scholarly journals Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits

2013 ◽  
Vol 12 (11) ◽  
pp. 3398-3408 ◽  
Author(s):  
Amitabh Sharma ◽  
Natali Gulbahce ◽  
Samuel J. Pevzner ◽  
Jörg Menche ◽  
Claes Ladenvall ◽  
...  
2010 ◽  
Vol 16 (5) ◽  
pp. 516-532 ◽  
Author(s):  
F J Bosker ◽  
C A Hartman ◽  
I M Nolte ◽  
B P Prins ◽  
P Terpstra ◽  
...  

Bone ◽  
2009 ◽  
Vol 44 ◽  
pp. S222-S223
Author(s):  
J. Richards ◽  
F.K. Kavvoura ◽  
F. Rivadeneira ◽  
U. Styrkarsdottir ◽  
K. Estrada ◽  
...  

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.


Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 318
Author(s):  
Tae-Ho Ham ◽  
Yebin Kwon ◽  
Yoonjung Lee ◽  
Jisu Choi ◽  
Joohyun Lee

We conducted a genome-wide association study (GWAS) of cold tolerance in a collection of 127 rice accessions, including 57 Korean landraces at the seedling stage. Cold tolerance of rice seedlings was evaluated in a growth chamber under controlled conditions and scored on a 0–9 scale, based on their low-temperature response and subsequent recovery. GWAS, together with principal component analysis (PCA) and kinship matrix analysis, revealed four quantitative trait loci (QTLs) on chromosomes 1, 4, and 5 that explained 16.5% to 18.5% of the variance in cold tolerance. The genomic region underlying the QTL on chromosome four overlapped with a previously reported QTL associated with cold tolerance in rice seedlings. Similarly, one of the QTLs identified on chromosome five overlapped with a previously reported QTL associated with seedling vigor. Subsequent bioinformatic and haplotype analyses revealed three candidate genes affecting cold tolerance within the linkage disequilibrium (LD) block of these QTLs: Os01g0357800, encoding a pentatricopeptide repeat (PPR) domain-containing protein; Os05g0171300, encoding a plastidial ADP-glucose transporter; and Os05g0400200, encoding a retrotransposon protein, Ty1-copia subclass. The detected QTLs and further evaluation of these candidate genes in the future will provide strategies for developing cold-tolerant rice in breeding programs.


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