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Association of MAX Copy Number Variation with Morphometric Traits in Chinese Cattle
Shiyi Lv1,2, Boyu Li1,2, Suyun Fan1,2
1Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China.
Abstract:
Copy number variation (CNV) is a major class of genomic structural variation that can shape economically important traits by altering gene dosage and gene expression. MAX (MYC-associated factor X), a core component of the MYC-MAX-MXD1 transcriptional regulatory network, is critically involved in cell proliferation, differentiation, and development. However, the relationship between MAX CNVs and morphometric traits in cattle remains largely unknown. Here, we genotyped MAX CNVs by quantitative real-time PCR (qPCR) in 572 Chinese cattle from five breeds, including Qinchuan (QC), Ji'an (JA), Jinnan (JN), Nanyang (NY), and Xianan (XN) cattle, and evaluated the association of MAX CNVs with morphometric traits. MAX CNVs exhibited distinct breed-specific distribution patterns: the gain type predominated in QC, the loss type predominated in JN, NY, and XN, whereas JA showed a relatively balanced distribution across the three CNV types. Based on raw p values, MAX CNVs showed a nominal association with chest girth in JN cattle and nominal associations with chest girth and hucklebone width in NY cattle (p < 0.05). Individuals with the medium type showed higher least-squares means for the nominally associated traits than those with the loss or gain types. MAX CNVs explained 5.9% of the phenotypic variance in chest girth in JN cattle and 13.6% and 12.2% of the phenotypic variance in chest girth and hucklebone width in NY cattle, respectively. These results suggest that MAX CNVs may represent a breed-specific candidate locus related to morphometric traits in Chinese cattle. However, because no formal multiple-testing correction was applied and this study did not include independent population validation or functional validation, further studies are needed before considering any potential application in marker-assisted selection.
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