Cellular source and mechanisms of high transcriptome complexity in the mammalian testis (RRBS and ChIP-Seq)

Understanding  the  extent  of  genomic  transcription  and  its  functional  relevance  is  a  central  goal  in  genomics research. However, detailed genome‐wide investigations of transcriptome complexities in major mammalian organs  and  their  underlying  cellular  sources,  transcriptional  mechanisms,  and  functional  relevance  have been  scarce.  Here  we  first  show,  using  extensive  RNA‐seq  data,  that  transcription  of  both  functional  and nonfunctional  genomic  elements  is  substantially  more  widespread  in  the  testis  than  in  other  organs  across representative mammals. By scrutinizing the transcriptomes of all main testicular cell types in the mouse, we then  reveal  that meiotic  spermatocytes  and  especially  post‐meiotic  round  spermatids  have  remarkably diverse  transcriptomes,  which  explains  the  high  transcriptome  complexity  of  the  testis  as  a  whole.  The widespread  transcriptional  activity  in  spermatocytes  and  spermatids  encompasses  protein‐coding  genes  and long  noncoding  RNA  genes  but  also  poorly  conserved  intergenic  sequences,  suggesting  that  much  of  it  is  not of  immediate  functional  relevance.  Rather,  our  analyses  of  genome‐wide  epigenetic  data  show  that  this prevalent  transcription,  which  apparently  promoted  the  birth  of  new  genes  during  evolution,  results  from  a highly  permissive  chromatin  state  during  and  after  meiosis  that  may  ultimately  facilitate  the  replacement  of histones by protamines during late spermatogenesis. To study the cellular source and mechanisms of high transcriptome complexity in the mammalian testis, we generated strand-specific deep coverage RNA‐Seq data for purified sertoli cells, spermatogonia, spermatocytes, spermatids and spermatozoa as well as for brain, liver and the whole testis from the mouse. We prepared 8 sequencing libraries for the polyadenylated RNA fraction of each sample and sequenced each library in 3 lanes of the Illumina Genome Analyser IIx platform, yielding a total of >60 millions strand-specific reads of 76 base pairs per sample. In addition, we generated ChIP-Seq data for the H3K4me2 modification as well as RRBS data for brain, liver, testis, spermatocytes and spermatids. RNA-seq, ChIP-seq and RRBS data were generated from the same individual or pool of individuals, in the case of purified cells.