Abstract
BackgroundIn animal breeding, identification of causative genetic variants is of major importance and high economical value. Usually, the number of candidate variants exceeds the number of variants that can be validated. One way of prioritizing probable candidates is by evaluating their potential to have a deleterious effect, e.g. by predicting their consequence. Due to experimental difficulties to evaluate variants that do not cause an amino-acid substitution, other prioritization methods are needed. For human genomes, the prediction of deleterious genomic variants has taken a step forward with the introduction of the combined annotation dependent depletion (CADD) method. In theory, this approach can be applied to any species. Here, we present pCADD (p for pig), a model to score single nucleotide variants (SNVs) in pig genomes.ResultsTo evaluate whether pCADD captures sites with biological meaning, we used transcripts from miRNAs and introns, sequences from genes that are specific for a particular tissue, and the different sites of codons, to test how well pCADD scores differentiate between functional and non-functional elements. Furthermore, we conducted an assessment of examples of non-coding and coding SNVs, which are causal for changes in phenotypes. Our results show that pCADD scores discriminate between functional and non-functional sequences and prioritize functional SNVs, and that pCADD is able to score the different positions in a codon relative to their redundancy. Taken together, these results indicate that based on pCADD scores, regions with biological relevance can be identified and distinguished according to their rate of adaptation.ConclusionsWe present the ability of pCADD to prioritize SNVs in the pig genome with respect to their putative deleteriousness, in accordance to the biological significance of the region in which they are located. We created scores for all possible SNVs, coding and non-coding, for all autosomes and the X chromosome of the pig reference sequence Sscrofa11.1, proposing a toolbox to prioritize variants and evaluate sequences to highlight new sites of interest to explain biological functions that are relevant to animal breeding.
Highlights
In animal breeding, identification of causative genetic variants is of major importance and high eco‐ nomical value
In this study, we trained a combined annotation dependent depletion (CADD)-like model for single nucleotide variants (SNVs) prioritisation in the pig genome, which is referred to as pCADD
PCADD scores for salivary glands and neuronal tissue specific genes are the lowest and highest, respectively we investigated whether genes considered to be housekeeping genes have different pCADD scores than genes expressed in certain tissues
Summary
Identification of causative genetic variants is of major importance and high eco‐ nomical value. The prediction of deleterious genomic variants has taken a step forward with the introduction of the combined annotation dependent depletion (CADD) method. In theory, this approach can be applied to any species. Because the number of tested single nucleotide variants (SNVs) is larger in whole-genome sequence data compared to array-based assays, truly causal genetic variants are more likely to be identified. The combined annotation dependent depletion (CADD) [10] model that was developed to investigate SNVs in human populations, can score variants at any location in the genome. The results demonstrated that applying the CADD methodology to non-human species is valid and powerful
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.