Search for: All records

The genomic characteristics of adaptively radiated groups could contribute to their high species number and ecological disparity, by increasing their evolutionary potential. Here, we explored the genomic variation of Anolis lizards, focusing on three species with distinct phenotypes: A. auratus, one of the species with the longest tail; A. frenatus, one of the largest species; and A. carolinensis, one of the species that inhabits the coldest environments. We assembled and annotated two new chromosome-level reference genomes for A. auratus and A. frenatus, and compared them with the available genomes of A. carolinensis and A. sagrei. We evaluated the presence of structural rearrangements, quantified the density of repeat elements, and identified potential signatures of positive selection in coding and regulatory regions. We detected substantial rearrangements in scaffolds 1, 2 and 3 of A. frenatus different from the other species, in which the rearrangement breakpoints corresponded to hotspots of developmental genes. Further, we detected an accumulation of repeats around key developmental genes in anoles and phrynosomatid outgroups. Finally, coding sequences and regulatory regions of genes relevant to development and physiology showed variation that could be associated with the unique phenotypes of the analyzed species. Our results show examples of the hierarchical genomic variation within anoles, that could provide the substrate that promoted phenotypic disparity and contributed to their adaptive radiation. 

Uta stansburiana are an emerging model system for studying sexual selection, polymorphism, and the evolution of pace-of-life syndromes (POLS) whose distribution covers variable environments and a wide latitudinal gradient. POLS are suites of traits causing variation of life history along a slow maturing-fast maturing continuum. We present a high-quality chromosome-level reference genome for U. stansburiana and pair it with RNA-seq gene expression data to demonstrate, for the first time, the molecular basis for pace-of-life differences between locations with higher and lower climate seasonality and sexual size dimorphism (SSD). Our assembly is 2.1 Gbp, has scaffold N50 of 320 Mbp, includes 104 scaffolds, and has an L50 of 3. The assembly comprises six macrochromosomes and 11 microchromosomes. We annotated 20,350 genes for the assembly and found a repeat element composition of 49.23%, similar to work in other phrynosomatid lizards. RNA-seq gene expression data demonstrate expression differences in genes associated with pace-of-life differences including those related to stress, sexual reproduction, and cell proliferation/carcinogenesis between different environments. Our results provide the first differential gene expression evidence of environmentally-mediated pace-of-life processes related to different degrees of SSD in U. stansburiana and demonstrate the utility of RNA-seq gene expression data in detecting POLS. 

Climatic changes can affect species distributions, population abundance, and evolution. Such organismal responses could be determined by the amount and quality of available habitats, which can vary independently. In this study, we assessed changes in habitat quantity and quality independently to generate explicit predictions of the species' responses to climatic changes between Last Glacial Maximum (LGM) and present day. We built ecological niche models for genetic groups within 21 reptile, mammal, and plant taxa from the Baja California peninsula inhabiting lowland or highland environments. Significant niche divergence was detected for all clades within species, along with significant differences in the niche breadth and area of distribution between northern and southern clades. We quantified habitat quantity from the distribution models, and most clades showed a reduction in distribution area towards LGM. Further, niche marginality (used as a measure of habitat quality) was higher during LGM for most clades, except for northern highland species. Our results suggest that changes in habitat quantity and quality can affect organismal responses independently. This allows the prediction of genomic signatures associated with changes in effective population size and selection pressure that could be explicitly tested from our models.