Gene expression differentiation in the reproductive tissues of Drosophila willistoni subspecies and their hybrids

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. In Drosophila hybrids, how regulatory evolution impacts different reproductive tissues remains understudied. Here, we generate a new genome assembly and annotation in Drosophila willistoni and analyse the patterns of transcriptome divergence between two allopatrically evolved D. willistoni subspecies, 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 celltype 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 the D. willistoni X chromosome. Compared to the autosomes, the X chromosome 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 diverged D. willistoni subspecies and their hybrids provides a more nuanced view of early regulatory changes during speciation.

Evolution and genetics of accessory gland transcriptome divergence betweenDrosophila melanogasterand D.simulans

“…reviewed inSignor and Nuzhdin 2018;Hill, Vande Zande, and Wittkopp 2021;Ranz et al 2023). Our results do not support this model, in line with results from some other studies(McManus et al 2010;Coolon et al 2014;Sánchez-Ramírez et al 2021).…”

“…Further, just a handful of genes have complete GOF or LOF expression phenotypes. These results suggest that the accessory gland is not prone to widespread dysgenesis between these species, in contrast to results from Drosophila testis or female whole-animal data (Ranz et al 2004;Haerty and Singh 2006;Moehring, Teeter, and Noor 2007;McManus et al 2010;Coolon et al 2014;Cartwright and Lott 2020;Ranz et al 2023), Caenorhabditis data (Sánchez-Ramírez et al 2021), mouse liver (Goncalves et al 2012) and testis (Mack, Campbell, and Nachman 2016) data. Thus, our transcriptomic data are consistent with the observations of Stumm-Zollinger and Chen (1988), that hybrid accessory glands have relatively normal morphology, seminal fluid, and ability to induce the female PMR.…”

“…Wittkopp, Haerum, and Clark 2008;McManus et al 2010;Wei, Clark, and Barbash 2014;Coolon et al 2014) or heads (Graze et al 2009). While this literature has generated important results and patterns, the possibility remains of henceforth undiscovered genetically and evolutionary important regulatory heterogeneity across organs in Drosophila (Ranz et al 2023). Additional studies used ASE to investigate interspecific regulatory divergence in Drosophila testis (Haerty and Singh 2006;Lu et al 2010;Llopart 2012;Brill et al 2016;Banho et al 2021); while this work has shed light on the regulatory basis of hybrid male sterility, conclusions from studies of this organ may not apply to gene regulatory evolution more broadly.…”

PhyloAln: a convenient reference-based tool to align sequences and high-throughput reads for phylogeny and evolution in the omic era

“…To assess PhyloAln’s capability in mapping sequences/reads into reference alignments across diverse species spanning the tree of life and its performance on contaminated data, we constructed a simulated dataset. This dataset comprises genomes from one bacterium ( Escherichia coli (Hayashi, et al 2001)), one plant ( Arabidopsis thaliana (Cheng, et al 2017)), one fungus ( Saccharomyces cerevisiae (Engel, et al 2022)), two vertebrates ( Danio rerio (Howe, et al 2013) and Homo sapiens (Collins, et al 2004)), eight fruit flies ( Scaptodrosophila lebanonensis (Flynn, et al 2020), Drosophila melanogaster (Hoskins, et al 2015), D. simulans (Wang, et al 2023), D. willistoni (Ranz, et al 2023), D. mojavensis (Kim, et al 2021), D. yakuba (Huang, et al 2022), D. busckii (Renschler, et al 2019), D. pseudoobscura (Barata, et al 2023)) and two other insects ( Tribolium castaneum (Herndon, et al 2020) and Aedes aegypti (Matthews, et al 2018)), sourced from the NCBI RefSeq database (Haft, et al 2023) (Table S1). The phylogeny of these species was obtained from the TimeTree database (Kumar, et al 2022).…”

PhyloAln: A Convenient Reference-Based Tool to Align Sequences and High-Throughput Reads for Phylogeny and Evolution in the Omic Era

“…To assess capability of PhyloAln in mapping sequences/reads into reference MSAs across diverse species spanning the tree of life and its performance on contaminated data, we constructed a simulated data set. This data set comprises genomes from one bacterium ( Escherichia coli [ Hayashi et al 2001 ]), one plant ( A. thaliana [ Cheng et al 2017 ]), one fungus ( Saccharomyces cerevisiae [ Engel et al 2022 ]), two vertebrates ( Danio rerio [ Howe et al 2013 ] and H. sapiens [ Collins et al 2004 ]), eight fruit flies ( S. lebanonensis [ Flynn et al 2020 ], D. melanogaster [ Hoskins et al 2015 ], D. simulans [ Wang et al 2023 ], D. willistoni [ Ranz et al 2023 ], Drosophila mojavensis [ Kim et al 2021 ], Drosophila yakuba [ Huang et al 2022 ], Drosophila busckii [ Renschler et al 2019 ], and Drosophila pseudoobscura [ Barata et al 2023 ]), and two other insects ( Tribolium castaneum [ Herndon et al 2020 ] and Aedes aegypti [ Matthews et al 2018 ]), sourced from the NCBI RefSeq database ( Haft et al 2024 ) ( supplementary table S1, Supplementary Material online). The phylogeny of these species was obtained from the TimeTree database ( Kumar et al 2022 ).…”