Genomewide identification and annotation of SNPs in Bubalus bubalis

Surya, Tarida Marlin; Vineeth, M R; Jayakumar, S.; Tantia, M. S.; Dixit, S. P.; Niranjan, S. K.; Gupta, I. D.

doi:10.1016/j.ygeno.2018.11.021

Cited by 28 publications

(13 citation statements)

References 17 publications

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“…This was additionally confirmed by sequencing ( Figure S3). A lack of polymorphisms in buffalo GHR.E4 was also reported in other studies [4,12].…”

Section: Analysis Of the Detected Snpssupporting

confidence: 84%

“…The sequence for the first three loci was assembled in one combined sequence and was submitted to GenBank (accession number KC107765), that of GHR.E8 (less than 200 bp) is presented in Figure S3. c.348T>C and c.381A>C SNPs [12]. The only shared SNP between Egyptian and Indian buffaloes was the c.387C>T SNP.…”

Section: Analysis Of the Detected Snpsmentioning

confidence: 91%

“…Although several studies have detected QTL and candidate genes related to milk production and composition in cattle, to date, there are nearly no available data on QTLs linked to milk production and composition traits in water buffalo. In their recent genome-wide search for mutations associated with Murrah buffalo economic traits, Surya et al [12] found 483 SNPs in 66 genes affecting milk traits. Among these SNPs, 35 SNPs were found in the GHR locus (NW_005785241.1 from nt 844295 to1151290): 9 in the promotor, 4 in intron2, 13 in intron3, 2 in intron4, 3 in E5, and 4 in inton6).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in this study, we screened coding sequences of E4-E6 and E8 for polymorphisms. These exons were selected due to their polymorphic nature as revealed in previous publications in cattle and buffalo [5,9,12,13].…”

Section: Introductionmentioning

confidence: 99%

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Association of GHR Polymorphisms with Milk Production in Buffaloes

El-Komy

Saleh

Abdel-Hamid

et al. 2020

Animals

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For its role in the mediation of growth hormone (GH) galactopoietic effect, growth hormone receptor (GHR) was considered a functional candidate gene for milk performance in cattle. However, its genetic variation and potential effect have not been investigated in Egyptian buffaloes. This study aimed to screen GHR for polymorphisms and study their associations with milk traits in Egyptian buffaloes. Polymerase chain reaction, single-strand conformation polymorphism, and sequencing were used to identify mutations in 4 exons (E4–E6 and E8) of the GHR gene in 400 Egyptian buffaloes. No polymorphisms were found in E4, while 2 SNPs (c.380G>A/p.Arg127Lys and c.387C>T/p.Gly129) in E5, one silent mutation (c.435A>G/p.Pro145) in E6, and another missense mutation (c.836T>A/p.Phe279Tyr) in E8 were detected. The c.380G>A SNP in the extracellular domain was associated with milk yield, fat %, protein %, and 305-day milk, fat and protein yield, with higher levels in animals carrying the mutant A allele. The c.836T>A SNP in the transmembrane domain was associated with milk yield, fat %, protein %, and 305-day milk, fat and protein yield, with higher milk yield and lower fat %, protein %, fat and protein yield in the mutant A allele-animals. Interestingly, animals with the two mutant AA alleles produced higher milk yield, fat %, protein %, fat and protein yield, accompanied with upregulated expressions of GHR, GH, insulin-like growth factor 1 (IGF1), prolactin (PRL), prolactin receptor (PRLR), β-casein (encoded by CSN2 gene), and diacylglycerol acyltransferase-1 (DGAT1) genes and proteins in milk somatic cells. Therefore, selection of Egyptian buffaloes with mutant AA haplotypes for the novel c.380G>A SNP and the well-known c.836T>A SNP could improve milk yield and quality in buffaloes.

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“…This was additionally confirmed by sequencing ( Figure S3). A lack of polymorphisms in buffalo GHR.E4 was also reported in other studies [4,12].…”

Section: Analysis Of the Detected Snpssupporting

confidence: 84%

Section: Analysis Of the Detected Snpsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Association of GHR Polymorphisms with Milk Production in Buffaloes

El-Komy

Saleh

Abdel-Hamid

et al. 2020

Animals

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“…Higher amount of variations in the intronic regions usually results in more variations in the allele size in the populations which usually gives a higher estimate of genetic diversity. Being a reduced representation approach of the whole genome in which the repetitive sequences are removed, the ddRAD approach has a genome coverage of 9.43% in the present study which is supported by the genome coverage of 13.4-14.8% in buffaloes 20 Table 7. Genetic distance among Indian Yak.…”

Section: Discussionsupporting

confidence: 65%

Genomic divergence reveals unique populations among Indian Yaks

Jayakumar

Vineeth

Surya

et al. 2020

Sci Rep

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The present study focused upon identification of genome-wide SNPs through the reduced representation approach and to study the genomic divergence of the indian yak populations. A total of 80 samples belonging to Arunachali yak (N = 20), Himachali yak (N = 20), Ladakhi yak (N = 20) and Sikkimi yak (N = 20) of India were used in the study. The results of the study revealed a total of 579575 high quality SNPs along with 50319 INDELs in the Indian yaks. The observed heterozygosity was found to be high in Himachali yak, followed by Arunachali yak, Ladakhi yak and Sikkimi yaks. The Sikkimi yaks was found to be genetically distant, followed by Ladakhi yaks which was observed to have some few individuals from Arunachali and Himachali yaks. Arunachali and Himachali yaks are found to get clustered together and are genetically similar. The study provides evidence about the genomic diversity in the indian yak populations and information generated in the present study may help to formulate a suitable breeding plan for endangered Indian yaks. Moreover, the unique yak populations identified in the study will further help to focus attention for future characterization and prioritization of the animals for conservation purposes through the ddRAD approach.

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