Short Insertion and Deletion Discoveries via Whole-Genome Sequencing of 101 Thoroughbred Racehorses.
Teruaki TozakiAoi OhnumaMio KikuchiTaichiro IshigeHironaga KakoiKei-Ichi HirotaYuji TakahashiShun-Ichi NagataPublished in: Genes (2023)
Thoroughbreds are some of the most famous racehorses worldwide and are currently animals of high economic value. To understand genomic variability in Thoroughbreds, we identified genome-wide insertions and deletions (INDELs) and obtained their allele frequencies in this study. INDELs were obtained from whole-genome sequencing data of 101 Thoroughbred racehorses by mapping sequence reads to the horse reference genome. By integrating individual data, 1,453,349 and 113,047 INDELs were identified in the autosomal (1-31) and X chromosomes, respectively, while 18 INDELs were identified on the mitochondrial genome, totaling 1,566,414 INDELs. Of those, 779,457 loci (49.8%) were novel INDELs, while 786,957 loci (50.2%) were already registered in Ensembl. The sizes of diallelic INDELs ranged from -286 to +476, and the majority, 717,736 (52.14%) and 220,672 (16.03%), were 1-bp and 2-bp variants, respectively. Numerous INDELs were found to have lower frequencies of alternative (Alt) alleles. Many rare variants with low Alt allele frequencies (<0.5%) were also detected. In addition, 5955 loci were genotyped as having a minor allele frequency of 0.5 and being heterogeneous genotypes in all the horses. While short-read sequencing and its mapping to reference genome is a simple way of detecting variants, fake variants may be detected. Therefore, our data help to identify true variants in Thoroughbred horses. The INDEL database we constructed will provide useful information for genetic studies and industrial applications in Thoroughbred horses, including a gene-editing test for gene-doping control and a parentage test using INDELs for horse registration and identification.
Keyphrases
- genome wide
- copy number
- dna methylation
- gene expression
- healthcare
- high resolution
- wastewater treatment
- emergency department
- big data
- genome wide association study
- single molecule
- oxidative stress
- single cell
- transcription factor
- artificial intelligence
- data analysis
- deep learning
- case control
- high density
- adverse drug