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“Omics”
Published in Kirk A. Phillips, Dirk P. Yamamoto, LeeAnn Racz, Total Exposure Health, 2020
A mosaic of several individuals is represented in the Genome Reference Consortium’s (GRC) human reference genome version GRCh38. Several large genome sequencing projects have captured a large amount of the variability, and GRCH38 has 261 alternate scaffolds to account for the “benign” variability in ethnically diverse populations. It is estimated that unrelated individuals would differ at ~15 million positions and carry as many as 2,000 structural variations like copy number variations (duplications and deletions) and genome rearrangements like inversions and translocations. Based on a genome size of 3.2 billion nucleotides, it can be expected that each human may have ~3 million nucleotide differences from the reference genome (1 every 300 base pair (bp)). Thus, variants (alleles) have to be contextualized and could be benign or associated with a phenotype or disease or yet to be determined significance (Jackson et al. 2018). Allelic variants are referred as single nucleotide variants (SNVs), and when present in >1% of the population are called polymorphisms (SNP). About 11 million SNPs in the human genome have been cataloged with any one individual carrying about 3 million of them (Chong et al. 2015). Currently, about 4,100 mutations linked to a phenotype have been documented; their current count and statistical breakdown of the spectrum of phenotypes associated with the genes can be found at (https://www.omim.org/statistics/geneMap).
Bioinformatics and Applications in Biotechnology
Published in Ram Chandra, R.C. Sobti, Microbes for Sustainable Development and Bioremediation, 2019
SNP is a single nucleotide DNA variation on the genomes of different members of a species and occurring ay specific positions. They occur due to substitutions, deletions, and insertions and give a fundamental insight into allelic variations and individual, ethnic predispositions. A major effort is being made to correlate the SNP variations and their contributions to disease and health in different individuals. The international HapMap project aims to develop a halotype map of human genome to find genetic variations responsible for disease, response to drugs, environmental factor, etc. In phase III of the project, 11 global ancestry groups have been assembled: ASW (African ancestry in Southwest USA); CEU (Utah residents with Northern and Western European ancestry from the CEPH collection); CHB (Han Chinese in Beijing, China); CHD (Chinese in Metropolitan Denver, Colorado); GIH (Gujarati Indians in Houston, Texas); JPT (Japanese in Tokyo, Japan); LWK (Luhya in Webuye, Kenya); MEX (Mexican ancestry in Los Angeles, California); MKK (Maasai in Kinyawa, Kenya); TSI (Tuscans in Italy); YRI (Yoruba in Ibadan, Nigeria) (Altshuler et al., 2010). We have also undertaken a study on genetic variations in Arg5Pro and Leu6Pro, which modulate the structure and activity of GPX1 and increase genetic risk for vitiligo (Mansuri et al., 2016). Bioinformatics tools of sequence alignment, modeling, etc. were extensively used in this study.
Graphical Models in Genetics, Genomics, and Metagenomics
Published in Marloes Maathuis, Mathias Drton, Steffen Lauritzen, Martin Wainwright, Handbook of Graphical Models, 2018
Genome-wide association studies (GWAS) attempt to identify commonly occurring genetic variants that contribute to disease risk, and so far have identified thousands of SNPs that are associated with many human traits [5]. In its simplest form, GWAS analysis is formulated as a sequence of logistic regressions where the disease status from all individuals serve as the response and each genotyped SNP is the covariate. The resulting p-value for each SNP is then corrected for multiple comparisons using e.g. the Bonferroni adjustment. Although this standard approach has the power of identifying common SNPs with strong effects on phenotypes, it ignores the possible synergistic effects of genetic variants on disease phenotypes. Therefore network-assisted methods have been proposed to prioritize the GWASresults and to identify subnetwork of genes that are associated with phenotypes. The rationale of such network-based methods is that topologically related genetic variants are more likely to produce similar phenotypic effects.
The polymorphisms in cGAS-STING pathway are associated with mitochondrial DNA copy number in coke oven workers
Published in International Journal of Environmental Health Research, 2022
Xiaohua Liu, Xinling Li, Wan Wei, Yahui Fan, Zhifeng Guo, Xiaoran Duan, Xiaoshan Zhou, Yongli Yang, Wei Wang
Since mitochondrial DNA (mtDNA) has a high copy number and lacks repairing mechanisms, the mtDNAcn is a sensitive genotoxic stress sentinel upon PAHs exposure. It has been shown that PAHs exposure could lead to mitochondria dysfunction (Wang et al. 2018; Lindberg and Di Giulio 2019) decrease the mitochondrial membrane potential (Ling et al. 2017), and affect mitophagy (Das et al. 2017). When the mitochondrial permeability transition pore changes or apoptosis occur, mtDNA can be released or extruded into the cytoplasm from mitochondria (Garcia and Chavez 2007; McArthur et al. 2018; Riley et al. 2018). The cyclic GMP-AMP synthase (cGAS) is able to recognize and bind to the released mtDNA, then activates the cGAS-stimulator of interferon genes (STING) pathway resulting in interferon stimulated gene (ISG) expression, ultimately promoting innate immunity and influencing nuclear DNA repair (Wu et al. 2019). The mechanisms of mitochondrial DNA replication are complex which regulated by nuclear genes and mitochondrial DNA (Al-Kafaji et al. 2018). Hence, STING and cGAS genes are likely involved in the maintenance of mtDNAcn through DNA damage repair or cell cycle change. Single nucleotide polymorphism (SNP) is the single base variation in genes, which could change the gene expression or the protein function. Our previous studies have shown that polymorphisms in cGAS-STING genes influence telomere shortening in coke oven workers (Duan et al. 2020). However, whether the polymorphisms in cGAS-STING genes are associated with mtDNAcn in coke oven workers remains unknown.
The association between polymorphisms in miRNA and the cholinesterase activity of workers in an omethoate-exposed environment
Published in International Journal of Environmental Health Research, 2022
Kaili Zou, Xiaoshan Zhou, Wei Wang, Liuhua Shi, Xiaoli Fu
Single nucleotide polymorphisms (SNPs) are the most common type of human genetic variation and contribute to differences in human phenotypes. SNPs are DNA sequence polymorphism caused by the transition, transversion, insertion, or deletion of a single base at the level of the genome. Evidence has shown that SNPs in miRNAs may potentially alter multiple biological processes through affecting the process and/or selection of miRNA’s target (Duan et al. 2007). A growing body of studies has also shown that SNPs in miRNA genes could potentially affect the risk of human diseases through regulating expression of miRNA or its target genes (Di Leva et al. 2014; Mullany et al. 2015). The results of our previous studies suggest that the TERT rs2736098 and P21 rs1801270 polymorphism loci are related to a decrease of ChE activity in omethoate-exposed workers (Ding et al. 2018; Duan et al. 2018). In an omethoate-exposed environment, the role of miRNAs polymorphisms in cholinesterase activity of the exposed workers is still unknown.
Discovery of genetic risk factors for disease
Published in Journal of the Royal Society of New Zealand, 2018
Polygenic risk scores (PRS) can be calculated by estimating the effect size from multiple disease associated SNPs in a discovery sample and using those estimated effects in an independent sample (Visscher et al. 2017). As discussed above, individual genetic factors have relatively small effects on disease, and disease risk for individual patients cannot be predicted from PRS. Risk scores can be applied to identify groups with the lowest and highest risk, for estimating genetic effects on disease subtypes and to compare risk across different diseases (Visscher et al. 2017). We used PRS to demonstrate higher genetic risk for endometriosis patients with severe compared with minimal/mild disease (Painter et al. 2011). Studies using PRS are also useful when there are problems with ascertainment such as potential common diagnosis in studies of endometriosis and ovarian cancer. We conducted PRS studies in samples ascertained independently for endometriosis and ovarian cancer to overcome issues of coincidental diagnosis of endometriosis at the time of surgery. Our PRS studies show there is shared genetic risk between endometriosis and ovarian cancer supporting evidence from epidemiological studies (Lu et al. 2015).