The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster
The Drosophila sex determination hierarchy is a classic example of a transcriptional regulatory hierarchy, with sex-specific isoforms regulating morphology and behavior. We use a structural equation modeling approach, leveraging natural genetic variation from two studies on Drosophila female head ti...
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description | The Drosophila sex determination hierarchy is a classic example of a transcriptional regulatory hierarchy, with sex-specific isoforms regulating morphology and behavior. We use a structural equation modeling approach, leveraging natural genetic variation from two studies on Drosophila female head tissues--DSPR collection (596 F1-hybrids from crosses between DSPR sub-populations) and CEGS population (75 F1-hybrids from crosses between DGRP/Winters lines to a reference strain w1118)--to expand understanding of the sex hierarchy gene regulatory network (GRN). This approach is completely generalizable to any natural population, including humans.
We expanded the sex hierarchy GRN adding novel links among genes, including a link from fruitless (fru) to Sex-lethal (Sxl) identified in both populations. This link is further supported by the presence of fru binding sites in the Sxl locus. 754 candidate genes were added to the pathway, including the splicing factors male-specific lethal 2 and Rm62 as downstream targets of Sxl which are well-supported links in males. Independent studies of doublesex and transformer mutants support many additions, including evidence for a link between the sex hierarchy and metabolism, via Insulin-like receptor.
The genes added in the CEGS population were enriched for genes with sex-biased splicing and components of the spliceosome. A common goal of molecular biologists is to expand understanding about regulatory interactions among genes. Using natural alleles we can not only identify novel relationships, but using supervised approaches can order genes into a regulatory hierarchy. Combining these results with independent large effect mutation studies, allows clear candidates for detailed molecular follow-up to emerge. |
doi_str_mv | 10.1186/s12918-015-0200-0 |
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We expanded the sex hierarchy GRN adding novel links among genes, including a link from fruitless (fru) to Sex-lethal (Sxl) identified in both populations. This link is further supported by the presence of fru binding sites in the Sxl locus. 754 candidate genes were added to the pathway, including the splicing factors male-specific lethal 2 and Rm62 as downstream targets of Sxl which are well-supported links in males. Independent studies of doublesex and transformer mutants support many additions, including evidence for a link between the sex hierarchy and metabolism, via Insulin-like receptor.
The genes added in the CEGS population were enriched for genes with sex-biased splicing and components of the spliceosome. A common goal of molecular biologists is to expand understanding about regulatory interactions among genes. Using natural alleles we can not only identify novel relationships, but using supervised approaches can order genes into a regulatory hierarchy. Combining these results with independent large effect mutation studies, allows clear candidates for detailed molecular follow-up to emerge.</description><identifier>ISSN: 1752-0509</identifier><identifier>EISSN: 1752-0509</identifier><identifier>DOI: 10.1186/s12918-015-0200-0</identifier><identifier>PMID: 26335107</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Analysis ; Animals ; Computational Biology - methods ; DNA-Binding Proteins - genetics ; Drosophila ; Drosophila melanogaster - genetics ; Drosophila Proteins - genetics ; Female ; Gene Regulatory Networks ; Genetic aspects ; Male ; Models, Genetic ; Nuclear Proteins - genetics ; Physiological aspects ; RNA, Messenger - genetics ; RNA, Messenger - metabolism ; Sex Determination Processes - genetics ; Supervised Machine Learning ; Unsupervised Machine Learning</subject><ispartof>BMC systems biology, 2015-09, Vol.9 (1), p.53-53, Article 53</ispartof><rights>COPYRIGHT 2015 BioMed Central Ltd.</rights><rights>Copyright BioMed Central 2015</rights><rights>Fear et al. 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c598t-12cdb3c99af445c4fbb2519b54bf791732a4c845f0515304cf961a09d5b2585d3</citedby><cites>FETCH-LOGICAL-c598t-12cdb3c99af445c4fbb2519b54bf791732a4c845f0515304cf961a09d5b2585d3</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/PMC4558766/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558766/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26335107$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fear, Justin M</creatorcontrib><creatorcontrib>Arbeitman, Michelle N</creatorcontrib><creatorcontrib>Salomon, Matthew P</creatorcontrib><creatorcontrib>Dalton, Justin E</creatorcontrib><creatorcontrib>Tower, John</creatorcontrib><creatorcontrib>Nuzhdin, Sergey V</creatorcontrib><creatorcontrib>McIntyre, Lauren M</creatorcontrib><title>The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster</title><title>BMC systems biology</title><addtitle>BMC Syst Biol</addtitle><description>The Drosophila sex determination hierarchy is a classic example of a transcriptional regulatory hierarchy, with sex-specific isoforms regulating morphology and behavior. We use a structural equation modeling approach, leveraging natural genetic variation from two studies on Drosophila female head tissues--DSPR collection (596 F1-hybrids from crosses between DSPR sub-populations) and CEGS population (75 F1-hybrids from crosses between DGRP/Winters lines to a reference strain w1118)--to expand understanding of the sex hierarchy gene regulatory network (GRN). This approach is completely generalizable to any natural population, including humans.
We expanded the sex hierarchy GRN adding novel links among genes, including a link from fruitless (fru) to Sex-lethal (Sxl) identified in both populations. This link is further supported by the presence of fru binding sites in the Sxl locus. 754 candidate genes were added to the pathway, including the splicing factors male-specific lethal 2 and Rm62 as downstream targets of Sxl which are well-supported links in males. Independent studies of doublesex and transformer mutants support many additions, including evidence for a link between the sex hierarchy and metabolism, via Insulin-like receptor.
The genes added in the CEGS population were enriched for genes with sex-biased splicing and components of the spliceosome. A common goal of molecular biologists is to expand understanding about regulatory interactions among genes. Using natural alleles we can not only identify novel relationships, but using supervised approaches can order genes into a regulatory hierarchy. Combining these results with independent large effect mutation studies, allows clear candidates for detailed molecular follow-up to emerge.</description><subject>Analysis</subject><subject>Animals</subject><subject>Computational Biology - methods</subject><subject>DNA-Binding Proteins - genetics</subject><subject>Drosophila</subject><subject>Drosophila melanogaster - genetics</subject><subject>Drosophila Proteins - genetics</subject><subject>Female</subject><subject>Gene Regulatory Networks</subject><subject>Genetic aspects</subject><subject>Male</subject><subject>Models, Genetic</subject><subject>Nuclear Proteins - genetics</subject><subject>Physiological aspects</subject><subject>RNA, Messenger - genetics</subject><subject>RNA, Messenger - metabolism</subject><subject>Sex Determination Processes - genetics</subject><subject>Supervised Machine Learning</subject><subject>Unsupervised Machine Learning</subject><issn>1752-0509</issn><issn>1752-0509</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNptkl9v1iAUxhujcXP6AbwxJN7oRSdQaMELk2XqXLLERGe8JJRCy9JCBfpm762fXJp3_97FcAHh_M7DOYenKF4jeIwQqz9EhDliJUS0hBjCEj4pDlFDcQkp5E8fnA-KFzFeQUgrjJvnxQGuq4oi2BwWfy8HDX4H2w8JxLQY8xEEbSfZW2ddD2aZBiCdHLfRxhzZaDlG4PxGj0D5afZOuxSBNyBlnaivQaeTDpN1MlnvwGB1kEENW2Ad-Bx89PNgRwkmPUrnexkz_LJ4ZrKqfnWzHxW_vn65PP1WXnw_Oz89uSgV5SyVCKuurRTn0hBCFTFtiyniLSWtaThqKiyJYoQaSBGtIFGG10hC3tHMMdpVR8Wnne68tJPuVK48yFHMIbcbtsJLK_Yjzg6i9xtBKGVNXWeBdzcCwf9ZdExislHpMbei_RIFaiBvEKGEZfTtI_TKLyHPcaUYRJjVGN5TvRy1sM74_K5aRcUJJYjUDWYkU8f_ofLq9GRV_gFj8_1ewvu9hMwkfZ16ucQozn_-2GfRjlX5c2LQ5m4eCIrVZGJnMpFNJlaTibXsNw8HeZdx66rqHzdtzWU</recordid><startdate>20150904</startdate><enddate>20150904</enddate><creator>Fear, Justin M</creator><creator>Arbeitman, Michelle N</creator><creator>Salomon, Matthew P</creator><creator>Dalton, Justin E</creator><creator>Tower, John</creator><creator>Nuzhdin, Sergey V</creator><creator>McIntyre, Lauren M</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>3V.</scope><scope>7QL</scope><scope>7TM</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P64</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20150904</creationdate><title>The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster</title><author>Fear, Justin M ; Arbeitman, Michelle N ; Salomon, Matthew P ; Dalton, Justin E ; Tower, John ; Nuzhdin, Sergey V ; McIntyre, Lauren M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c598t-12cdb3c99af445c4fbb2519b54bf791732a4c845f0515304cf961a09d5b2585d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Analysis</topic><topic>Animals</topic><topic>Computational Biology - methods</topic><topic>DNA-Binding Proteins - genetics</topic><topic>Drosophila</topic><topic>Drosophila melanogaster - genetics</topic><topic>Drosophila Proteins - genetics</topic><topic>Female</topic><topic>Gene Regulatory Networks</topic><topic>Genetic aspects</topic><topic>Male</topic><topic>Models, Genetic</topic><topic>Nuclear Proteins - genetics</topic><topic>Physiological aspects</topic><topic>RNA, Messenger - genetics</topic><topic>RNA, Messenger - metabolism</topic><topic>Sex Determination Processes - genetics</topic><topic>Supervised Machine Learning</topic><topic>Unsupervised Machine Learning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fear, Justin M</creatorcontrib><creatorcontrib>Arbeitman, Michelle N</creatorcontrib><creatorcontrib>Salomon, Matthew P</creatorcontrib><creatorcontrib>Dalton, Justin E</creatorcontrib><creatorcontrib>Tower, John</creatorcontrib><creatorcontrib>Nuzhdin, Sergey V</creatorcontrib><creatorcontrib>McIntyre, Lauren M</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>Bacteriology Abstracts (Microbiology B)</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</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>AIDS and Cancer Research Abstracts</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>Algology Mycology and Protozoology Abstracts (Microbiology C)</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 systems biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fear, Justin M</au><au>Arbeitman, Michelle N</au><au>Salomon, Matthew P</au><au>Dalton, Justin E</au><au>Tower, John</au><au>Nuzhdin, Sergey V</au><au>McIntyre, Lauren M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster</atitle><jtitle>BMC systems biology</jtitle><addtitle>BMC Syst Biol</addtitle><date>2015-09-04</date><risdate>2015</risdate><volume>9</volume><issue>1</issue><spage>53</spage><epage>53</epage><pages>53-53</pages><artnum>53</artnum><issn>1752-0509</issn><eissn>1752-0509</eissn><abstract>The Drosophila sex determination hierarchy is a classic example of a transcriptional regulatory hierarchy, with sex-specific isoforms regulating morphology and behavior. We use a structural equation modeling approach, leveraging natural genetic variation from two studies on Drosophila female head tissues--DSPR collection (596 F1-hybrids from crosses between DSPR sub-populations) and CEGS population (75 F1-hybrids from crosses between DGRP/Winters lines to a reference strain w1118)--to expand understanding of the sex hierarchy gene regulatory network (GRN). This approach is completely generalizable to any natural population, including humans.
We expanded the sex hierarchy GRN adding novel links among genes, including a link from fruitless (fru) to Sex-lethal (Sxl) identified in both populations. This link is further supported by the presence of fru binding sites in the Sxl locus. 754 candidate genes were added to the pathway, including the splicing factors male-specific lethal 2 and Rm62 as downstream targets of Sxl which are well-supported links in males. Independent studies of doublesex and transformer mutants support many additions, including evidence for a link between the sex hierarchy and metabolism, via Insulin-like receptor.
The genes added in the CEGS population were enriched for genes with sex-biased splicing and components of the spliceosome. A common goal of molecular biologists is to expand understanding about regulatory interactions among genes. Using natural alleles we can not only identify novel relationships, but using supervised approaches can order genes into a regulatory hierarchy. Combining these results with independent large effect mutation studies, allows clear candidates for detailed molecular follow-up to emerge.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>26335107</pmid><doi>10.1186/s12918-015-0200-0</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Animals Computational Biology - methods DNA-Binding Proteins - genetics Drosophila Drosophila melanogaster - genetics Drosophila Proteins - genetics Female Gene Regulatory Networks Genetic aspects Male Models, Genetic Nuclear Proteins - genetics Physiological aspects RNA, Messenger - genetics RNA, Messenger - metabolism Sex Determination Processes - genetics Supervised Machine Learning Unsupervised Machine Learning |
title | The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster |
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