Browsing Conservation Science Publications by Author "Wall, Jeffrey D."
Extreme selective sweeps independently targeted the X chromosomes of the great apesNam, Kiwoong; Munch, Kasper; Hobolth, Asger; Dutheil, Julien Yann; Veeramah, Krishna R.; Woerner, August E.; Hammer, Michael F.; Great Ape Genome Diversity Project; Mailund, Thomas; Schierup, Mikkel Heide; et al. (2015)…We perform a comparative analysis of X chromosome polymorphism in 10 great ape species, including humans. In most species, we identify striking megabase-wide regions, where nucleotide diversity is less than 20% of the chromosomal average....
Great ape genetic diversity and population historyPrado-Martinez, Javier; Sudmant, Peter H.; Kidd, Jeffrey M.; Li, Heng; Kelley, Joanna L.; Lorente-Galdos, Belen; Veeramah, Krishna R.; Woerner, August E.; O’Connor, Timothy D.; Santpere, Gabriel; et al. (2013)Most great ape genetic variation remains uncharacterized; however, its study is critical for understanding population history, recombination, selection and susceptibility to disease. Here we sequence to high coverage a total of 79 wild- and captive-born individuals representing all six great ape species and seven subspecies and report 88.8 million single nucleotide polymorphisms. Our analysis provides support for genetically distinct populations within each species, signals of gene flow, and the split of common chimpanzees into two distinct groups: Nigeria–Cameroon/western and central/eastern populations. We find extensive inbreeding in almost all wild populations, with eastern gorillas being the most extreme. Inferred effective population sizes have varied radically over time in different lineages and this appears to have a profound effect on the genetic diversity at, or close to, genes in almost all species. We discover and assign 1,982 loss-of-function variants throughout the human and great ape lineages, determining that the rate of gene loss has not been different in the human branch compared to other internal branches in the great ape phylogeny. This comprehensive catalogue of great ape genome diversity provides a framework for understanding evolution and a resource for more effective management of wild and captive great ape populations.
Inference of gorilla demographic and selective history from whole-genome sequence dataMcManus, Kimberly F.; Kelley, Joanna L.; Song, Shiya; Veeramah, Krishna R.; Woerner, August E.; Stevison, Laurie S.; Ryder, Oliver A.; Great Ape Genome Project; Kidd, Jeffrey M.; Wall, Jeffrey D.; et al. (2015)Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection.