Technical note: High fidelity of whole-genome amplified sheep (Ovis aries) deoxyribonucleic acid using a high-density single nucleotide polymorphism array-based genotyping platform

Population structure and selection signal analysis of indigenous sheep from the southern edge of the Taklamakan Desert

Analyzing the genetic diversity and selection characteristics of sheep (Ovis aries) holds significant value in understanding their environmental adaptability, enhancing breeding efficiency, and achieving effective conservation and rational utilization of genetic resources. In this study, we utilized Illumina Ovine SNP 50 K BeadChip data from four indigenous sheep breeds from the southern margin of the Taklamakan Desert (Duolang sheep: n = 36, Hetian sheep: n = 74, Kunlun sheep: n = 27, Qira black sheep: n = 178) and three foreign meat sheep breeds (Poll Dorset sheep: n = 105, Suffolk sheep: n = 153, Texel sheep: n = 150) to investigate the population structure, genetic diversity, and genomic signals of positive selection within the indigenous sheep. According to the Principal component analysis (PCA), the Neighbor-Joining tree (NJ tree), and Admixture, we revealed distinct clustering patterns of these seven sheep breeds based on their geographical distribution. Then used Cross Population Extended Haplotype Homozygosity (XP-EHH), Fixation Index (FST), and Integrated Haplotype Score (iHS), we identified a collective set of 32 overlapping genes under positive selection across four indigenous sheep breeds. These genes are associated with wool follicle development and wool traits, desert environmental adaptability, disease resistance, reproduction, and high-altitude adaptability. This study reveals the population structure and genomic selection characteristics in the extreme desert environments of native sheep breeds from the southern edge of the Taklimakan Desert, providing new insights into the conservation and sustainable use of indigenous sheep genetic resources in extreme environments. Additionally, these findings offer valuable genetic resources for sheep and other mammals to adapt to global climate change.

Design and characterization of a high-resolution multiple-SNP capture array by target sequencing for sheep

The efficiency of molecular breeding largely depends on inexpensive genotyping arrays. In this study, we aimed to develop an ovine high-resolution multiple-single-nucleotide polymorphism (SNP) capture array, based on genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology. All the markers were from 40K captured regions, including genes located within selective sweep regions, breed-specific regions, quantitative trait loci (QTL), and the potential functional SNPs on the sheep genome. The results showed that a total of 210K high-quality SNPs were identified in the 40K regions, indicating a high average capture ratio (99.7%) for the target genomic regions. Using genotyped data (n = 317) from liquid chip technology, we further performed genome-wide association studies (GWAS) to detect the genetic loci affecting sheep hair types and teat number. A single significant association signal for hair types was identified on 6.7-7.1 Mb of chromosome 25. The IRF2BP2 gene (chr25: 7,067,974-7,071,785), which is located within this genomic region, has been previously known to be involved in hair/wool traits in sheep. The results further showed a new candidate region around 26.4 Mb of chromosome 13, between the ARHGAP21 and KIAA1217 genes, that was significantly related to teat number in sheep. The haplotype patterns of this region also showed differences in animals with 2, 3, or 4 teats. Advances in using the high-accuracy and low-cost liquid chip are expected to accelerate sheep genomic and breeding studies in the coming years.

Inference of Breed Structure in Farm Animals: Empirical Comparison between SNP and Microsatellite Performance

Knowledge of population structure is essential to improve the management and conservation of farm animal genetic resources. Microsatellites, which have long been popular for this type of analysis, are more and more neglected in favor of whole-genome single nucleotide polymorphism (SNP) chips that are now available for the main farmed animal species. In this study, we compared genetic patterns derived from microsatellites to that inferred by SNPs, considering three pairs of datasets of sheep and cattle. Population genetic differentiation analyses (Fixation index, F_ST), as well as STRUCTURE analyses showed a very strong consistency between the two types of markers. Microsatellites gave pictures that were largely concordant with SNPs, although less accurate. The best concordance was found in the most complex dataset, which included 17 French sheep breeds (with a Pearson correlation coefficient of 0.95 considering the 136 values of pairwise F_ST, obtained with both types of markers). The use of microsatellites reduces the cost and the related analyses do not require specific computer equipment (i.e., information technology (IT) infrastructure able to provide adequate computing and storage capacity). Therefore, this tool may still be a very appropriate solution to evaluate, in a first stage, the general state of livestock at national scales. At a time when local breeds are disappearing at an alarming rate, it is urgent to improve our knowledge of them, in particular by promoting tools accessible to the greatest number.

Genotyping performance assessment of whole genome amplified DNA with respect to multiplexing level of assay and its period of storage

Whole genome amplification can faithfully amplify genomic DNA (gDNA) with minimal bias and substantial genome coverage. Whole genome amplified DNA (wgaDNA) has been tested to be workable for high-throughput genotyping arrays. However, issues about whether wgaDNA would decrease genotyping performance at increasing multiplexing levels and whether the storage period of wgaDNA would reduce genotyping performance have not been examined. Using the Sequenom MassARRAY iPLEX Gold assays, we investigated 174 single nucleotide polymorphisms for 3 groups of matched samples: group 1 of 20 gDNA samples, group 2 of 20 freshly prepared wgaDNA samples, and group 3 of 20 stored wgaDNA samples that had been kept frozen at −70°C for 18 months. MassARRAY is a medium-throughput genotyping platform with reaction chemistry different from those of high-throughput genotyping arrays. The results showed that genotyping performance (efficiency and accuracy) of freshly prepared wgaDNA was similar to that of gDNA at various multiplexing levels (17-plex, 21-plex, 28-plex and 36-plex) of the MassARRAY assays. However, compared with gDNA or freshly prepared wgaDNA, stored wgaDNA was found to give diminished genotyping performance (efficiency and accuracy) due to potentially inferior quality. Consequently, no matter whether gDNA or wgaDNA was used, better genotyping efficiency would tend to have better genotyping accuracy.

The development and characterization of a 60K SNP chip for chicken

BACKGROUND

In livestock species like the chicken, high throughput single nucleotide polymorphism (SNP) genotyping assays are increasingly being used for whole genome association studies and as a tool in breeding (referred to as genomic selection). To be of value in a wide variety of breeds and populations, the success rate of the SNP genotyping assay, the distribution of the SNP across the genome and the minor allele frequencies (MAF) of the SNPs used are extremely important.

RESULTS

We describe the design of a moderate density (60k) Illumina SNP BeadChip in chicken consisting of SNPs known to be segregating at high to medium minor allele frequencies (MAF) in the two major types of commercial chicken (broilers and layers). This was achieved by the identification of 352,303 SNPs with moderate to high MAF in 2 broilers and 2 layer lines using Illumina sequencing on reduced representation libraries. To further increase the utility of the chip, we also identified SNPs on sequences currently not covered by the chicken genome assembly (Gallus_gallus-2.1). This was achieved by 454 sequencing of the chicken genome at a depth of 12x and the identification of SNPs on 454-derived contigs not covered by the current chicken genome assembly. In total we added 790 SNPs that mapped to 454-derived contigs as well as 421 SNPs with a position on Chr_random of the current assembly. The SNP chip contains 57,636 SNPs of which 54,293 could be genotyped and were shown to be segregating in chicken populations. Our SNP identification procedure appeared to be highly reliable and the overall validation rate of the SNPs on the chip was 94%. We were able to map 328 SNPs derived from the 454 sequence contigs on the chicken genome. The majority of these SNPs map to chromosomes that are already represented in genome build Gallus_gallus-2.1.0. Twenty-eight SNPs were used to construct two new linkage groups most likely representing two micro-chromosomes not covered by the current genome assembly.

CONCLUSIONS

The high success rate of the SNPs on the Illumina chicken 60K Beadchip emphasizes the power of Next generation sequence (NGS) technology for the SNP identification and selection step. The identification of SNPs from sequence contigs derived from NGS sequencing resulted in improved coverage of the chicken genome and the construction of two new linkage groups most likely representing two chicken micro-chromosomes.