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Abstract Early lineage diversification is central to understand what mutational events drive species divergence. Particularly, gene misregulation in interspecific hybrids can inform about what genes and pathways underlie hybrid dysfunction. InDrosophilahybrids, how regulatory evolution impacts different reproductive tissues remains understudied. Here, we generate a new genome assembly and annotation inDrosophila willistoniand analyse the patterns of transcriptome divergence between two allopatrically evolvedD. willistonisubspecies, their male sterile and female fertile hybrid progeny across testis, male accessory gland, and ovary. Patterns of transcriptome divergence and modes of regulatory evolution were tissue‐specific. Despite no indication for cell‐type differences in hybrid testis, this tissue exhibited the largest magnitude of expression differentiation between subspecies and between parentals and hybrids. No evidence for anomalous dosage compensation in hybrid male tissues was detected nor was a differential role for the neo‐ and the ancestral arms of theD. willistoni Xchromosome. Compared to the autosomes, theXchromosome appeared enriched for transgressively expressed genes in testis despite being the least differentiated in expression between subspecies. Evidence for fine genome clustering of transgressively expressed genes suggests a role of chromatin structure on hybrid gene misregulation. Lastly, transgressively expressed genes in the testis of the sterile male progeny were enriched for GO terms not typically associated with sperm function, instead hinting at anomalous development of the reproductive tissue. Our thorough tissue‐level portrait of transcriptome differentiation between recently divergedD. willistonisubspecies and their hybrids provides a more nuanced view of early regulatory changes during speciation.
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Gene communities in co-expression networks across different tissues
With the recent availability of tissue-specific gene expression data, e.g., provided by the GTEx Consortium, there is interest in comparing gene co-expression patterns across tissues. One promising approach to this problem is to use a multilayer network analysis framework and perform multilayer community detection. Communities in gene co-expression networks reveal groups of genes similarly expressed across individuals, potentially involved in related biological processes responding to specific environmental stimuli or sharing common regulatory variations. We construct a multilayer network in which each of the four layers is an exocrine gland tissue-specific gene co-expression network. We develop methods for multilayer community detection with correlation matrix input and an appropriate null model. Our correlation matrix input method identifies five groups of genes that are similarly co-expressed in multiple tissues (a community that spans multiple layers, which we call a generalist community) and two groups of genes that are co-expressed in just one tissue (a community that lies primarily within just one layer, which we call a specialist community). We further found gene co-expression communities where the genes physically cluster across the genome significantly more than expected by chance (on chromosomes 1 and 11). This clustering hints at underlying regulatory elements determining similar expression patterns across individuals and cell types. We suggest thatKRTAP3-1,KRTAP3-3, andKRTAP3-5share regulatory elements in skin and pancreas. Furthermore, we find thatCELA3AandCELA3Bshare associated expression quantitative trait loci in the pancreas. The results indicate that our multilayer community detection method for correlation matrix input extracts biologically interesting communities of genes.
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- PAR ID:
- 10493890
- Editor(s):
- Fu, Feng
- Publisher / Repository:
- Plos Computational Biology
- Date Published:
- Journal Name:
- PLOS Computational Biology
- Volume:
- 19
- Issue:
- 11
- ISSN:
- 1553-7358
- Page Range / eLocation ID:
- e1011616
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pcbi.1011616
