Disentangling the effect on genomic diversity of natural selection from that of demography is notoriously difficult, but necessary to properly reconstruct the history of species. Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome. We find that the magnitude and relative importance of BGS and gBGC are largely determined by variation in recombination rate and base composition. Importantly, synonymous sites and non-transcribed regions are also affected, albeit to different degrees. Their use for demographic inference can lead to strong biases. However, by conditioning on genomic regions with recombination rates above 1.5 cM/Mb and mutation types (C↔G, A↔T), we identify a set of SNPs that is mostly unaffected by BGS or gBGC, and that avoids these biases in the reconstruction of human history.

Species conservation can be improved by knowledge of evolutionary and genetic history. Tigers are among the most charismatic of endangered species and garner significant conservation attention. However, their evolutionary history and genomic variation remains poorly known, especially for Indian tigers. With 70% of the worlds wild tigers living in India, such knowledge is critical. We re-sequenced 65 individual tiger genomes representing most extant subspecies with a specific focus on tigers from India. As suggested by earlier studies, we found strong genetic differentiation between the putative tiger subspecies. Despite high total genomic diversity in India, individual tigers host longer runs of homozygosity, potentially suggesting recent inbreeding or founding events, possibly due to small and fragmented protected areas. We suggest the impacts of ongoing connectivity loss on inbreeding and persistence of Indian tigers be closely monitored. Surprisingly, demographic models suggest recent divergence (within the last 20,000 years) between subspecies, and strong population bottlenecks. Amur tiger genomes revealed the strongest signals of selection related to metabolic adaptation to cold, while Sumatran tigers show evidence of weak selection for genes involved in body size regulation. We recommend detailed investigation of local adaptation in Amur and Sumatran tigers prior to initiating genetic rescue.

The interpretation of matching between DNA profiles of a person of interest and an item of evidence is undertaken using population genetic models to predict the probability of matching by chance. Calculation of matching probabilities is straightforward if allelic probabilities are known, or can be estimated, in the relevant population. It is more often the case, however, that the relevant population has not been sampled and allele frequencies are available only from a broader collection of populations as might be represented in a national or regional database. Variation of allele probabilities among the relevant populations is quantified by the population structure quantity FST and this quanity affects matching propoptions. Matching within a population can be interpreted only with respect to matching between populations and we show here that FST, can be estimated from sample allelic matching proportions within and between populations. We report such estimates from data we extracted from 250 papers in the forensic literature, representing STR profiles at up to 24 loci from nearly 500,000 people in 446 different populations. The results suggest that theta values in current forensic use do not have the buffer of conservativism often thought.