Data from: A novel iterative mixed model to remap three complex orthopedic traits in dogs

Hip dysplasia (HD), elbow dysplasia (ED), and rupture of the cranial (anterior) cruciate ligament (RCCL) are the most common complex orthopedic traits of dogs and all result in debilitating osteoarthritis. Herein we reanalyzed previously reported data: the Norberg angle (a quantitative measure of HD) in 921 dogs, ED in 113 cases and 633 controls, and RCCL in 271 cases and 399 controls and their genotypes at ~185,000 single nucleotide polymorphisms. A novel fixed and random model with a circulating probability unification (FarmCPU) function, with marker-based principal components and a kinship matrix to correct for population stratification, was used. A Bonferroni correction at p<0.01 resulted in a pgenome of 6.96 ×10-8. Six loci were identified; three for HD and three for RCCL. An associated locus at CFA28:34,369,342 for HD was described in the same dogs using a conventional mixed model. No loci were identified for RCCL in the previous report but the two loci for ED in the previous report did not reach genome-wide significance using the FarmCPU model. These results were supported by simulation which demonstrated that the FarmCPU held no power advantage over the linear mixed model for the ED sample but provided additional power for the HD and RCCL samples. Candidate genes for HD and RCCL are discussed. When using FarmCPU software, we recommend a resampling test, that a positive control be used to determine the optimum pseudo quantitative trait nucleotide-based covariate structure of the model, and a negative control be used consisting of permutation testing and the identical resampling test as for the non-permuted phenotypes.

犬髋关节发育不良（Hip dysplasia, HD）、肘关节发育不良（elbow dysplasia, ED）以及颅侧（前）十字韧带断裂（rupture of the cranial [anterior] cruciate ligament, RCCL）是犬类最常见的复合型骨科性状，且均会引发致残性骨关节炎。本研究对已发表的数据进行了重新分析：涵盖921只犬的诺伯格角（Norberg angle，定量评估HD的指标）、113例ED病例与633例对照的ED数据、271例RCCL病例与399例对照的RCCL数据，以及约18.5万个单核苷酸多态性位点的基因型数据。本研究采用了一种新型循环概率统一固定随机模型（FarmCPU），该模型结合基于标记的主成分分析与亲缘关系矩阵以校正群体分层效应。经邦费罗尼校正（p<0.01）后，得到基因组水平显著性阈值P值为6.96×10^-8。最终共鉴定出6个关联位点：3个与HD相关，3个与RCCL相关。其中针对HD的CFA28:34,369,342位点的关联信号，已通过传统混合模型在该群犬中被报道过。既往研究未在RCCL样本中鉴定到关联位点，且既往报道的2个ED关联位点在本研究的FarmCPU模型中未达到基因组水平显著性。模拟分析验证了上述结果：相较于线性混合模型，FarmCPU在ED样本中未体现出检验效能优势，但在HD与RCCL样本中可提供更强的检验效能。本研究还对HD与RCCL的候选基因进行了讨论。在使用FarmCPU软件时，我们建议开展重采样检验，设置阳性对照以确定模型最优的基于伪数量性状核苷酸的协变量结构，同时设置由置换检验与非置换表型所用的相同重采样检验组成的阴性对照。