The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster.
BACKGROUND
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.


RESULTS
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.


CONCLUSIONS
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.
Department of Molecular Genetics and Microbiology, University of Florida, CGRC Room 116, PO Box 100266, FL 32610-0266, Gainesville, FL, USA. jfear@ufl.edu.
Justin M
JM
Fear
Biomedical Science, Florida State University, Tallahassee, FL, USA. michelle.arbeitman@med.fsu.edu.
Michelle N
MN
Arbeitman
Molecular and Computational Biology, University of California, Los Angeles, CA, USA. msalomon@usc.edu.
Matthew P
MP
Salomon
Biomedical Science, Florida State University, Tallahassee, FL, USA. justin.eric.dalton@gmail.com.
Justin E
JE
Dalton
Molecular and Computational Biology, University of California, Los Angeles, CA, USA. jtower@usc.edu.
John
J
Tower
Molecular and Computational Biology, University of California, Los Angeles, CA, USA. snuzhdin@usc.edu.
Sergey V
SV
Nuzhdin
Department of Molecular Genetics and Microbiology, University of Florida, CGRC Room 116, PO Box 100266, FL 32610-0266, Gainesville, FL, USA. mcintyre@ufl.edu.
Lauren M
LM
McIntyre
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D004268:DNA-Binding Proteins / Q000235:genetics; D029721:Drosophila Proteins / Q000235:genetics; D004331:Drosophila melanogaster / Q000235:genetics*; D005260:Female; D053263:Gene Regulatory Networks; D008297:Male; D008957:Models, Genetic; D009687:Nuclear Proteins / Q000235:genetics; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D019849:Sex Determination Processes / Q000235:genetics*; D000069553:Supervised Machine Learning; D000069558:Unsupervised Machine Learning
D004268:DNA-Binding Proteins; C070369:DSX protein, Drosophila; D029721:Drosophila Proteins; D009687:Nuclear Proteins; D012333:RNA, Messenger; C097162:Tra protein, Drosophila