bioRxivDevelopmental BiologyPreprint
Determination of novel members in the Drosophila melanogaster anterior-posterior patterning system using natural variation
Ashley A. JermusykiD, Sarah E. Gharavi, Aslesha S. Tingare, Gregory T. ReevesiD
Abstract
The anterior-posterior axis of the developing Drosophila melanogaster embryo is patterned by a well-studied gene regulatory network called the Gap Gene Network. This network acts to buffer the developing pattern against noise, thereby minimizing errors in gene expression and preventing patterning defects.\n\nIn this paper, we sought to discover novel regulatory regions and transcription factors acting in a subset of the Gap network using a selection of wild-caught fly lines derived from the Drosophila Genetic Reference Panel (DGRP). The fly lines in the DGRP contain subtle genomic differences due to natural variation; we quantified the differences in positioning of gene expression borders of two anterior-poster patterning genes, Kruppel (Kr) and Even-skipped in 13 of the DGRP lines. The differences in the positions of Kruppel and Even-skipped were then correlated to specific single nucleotide polymorphisms and insertions/deletions within the select fly lines. Putative enhancers containing these genomic differences were validated for their ability to produce expression using reporter constructs and analyzed for possible transcription factor binding sites. The identified transcription factors were then perturbed and the resulting Eve and Kr positioning was determined. In this way, we found medea, ultraspiracle, glial cells missing, and orthopedia effect Kr and Eve positioning in subtle ways, while knock-down of pangolin produces significant shifts in Kr and subsequent Eve expression patterns. Most importantly this study points to the existence of many additional novel members that have subtle effects on this system and the degree of complexity that is present in patterning the developing embryo.
- organism: Drosophila
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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