Comparison of kinship estimates in Santa Inês sheep using microsatellite and genome-wide SNP markers

A pipeline for effectively developing highly polymorphic simple sequence repeats markers based on multi-sample genomic data

Simple sequence repeats (SSRs) are widely used genetic markers in ecology, evolution, and conservation even in the genomics era, while a general limitation to their application is the difficulty of developing polymorphic SSR markers. Next-generation sequencing (NGS) offers the opportunity for the rapid development of SSRs; however, previous studies developing SSRs using genomic data from only one individual need redundant experiments to test the polymorphisms of SSRs. In this study, we designed a pipeline for the rapid development of polymorphic SSR markers from multi-sample genomic data. We used bioinformatic software to genotype multiple individuals using resequencing data, detected highly polymorphic SSRs prior to experimental validation, significantly improved the efficiency and reduced the experimental effort. The pipeline was successfully applied to a globally threatened species, the brown eared-pheasant (Crossoptilon mantchuricum), which showed very low genomic diversity. The 20 newly developed SSR markers were highly polymorphic, the average number of alleles was much higher than the genomic average. We also evaluated the effect of the number of individuals and sequencing depth on the SSR mining results, and we found that 10 individuals and ~10X sequencing data were enough to obtain a sufficient number of polymorphic SSRs, even for species with low genetic diversity. Furthermore, the genome assembly of NGS data from the optimal number of individuals and sequencing depth can be used as an alternative reference genome if a high-quality genome is not available. Our pipeline provided a paradigm for the application of NGS technology to mining and developing molecular markers for ecological and evolutionary studies.

Next Generation Sequencing of Single Nucleotide Polymorphic DNA-Markers in Selecting for Intramuscular Fat, Fat Melting Point, Omega-3 Long-Chain Polyunsaturated Fatty Acids and Meat Eating Quality in Tattykeel Australian White MARGRA Lamb

Meat quality data can only be obtained after slaughter when selection decisions about the live animal are already too late. Carcass estimated breeding values present major precision problems due to low accuracy, and by the time an informed decision on the genetic merit for meat quality is made, the animal is already dead. We report for the first time, a targeted next-generation sequencing (NGS) of single nucleotide polymorphisms (SNP) of lipid metabolism genes in Tattykeel Australian White (TAW) sheep of the MARGRA lamb brand, utilizing an innovative and minimally invasive muscle biopsy sampling technique for directly quantifying the genetic worth of live lambs for health-beneficial omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA), intramuscular fat (IMF), and fat melting point (FMP). NGS of stearoyl-CoA desaturase (SCD), fatty acid binding protein-4 (FABP4), and fatty acid synthase (FASN) genes identified functional SNP with unique DNA marker signatures for TAW genetics. The SCD g.23881050T>C locus was significantly associated with IMF, C22:6n-3, and C22:5n-3; FASN g.12323864A>G locus with FMP, C18:3n-3, C18:1n-9, C18:0, C16:0, MUFA, and FABP4 g.62829478A>T locus with IMF. These add new knowledge, precision, and reliability in directly making early and informed decisions on live sheep selection and breeding for health-beneficial n-3 LC-PUFA, FMP, IMF and superior meat-eating quality at the farmgate level. The findings provide evidence that significant associations exist between SNP of lipid metabolism genes and n-3 LC-PUFA, IMF, and FMP, thus underpinning potential marker-assisted selection for meat-eating quality traits in TAW lambs.