Gene-Set Enrichment Analysis for Identifying Genes and Biological Activities Associated with Growth Traits in Dromedaries

Growth is an important heritable economic trait for dromedaries and necessary for planning a successful breeding program. Until now, genome-wide association studies (GWAS) and QTL-mapping have identified significant single nucleotide polymorphisms (SNPs) associated with growth in domestic animals, but in dromedaries, the number of studies is very low. This project aimed to find biological themes affecting growth in dromedaries. In the first step, 99 candidate SNPs were chosen from a previously established set of SNPs associated with body weight, gain, and birth weight in Iranian dromedaries. Next, 0.5 kb upstream and downstream of each candidate SNP were selected from NCBI (assembly accession: GCA_000803125.3). The annotation of fragments with candidate SNPs regarding the reference genome was retrieved using the Blast2GO tool. Candidate SNPs associated with growth were mapped to 22 genes, and 25 significant biological themes were identified to be related to growth in dromedaries. The main biological functions included calcium ion binding, protein binding, DNA-binding transcription factor activity, protein kinase activity, tropomyosin binding, myosin complex, actin-binding, ATP binding, receptor signaling pathway via JAK-STAT, and cytokine activity. EFCAB5, MTIF2, MYO3A, TBX15, IFNL3, PREX1, and TMOD3 genes are candidates for improving growth in camel breeding programs.

An integrated genome and phenome-wide association study approach to understanding Alzheimer's disease predisposition

Background: Genome-wide association studies (GWAS) have identified common, heritable alleles that increase late-onset Alzheimer's disease (LOAD) risk. We recently published an analytic approach to integrate GWAS and phenome-wide association study (PheWAS) data, enabling identification of candidate traits and trait-associated variants impacting disease risk, and apply it here to LOAD. Methods: PheWAS was performed for 23 known LOAD-associated single nucleotide polymorphisms (SNPs) and 4:1 matched control SNPs using UK Biobank data. Traits enriched for association with LOAD SNPs were ascertained and used to identify trait-associated candidate SNPs to be tested for association with LOAD risk (17,008 cases; 37,154 controls). Results: LOAD-associated SNPs were significantly enriched for associations with 6/778 queried traits, including three platelet traits. The strongest enrichment was for platelet distribution width (PDW) (P=1.2x10-5), but no consistent direction of effect was observed between increased PDW and LOAD susceptibility across variants or in Mendelian randomization analysis. Of 384 PDW-associated SNPs identified by prior GWAS, 36 were nominally associated with LOAD risk and 5 survived false-discovery rate correction for multiple testing. Associations confirmed known LOAD risk loci near PICALM, CD2AP, SPI1, and NDUFAF6, and identified a novel risk locus in the epidermal growth factor receptor (EGFR) gene. Conclusions: Through integration of GWAS and PheWAS data, we identify substantial pleiotropy between genetic determinants of LOAD and of platelet morphology, and for the first time implicate EGFR - a mediator of Beta amyloid toxicity - in Alzheimer's disease susceptibility.

3DFAACTS-SNP: Using Regulatory T Cell-specific Epigenomics Data to Uncover Candidate Mechanisms of Type-1 Diabetes (T1D) risk

BackgroundGenome-wide association studies (GWAS) have enabled the discovery of single nucleotide polymorphisms (SNPs) that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the identified variants lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression. To address this problem, we developed a variant filtering workflow called 3DFAACTS-SNP to link genetic variants to target genes in a cell specific manner. Here we use 3DFAACTS-SNP to identify candidate SNPs and target genes associated with the loss of immune tolerance in regulatory T cells (Treg) in T1D. ResultsUsing 3DFAACTS-SNP we identified from a list of 1,228 previously fine-mapped variants, 36 SNPs with plausible Treg-specific mechanisms of action. The integration of cell-type specific chromosome conformation capture data in 3DFAACTS-SNP, identified 119 regulatory regions and 51 candidate target genes that interact with these variant-containing regions in Treg cells. We further demonstrated the utility of the workflow by applying it to three other SNP autoimmune datasets, identifying 17 Treg-centric candidate variants and 35 interacting genes. Finally, we demonstrate the broad utility of 3DFAACTS-SNP for functional annotation of all known common (>10% allele frequency) variants from the Genome Aggregation Database (gnomAD). We identified 7,900 candidate variants and 3,245 candidate target genes, generating a list of potential sites for future T1D or autoimmune research. ConclusionsWe demonstrate that it is possible to further prioritise variants that contribute to T1D based on regulatory function and illustrate the power of using cell type specific multi-omics datasets to determine disease mechanisms. Our workflow can be customised to any cell type for which the individual datasets for functional annotation have been generated, giving broad applicability and utility.

Detection of Novel Variations Related to Litter Size in BMP15 Gene of Luzhong Mutton Sheep (Ovis aries)

Litter size is an important economic trait in the mutton sheep industry. BMP15 is one of the key candidate genes for litter size in sheep. In this study, the entire ORF region of BMP15 was sequenced in 154 Luzhong mutton ewes, and the novel variations were determined. The association between polymorphism in BMP15 and litter size was analyzed using a general linear model. Six out of a total of thirteen variations were identified to be novel. Association analysis indicated that four (SNPs ENSOART00000010201.1:c.352+342C>A, c.352+1232T>C, c.352+1165A>G and c.353-2036T>A) were significantly associated with litter size. The joint analysis among three major genes (BMP15, BMPR1B and GDF9) exhibited significant interaction effects in three combinations (FecB and c.352+1232T>C of BMP15; FecB and c.352+1165A>G of BMP15; c.352+342C>A of BMP15 and ENSOART00000014382.1:c.994G>A of GDF9). For the SNPs c.352+1232T>C and c.352+342C>A, the global distribution of allele frequencies showed that the highest variation frequency occurs in Western Europe. In conclusion, the results demonstrated that BMP15 is a major gene for litter size in Luzhong mutton sheep and candidate SNPs associated with litter size were identified.

Integrated Genomic, Transcriptomic and Proteomic Analysis for Identifying Markers of Alzheimer’s Disease

There is an urgent need to identify biomarkers for Alzheimer’s disease (AD), but the identification of reliable blood-based biomarkers has proven to be much more difficult than initially expected. The current availability of high-throughput multi-omics data opens new possibilities in this titanic task. Candidate Single Nucleotide Polymorphisms (SNPs) from large, genome-wide association studies (GWAS), meta-analyses exploring AD (case-control design), and quantitative measures for cortical structure and general cognitive performance were selected. The Genotype-Tissue Expression (GTEx) database was used for identifying expression quantitative trait loci (eQTls) among candidate SNPs. Genes significantly regulated by candidate SNPs were investigated for differential expression in AD cases versus controls in the brain and plasma, both at the mRNA and protein level. This approach allowed us to identify candidate susceptibility factors and biomarkers of AD, facing experimental validation with more evidence than with genetics alone.

Identification of ATP2B4 regulatory element containing functional genetic variants associated with severe malaria

Genome-wide association studies (GWAS) for severe malaria have identified 30 genetic variants that are mostly located in non-coding regions, with only a few associations replicated in independent populations. In this study, we aimed at identifying potential causal genetic variants located in these loci and demonstrate their functional activity. We systematically investigated the regulatory effect of the SNPs in linkage disequilibrium with the tagSNPs associated with severe malaria in several populations. Annotating and prioritizing genetic variants led to the identification of a regulatory region containing 5 ATP2B4 SNPs in linkage disequilibrium with the tagSNP rs10900585. We confirmed the association of rs10900585 and also found significant associations of severe malaria with our candidate SNPs (rs11240734, rs1541252, rs1541253, rs1541254, and rs1541255) in a Senegalese population. Then, we showed that this region had both promoter and enhancer activities and that both individual SNPs and the combination of SNPs had regulatory effects using luciferase reporter assays. Moreover, CRISPR/Cas9-mediated deletion of this region decreased ATP2B4 transcript and protein levels and increased Ca2+ intracellular concentration in the K562 cell line. Taken together, our data show that severe malaria-associated genetic variants alter the activity of a promoter with enhancer function. We showed that this regulatory element controls the expression of ATP2B4 that encodes a plasma membrane calcium-transporting ATPase 4 (PMCA4), which is the major calcium pump on red blood cells. Altering the activity of this regulatory element affects the risk of severe malaria probably through calcium concentration effect on parasitaemia.

Competitive endogenous RNA network and pathway-based analysis of LncRNA single-nucleotide polymorphism in myasthenia gravis

Myasthenia gravis (MG) is a complex neurological autoimmune disease with a pathogenetic mechanism that has yet to be elucidated. Emerging evidence has revealed that genes, non-coding RNAs and genetic variants play significant roles in the pathogenesis of MG. However, the molecular mechanisms of single nucleotide polymorphisms (SNPs) located on lncRNAs could disturb lncRNA-mediated ceRNA regulatory functions still unclear in MG. In this study, we collated 276 experimentally confirmed MG risk genes and 192 MG risk miRNAs. We then constructed a lncRNA-mediated ceRNA network for MG based on multi-step computational strategies. Next, we systematically integrated risk pathways and identified candidate SNPs in lncRNAs for MG based on data acquired from public databases. In addition, we constructed a pathway-based lncRNA-SNP mediated network (LSPN) that contained 128 lncRNAs targeting 8 MG risk pathways. By analyzing network, we propose a latent mechanism for how the “lncRNA-SNP-mRNA-pathway” axis affects the pathogenesis of MG. Moreover, 25 lncRNAs and 51 SNPs on lncRNAs were extracted from the “lncRNA-SNP-mRNA-pathway” axis. Finally, functional analyses demonstrated lncRNA-SNPs mediated ceRNA regulation pairs associated with MG participated in the MAPK signaling pathway. In summary, we constructed MG-specific lncRNA-SNPs mediated ceRNA regulatory networks based on pathway in the present study, which was helpful to elucidate the roles of lncRNA-SNPs in the pathogenesis of MG and provide novel insights into mechanism of lncRNA-SNPs as potential genetic risk biomarkers of MG.

Genetic Variability of Methane Production and Concentration Measured in the Breath of Polish Holstein-Friesian Cattle

The genetic architecture of methane (CH4) production remains largely unknown. We aimed to estimate its heritability and to perform genome-wide association studies (GWAS) for the identification of candidate genes associated with two phenotypes: CH4 in parts per million/day (CH4 ppm/d) and CH4 in grams/day (CH4 g/d). We studied 483 Polish Holstein-Friesian cows kept on two commercial farms in Poland. Measurements of CH4 and carbon dioxide (CO2) concentrations exhaled by cows during milking were obtained using gas analyzers installed in the automated milking system on the farms. Genomic analyses were performed using a single-step BLUP approach. The percentage of genetic variance explained by SNPs was calculated for each SNP separately and then for the windows of neighbouring SNPs. The heritability of CH4 ppm/d ranged from 0 to 0.14, with an average of 0.085. The heritability of CH4 g/d ranged from 0.13 to 0.26, with an average of 0.22. The GWAS detected potential candidate SNPs on BTA 14 which explained ~0.9% of genetic variance for CH4 ppm/d and ~1% of genetic variance for CH4 g/d. All identified SNPs were located in the TRPS1 gene. We showed that methane traits are partially controlled by genes; however, the detected SNPs explained only a small part of genetic variation—implying that both CH4 ppm/d and CH4 g/d are highly polygenic traits.

CTNNA3 genetic polymorphism may be a new genetic signal of type 2 diabetes in the Chinese Han population: a case control study

Background Type 2 Diabetes (T2D) is the result of a combination of genes and environment. The identified genetic loci can only explain part of T2D risk. Our study is aimed to explore the association between CTNNA3 single nucleotide polymorphisms (SNPs) and T2D risk. Methods We conducted a 'case–control' study among 1002 Chinese Han participants. Four candidate SNPs of CTNNA3 were selected (rs10822745 C/T, rs7920624 A/T, rs2441727 A/G, rs7914287 A/G), and logistic regression analysis was used to evaluate the association between candidate SNPs and T2D risk. We used single factor analysis of variance to analyze the differences of clinical characteristics among different genotypes. In this study, haplotype analysis was conducted by plink1.07 and Haploview software and linkage disequilibrium (LD) was calculated. The interaction of candidate SNPs in T2D risk was evaluated by multi-factor dimensionality reduction (MDR). Finally, we conducted a false-positive report probability (FPRP) analysis to detect whether the significant findings were just chance or noteworthy observations. Results The results showed that CTNNA3-rs7914287 was a risk factor for T2D (‘T’: OR = 1.33, p = 0.003; ‘TT’: OR = 2.21, p = 0.001; ‘TT’ (recessive): OR = 2.09, p = 0.001; Log-additive: OR = 1.34, p = 0.003). The results of subgroup analysis showed that rs7914287 was significantly associated with the increased risk of T2D among participants who were older than 60 years, males, smoking, drinking, or BMI > 24. We also found that rs2441727 was associated with reducing the T2D risk among participants who were older than 60 years, smoking, or drinking. In addition, rs7914287 was associated with T2D patients with no retinal degeneration; rs10822745 and rs7920624 were associated with the course of T2D patients. High density lipoprotein levels had significant differences under different genotypes of rs10822745. Under the different genotypes of rs7914287, the levels of aspartate aminotransferase, alanine aminotransferase and gamma-glutamyltransferase were also significantly different. Conclusion We found that CTNNA3 genetic polymorphisms can be used as a new genetic signal of T2D risk in Chinese Han population. Especially, CTNNA3-rs7914287 showed an outstanding and significant association with T2D risk in both overall analysis and subgroup analysis.

Relationship of Cytochrome P450 Gene Polymorphisms With Blood Concentration of Hydroxychloroquine and Its Metabolites and Adverse Drug Reactions

Background: Hydroxychloroquine (HCQ) is a cornerstone therapy for systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). This study aimed to investigate the relationship of cytochrome P450 (CYP450) gene polymorphisms with blood concentration of HCQ and its metabolites and adverse drug reactions (ADRs) in patients with SLE and RA. Methods: A cohort of 146 patients with SLE and RA treated with HCQ was reviewed. The ADRs of patients were recorded. The blood concentration of HCQ and its metabolites were measured by liquid chromatography–mass spectrometry analysis. Genotyping of single nucleotide polymorphism (SNP) in CYP450 metabolic enzyme involved in HCQ metabolic pathway was performed using a MassARRAY system. Chi-square test, T-test, and one-way analysis of variance were used to analyze data. Results: Among 29 candidate SNPs, we found that CYP3A4 (rs3735451) was significantly associated with blood levels of HCQ and its metabolites in unadjusted model and adjusted model (patients taking HCQ for >10 years) (P<0.05). For CYP3A5 (rs776746), skin and mucous membrane ADRs associated with the TT genotype were a greater risk than for the CT+CC genotypes (P=0.033). For CYP2C8 (rs1058932), abnormal renal function with the AG genotype carried a greater risk than with the AA+GG genotype (P=0.017); for rs10882526, ophthalmic ADRs of the GG genotype carried a greater risk than for the AA+AG genotypes (P=0.026). Conclusions: The CYP2C8 (rs1058932 and rs10882526) and CYP3A5 (rs776746) polymorphisms are likely involved in the ADRs of HCQ. Gene polymorphism analysis of CYP450 and therapeutic drug monitoring of HCQ and its metabolites might be useful to optimize HCQ administration and predict ADRs.