The genetic architecture of adaptation: convergence and pleiotropy in Heliconius wing pattern evolution

Abstract

Unravelling the genetic basis of adaptive traits is a major challenge in evolutionary biology. Doing so informs our understanding of evolution towards an adaptive optimum, the distribution of locus effect sizes, and the influence of genetic architecture on the evolvability of a trait. In the Müllerian co-mimics Heliconius melpomene and Heliconius erato some Mendelian loci affecting mimicry shifts are well known. However, several phenotypes in H. melpomene remain to be mapped, and the quantitative genetics of colour pattern variation has rarely been analysed. Here we use quantitative trait loci (QTL) analyses of crosses between H. melpomene races from Peru and Suriname to map, for the first time, the control of the broken band phenotype to WntA and identify a ~100 kb region controlling this variation. Additionally, we map variation in basal forewing red-orange pigmentation to a locus centred around the gene ventral veins lacking (vvl). The locus also appears to affect medial band shape variation as it was previously known to do in H. erato. This adds to the list of homologous regions controlling convergent phenotypes between these two species. Finally we show that Heliconius wing-patterning genes are strikingly pleiotropic among wing pattern traits. Our results demonstrate how genetic architecture can shape, aid and constrain adaptive evolution.

Perfect mimicry betweenHeliconiusbutterflies is constrained by genetics and development

“…e. notabilis compared to H. m. ecuadorensis/H. m. plesseni (Figure 3) matches the distal area of the wing that is described to be affected by an additional locus called Ro, described in H. erato over 30 years ago [16,36,37] and recently also identified to potentially affect the distal margin of the mid-forewing band in H. melpomene [38]. Next, differences in the mismatch between the Split band phenotypes H. e. notabilis/H.…”

“…Heliconius butterflies are also known for the incredibly diverse wing color pattern differences found in geographic races of the same species. Apart from the major effect loci involved in these color patterns, QTL studies of pattern variation in H. erato [39] [38][39][40]. This larger set of genetic variants controlling quantitative variation is additional to the regulatory complexity that modulates the expression of the major color pattern genes [5,16,41].…”

Selective sweeps on novel and introgressed variation shape mimicry loci in a butterfly adaptive radiation

“…In the unpalatable Heliconius butterflies, mimicry of wing patterns is advantageous because resemblance to a common, well-protected pattern confers protection from predator attacks on individuals. The vast majority of pattern diversity seen in this group is controlled by a surprisingly simple genetic system, involving allelic variation at just 4 major effect loci, although additional regulators and modifiers of these mimicry patterns have also been mapped [26,[28][29][30][31][32][33][34]. Although these regions comprise several genes with a putative function for colour patterning, current evidence suggests a major role for the transcription factors, optix [35] and aristaless, which comes in 2 tandem copies al1 and al2 [28], a signalling ligand, WntA [29], and a gene in a family of cell cycle regulators whose exact function remains unclear, cortex [30].…”

“…A complex series of regulatory variants at each of these loci is found in different combinations across populations and species, leading to great diversity of wing patterns. In many cases, candidate noncoding, cis-regulatory elements (CREs) are associated with specific wing patterns: CREs in the optix region are associated with the red forewing band, hindwing rays, and dennis patch [36][37][38]; in the cortex region with the yellow hindwing bar [30,38,39]; in the WntA region with various shape elements of the forewing band [33,38]; and in the aristaless region with white versus yellow colour variation [28].…”

Integrating natural history collections and comparative genomics to study the genetic architecture of convergent evolution

“…nucleotide, gene, protein, regulatory networks, function; figure 1) [5]. Additionally, high-levels of pleiotropy, already recognized as a likely component of many cases of convergence [17], means that our definition of 'genomic basis' of convergence may require expansion to include the role of individual genes participating in multiple networks as well as functionally overlapping networks that may not share many genes.…”