Abstract

Signal transducer and activator of transcription 5A (STAT5A), previously known as mammary gland factor (MGF), belongs to the prolactin/JAK2/STAT5 pathway, and plays an important role in growth and development, milking, and lipid accumulation in mammals. The aim of this study was to identify novel genetic variants of the goat STAT5A gene, as well as to test the possible effects of these variants on body measurement traits in the Xinong Saanen dairy goat (XNSN, milking breed) and the Hainan black goat (HNBG, meat breed) that thrive in Northwest China and Southeast China, respectively, which concurrently need improvement in terms of growth. Three novel single nucleotide polymorphisms (SNPs) (IVS1+254C>T, SNP1; Tyr90Tyr, SNP2; and IVS3+303T>C, SNP3) within the goat STAT5A gene were identified in intron 1, exon 2, and intron 3, respectively, as well as a documented SNP (Pro268Pro, SNP4) was also detected in exon 7. These SNPs were genotyped using the amplification created restriction site-polymerase chain reaction-restriction fragment length polymorphism (aCRS-PCR-RFLP) and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) methods; their minor allelic frequencies varied from 0.079 (SNP4) to 0.372 (SNP2) in the HNBG breed as well as from 0 (SNP1) to 0.362 (SNP4) in the XNSN breed, respectively. The PIC values of these loci varied from 0 to 0.358. Haplotype analysis uncovered only 8 haplotypes; the major haplotypes were Hap1 (CCCC), Hap2 (CCTC), and Hap4 (CTTC). During linkage disequilibrium analysis, only SNP1 and SNP3 loci showed strong linkage (r2=0.999) in the HNBG breed. Statistical analyses indicated that only the known variant (SNP4, Pro268Pro) was significantly associated with body measurement traits in the two breeds when analyzed separately or in combination (P<0.05 or P<0.01), implying that this SNP significantly affected goat body measurement traits. Therefore, the STAT5A gene is a candidate gene affecting goat body measurement traits and could contribute to goat breeding improvement programs through marker-assisted selection (MAS).

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