Genotyping-by-Sequencing (GBS): A Novel, Efficient and Cost-Effective Genotyping Method for Cattle Using Next-Generation Sequencing

Abstract

High-throughput genotyping methods have increased the analytical power to study complex traits but high cost has remained a barrier for large scale use in animal improvement. We have adapted genotyping-by-sequencing (GBS) used in plants for genotyping 47 animals representing 7 taurine and indicine breeds of cattle from the US and Africa. Genomic DNA was digested with different enzymes, ligated to adapters containing one of 48 unique bar codes and sequenced by the Illumina HiSeq 2000. PstI was the best enzyme producing 1.4 million unique reads per animal and initially identifying a total of 63,697 SNPs. After removal of SNPs with call rates of less than 70%, 51,414 SNPs were detected throughout all autosomes with an average distance of 48.1 kb, and 1,143 SNPs on the X chromosome at an average distance of 130.3 kb, as well as 191 on unmapped contigs. If we consider only the SNPs with call rates of 90% and over, we identified 39,751 on autosomes, 850 on the X chromosome and 124 on unmapped contigs. Of these SNPs, 28,843 were not tightly linked to other SNPs. Average marker density per autosome was highly correlated with chromosome size (coefficient of correlation = −0.798, r2 = 0.637) with higher density in smaller chromosomes. Average SNP call rate was 86.5% for all loci, with 53.0% of the loci having call rates >90% and the average minor allele frequency being 0.212. Average observed heterozygosity ranged from 0.046–0.294 among individuals, and from 0.064–0.197 among breeds, with Brangus showing the highest diversity as expected. GBS technique is novel, flexible, sufficiently high-throughput, and capable of providing acceptable marker density for genomic selection or genome-wide association studies at roughly one third of the cost of currently available genotyping technologies.

Investigation of the genetic distances of bovids and cervids using BovineSNP50k BeadChip

“…The number and variability of individuals used in SNP discovery panel in non-model species can also lead to some degree of ascertainment bias because the panel consists of only a small subset of the genotyped individuals (Albrechtsen et al, 2010). The degree of ascertainment bias depends on the number in which the SNPs were originally found and results in a skewing of the allele frequency spectrum towards common alleles (De Donato et al, 2013). In our data set, some level of ascertainment bias could be introduced because bovine genotyping array was used to determine polymorphic SNPs in closely related (Bos primigenius indicus) and more phylogenetically distant species from the family Cervidae, and therefore the comparison should be interpreted with caution.…”

Molecular Breeding for Improved Second Generation Bioenergy Crops

“…Next generation sequencing (NGS), high-throughput genotyping, and molecular breeding (see Glossary) methodologies such as marker assisted selection (MAS), genomic selection (GS), and genetic modification (GM) have been applied in a significant number of important species. These include cereals such as rice (Oryza sativa) [2], maize (Zea mays) [3], and barley (Hordeum vulgare) [4]; other crops including potato (Solanum tuberosum) [5], apple (Malus domestica) [6], and soybean (Glycine max) [7]; and domestic livestock species including cattle [8] and pigs [9]. In total more than 100 plant genomes have been sequenced since 2000 [10] as costs for sequencing technology have plummeted and instrument capacity increased millionfold [11].…”

BREEDING AND GENETICS SYMPOSIUM: Networks and pathways to guide genomic selection1–3

“…Technologies for low-cost genotyping by sequence (Elshire et al, 2011;DeDonato et al, 2012) and less expensive, low-density SNP chips (Boichard et al, 2012) using imputation to infer greater-density genotypes (Browning and Browning, 2009;Sargolzaei et al, 2011;Van Raden et al, 2011) may enable more cost-effective genomic prediction within performance-recorded populations. Low-cost targeted genotyping with next-generation sequencing (Thallman and Koshinsky, 2012) can also support imputation to greaterdensity genotypes and enable genotyping specifi c variants likely to have functional effects.…”