, tissues and disease [J].
Deng, Xinxian ;
Berletch, Joel B. ;
Nguyen, Di K. ;
Disteche, Christine M. .
NATURE REVIEWS GENETICS, 2014, 15 (06) :367-378
[10]  
DENNIS G, 2003, GENOME BIOL, V4, DOI DOI 10.1186/GB-2003-4-5-P3