Functional organization of the genome may shape the species boundary in the house mouse - PubMed (original) (raw)

Functional organization of the genome may shape the species boundary in the house mouse

Václav Janoušek et al. Mol Biol Evol. 2015 May.

Abstract

Genomic features such as rate of recombination and differentiation have been suggested to play a role in species divergence. However, the relationship of these phenomena to functional organization of the genome in the context of reproductive isolation remains unexplored. Here, we examine genomic characteristics of the species boundaries between two house mouse subspecies (Mus musculus musculus/M. m. domesticus). These taxa form a narrow semipermeable zone of secondary contact across Central Europe. Due to the incomplete nature of reproductive isolation, gene flow in the zone varies across the genome. We present an analysis of genomic differentiation, rate of recombination, and functional composition of genes relative to varying amounts of introgression. We assessed introgression using 1,316 autosomal single nucleotide polymorphism markers, previously genotyped in hybrid populations from three transects. We found a significant relationship between amounts of introgression and both genomic differentiation and rate of recombination with genomic regions of reduced introgression associated with higher genomic differentiation and lower rates of recombination, and the opposite for genomic regions of extensive introgression. We also found a striking functional polarization of genes based on where they are expressed in the cell. Regions of elevated introgression exhibit a disproportionate number of genes involved in signal transduction functioning at the cell periphery, among which olfactory receptor genes were found to be the most prominent group. Conversely, genes expressed intracellularly and involved in DNA binding were the most prevalent in regions of reduced introgression. We hypothesize that functional organization of the genome is an important driver of species divergence.

Keywords: hybrid zone; mouse genome; speciation.

© The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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Figures

F<sc>ig</sc>. 1.

Fig. 1.

The location of the house mouse hybrid zone in Europe. The black line demarcates the hybrid zone and the shaded rectangles indicate the location of the three transects studied. Collecting localities for the Czech-Bavarian (CZ) and Bavarian-Austrian (BV) transects can be found in Wang et al. (2011) and for the Saxony (SX) transect in Teeter et al. (2008).

F<sc>ig</sc>. 2.

Fig. 2.

Example of genomic clines for three SNP markers (1-21122670, 19-31060431, and 11-40245735) which differ in their pattern of introgression. The genomic cline for the 1-21122670 SNP marker (blue) represents a case where the cline is wide (β < 0) and at the same time is shifted to _Mus musculus domesticus_ range (α > 0). The genomic cline for the 19-31060431 SNP marker (gray) represents a case where the genomic cline does not differ from the null model (black diagonal). The genomic cline for the 11-40245735 SNP marker represents a likely case of selection against hybrids where the genomic cline is much steeper than the null model (β > 0). This genomic cline is also slightly shifted to the M. m. musculus range (α < 0).

F<sc>ig</sc>. 3.

Fig. 3.

The nonlinear relationship between α and β parameters for each transect. The black curves represent the polynomial model (y = a + bx + _cx_2) and its 95% confidential intervals.

F<sc>ig</sc>. 4.

Fig. 4.

The difference in genomic differentiation (A) and rate of recombination (B) between SNPs markers of positive (red), zero (gray), and negative (blue) β values, respectively. Genomic differentiation was plotted for three window sizes (250, 500 kb, and 1 Mb) and rate of recombination was plotted for three conditions (SA, MS, and FS). The average estimates with 95% confidential intervals were plotted along with significance (***P ≤ 0.001; **P ≤ 0.01; *P ≤ 0.05) of the effect of the β category for each transect separately. Significance of the β category effect over all three transects is plotted as well. All of the measures were estimated using mixed-effect linear models where individual markers were nested within genomic regions to treat for underlying linkage structure (see Materials and Methods). Rate of recombination was transformed using a Box–Cox transformation to normalize the data.

F<sc>ig</sc>. 5.

Fig. 5.

Functional analysis of genes. (A) Heat map based on hierarchical clustering of functional profiles (x axis) for genes from around SNP markers for a given transect, window size and β parameter category (β > 0: red, β < 0: blue, β = 0: gray) and GO terms (y axis). The degree of GO term enrichment and depletion for each functional profile reflected by the varying intensity of green and purple colors, respectively. The red rectangle marks the GO terms that are the most polarized for genes around SNPs markers with β negative values and genes from the other two β categories. This figure shows that for all three transects the functional composition is distinct for genomic regions belonging to a different β category. (B) Significantly more/less prevalent GO terms marked by red rectangle in (A). They correspond to two clusters (#112 and #113 in

supplementary fig. S8_A_

,

Supplementary Material

online). Green and purple colors depict significantly higher and lower prevalence, respectively. The positive and negative numbers represent the number of window sizes for a given combination of transect and β category for which the GO term was significantly more (positive) or less (negative) prevalent.

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