Contemporary Demographic Reconstruction Methods Are Robust to Genome Assembly Quality: A Case Study in Tasmanian Devils

Abstract

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.

Signatures of selection in the coral holobiont reveal complex adaptations to inshore environments driven by Holocene climate change

“…Although this bottleneck was consistently observed across all models, MSMC estimates of the timing were much older (~100Kya) than those inferred by the best fitting ∂a∂i model (3Kya). In this instance ∂a∂i estimates are more likely to be reliable since the single diploid genomes used for MSMC (one each from Magnetic Island and Northern populations) provide few recent coalescent events with which to estimate recent demographic change 45,46 .…”

Contemporary and historical selection in Tasmanian devils (Sarcophilus harrisii) support novel, polygenic response to transmissible cancer

“…However, our results do not conclusively eliminate or support the possibility that devils have previously been impacted by transmissible cancers. The low genetic diversity observed in devils could be the result of the widespread historical positive selection resulting from transmissible cancers or other diseases (84), or historical bottlenecks due to climate change and habitat loss (30)(31)(32).The genes (Supplemental Table S6) and functional gene sets (Supplemental Table 8; Supplemental Figure S4) under selection at both timescales may reflect historical transmissible cancers, or indicate ongoing selection by a similar selective force. A hypothesis for the lack of greater overlap than we observed between historical and contemporary candidates is that there is redundancy in the genetic mechanisms underlying resistance to transmissible cancers, potentially as a result of repeated selection for resistance (85).…”

“…At the same time, the wide distribution of contemporary candidates across the genome also highlights the importance of standing genetic variation to continue to respond to unique selective forces, including their local environments (48). The low genetic diversity observed in devils may be the result of historical population declines (30)(31)(32) and/or similarly diffuse selection operating historically in the devil lineage. Genomic monitoring could be useful for maintaining both functional diversity at candidate loci and genome-wide variation in breeding captive populations (46,90,91) and in the wild.…”

“…Most populations will reach 90% decline after about 6 years, with just a few exceptions (29). This is particularly alarming because devils have notoriously low genome-wide diversity, attributed to climate-and anthropogenic-induced bottlenecks (30)(31)(32). Depleted genetic diversity at immune-related loci has likely further contributed to DFTD vulnerability (33).…”

“…Since the first disease detection in 1996, field sites have been established across the island of Tasmania to consistently monitor the spread and effects of the disease and wild devil populations (41). A high-quality reference genome for the devil yields deep evolutionary history insight and fine-scale mapping for functional inference of individual genotypes (27,32). Population genomic studies have already shown that devils are rapidly evolving in response to DFTD (2,47,48).…”