Data from: Quantitative proteomics reveals rapid divergence in the postmating response of female reproductive tracts among sibling species
McCullough, Erin; McDonough, Caitlin; Pitnick, Scott; Dorus, Steve (2020), Data from: Quantitative proteomics reveals rapid divergence in the postmating response of female reproductive tracts among sibling species, Dryad, Dataset, https://doi.org/10.5061/dryad.8cz8w9gm8
Fertility depends, in part, on interactions between male and female reproductive proteins inside the female reproductive tract (FRT) that mediate postmating changes in female behavior, morphology, and physiology. Coevolution between interacting proteins within species may drive reproductive incompatibilities between species, yet the mechanisms underlying postmating-prezygotic isolating barriers remain poorly resolved. Here, we used quantitative proteomics in sibling Drosophila species to investigate the molecular composition of the FRT environment and its role in mediating species-specific postmating responses. We found that (1) FRT proteomes in D. simulans and D. mauritiana virgin females express unique combinations of secreted proteins and are enriched for distinct functional categories, (2) mating induces substantial changes to the FRT proteome in D. mauritiana but not in D. simulans, and (3) the D. simulans FRT proteome exhibits limited postmating changes irrespective of whether females mate with conspecific or heterospecific males, suggesting an active female role in mediating reproductive interactions. Comparisons with similar data in the closely related outgroup species D. melanogaster suggest that divergence is concentrated on the D. simulans lineage. Our study suggests that divergence in the FRT extracellular environment and postmating response contribute to previously described patterns of postmating-prezygotic isolation and the maintenance of species boundaries.
D. simulans and D. mauritiana FRT proteins
FRT samples were collected from the following five conditions: Drosophila simulans virgins (sim virgins), D. mauritiana virgins (mau virgins), D. simulans females mated to D. simulans males (sim × sim), D. mauritiana females mated to D. mauritiana males (mau × mau), and D. simulans females mated to D. mauritiana males (sim × mau). Mated samples were collected 6h after the end of a successful copulation. FRTs (i.e., bursa, oviduct, seminal receptacle, spermathecae, parovaria, and associated fat body) of ~100 females from each condition were dissected, pooled in PBS per replicate, and solubilized in 1M HEPES with 2% SDS and 5% b-mercaptoethanol. Two replicates were collected per condition resulting in ten samples. Samples were labelled with TMT isobaric tags and analyzed by LC-MS/MS. Peptides were quantified using a synchronous precursor selection MS3 method. Mass spectra were searched against the D. simulans protein database (dsim-all-translation-r2.02, FlyBase.org) using PEAKS X (Bioinformatics Solutions Inc.). Reporter ion intensities were calculated by summing the centroided reporter ions, and protein abundances were calculated by summing the reporter ion intensities in each channel. Peptide identifications were accepted if the false discovery rate (FDR) < 1% based on the decoy-fusion approach, and protein identifications were accepted if the FDR < 1%. D. simulans FlyBase gene (FBgn) identifiers were converted to their orthologous D. melanogaster FBgn identifiers using the FlyBase Drosophila Orthologs database. To compare the mating-induced abundance changes of FRT proteins, we identified and removed putative male-derived proteins. Proteins were classified as male-derived if they had been previously identified as either D. melanogaster sperm proteins or D. melanogaster SFPs, or if they showed signatures of being male-derived ejaculate proteins unique to D. simulans and/or D. mauritiana. Raw protein abundances were log2-transformed and median-normalized using the MSnbase package within BioConductor in R. Protein abundances were highly correlated between replicates, with Pearson’s r > 0.97 for all pairwise comparisons. Differential protein abundances were evaluated with empirical Bayes moderated t-tests using the LIMMA package in BioConductor.
D. melanogaster FRT proteins
FRT samples were collected from virgin and mated D. melanogaster females. Consistent with the simulans/mauritiana samples, mated D. melanogaster samples were collected 6h after copulation. Two replicates were collected per condition. FRTs from ~150 females were dissected and pooled in PBS per replicate, solubilized in 2× Laemmli buffer with 10% TCEP, and analyzed by LC-MS/MS. Mass spectra were searched against the D. melanogaster protein database (dmel-all-translation-r6.30, FlyBase.org) in PEAKS X. Proteins that had previously identified as sperm proteins or SFPs were removed. Protein abundances were quantified as spectral counts corrected for protein length, and analyzed using identical methods in BioConductor.
Molecular evolutionary rate analysis
Molecular evolutionary rate analysis between D. simulans, and D. mauritiana were based on established orthology relationships from FlyBase. Protein-coding nucleotide sequences were aligned using the linsi algorithm in MAFFT and reverse translated in frame. We estimated pairwise values of dN (non-synonymous substitution rate) and dS (synonymous substitution rate) using the Yang and Nielsen method as implemented by PAML.
Table 1: D. simulans and D. mauritiana FRT proteins
Final dataset of the 3287 D. simulans and D. mauritiana proteins used in the analyses
Table 2: D. melanogaster FRT proteins
Final dataset of the 1909 D. melanogaster FRT proteins used in the analyses
Table 3: dNdS estimates
Estimates of non-synonymous (dN) and synonymous (dS) substitution rates for pairwise comparisons between D. simulans and D. mauritiana
Raw protein abundance estimates (i.e., before transformation and normalization) for the simulans/mauritiana dataset
R code for normalization and differential expression analysis
R code for normalizing the data and conducting the differential expression analyses on the simulans/mauritiana dataset
National Science Foundation, Award: DEB 1655840
National Institutes of Health, Award: NICHD R21HD088910