Efficiency of genotyping by sequencing in inferring genomic relatedness and molecular insights into fat tail selection in Tunisian sheep.

In developing countries, the use of simple and cost-efficient molecular technology is crucial for genetic characterization of local animal resources and better development of conservation strategies. The genotyping by sequencing (GBS) technique, also called restriction enzyme- reduced representational sequencing, is an efficient, cost-effective method for simultaneous discovery and genotyping of many markers. In the present study, we applied a two-enzyme GBS protocol (PstI/MspI) to discover and genotype SNP markers among 197 Tunisian sheep samples. A total of 100 333 bi-allelic SNPs were discovered and genotyped with an SNP call rate of 0.69 and mean sample depth 3.33. The genomic relatedness between 183 samples grouped the samples perfectly to their populations and pointed out a high genetic relatedness of inbred subpopulation reflecting the current adopted reproductive strategies. The genome-wide association study contrasting fat vs. thin-tailed breeds detected 41 significant variants including a peak positioned on OAR20. We identified FOXC1, GMDS, VEGFA, OXCT1, VRTN and BMP2 as the most promising for sheep tail-type trait. The GBS data have been useful to assess the population structure and improve our understanding of the genomic architecture of distinctive characteristics shaped by selection pressure in local sheep breeds. This study successfully investigates a cost-efficient method to discover genotypes, assign populations and understand insights into sheep adaptation to arid area. GBS could be of potential utility in livestock species in developing/emerging countries.

Construction of relatedness matrices using genotyping-by-sequencing data.

BACKGROUND: Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set. RESULTS: We show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. We refer to these methods of estimation as kinship using GBS with depth adjustment (KGD). The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2-4 for relatedness between individuals and 5-10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a 'fin plot') is given to illustrate this issue and to guide filtering parameters. CONCLUSION: We provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method.

A high throughput single nucleotide polymorphism multiplex assay for parentage assignment in New Zealand sheep.

Accurate pedigree information is critical to animal breeding systems to ensure the highest rate of genetic gain and management of inbreeding. The abundance of available genomic data, together with development of high throughput genotyping platforms, means that single nucleotide polymorphisms (SNPs) are now the DNA marker of choice for genomic selection studies. Furthermore the superior qualities of SNPs compared to microsatellite markers allows for standardization between laboratories; a property that is crucial for developing an international set of markers for traceability studies. The objective of this study was to develop a high throughput SNP assay for use in the New Zealand sheep industry that gives accurate pedigree assignment and will allow a reduction in breeder input over lambing. This required two phases of development--firstly, a method of extracting quality DNA from ear-punch tissue performed in a high throughput cost efficient manner and secondly a SNP assay that has the ability to assign paternity to progeny resulting from mob mating. A likelihood based approach to infer paternity was used where sires with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) are assigned. An 84 "parentage SNP panel" was developed that assigned, on average, 99% of progeny to a sire in a problem where there were 3,000 progeny from 120 mob mated sires that included numerous half sib sires. In only 6% of those cases was there another sire with at least a 0.02 probability of paternity. Furthermore dam information (either recorded, or by genotyping possible dams) was absent, highlighting the SNP test's suitability for paternity testing. Utilization of this parentage SNP assay will allow implementation of progeny testing into large commercial farms where the improved accuracy of sire assignment and genetic evaluations will increase genetic gain in the sheep industry.

The locus for an inherited cataract in sheep maps to ovine chromosome 6.

PURPOSE: Cataracts are an important cause of blindness in humans but there are few large animal models available. One of these animal models is Ovine Heritable Cataract, a bilateral cortical cataract which develops after birth. This cataract has been used as a model for human cataracts in drug trials, but the gene responsible for the cataract trait is unknown. A genetic test for cataract would improve the efficiency of the model by predicting which animals would develop cataracts. Identifying the genetic basis of the cataract would indicate its relevance to human cataract. METHODS: A genome scan was performed on 20 sheep chromosomes, representing 86% of the genome, to determine the position of the cataract locus. Additional microsatellite markers were tested on chromosome 6 using a larger pedigree. Fine mapping was performed using a breakpoint panel of 36 animals and novel microsatellite markers taken from the bovine genome assembly. All exons of the candidate gene nudix (nucleoside diphosphate linked moiety X)-type motif 9 (NUDT9) were sequenced in normal and affected sheep. RESULTS: Significant linkage was found between cataract status and markers on chromosome 6. Linkage analysis on the larger pedigree showed the most likely position of the cataract locus was between 112.3 and 132.9 cM from the centromere. During fine mapping, NUDT9 was considered as a positional candidate for the cataract gene because it was located within the linked interval and is expressed in the lens. The gene was ruled out as the cataract gene after extensive genotype analysis, but a single nucleotide polymorphism (SNP) inside it provided a useful restriction fragment length polymorphism (RFLP) marker for further fine mapping. Twelve new markers were found and used to map the cataract locus to between 131.1 and 131.8 cM from the centromere. CONCLUSIONS: A region of ovine chromosome 6 strongly linked to cataract has been identified, and a genetic test for cataract based on a SNP within this region has been developed. The best candidate gene within this region is AF4/FMR2 family, member 1 (AFF1), the mouse equivalent of which is associated with an inherited cataract.

A deer (subfamily Cervinae) genetic linkage map and the evolution of ruminant genomes.

Comparative maps between ruminant species and humans are increasingly important tools for the discovery of genes underlying economically important traits. In this article we present a primary linkage map of the deer genome derived from an interspecies hybrid between red deer (Cervus elaphus) and Père David's deer (Elaphurus davidianus). The map is approximately 2500 cM long and contains >600 markers including both evolutionary conserved type I markers and highly polymorphic type II markers (microsatellites). Comparative mapping by annotation and sequence similarity (COMPASS) was demonstrated to be a useful tool for mapping bovine and ovine ESTs in deer. Using marker order as a phylogenetic character and comparative map information from human, mouse, deer, cattle, and sheep, we reconstructed the karyotype of the ancestral Pecoran mammal and identified the chromosome rearrangements that have occurred in the sheep, cattle, and deer lineages. The deer map and interspecies hybrid pedigrees described here are a valuable resource for (1) predicting the location of orthologs to human genes in ruminants, (2) mapping QTL in farmed and wild deer populations, and (3) ruminant phylogenetic studies.