Integrated transcriptome analysis of mouse spermatogenesis
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...
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description | 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.
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.
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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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.
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.</description><identifier>ISSN: 1471-2164</identifier><identifier>EISSN: 1471-2164</identifier><identifier>DOI: 10.1186/1471-2164-15-39</identifier><identifier>PMID: 24438502</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Algorithms ; Alternative Splicing ; Analysis ; Animals ; Cluster Analysis ; Gene expression ; Gene Expression Profiling ; Genetic aspects ; Genetic diversity ; Genomes ; Genomics ; Male ; Meiosis ; Messenger RNA ; Mice ; Open Reading Frames ; RNA polymerase ; RNA Polymerase II - metabolism ; RNA sequencing ; Rodents ; Sequence Analysis, RNA ; Sperm ; Spermatogenesis ; Spermatogenesis - genetics ; Spermatozoa - metabolism ; Studies ; Transcriptional Elongation Factors - genetics ; Transcriptional Elongation Factors - metabolism</subject><ispartof>BMC genomics, 2014-01, Vol.15 (1), p.39-39, Article 39</ispartof><rights>COPYRIGHT 2014 BioMed Central Ltd.</rights><rights>2014 Margolin et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><rights>Copyright © 2014 Margolin et al.; licensee BioMed Central Ltd. 2014 Margolin et al.; licensee BioMed Central Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b680t-3b00be3d3f3f59f72bba7fcb978de15a7390580d51024a25098659dba26559143</citedby><cites>FETCH-LOGICAL-b680t-3b00be3d3f3f59f72bba7fcb978de15a7390580d51024a25098659dba26559143</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3906902/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3906902/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24438502$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Margolin, Gennady</creatorcontrib><creatorcontrib>Khil, Pavel P</creatorcontrib><creatorcontrib>Kim, Joongbaek</creatorcontrib><creatorcontrib>Bellani, Marina A</creatorcontrib><creatorcontrib>Camerini-Otero, R Daniel</creatorcontrib><title>Integrated transcriptome analysis of mouse spermatogenesis</title><title>BMC genomics</title><addtitle>BMC Genomics</addtitle><description>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.
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.
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.</description><subject>Algorithms</subject><subject>Alternative Splicing</subject><subject>Analysis</subject><subject>Animals</subject><subject>Cluster Analysis</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Genetic aspects</subject><subject>Genetic diversity</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Male</subject><subject>Meiosis</subject><subject>Messenger RNA</subject><subject>Mice</subject><subject>Open Reading Frames</subject><subject>RNA polymerase</subject><subject>RNA Polymerase II - metabolism</subject><subject>RNA sequencing</subject><subject>Rodents</subject><subject>Sequence Analysis, RNA</subject><subject>Sperm</subject><subject>Spermatogenesis</subject><subject>Spermatogenesis - genetics</subject><subject>Spermatozoa - metabolism</subject><subject>Studies</subject><subject>Transcriptional Elongation Factors - 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metabolism</topic><topic>RNA sequencing</topic><topic>Rodents</topic><topic>Sequence Analysis, RNA</topic><topic>Sperm</topic><topic>Spermatogenesis</topic><topic>Spermatogenesis - genetics</topic><topic>Spermatozoa - metabolism</topic><topic>Studies</topic><topic>Transcriptional Elongation Factors - genetics</topic><topic>Transcriptional Elongation Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Margolin, Gennady</creatorcontrib><creatorcontrib>Khil, Pavel P</creatorcontrib><creatorcontrib>Kim, Joongbaek</creatorcontrib><creatorcontrib>Bellani, Marina A</creatorcontrib><creatorcontrib>Camerini-Otero, R Daniel</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BMC genomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Margolin, Gennady</au><au>Khil, Pavel P</au><au>Kim, Joongbaek</au><au>Bellani, Marina A</au><au>Camerini-Otero, R Daniel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrated transcriptome analysis of mouse spermatogenesis</atitle><jtitle>BMC genomics</jtitle><addtitle>BMC Genomics</addtitle><date>2014-01-18</date><risdate>2014</risdate><volume>15</volume><issue>1</issue><spage>39</spage><epage>39</epage><pages>39-39</pages><artnum>39</artnum><issn>1471-2164</issn><eissn>1471-2164</eissn><abstract>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.
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.
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.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>24438502</pmid><doi>10.1186/1471-2164-15-39</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Alternative Splicing Analysis Animals Cluster Analysis Gene expression Gene Expression Profiling Genetic aspects Genetic diversity Genomes Genomics Male Meiosis Messenger RNA Mice Open Reading Frames RNA polymerase RNA Polymerase II - metabolism RNA sequencing Rodents Sequence Analysis, RNA Sperm Spermatogenesis Spermatogenesis - genetics Spermatozoa - metabolism Studies Transcriptional Elongation Factors - genetics Transcriptional Elongation Factors - metabolism |
title | Integrated transcriptome analysis of mouse spermatogenesis |
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