Analysis of dog breed diversity using a composite selection index

Abstract

During breed development, domestic dogs have undergone genetic bottlenecks and sustained selective pressures, as a result distinctive genomic diversity occurs to varying degrees within and between breed groups. This diversity can be identified using standard methods or combinations of these methods. This study explored the application of a combined selection index, composite selection signals (CSS), derived from multiple methods to an existing genotype dataset from three breed groups developed in distinct regions of Asia: Qinghai-Tibet plateau dogs (adapted to living at altitude), Xi dogs (with superior running ability) and Mountain hounds (used for hunting ability). The CSS analysis confirmed top ranked genomic regions on CFA10 and CFA21 in Qinghai-Tibet plateau dogs, CFA1 in Xi dogs and CFA5 in Mountain hounds. CSS analysis identified additional significant genomic regions in each group, defined by a total of 1,397, 1,475 and 1,675 significant SNPs in the Qinghai-Tibetan Plateau dogs, Xi dogs and Mountain hounds, respectively. Chitinase 3 Like 1 (CHI3L1) and Leucine Rich Repeat Containing G Protein-Coupled Receptor 6 (LGR6) genes were located in the top ranked region on CFA7 (0.02–1 Mb) in the Qinghai-Tibetan Plateau dogs. Both genes have been associated with hypoxia responses or altitude adaptation in humans. For the Xi dogs, the top ranked region on CFA25 contained the Transient Receptor Potential Cation Channel Subfamily C Member 4 (TRPC4) gene. This calcium channel is important for optimal muscle performance during exercise. The outstanding signals in the Mountain dogs were on CFA5 with 213 significant SNPs that spanned genes involved in cardiac development, sight and generation of biochemical energy. These findings support the use of the combined index approach for identifying novel regions of genome diversity in dogs. As with other methods, the results do not prove causal links between these regions and phenotypes, but they may assist in focusing future studies that seek to identify functional pathways that contribute to breed diversity.

Identification of Genomic Signatures in Bullmastiff Dogs Using Composite Selection Signals Analysis of 23 Purebred Clades

“…In this study, the CSS test was used to identify genomic signatures in multiple-breed comparisons with a focus on the Bullmastiff breed. CSS combines three commonly used test statistics into complementary signals so that regions harbouring common signals can be identified with high sensitivity [ 8 , 44 , 45 , 46 , 47 ].…”

“…The top 0.005 fractions (0.5%) of smoothed CSS scores were considered as significant regions. The average CSS value was the mean of smoothed CSS values of all significant SNPs in the region [ 8 ].…”

“…The normal distribution of derived allele frequency was estimated, and the ∆DAF values were transferred to Z scores (0,1). In the present study, the major alleles in wolves were assigned as ancestral alleles, following the approach used previously [ 8 , 15 , 36 ] and in comparison with data from 10 Alaskan Huskies as in a prior study [ 35 ]. The major alleles (common variants) from this dataset were assigned as ancestral alleles.…”

“…The advantage of this approach is that it does not require detailed phenotyping. A number of statistical methods can be employed to detect such variation, including a multi-statistical index method referred to as combined selection signals (CSS) analysis, which was originally developed for application in farm animals and which we recently showed to be a sensitive test for use in dogs [ 8 ].…”

Ascertaining the genetic background of the Celtic‐Iberian pig strain: A signatures of selection approach

“…The Δ DAF test requires the definition of an ancestral allele and a derived allele (Grossman et al, 2010). Following Hsu et al (2023), the major alleles (more frequent variants at a locus) were assigned as ancestral alleles. Δ DAF was computed as Δ DAF = DAF test – DAF reference , where DAF is the frequency of the derived allele in either the test, putatively selected, population or the reference, alternative non‐selected, population (ancestral population in terms of Grossman et al, 2010).…”