Identification of the Causal Mutation for Transverse Hemimelia in Mediterranean Italian River Buffalo Using Whole Genome Sequence Data

Mediterranean river buffalo have recently undergone strong selection for increased quality and quantity of milk for mozzarella cheese production. Strong selection for traits such as milk production are often associated with increased inbreeding, leading to decreased genetic diversity and an increase in the prevalence of genetic diseases. Transverse hemimelia (TH) is a congenital developmental abnormality characterized by the absence of a variable portion of the distal limbs. It occurs at the rate of approximately 2-5% in Mediterranean river buffalo populations and causes significant production loss in affected animals as well as in carriers of the disease, which are eliminated from the breeding herd once identified. Thus, there is significant motivation to identify the causal mutation for TH and develop a genetic test to identify carriers and implement a selective breeding program to eliminate carrier-to-carrier matings. In order to localize the mutation, the genomes of 4 cases and 14 carriers were sequenced using Illumina technology with paired-end libraries and an average depth of 10X coverage. Variant calling from whole genome sequence data resulted in 17.9 million high confidence single nucleotide polymorphisms (SNPs) to be analyzed. Because TH is believed to be an autosomal recessive disorder, variants were only selected for further analysis if all cases were homozygous for the non-reference allele at the SNP and if the frequency of this allele was <30% in the controls. This drastically reduced the number of candidate variants to 459 SNPs. Annotation of these variants identified a single candidate gene, SMARCA4, which had previously been implicated in embryonic limb development. Further investigation of SMARCA4 revealed that it is contained within a run of homozygosity in the affected animals. Ongoing research, including de novo assembly for structural variant detection and variant effect prediction, is underway to elucidate the causal mutation.