Variation in Pleiotropic Hub Gene Expression Is Associated with Interspecific Differences in Head Shape and Eye Size in Drosophila

Abstract

Revealing the mechanisms underlying the breathtaking morphological diversity observed in nature is a major challenge in Biology. It has been established that recurrent mutations in hotspot genes cause the repeated evolution of morphological traits, such as body pigmentation or the gain and loss of structures. To date, however, it remains elusive whether hotspot genes contribute to natural variation in the size and shape of organs. As natural variation in head morphology is pervasive in Drosophila, we studied the molecular and developmental basis of differences in compound eye size and head shape in two closely related Drosophila species. We show differences in the progression of retinal differentiation between species and we applied comparative transcriptomics and chromatin accessibility data to identify the GATA transcription factor Pannier (Pnr) as central factor associated with these differences. Although the genetic manipulation of Pnr affected multiple aspects of dorsal head development, the effect of natural variation is restricted to a subset of the phenotypic space. We present data suggesting that this developmental constraint is caused by the coevolution of expression of pnr and its cofactor u-shaped (ush). We propose that natural variation in expression or function of highly connected developmental regulators with pleiotropic functions is a major driver for morphological evolution and we discuss implications on gene regulatory network evolution. In comparison to previous findings, our data strongly suggest that evolutionary hotspots are not the only contributors to the repeated evolution of eye size and head shape in Drosophila.

A data-driven biocomputing pipeline with meta-analysis on high throughput transcriptomics to identify genome-wide miRNA markers associated with type 2 diabetes

“…Concordant findings from contemporary studies with respect to the meta-signature are summarized in S6 Table . Systems biology insights on miRNA-T2D associations, rendered by network analyses are noteworthy. Since the two hub nodes (hsa-miR-106b-5p & hsa-miR-15b-5p) which formed epicenters of the two most densely and extensively connected sub-networks might have crucial functional roles as well [35,36], further research on their roles on T2D pathogenesis is warranted. Another insightful observation was the disproportionately high representation of three markers (hsa-miR-15b-5p, hsa-miR-106b-3p, hsa-miR-146a-5p) within the miRNA-disease associations network, which suggested that they likely have key roles in the development of not only T2D but also other cardiometabolic diseases and co-morbidities via multiple cross-talk and pleiotropic mechanisms.…”

“…Network analysis of the meta-signature was carried out on the miRNet 2.0 [34], which, by default, defines hub-nodes as those miRNAs with above-average degree and betweenness in the miRNA-target gene interactions network. These two measures of centrality can be defined as follows: As the densely and tightly connected hub nodes in biological networks [35] tend to be critical functional regulators as well, they are sought after in precision medicine approaches [36]. We visualized the miRNA-target gene interactions network on miRNet 2.0 and determined the network attributes including hub nodes, modules, and continents versus islands.…”

Marker genes of incident type 1 diabetes in peripheral blood mononuclear cells of children: A machine learning strategy for large-p, small-n scenarios

“…Further studies exploring these interactions could enhance our understanding of the genetic basis of T1D. Hub genes which appear as extensively and densely connected nodes in scale-free gene regulatory networks [50] tend to have important regulatory functions and offer value as potential therapeutic targets [51]. Therefore, hub genes identified in this analysis may be useful for guiding pharmacogenomics studies focused on T1D.…”

Behavior Individuality: A Focus on Drosophila melanogaster

“…Also, variation in odor guidance to 2,3-butanedione showed genes associated with neural development and the later processing in the central nervous system which might be related to that behavioral variation (Brown et al, 2013 ). This genotypic variation is seen not only at the behavioral level but also, for example, in lifespan or morphological and anatomical traits as brain, wing, thorax, or eye size (Carreira et al, 2016 ; Buchberger et al, 2021 ).…”