Search for: All records

Abstract Hares (genus Lepus) provide clear examples of repeated and often massive introgressive hybridization and striking local adaptations. Genomic studies on this group have so far relied on comparisons to the European rabbit (Oryctolagus cuniculus) reference genome. Here, we report the first de novo draft reference genome for a hare species, the mountain hare (Lepus timidus), and evaluate the efficacy of whole-genome re-sequencing analyses using the new reference versus using the rabbit reference genome. The genome was assembled using the ALLPATHS-LG protocol with a combination of overlapping pair and mate-pair Illumina sequencing (77x coverage). The assembly contained 32,294 scaffolds with a total length of 2.7 Gb and a scaffold N50 of 3.4 Mb. Re-scaffolding based on the rabbit reference reduced the total number of scaffolds to 4,205 with a scaffold N50 of 194 Mb. A correspondence was found between 22 of these hare scaffolds and the rabbit chromosomes, based on gene content and direct alignment. We annotated 24,578 protein coding genes by combining ab-initio predictions, homology search, and transcriptome data, of which 683 were solely derived from hare-specific transcriptome data. The hare reference genome is therefore a new resource to discover and investigate hare-specific variation. Similar estimates of heterozygosity and inferred demographic history profiles were obtained when mapping hare whole-genome re-sequencing data to the new hare draft genome or to alternative references based on the rabbit genome. Our results validate previous reference-based strategies and suggest that the chromosome-scale hare draft genome should enable chromosome-wide analyses and genome scans on hares. 

Abstract Accurately quantifying species’ area requirements is a prerequisite for effective area‐based conservation. This typically involves collecting tracking data on species of interest and then conducting home‐range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home‐range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross‐validation to quantify bias in empirical home‐range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation‐induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home‐range estimates. As a correction, we tested whether data thinning or autocorrelation‐informed home‐range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation‐informed home‐range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.