scholarly journals Association analysis of polymorphism in thyroglobulin gene promoter with milk production traits in riverine buffalo (Bubalus bubalis)

Meta Gene ◽  
2015 ◽  
Vol 5 ◽  
pp. 157-161 ◽  
Author(s):  
P.K. Dubey ◽  
S. Goyal ◽  
S.K. Mishra ◽  
A.K. Yadav ◽  
P. Kathiravan ◽  
...  
2012 ◽  
Vol 44 (7) ◽  
pp. 1587-1592 ◽  
Author(s):  
Tushar Tanpure ◽  
Praveen Kumar Dubey ◽  
Kunwar Pal Singh ◽  
Periasamy Kathiravan ◽  
Bishnu Prasad Mishra ◽  
...  

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruike Jia ◽  
Yihan Fu ◽  
Lingna Xu ◽  
Houcheng Li ◽  
Yanhua Li ◽  
...  

Abstract Background Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bβ) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. Results By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle. Conclusions In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified.


2021 ◽  
Vol 923 (1) ◽  
pp. 012040
Author(s):  
Ahmed R. Alkhateeb ◽  
Wafaa Ismail Ibrahim ◽  
Nasr Noori Al-Anbari

Abstract Seventy two adult lactating Iraqi buffaloes (Bubalus bubalis) were chosen randomly from two regions of Iraq, Baghdad (Abu Ghraib Ruminants Researches Station in the west of Baghdad, Iraq) and AL-Muthanna province (Alhilal township), during 2018/2019 lactating season. The effect of location and parity in the body, udder conformation and milk production traits were studied. The body conformation, body weight, udder measurements, and milk production traits were significant to high significant effected by both the location and the parity except there is the non-significant effect of location on body height at the shoulder, front teat diameter, rear teat length and rear teat diameter. Similarly non-significant effect of parity was observed on front teat diameter, rear teat length, distance between front and rear teats, fat%, lactose%, and SNF%.


2017 ◽  
Vol 115 ◽  
pp. 307-309
Author(s):  
P.K. Dubey ◽  
S. Dubey ◽  
S.K. Mishra ◽  
R. Arora ◽  
J. Patel ◽  
...  

2019 ◽  
Vol 50 (3) ◽  
pp. 207-216 ◽  
Author(s):  
C. Du ◽  
T. Deng ◽  
Y. Zhou ◽  
T. Ye ◽  
Z. Zhou ◽  
...  

2017 ◽  
Vol 48 (6) ◽  
pp. 720-721 ◽  
Author(s):  
Tingxian Deng ◽  
Chunying Pang ◽  
Xiaoya Ma ◽  
Anqin Duan ◽  
Shasha Liang ◽  
...  

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