Regulatory complexity revealed by integrated cytological and RNA-seq analyses of meiotic substages in mouse spermatocytes

BMC Genomics

Research Article

Fengyun Sun¹  Mary Ann Handel¹  Gregory W. Carter¹  Robyn L. Ball¹  Yasuhiro Fujiwara¹  Jianjun Hu¹  Matthew A. Hibbs² 

[1] The Jackson Laboratory, Bar Harbor, ME, USA;The Jackson Laboratory, Bar Harbor, ME, USA;Department of Computer Science, Trinity University, San Antonio, TX, USA;

关键词: Meiosis;    Spermatogenesis;    Maximum covariance analysis;    Mouse;    Transcriptome;    RNA-seq;   

DOI  :  10.1186/s12864-016-2865-1

 received in 2015-09-11, accepted in 2016-06-28,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThe continuous and non-synchronous nature of postnatal male germ-cell development has impeded stage-specific resolution of molecular events of mammalian meiotic prophase in the testis. Here the juvenile onset of spermatogenesis in mice is analyzed by combining cytological and transcriptomic data in a novel computational analysis that allows decomposition of the transcriptional programs of spermatogonia and meiotic prophase substages.ResultsGerm cells from testes of individual mice were obtained at two-day intervals from 8 to 18 days post-partum (dpp), prepared as surface-spread chromatin and immunolabeled for meiotic stage-specific protein markers (STRA8, SYCP3, phosphorylated H2AFX, and HISTH1T). Eight stages were discriminated cytologically by combinatorial antibody labeling, and RNA-seq was performed on the same samples. Independent principal component analyses of cytological and transcriptomic data yielded similar patterns for both data types, providing strong evidence for substage-specific gene expression signatures. A novel permutation-based maximum covariance analysis (PMCA) was developed to map co-expressed transcripts to one or more of the eight meiotic prophase substages, thereby linking distinct molecular programs to cytologically defined cell states. Expression of meiosis-specific genes is not substage-limited, suggesting regulation of substage transitions at other levels.ConclusionsThis integrated analysis provides a general method for resolving complex cell populations. Here it revealed not only features of meiotic substage-specific gene expression, but also a network of substage-specific transcription factors and relationships to potential target genes.

【 授权许可】

CC BY   
© The Author(s). 2016

【 图 表 】

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