Differential gene expression and gene variants drive color and pattern development in divergent color morphs of a mimetic poison frog

Evolutionary biologists have long investigated the ecological contexts, evolutionary forces, and proximate mechanisms that produce the diversity of animal coloration we see in the natural world. In aposematic species, color and pattern is directly tied to survival and thus understanding the origin of the phenotype has been a focus of both theoretical and empirical inquiry. In order to better understand this diversity, we examined gene expression in skin tissue during development in four different color morphs of the aposematic mimic poison frog, Ranitomeya imitator. We identified a suite of candidate color-related genes a priori and identified the pattern of expression in these genes over time, differences in expression of these genes between the mimetic morphs, and genetic variants that differ between color morphs. We identified several candidate color genes that are differentially expressed over time or across populations, as well as a number of color genes with fixed genetic variants between color morphs. Many of the color genes we discovered in our dataset are involved in the canonical Wnt signaling pathway, including several fixed SNPs between color morphs. Further, many genes in this pathway were differentially expressed at different points in development (e.g., lef1, tyr, tyrp1). Importantly, Wnt signaling pathway genes are overrepresented relative to expression in Xenopus tropicalis. Taken together, this provides evidence that the Wnt signaling pathway is contributing to color pattern production in R. imitator, and is an excellent candidate for producing some of the differences in color pattern between morphs. In addition, we found evidence that sepiapterin reductase is likely important in the production of yellow-green coloration in this adaptive radiation. Finally, two iridophore genes (arfap1, gart) draw a strong parallel to previous work in another dendrobatid, indicating that these genes are also strong candidates for differential color production. We have used high throughput sequencing throughout development to examine the evolution of coloration in a rapid mimetic adaptive radiation and found that these divergent color patterns are likely to be affected by a combination of developmental patterns of gene expression, color morph-specific gene expression, and color morph-specific gene variants.Joyner Open Access Publishing Support Fun

Genome-wide signatures of complex introgression and adaptive evolution in the big cats.

The great cats of the genus Panthera comprise a recent radiation whose evolutionary history is poorly understood. Their rapid diversification poses challenges to resolving their phylogeny while offering opportunities to investigate the historical dynamics of adaptive divergence. We report the sequence, de novo assembly, and annotation of the jaguar (Panthera onca) genome, a novel genome sequence for the leopard (Panthera pardus), and comparative analyses encompassing all living Panthera species. Demographic reconstructions indicated that all of these species have experienced variable episodes of population decline during the Pleistocene, ultimately leading to small effective sizes in present-day genomes. We observed pervasive genealogical discordance across Panthera genomes, caused by both incomplete lineage sorting and complex patterns of historical interspecific hybridization. We identified multiple signatures of species-specific positive selection, affecting genes involved in craniofacial and limb development, protein metabolism, hypoxia, reproduction, pigmentation, and sensory perception. There was remarkable concordance in pathways enriched in genomic segments implicated in interspecies introgression and in positive selection, suggesting that these processes were connected. We tested this hypothesis by developing exome capture probes targeting ~19,000 Panthera genes and applying them to 30 wild-caught jaguars. We found at least two genes (DOCK3 and COL4A5, both related to optic nerve development) bearing significant signatures of interspecies introgression and within-species positive selection. These findings indicate that post-speciation admixture has contributed genetic material that facilitated the adaptive evolution of big cat lineages

Identifying Population Histories, Adaptive Genes, and Genetic Duplication from Population-Scale Next Generation Sequencing

The arrival of next-generation sequencing (NGS) technologies in the mid 2000s opened the floodgates to a massive amount of genetic data. Not only does NGS permit relatively easy access to the genome of nearly any species, it also enables sequencing highly degraded DNA characteristic of ancient samples and museum specimens. The representation of genomic data across the tree of life has been spreading rapidly over the past decade owing to the emergence of numerous methods for inexpensively sequencing entire genomes and reduced representations of genomes based on NGS. However, without any high-quality preexisting genomic resources, species with large, highly paralogous genomes pose a major obstacle for NGS because accurately assembling short read data becomes extremely challenging. Furthermore, reads derived from paralogs will likely map to the same locus, which can inflate apparent levels of diversity, obscuring accurate population genetic inference and scans for adaptive loci. These problems can also effect population genetic studies using historic DNA from museum specimens, which often face the additional challenges of high sampling variability across space and time, and DNA degradation. The research presented in this thesis aims at overcoming these challenges using a combination of pioneering experimental and computational approaches. First, I present a method for identifying paralogy from NGS data, ngsParalog, that jointly leverages information from read proportions within and across individuals and sequencing coverage in a probabilistic framework. Combining information in this manner achieves superior power for identifying paralogy at lower false positive rates than using paralogy signatures separately as other current methods do. It also is widely applicable to both single and paired-end data ranging from low to high coverage. I use ngsParalog to detect paralogy in humans, chipmunks, and stick insects, representing a broad range of sequencing approaches. In the next chapter of the thesis I, along with colleagues, demonstrate how transcriptome-enabled exon capture applied to populations of century-old and modern Tamias chipmunks comprising multiple species, in conjunction with a new Approximate Bayesian Computation approach for fitting joint site frequency spectra between time periods can be used to infer recent population histories. Knowing these population histories allowed for disentangling the genetic signature of demographic changes from selection, which led to identifying a gene that may be helping chipmunk populations rapidly adapt to climate-induced environmental change. In the fourth chapter, I, along with other colleagues, employed the same exon capture technique and ngsParalog to overcome the challenge of mapping color and pattern genes in the ~12 gigabase, highly paralogous genome of the mimic poison frog, Ranitomeya imitator. I applied statistical divergence and admixture mapping methods to differentR. imitator color morphs in order to identify seven out of 13,086 examined genes that showed compelling evidence of influencing color and/or pattern in R. imitator. These candidate genes will likely be valuable for gaining insight into the R. imitator mimetic radiation. The combination of methods presented in this thesis advances the utility of NGS into taxa with genomes that previously precluded gene mapping and provides an analytical framework for identifying demographies and adaptive genes from museum collections

<i>ngsTools </i>:methods for population genetics analyses from next-generation sequencing data

Next-generation sequencing technologies produce short reads that are either de novo assembled or mapped to a reference genome. Genotypes and/or single-nucleotide polymorphisms are then determined from the read composition at each site, which become the basis for many downstream analyses. However, for low sequencing depths, e.g. , there is considerable statistical uncertainty in the assignment of genotypes because of random sampling of homologous base pairs in heterozygotes and sequencing or alignment errors. Recently, several probabilistic methods have been proposed to account for this uncertainty and make accurate inferences from low quality and/or coverage sequencing data. We present ngsTools, a collection of programs to perform population genetics analyses from next-generation sequencing data. The methods implemented in these programs do not rely on single-nucleotide polymorphism or genotype calling and are particularly suitable for low sequencing depth data

Unlocking the vault: Next-generation museum population genomics

Natural history museum collections provide unique resources for understanding how species respond to environmental change, including the abrupt, anthropogenic climate change of the past century. Ideally, researchers would conduct genome-scale screening o