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

Abstract

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.

Fig. 1

The Drosophila sex determination hierarchy in females. Transcripts are in red and proteins are in blue. Solid arrows are genetic interactions (e.g. splicing, transcription) and dashed arrows are protein translation. (1) Spf45 → Sxl [122], (2) Snf → Sxl [123], (3) vir → Sxl [27], (4) vir → tra [27], (5) fl(2)d → Sxl [10], (6) Sxl → Sxl [122], (7) Sxl → Tra [28, 124], (8) Sxl -| Msl-2 [2, 88, 125], (9) fl(2)d → Tra [126], (10) Tra → DsxF [71], (11) Tra2 → DsxF [71], (12) DsxF → Yps [16, 127, 128], (13) Her → Yps [129], (14) ix → Yps [67]

Fig. 2

Identification of appropriate covariance structure for baseline model. Three separate covariance models were compared for the DSPR (a-c) and the CEGS (d-e). The full covariance model (a and d) allows all independent, or exogenous, genes to freely co-vary (blue lines). The full covariance model implies that there are unknown regulatory factor(s) that is drive expression of the genes in the sex hierarchy GRN. The no covariance model (b and e) constrains all covariances between exogenous genes to 0. The no covariance implies that the independent genes in the model are truly independent and are not regulated by some unknown factor. The partial covariance model (c and f) allows exogenous genes to freely covary (blue lines). The partial covariance models implies that some of the exogenous genes in the sex hierarchy GRN may be controlled by an unknown factor such as the transcriptional or splicing machinery

Fig. 3

New paths added in both the DSPR and CEGS populations. Directional arrows represent the path between genes. The baseline sex hierarchy SEM is indicated with black arrows and is based on the current understanding of the literature (summarized in Fig. 1). Twelve additional paths improved model fit for both the DSPR and CEGS population compared to their respective baseline models (Fig. 2). Ten of these show bi-directional relationships (blue arrows) and two had a single directional relationship (unidirectional red arrows)

Fig. 4

Sex hierarchy expansion. a All genes expressed in the CEGS data were added to the baseline model one at a time to all possible paths and model fit was assessed using BIC. For each possible addition the regulatory relationship (arrows) has a parameter estimate (γ for exogenous → endogenous and β endogenous → endogenous). There were 754 genes with BIC values lower than the baseline. Some examples include: msl-2 downstream of Sxl b , Psa in between tra and fru c, and InR downstream of Sxl d

Fig. 5

Genome-wide graphical Gaussian network of genes in the DSPR and CEGS. Red boxes represent genes that are part of the sex hierarchy or associated splicing factors. Blue boxes are remaining genes in the DSPR (a, c, e) or CEGS (b, d, f). (a-b) Visualization of the genome-wide GGN. (c-d) The primary neighborhood 1-step out from sex determination genes. (e-f) The secondary neighborhood 2-steps out from sex determination genes