Abstract
The choice of a genetic marker genotyping platform is important for genomic prediction in livestock and poultry. High-throughput sequencing can produce more genetic markers, but the genotype quality is lower than that obtained with single nucleotide polymorphism (SNP) chips. The aim of this study was to compare the accuracy of genomic prediction between high-throughput sequencing and SNP chips in broilers. In this study, we developed a new SNP marker screening method, the pre-marker-selection (PMS) method, to determine whether an SNP marker can be used for genomic prediction. We also compared a method which preselection marker based results from genome-wide association studies (GWAS). With the two methods, we analysed body weight at the12th week (BW) and feed conversion ratio (FCR) in a local broiler population. A total of 395 birds were selected from the F2 generation of the population, and 10X specific-locus amplified fragment sequencing (SLAF-seq) and the Illumina Chicken 60K SNP Beadchip were used for genotyping. The genomic best linear unbiased prediction method (GBLUP) was used to predict the genomic breeding values. The accuracy of genomic prediction was validated by the leave-one-out cross-validation method. Without SNP marker screening, the accuracies of the genomic estimated breeding value (GEBV) of BW and FCR were 0.509 and 0.249, respectively, when using SLAF-seq, and the accuracies were 0.516 and 0.232, respectively, when using the SNP chip. With SNP marker screening by the PMS method, the accuracies of GEBV of the two traits were 0.671 and 0.499, respectively, when using SLAF-seq, and 0.605 and 0.422, respectively, when using the SNP chip. Our SNP marker screening method led to an increase of prediction accuracy by 0.089–0.250. With SNP marker screening by the GWAS method, the accuracies of genomic prediction for the two traits were also improved, but the gains of accuracy were less than the gains with PMS method for all traits. The results from this study indicate that our PMS method can improve the accuracy of GEBV, and that more accurate genomic prediction can be obtained from an increased number of genomic markers when using high-throughput sequencing in local broiler populations. Due to its lower genotyping cost, high-throughput sequencing could be a good alternative to SNP chips for genomic prediction in breeding programmes of local broiler populations.
Highlights
Genomic prediction is a new generation breeding technology, and it has been widely implemented in animal and plant breeding (Meuwissen et al, 2001; Su et al, 2016; Wang et al, 2019)
single nucleotide polymorphism (SNP) Marker Screening Method In this study, we provide a new method, the pre-marker-selection (PMS) method, to screen informative markers for genomic prediction based on the difference between phenotypes of the two homozygous genotypes at the marker with the data of the reference population, and the marks which have no homozygote or only have one homozygote will be deleted
The coefficient of variation for the SNP markers in the minor allele frequency (MAF) intervals, which was calculated as the ratio of the standard deviation to the mean, was 0.355 for SLAF-seq and 0.154 for the SNP chip
Summary
Genomic prediction is a new generation breeding technology, and it has been widely implemented in animal and plant breeding (Meuwissen et al, 2001; Su et al, 2016; Wang et al, 2019). The high cost of genome marker genotyping limits the application of genomic prediction in poultry. With the development of low-cost and high-throughput sequencing, various marker genotyping platforms have provided alternatives to chip-based genotyping. The choice of marker genotyping platform is a key factor affecting the accuracy of genomic estimated breeding values (GEBV) (Tan et al, 2017; Wang et al, 2019; Whalen et al, 2019). With the development of high-throughput sequencing technology, reduced-representation genome sequencing (RRGS) has been developed. RRGS uses restriction endonucleases to digest genomic DNA and sequence the digested fragments, such as restriction site associated DNA (RAD) (Baird et al, 2008), genotyping-by-sequencing (GBS) (Elshire et al, 2011; Wang et al, 2017), and specific-locus amplified fragment sequencing (SLAF-seq) (Sun et al, 2013)
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