Reconstructing species’ demographic histories is a central focus of molecular ecology and evolution. Recently, an expanding suite of methods leveraging either the sequentially Markovian coalescent (SMC) or the site-frequency spectrum has been developed to reconstruct population size histories from genomic sequence data. However, few studies have investigated the robustness of these methods to genome assemblies of varying quality. In this study, we first present an improved genome assembly for the Tasmanian devil using the Chicago library method. Compared with the original reference genome, our new assembly reduces the number of scaffolds (from 35,975 to 10,010) and increases the scaffold N90 (from 0.101 to 2.164 Mb). Second, we assess the performance of four contemporary genomic methods for inferring population size history (PSMC, MSMC, SMC++, Stairway Plot), using the two devil genome assemblies as well as simulated, artificially fragmented genomes that approximate the hypothesized demographic history of Tasmanian devils. We demonstrate that each method is robust to assembly quality, producing similar estimates of Ne when simulated genomes were fragmented into up to 5,000 scaffolds. Overall, methods reliant on the SMC are most reliable between ∼300 generations before present (gbp) and 100 kgbp, whereas methods exclusively reliant on the site-frequency spectrum are most reliable between the present and 30 gbp. Our results suggest that when used in concert, genomic methods for reconstructing species’ effective population size histories 1) can be applied to nonmodel organisms without highly contiguous reference genomes, and 2) are capable of detecting independently documented effects of historical geological events.
Identifying the genetic architecture of complex phenotypes is a central goal of modern biology, particularly for disease-related traits. Genome-wide association methods are a classical approach for identifying the genomic basis of variation in disease phenotypes, but such analyses are particularly challenging in natural populations due to sample size difficulties. Extensive mark-recapture data, strong linkage disequilibrium and a lethal transmissible cancer make the Tasmanian devil (Sarcophilus harrisii) an ideal model for such an association study. We used a RAD-capture approach to genotype 624 devils at ~16,000 loci and then used association analyses to assess the heritability of three cancer-related phenotypes: infection case-control (where cases were infected devils and controls were devils that were never infected), age of first infection and survival following infection. The SNP array explained much of the phenotypic variance for female survival (>80%) and female case-control (>61%). We found that a few large-effect SNPs explained much of the variance for female survival (~5 SNPs explained >61% of the total variance), whereas more SNPs (~56) of smaller effect explained less of the variance for female case-control (~23% of the total variance). By contrast, these same SNPs did not account for a significant proportion of phenotypic variance in males, suggesting that the genetic bases of these traits and/or selection differ across sexes. Loci involved with cell adhesion and cell-cycle regulation underlay trait variation, suggesting that the devil immune system is rapidly evolving to recognize and potentially suppress cancer growth through these pathways. Overall, our study provided necessary data for genomics-based conservation and management in Tasmanian devils.
Landscape genomics studies focus on identifying candidate genes under selection via spatial variation in abiotic environmental variables, but rarely by biotic factors (i.e., disease). The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a transmissible cancer, devil facial tumor disease (DFTD). Devils persist in regions of long‐term infection despite epidemiological model predictions of species’ extinction, suggesting possible adaptation to DFTD. Here, we test the extent to which spatial variation and genetic diversity are associated with the abiotic environment (i.e., climatic variables, elevation, vegetation cover) and/or DFTD. We employ genetic‐environment association analyses using 6886 SNPs from 3287 individuals sampled pre‐ and post‐disease arrival across the devil's geographic range. Pre‐disease, we find significant correlations of allele frequencies with environmental variables, including 365 unique loci linked to 71 genes, suggesting local adaptation to abiotic environment. The majority of candidate loci detected pre‐DFTD are not detected post‐DFTD arrival. Several post‐DFTD candidate loci are associated with disease prevalence and were in linkage disequilibrium with genes involved in tumor suppression and immune response. Loss of apparent signal of abiotic local adaptation post‐disease suggests swamping by strong selection resulting from the rapid onset of DFTD.
Mouse lemurs (Microcebus) are a radiation of morphologically cryptic primates distributed throughout Madagascar for which the number of recognized species has exploded in the past two decades. This taxonomic explosion has prompted understandable concern that there has been substantial oversplitting in the mouse lemur clade. Here, we take an integrative approach to investigate species diversity in two pairs of sister lineages that occur in a region in northeastern Madagascar with high levels of microendemism and predicted habitat loss. We analyzed RADseq data with multispecies coalescent (MSC) species delimitation methods for three named species and an undescribed lineage previously identified to have divergent mtDNA. Marked differences in effective population sizes, levels of gene flow, patterns of isolation-by-distance, and species delimitation results were found among them. Whereas all tests support the recognition of the presently undescribed lineage as a separate species, the species-level distinction of two previously described species, M. mittermeieri and M. lehilahytsara is not supported – a result that is particularly striking when using the genealogical discordance index (gdi). Non-sister lineages occur sympatrically in two of the localities sampled for this study, despite an estimated divergence time of less than 1 Ma. This suggests rapid evolution of reproductive isolation in the focal lineages, and in the mouse lemur clade generally. The divergence time estimates reported here are based on the MSC and calibrated with pedigree-based mutation rates and are considerably more recent than previously published fossil-calibrated concatenated likelihood estimates, however. We discuss the possible explanations for this discrepancy, noting that there are theoretical justifications for preferring the MSC estimates in this case.
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