AdaptMap: exploring goat diversity and adaptation

• Published in: Genetics selection evolution (Paris) 2018-11, Vol.50 (1), p.61-61, Article 61
• Main Authors: Stella, Alessandra, Nicolazzi, Ezequiel Luis, Van Tassell, Curtis P, Rothschild, Max F, Colli, Licia, Rosen, Benjamin D, Sonstegard, Tad S, Crepaldi, Paola, Tosser-Klopp, Gwenola, Joost, Stephane
• Format: Article
• Language: English
• Subjects: Adaptation; Adaptation (Biology); Adaptation, Physiological; Agricultural development; Agricultural research; Analysis; Animal populations; Animals; Biological diversity; Consortia; Databases, Genetic; Datasets; Deoxyribonucleic acid; DNA; Domestication; Gene polymorphism; Gene sequencing; Genetic aspects; Genetic diversity; Genetic Variation; Genetics, Population; Genomes; Genomics; Genomics - methods; Genotype & phenotype; Genotypes; Germplasm; Goats; Goats - genetics; Goats - physiology; Life Sciences; Livestock; Nucleotides; Physiological aspects; Polymorphism; Polymorphism, Single Nucleotide; Populations; R&D; Rangelands; Research & development; Single-nucleotide polymorphism; Whole genome sequencing
• ISSN: 1297-9686; 0999-193X; 1297-9686
• DOI: 10.1186/s12711-018-0427-5

In 2013, the 50 K goat single nucleotide polymorphism (SNP) panel was developed (http://www.goatgenome.org; [3]) by combining whole-genome sequencing and reduced representation libraries from eight breeds/populations from Europe and Asia through the cooperation of the Institut National de la Recherche Agronomique (Inra) in France, Utrecht University in The Netherlands, the Malaysian Agricultural Research and Development Institute (MARDI) in Malaysia, and DNA Landmarks in Canada. Several large projects took advantage of this newly-developed SNP panel to genotype many goat populations across the world with a range of objectives and hypotheses: genome-wide association analyses across a spectrum of research and production traits, germplasm characterization and diversity studies, and genetic prediction for selection in commercial populations. [...]Australia and New Zealand (Fig. 6) samples from three breeds were provided, with rangeland uniquely represented in the dataset by sampling sites in the western part of the continent. Individuals and SNPs that did not pass the following thresholds were removed: individual genotype call rate higher than 0.96, SNP call rate higher than 0.98, and identity-by-state (IBS) between genotypes (compared pairwise based on all markers) less than 0.99. [...]SNPs that were completely monomorphic over the whole dataset were also removed.