کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10157372 | 1666459 | 2018 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Integrating RNA-seq and GWAS reveals novel genetic mutations for buffalo reproductive traits
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم دامی و جانورشناسی
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چکیده انگلیسی
Genome-wide association study (GWAS) has been applied in buffalo breeding programs and been used to identify a number of candidate genes associated with buffalo reproductive traits. The genetic code of specific genes underlying buffalo reproductive traits remains unclear. Association study that measures both genetic and transcriptional variation has been applied for the investigation of complex traits. To investigate genes involved in buffalo reproductive traits, integrated RNA-seq results were investigated of buffalo granulosa cells and candidate genes which were reported to be associated with buffalo reproductive traits in a previous GWAS. A large number of variants were detected by RNA-seq, and 214 variants were located within the buffalo reproductive candidate genes identified by GWAS. A further association study in 462 Italian Mediterranean buffalo indicated that 25 SNPs distributed in 13 genes were associated with reproductive traits. Of the 13 genes, 11 were expressed in granulosa cells of all antral follicle development stages, and significant difference was found in the expression of NDUFS2 between follicles of diameter <8âmm and > 8âmm. These findings extend the results of GWAS by expanding the knowledge about new and potentially functional single-nucleotide polymorphisms and provide useful information about regulatory genes affecting buffalo reproductive traits.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Animal Reproduction Science - Volume 197, October 2018, Pages 290-295
Journal: Animal Reproduction Science - Volume 197, October 2018, Pages 290-295
نویسندگان
J. Li, J. Liu, S. Liu, G. Plastow, C. Zhang, Z. Wang, G. Campanile, A. Salzano, B. Gasparrini, G. Hua, A. Liang, L. Yang,