Mucha Anna, Nowak Błażej, Dzimira Stanisław, Liszka Bartłomiej, Zatoń-Dobrowolska Magdalena
Department of Genetics, Wrocław University of Environmental and Life Sciences, 51-631 Wrocław, Poland.
Department of Pathology, Wrocław University of Environmental and Life Sciences; 50-375 Wrocław, Poland.
J Vet Res. 2023 Sep 20;67(3):427-436. doi: 10.2478/jvetres-2023-0040. eCollection 2023 Sep.
The development of genetic research over recent decades has enabled the discovery of new genetic markers, such as single nucleotide polymorphisms (SNPs). This, as well as the full sequencing of the dog genome, has enabled genome-wide association studies (GWAS) to be used in the search for genetic causes of canine mammary tumours (CMTs).
Genotypic data containing 175,000 SNPs, which had been obtained using the Illumina CanineHD BeadChip microarray technique, were available for analysis in this study. The data concerned 118 bitches, including 36 animals with CMT, representing various breeds and age groups. Statistical analysis was performed in two steps: quality control of genotyping data and genome-wide association analysis based on dominant, recessive, overdominant, codominant, and log-additive models with the single SNP effects.
A total of 40 different SNPs significantly associated with CMT appearance were detected. Moreover, twelve SNPs showed statistical significance in more than one model. Of all the significant SNPs, two, namely in the overdominant model and in the log-additive model, reached the 5 significance level. The other SNPs were significant to a 1 level.
In the group of SNPs indicated as significant in the GWAS analysis, several transpired to be localised within genes that may play an important role in CMT.
近几十年来,基因研究的发展使得新的基因标记得以发现,如单核苷酸多态性(SNP)。这以及犬类基因组的全序列测定,使得全基因组关联研究(GWAS)能够用于寻找犬类乳腺肿瘤(CMT)的遗传病因。
本研究可获得使用Illumina犬类HD BeadChip微阵列技术获得的包含175,000个SNP的基因分型数据。数据涉及118只母犬,包括36只患有CMT的动物,代表了不同品种和年龄组。统计分析分两步进行:基因分型数据的质量控制和基于显性、隐性、超显性、共显性和对数加性模型以及单SNP效应的全基因组关联分析。
共检测到40个与CMT出现显著相关的不同SNP。此外,12个SNP在不止一种模型中显示出统计学意义。在所有显著的SNP中,两个,即在超显性模型中的 和在对数加性模型中的 ,达到了5%的显著水平。其他SNP在1%水平上显著。
在GWAS分析中显示为显著的SNP组中,有几个被发现位于可能在CMT中起重要作用的基因内。