On the origin of species: insights from the ecological genomics of lake whitefish

Abstract

In contrast to the large amount of ecological information supporting the role of natural selection as a main cause of population divergence and speciation, an understanding of the genomic basis underlying those processes is in its infancy. In this paper, we review the main findings of a long-term research programme that we have been conducting on the ecological genomics of sympatric forms of whitefish (Coregonus spp.) engaged in the process of speciation. We present this system as an example of how applying a combination of approaches under the conceptual framework of the theory of adaptive radiation has yielded substantial insight into evolutionary processes in a non-model species. We also discuss how the joint use of recent biotechnological developments will provide a powerful means to address issues raised by observations made to date. Namely, we present data illustrating the potential offered by combining next generation sequencing technologies with other genomic approaches to reveal the genomic bases of adaptive divergence and reproductive isolation. Given increasing access to these new genomic tools, we argue that non-model species studied in their ecological context such as whitefish will play an increasingly important role in generalizing knowledge of speciation.

Figure 1.

Q_st estimates for 10 morphological traits (in order: preorbital length, orbital length, trunk length, dorsal fin length, caudal peduncle length, maxillary width, maxillary length, body depth, head depth and interorbital width), four meristic traits (suprapelvic scales, dorsal ray count, pectoral ray count and gill-raker count), growth rate, and two swimming behaviour parameters (depth selection and burst swimming), with 95% CIs (CIs denote swimming activities). The 95% CI of neutral expectations (F_st value of 0.24) is delineated by dotted lines (modified from Rogers et al. 2002).

Figure 2.

Heat-map illustrating parallel patterns of regulation between sympatric dwarf and normal whitefish from the two natural lakes (modified from St-Cyr et al. 2008). The dendrogram on top clusters individuals based on similar patterns of transcription for genes. Individuals are designated by the letters N and D for ‘normal’ and ‘dwarf’ whitefish (red, Cliff Lake; green, Indian Pond). The dendrogram on the left cluster genes with similar patterns of expression among individuals. Expression values shown in red represent genes that are upregulated in dwarf on average whereas those in green are upregulated in normal on average. To the left of the heat-map are listed functional groups that were over-represented in terms of number of parallel genes showing differences between dwarf and normal whitefish relative to the total number of genes that were expressed in both forms for each functional group (see details in the main text).

Figure 3.

Genome locations of significant pQTL and eQTL observed both in white muscle and brain transcriptome. Locations of eQTL are illustrated on the right-hand side of linkage groups (white muscle, purple square; brain, black squares) and locations of pQTL are illustrated by various colours on the left side. Data for eQTL locations were compiled from combined and sex-specific eQTL maps constructed by Whiteley et al. (2008) (brain) and Derome et al. (2008) (white muscle). Each square represents the location of at least one eQTL. Data for pQTL are from Rogers & Bernatchez (2007).

Figure 4.

Venn diagram showing the number of significant mapped outlier AFLP identified in a genome scan of natural populations (Campbell & Bernatchez 2004), the number of significant mapped pQTL for eight different phenotypes (Rogers & Bernatchez 2007), and the number of significant eQTL locations (with number of associated unigenes in parentheses) combined over both studies on brain (Whiteley et al. 2008) and white muscle tissue (Derome et al. 2008). Numbers are presented for each separate group, as well as for the number of loci shared between any of the two or all three groups.

Figure 5.

(a) Linkage groups showing location of AFLP markers linked to a growth pQTL (CATA104) on linkage group 4 and to an eQTL for cytochrome c oxidase subunit VI (CATA073), which is also a possible candidate for hitchhiking divergence with a pQTL for condition factor on linkage group 6 (grey-filled box, muscle eQTL; filled black box, brain eQTL). (b–d) Comparison of simulated (open bars) and observed (filled bars) distributions of F_st (with 95% CIs) for sympatric dwarf and normal whitefish from three different lakes (Webster, East, Cliff, respectively; Campbell & Bernatchez 2004), and position of F_st values observed for outliers CATA104 and CATA073 in each case.

Figure 6.

(a) Percentage of surviving embryos as a function of developmental time for dwarf, normal, F₁ hybrids and backcrosses hybrids (dwarf and hybrid X normal). Vertical lines delineate distinct developmental stages (modified from Rogers & Bernatchez 2006). (b) Genotypic response of embryonic mortality as a function of linked intrinsic genetic incompatibilities during development on linkage group 3 (Rogers & Bernatchez 2006). Developmental time on the x-axis is proportional to (a) for comparison with embryonic mortality rates. Four loci exhibited a significant shift in segregation ratios during development. Locus CAAG143.7 is identified by the dark line and its position on linkage group 3 is shown (Rogers et al. 2007), where it overlaps with a hotspot comprising eQTL for 11 genes involved in various biological functions (Derome et al. 2008; see main text for details).

Figure 7.

Distribution of dominance effects (d/a ratio) for (a) F₁-hybrids and (b) backcrosses for 501 transcripts significantly different between pure dwarf and normal whitefish. A |d/a| ratio between 0.5 and 1.5 is considered as dominant, >1.5 non-additive, < 0.5 additive (modified from Renaut et al. 2009) (red bar, non-additivity; blue bar, dominance; green bar; additivity).

Figure 8.

Position of F_st value (F_st = 0.658) for a SNP of the Triosephosphate isomerase gene between dwarf and normal whitefish in Cliff Lake (open bar, simulated; filled bar, mapped loci) (a), which was also differentially expressed between dwarf and normal whitefish (b). Position of F_st value (F_st = 0.871) for AFLP marker CCTC-051 between dwarf and normal whitefish which was linked to an eQTL for Triosephosphate isomerase (c), itself located within an eQTL hotspot on linkage group 19 comprising other genes with various physiological functions (d). AFLP Genome scan data are from Campbell & Bernatchez (2004), and those from eQTL mapping are from Derome et al. (2008).