Integrated transcriptome analysis of mouse spermatogenesis

被引:109
作者
Margolin, Gennady [1 ]
Khil, Pavel P. [1 ]
Kim, Joongbaek [1 ]
Bellani, Marina A. [2 ]
Camerini-Otero, R. Daniel [1 ]
机构
[1] NIDDK, Genet & Biochem Branch, NIH, Bethesda, MD 20892 USA
[2] NIA, NIH, Baltimore, MD 21224 USA
来源
BMC GENOMICS | 2014年 / 15卷
关键词
Spermatogenesis; Meiosis; RNA-Seq; Transcriptome; Deconvolution; RNA Pol II; piRNA; GENOME-WIDE ANALYSIS; GENE-EXPRESSION; MICROARRAY DATA; X-CHROMOSOME; REVEALS; DECONVOLUTION; RECOMBINATION; COMPLEX; TESTIS; CELLS;
D O I
10.1186/1471-2164-15-39
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: Differentiation of primordial germ cells into mature spermatozoa proceeds through multiple stages, one of the most important of which is meiosis. Meiotic recombination is in turn a key part of meiosis. To achieve the highly specialized and diverse functions necessary for the successful completion of meiosis and the generation of spermatozoa thousands of genes are coordinately regulated through spermatogenesis. A complete and unbiased characterization of the transcriptome dynamics of spermatogenesis is, however, still lacking. Results: In order to characterize gene expression during spermatogenesis we sequenced eight mRNA samples from testes of juvenile mice from 6 to 38 days post partum. Using gene expression clustering we defined over 1,000 novel meiotically-expressed genes. We also developed a computational de-convolution approach and used it to estimate cell type-specific gene expression in pre-meiotic, meiotic and post-meiotic cells. In addition, we detected 13,000 novel alternative splicing events around 40% of which preserve an open reading frame, and found experimental support for 159 computational gene predictions. A comparison of RNA polymerase II (Pol II) ChIP-Seq signals with RNA-Seq coverage shows that gene expression correlates well with Pol II signals, both at promoters and along the gene body. However, we observe numerous instances of non-canonical promoter usage, as well as intergenic Pol II peaks that potentially delineate unannotated promoters, enhancers or small RNA clusters. Conclusions: Here we provide a comprehensive analysis of gene expression throughout mouse meiosis and spermatogenesis. Importantly, we find over a thousand of novel meiotic genes and over 5,000 novel potentially coding isoforms. These data should be a valuable resource for future studies of meiosis and spermatogenesis in mammals.
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页数:19
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