BACKGROUND In 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. RESULTS To 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. CONCLUSIONS We 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.

中文翻译：

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pCADD：Sus scrofa中的SNV优先级。

背景技术在动物育种中，致病性遗传变异的鉴定非常重要并且具有很高的经济价值。通常，候选变体的数量超过可以验证的变体的数量。优先考虑可能的候选者的一种方法是通过评估其具有有害作用的潜力，例如，通过预测其后果。由于实验上难以评估不会引起氨基酸取代的变体，因此需要其他优先排序方法。对于人类基因组，有害基因组变异的预测已随着引入依赖于注释的组合耗尽（CADD）方法而向前迈进了一步。从理论上讲，这种方法可以应用于任何物种。在这里，我们提出了pCADD（猪为p），该模型可对猪基因组中的单核苷酸变异（SNV）进行评分。结果为了评估pCADD是否捕获具有生物学意义的位点，我们使用了miRNA和内含子的转录本，特定于特定组织的基因序列以及密码子的不同位点，以测试pCADD分数在功能性和非功能性上的区别程度元素。此外，我们对非编码和编码SNV的示例进行了评估，这可能是表型变化的原因。我们的结果表明，pCADD分数可区分功能序列和非功能序列，并区分功能性SNV，并且pCADD能够对密码子中相对于其冗余的不同位置进行评分。综上所述，这些结果表明，基于pCADD分数，可以根据其适应率来识别和区分具有生物学相关性的区域。结论我们根据pCADD所处区域的生物学意义，提出了关于pCADD在猪基因组中优先考虑其有害性的SNV的能力。我们为所有常染色体和猪参考序列Sscrofa11.1的X染色体的所有可能的SNV（编码和非编码）创建了分数，提出了一个工具箱来对变种进行优先级排序并评估序列以突出显示感兴趣的新位点，以解释生物学功能，与动物育种有关。