Roux Pierre-François, Boutin Morgane, Désert Colette, Djari Anis, Esquerré Diane, Klopp Christophe, Lagarrigue Sandrine, Demeure Olivier
INRA, UMR1348 PEGASE, Saint-Gilles, France; Agrocampus Ouest, UMR1348 PEGASE, Rennes, France; Université Européenne de Bretagne, Rennes, France.
INRA, SIGENAE, Castanet-Tolosan, France.
PLoS One. 2014 Oct 21;9(10):e111299. doi: 10.1371/journal.pone.0111299. eCollection 2014.
In this study, we propose an approach aiming at fine-mapping adiposity QTL in chicken, integrating whole genome re-sequencing data. First, two QTL regions for adiposity were identified by performing a classical linkage analysis on 1362 offspring in 11 sire families obtained by crossing two meat-type chicken lines divergently selected for abdominal fat weight. Those regions, located on chromosome 7 and 19, contained a total of 77 and 84 genes, respectively. Then, SNPs and indels in these regions were identified by re-sequencing sires. Considering issues related to polymorphism annotations for regulatory regions, we focused on the 120 and 104 polymorphisms having an impact on protein sequence, and located in coding regions of 35 and 42 genes situated in the two QTL regions. Subsequently, a filter was applied on SNPs considering their potential impact on the protein function based on conservation criteria. For the two regions, we identified 42 and 34 functional polymorphisms carried by 18 and 24 genes, and likely to deeply impact protein, including 3 coding indels and 4 nonsense SNPs. Finally, using gene functional annotation, a short list of 17 and 4 polymorphisms in 6 and 4 functional genes has been defined. Even if we cannot exclude that the causal polymorphisms may be located in regulatory regions, this strategy gives a complete overview of the candidate polymorphisms in coding regions and prioritize them on conservation- and functional-based arguments.
在本研究中，我们提出了一种旨在对鸡的肥胖QTL进行精细定位的方法，该方法整合了全基因组重测序数据。首先，通过对由两个因腹脂重量差异选择的肉用型鸡品系杂交获得的11个父系家族中的1362只后代进行经典连锁分析，确定了两个肥胖QTL区域。这些区域分别位于7号和19号染色体上，共包含77个和84个基因。然后，通过对父系进行重测序，鉴定了这些区域中的单核苷酸多态性（SNPs）和插入缺失（indels）。考虑到与调控区域多态性注释相关的问题，我们重点关注了120个和104个对蛋白质序列有影响且位于两个QTL区域中35个和42个基因编码区域的多态性。随后，根据保守性标准，对SNPs施加了一个基于其对蛋白质功能潜在影响的筛选。对于这两个区域，我们鉴定出了分别由18个和24个基因携带的42个和34个功能性多态性，这些多态性可能对蛋白质有深远影响，包括3个编码插入缺失和4个无义SNPs。最后，通过基因功能注释，确定了6个和4个功能基因中17个和4个多态性的简短列表。即使我们不能排除因果多态性可能位于调控区域，但该策略全面概述了编码区域中的候选多态性，并基于保守性和功能性论据对它们进行了优先排序。
