Gene-methylation epistatic analyses via the W-test identifies enriched signals of neuronal genes in patients undergoing lipid-control treatment

Sun, Rui; Weng, Haoyi; Men, Ruoting; Xia, Xiaoxuan; Chong, Ka Chun; Wu, William Ka Kei; Zee, Benny; Wang, Maggie Haitian

doi:10.1186/s12919-018-0143-8

Cited by 5 publications

(5 citation statements)

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“…This application was originally reported in Sun et al 2018 [3]. The data set contains 476 diabetic patients undergone lipid control treatments, and 150,000 candidate SNP-CpG pairs within 10kb genome distance ( w i n d o w .…”

Section: Resultsmentioning

confidence: 99%

“…s i z e =10,000). The phenotype is whether or not a subject responded to the treatment, calculated by comparing the before and after treatment triglyceride levels [3]. The h and f are estimated by hf.snps.meth() , and the gene-methylation interactions are calculated by wtest.snps.meth() .…”

Section: Resultsmentioning

confidence: 99%

“…We also use a novel triangular network diagram to display interaction effects up to the third order. Extensive simulation studies testing the power and type I error of the W-test can be found in Wang, Sun et al (2016) [2] and Sun et al (2017) [3].…”

Section: Methodsmentioning

confidence: 99%

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wtest: an integrated R package for genetic epistasis testing

et al. 2019

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BackgroundWith the increasing amount of high-throughput genomic sequencing data, there is a growing demand for a robust and flexible tool to perform interaction analysis. The identification of SNP-SNP, SNP-CpG, and higher order interactions helps explain the genetic etiology of human diseases, yet genome-wide analysis for interactions has been very challenging, due to the computational burden and a lack of statistical power in most datasets.ResultsThe wtest R package performs association testing for main effects, pairwise and high order interactions in genome-wide association study data, and cis-regulation of SNP and CpG sites in genome-wide and epigenome-wide data. The software includes a number of post-test diagnostic and analysis functions and offers an integrated toolset for genetic epistasis testing.ConclusionsThe wtest is an efficient and powerful statistical tool for integrated genetic epistasis testing. The package is available in CRAN: https://CRAN.R-project.org/package=wtest.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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wtest: an integrated R package for genetic epistasis testing

et al. 2019

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“…In all brain regions studied, the levels of NAV2 observed in late gestation and early postnatal life were the highest [27]. It was reported that NAV2 was associated with hyperlipidemia [29]. The glycoprotein MUC15 was initially isolated from the bovine milk fat globule membrane, and had potential physiological function in signal transduction [30].…”

Section: Discussionmentioning

confidence: 97%

Identification of SNPs and Candidate Genes for Milk Produce Ability in Yorkshire Pig

Shi

Liu

et al. 2021

Preprint

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Background: Sow milk produce ability is an important limiting factor impacting suboptimal growth and survival of piglets. By pig genetic improvement, the litter size has been increased, and larger litters need more suckled mammary glands, that results in increased milk from lactating sow. Hence, it has much significance to explore the sow lactation performance. The aim of this study was to estimate genetic parameters and screen single nucleotide polymorphisms (SNPs) for milk produce ability trait in 985 Yorkshire pigs by a genome-wide association study (GWAS), and to further identify the candidate genes.Results: By ASReml, we estimated the heritability of sow milk produce ability: 0.18 ± 0.07. With the Fixed and random effect model Circulating Probability Unification (FarmCPU), we performed a GWAS, and detected seven genome-wide significant SNPs, namely, Sus scrofa Chromosome (SSC) 2: ASGA0010040 (P = 7.73E-11); SSC2:MARC0029355 (P = 1.30E-08), SSC6: WU_10.2_6_65751151 (P = 1.32E-10), SSC7: MARC0058875 (P = 4.99E-09), SSC10: WU_10.2_10_49571394 (P = 6.79E-08), SSC11: M1GA0014659 (P = 1.19E-07), and SSC15: MARC0042106 (P = 1.16E-07). We performed the distribution of phenotypes corresponding to genotypes of the seven SNPs, and showed that ASGA0010040, MARC0029355, MARC0058875, WU_10.2_10_49571394, M1GA0014659, and MARC0042106 have extreme phenotypic values corresponded to the homozygous genotypes, while the intermediate values corresponded to the heterozygous genotypes. Further, we screened for flanking regions ± 200 kb nearby seven significant SNPs, and identified 30 genes. Among of them, 24 as the candidates were involved in lactose metabolism, colostrum immunity, milk protein, and milk fat by the gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis. Through the combined analysis between 24 candidate genes and differently expressed genes (DEGs) detected in transcriptome data (GSE101983), we found 11 commons (NAV2, ANO3, MUC15, DISP3, FBXO6, CLCN6, SLA-DQB1, PSMB8, PSMB9, TAP1, and KIF5C). Further, by comparing the chromosome positions of the candidate genes with the quantitative trait locus (QTLs) previously reported, a total of 13 genes were found to be within 0.86 Mb to 93.92 Mb of the reported QTLs for sow milk yield, in which, NAV2 was found to be located with 0.86 Mb of the QTL region ssc2: 40936355.Conclusions: In conclusion, we identified seven significant SNPs located on SSC2, 6, 7, 10, 11, and 15, and proposed 24 candidate genes for milk produce ability trait in Yorkshire pig. Among of them, 11 were the key candidates. These results contribute to the identification of variants and candidate genes for sow milk produce ability.

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“…Studies reported that MTHFR was an important candidate gene for sheep milk yield traits ( Hou et al, 2015 ; An et al, 2016 ). NPPB and BTNL2 were involved in PI3K/AKT, Ca 2+ , K + , ATP, and immunity ( Fioretti et al, 2004 ; Dolovcak et al, 2009 ; Sun et al, 2018b ; Zhao et al, 2020 ). KIAA2013 was related to DNA methylation levels of newborns ( Yeung et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of SNPs and Candidate Genes for Milk Production Ability in Yorkshire Pigs

et al. 2021

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Sow milk production ability is an important limiting factor impacting suboptimal growth and the survival of piglets. Through pig genetic improvement, litter sizes have been increased. Larger litters need more suckling mammary glands, which results in increased milk from the lactating sow. Hence, there is much significance to exploring sow lactation performance. For milk production ability, it is not practical to directly measure the milk yield, we used litter weight gain (LWG) throughout sow lactation as an indicator. In this study, we estimated the heritability of LWG, namely, 0.18 ± 0.07. We then performed a GWAS, and detected seven significant SNPs, namely, Sus scrofa Chromosome (SSC) 2: ASGA0010040 (p = 7.73E-11); SSC2:MARC0029355 (p = 1.30E-08), SSC6: WU_10.2_6_65751151 (p = 1.32E-10), SSC7: MARC0058875 (p = 4.99E-09), SSC10: WU_10.2_10_49571394 (p = 6.79E-08), SSC11: M1GA0014659 (p = 1.19E-07), and SSC15: MARC0042106 (p = 1.16E-07). We performed the distribution of phenotypes corresponding to the genotypes of seven significant SNPs and showed that ASGA0010040, MARC0029355, MARC0058875, WU_10.2_10_49571394, M1GA0014659, and MARC0042106 had extreme phenotypic values that corresponded to the homozygous genotypes, while the intermediate values corresponded to the heterozygous genotypes. We screened for flanking regions ± 200 kb nearby the seven significant SNPs, and identified 38 genes in total. Among them, 28 of the candidates were involved in lactose metabolism, colostrum immunity, milk protein, and milk fat by functional enrichment analysis. Through the combined analysis between 28 candidate genes and transcriptome data of the sow mammary gland, we found nine commons (ANO3, MUC15, DISP3, FBXO6, CLCN6, HLA-DRA, SLA-DRB1, SLA-DQB1, and SLA-DQA1). Furthermore, by comparing the chromosome positions of the candidate genes with the quantitative trait locus (QTLs) as previously reported, a total of 17 genes were found to be within 0.86–94.02 Mb of the reported QTLs for sow milk production ability, in which, NAV2 was found to be located with 0.86 Mb of the QTL region ssc2: 40936355. In conclusion, we identified seven significant SNPs located on SSC2, 6, 7, 10, 11, and 15, and propose 28 candidate genes for the ability to produce milk in Yorkshire pigs, 10 of which were key candidates.

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Gene-methylation epistatic analyses via the W-test identifies enriched signals of neuronal genes in patients undergoing lipid-control treatment

Cited by 5 publications

References 26 publications

wtest: an integrated R package for genetic epistasis testing

wtest: an integrated R package for genetic epistasis testing

Identification of SNPs and Candidate Genes for Milk Produce Ability in Yorkshire Pig

Identification of SNPs and Candidate Genes for Milk Production Ability in Yorkshire Pigs

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