Catherine E Grueber1, Bianca Haase2, Georgina Samaha3, Claire M Wade1, Hamutal Mazrier2. 1. School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia. 2. Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Sydney, NSW, Australia. 3. Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Sydney, NSW, Australia. georgina.samaha@sydney.edu.au.
Abstract
BACKGROUND: While recent advances in genomics has enabled vast improvements in the quantification of genome-wide diversity and the identification of adaptive and deleterious alleles in model species, wildlife and non-model species have largely not reaped the same benefits. This has been attributed to the resources and infrastructure required to develop essential genomic datasets such as reference genomes. In the absence of a high-quality reference genome, cross-species alignments can provide reliable, cost-effective methods for single nucleotide variant (SNV) discovery. Here, we demonstrated the utility of cross-species genome alignment methods in gaining insights into population structure and functional genomic features in cheetah (Acinonyx jubatas), snow leopard (Panthera uncia) and Sumatran tiger (Panthera tigris sumatrae), relative to the domestic cat (Felis catus). RESULTS: Alignment of big cats to the domestic cat reference assembly yielded nearly complete sequence coverage of the reference genome. From this, 38,839,061 variants in cheetah, 15,504,143 in snow leopard and 13,414,953 in Sumatran tiger were discovered and annotated. This method was able to delineate population structure but limited in its ability to adequately detect rare variants. Enrichment analysis of fixed and species-specific SNVs revealed insights into adaptive traits, evolutionary history and the pathogenesis of heritable diseases. CONCLUSIONS: The high degree of synteny among felid genomes enabled the successful application of the domestic cat reference in high-quality SNV detection. The datasets presented here provide a useful resource for future studies into population dynamics, evolutionary history and genetic and disease management of big cats. This cross-species method of variant discovery provides genomic context for identifying annotated gene regions essential to understanding adaptive and deleterious variants that can improve conservation outcomes.
BACKGROUND: While recent advances in genomics has enabled vast improvements in the quantification of genome-wide diversity and the identification of adaptive and deleterious alleles in model species, wildlife and non-model species have largely not reaped the same benefits. This has been attributed to the resources and infrastructure required to develop essential genomic datasets such as reference genomes. In the absence of a high-quality reference genome, cross-species alignments can provide reliable, cost-effective methods for single nucleotide variant (SNV) discovery. Here, we demonstrated the utility of cross-species genome alignment methods in gaining insights into population structure and functional genomic features in cheetah (Acinonyx jubatas), snow leopard (Panthera uncia) and Sumatran tiger (Panthera tigris sumatrae), relative to the domestic cat (Felis catus). RESULTS: Alignment of big cats to the domestic cat reference assembly yielded nearly complete sequence coverage of the reference genome. From this, 38,839,061 variants in cheetah, 15,504,143 in snow leopard and 13,414,953 in Sumatran tiger were discovered and annotated. This method was able to delineate population structure but limited in its ability to adequately detect rare variants. Enrichment analysis of fixed and species-specific SNVs revealed insights into adaptive traits, evolutionary history and the pathogenesis of heritable diseases. CONCLUSIONS: The high degree of synteny among felid genomes enabled the successful application of the domestic cat reference in high-quality SNV detection. The datasets presented here provide a useful resource for future studies into population dynamics, evolutionary history and genetic and disease management of big cats. This cross-species method of variant discovery provides genomic context for identifying annotated gene regions essential to understanding adaptive and deleterious variants that can improve conservation outcomes.
Authors: Stephanie J Galla; Roger Moraga; Liz Brown; Simone Cleland; Marc P Hoeppner; Richard F Maloney; Anne Richardson; Lyndon Slater; Anna W Santure; Tammy E Steeves Journal: Evol Appl Date: 2020-01-27 Impact factor: 5.183
Authors: Jocelyn Plassais; Jaemin Kim; Brian W Davis; Danielle M Karyadi; Andrew N Hogan; Alex C Harris; Brennan Decker; Heidi G Parker; Elaine A Ostrander Journal: Nat Commun Date: 2019-04-02 Impact factor: 14.919
Authors: Barbara Gandolfi; Hasan Alhaddad; Mona Abdi; Leslie H Bach; Erica K Creighton; Brian W Davis; Jared E Decker; Nicholas H Dodman; Edward I Ginns; Jennifer C Grahn; Robert A Grahn; Bianca Haase; Jens Haggstrom; Michael J Hamilton; Christopher R Helps; Jennifer D Kurushima; Hannes Lohi; Maria Longeri; Richard Malik; Kathryn M Meurs; Michael J Montague; James C Mullikin; William J Murphy; Sara M Nilson; Niels C Pedersen; Carlyn B Peterson; Clare Rusbridge; Rashid Saif; G Diane Shelton; Wesley C Warren; Muhammad Wasim; Leslie A Lyons Journal: Sci Rep Date: 2018-05-04 Impact factor: 4.379