Dataset Information

New insights of CYP1A in endogenous metabolism: a focus on single nucleotide polymorphisms and diseases.

ABSTRACT: Cytochrome P450 1A (CYP1A), one of the major CYP subfamily in humans, not only metabolizes xenobiotics including clinical drugs and pollutants in the environment, but also mediates the biotransformation of important endogenous substances. In particular, some single nucleotide polymorphisms (SNPs) for CYP1A genes may affect the metabolic ability of endogenous substances, leading to some physiological or pathological changes in humans. This review first summarizes the metabolism of endogenous substances by CYP1A, and then introduces the research progress of CYP1A SNPs, especially the research related to human diseases. Finally, the relationship between SNPs and diseases is discussed. In addition, potential animal models for CYP1A gene editing are summarized. In conclusion, CYP1A plays an important role in maintaining the health in the body.

SUBMITTER: Lu J

PROVIDER: S-EPMC6984740 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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New insights of CYP1A in endogenous metabolism: a focus on single nucleotide polymorphisms and diseases.

Lu Jian J Shang Xuyang X Zhong Weiguo W Xu Yuan Y Shi Rong R Wang Xin X

Acta pharmaceutica Sinica. B 20191202 1

Cytochrome P450 1A (CYP1A), one of the major CYP subfamily in humans, not only metabolizes xenobiotics including clinical drugs and pollutants in the environment, but also mediates the biotransformation of important endogenous substances. In particular, some single nucleotide polymorphisms (SNPs) for <i>CYP1A</i> genes may affect the metabolic ability of endogenous substances, leading to some physiological or pathological changes in humans. This review first summarizes the metabolism of endogeno ...[more]

PMID: 31998606

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Project description:BACKGROUND: Studies on the relationship between disease and genetic variations such as single nucleotide polymorphisms (SNPs) are important. Genetic variations can cause disease by influencing important biological regulation processes. Despite the needs for analyzing SNP and disease correlation, most existing databases provide information only on functional variants at specific locations on the genome, or deal with only a few genes associated with disease. There is no combined resource to widely support gene-, SNP-, and disease-related information, and to capture relationships among such data. Therefore, we developed an integrated database-pipeline system for studying SNPs and diseases. RESULTS: To implement the pipeline system for the integrated database, we first unified complicated and redundant disease terms and gene names using the Unified Medical Language System (UMLS) for classification and noun modification, and the HUGO Gene Nomenclature Committee (HGNC) and NCBI gene databases. Next, we collected and integrated representative databases for three categories of information. For genes and proteins, we examined the NCBI mRNA, UniProt, UCSC Table Track and MitoDat databases. For genetic variants we used the dbSNP, JSNP, ALFRED, and HGVbase databases. For disease, we employed OMIM, GAD, and HGMD databases. The database-pipeline system provides a disease thesaurus, including genes and SNPs associated with disease. The search results for these categories are available on the web page http://diseasome.kobic.re.kr/, and a genome browser is also available to highlight findings, as well as to permit the convenient review of potentially deleterious SNPs among genes strongly associated with specific diseases and clinical phenotypes. CONCLUSION: Our system is designed to capture the relationships between SNPs associated with disease and disease-causing genes. The integrated database-pipeline provides a list of candidate genes and SNP markers for evaluation in both epidemiological and molecular biological approaches to diseases-gene association studies. Furthermore, researchers then can decide semi-automatically the data set for association studies while considering the relationships between genetic variation and diseases. The database can also be economical for disease-association studies, as well as to facilitate an understanding of the processes which cause disease. Currently, the database contains 14,674 SNP records and 109,715 gene records associated with human diseases and it is updated at regular intervals.

Project description:Single-nucleotide polymorphisms (SNPs) provide an abundant source of DNA polymorphisms in a number of eukaryotic species. Information on the frequency, nature, and distribution of SNPs in plant genomes is limited. Thus, our objectives were (1) to determine SNP frequency in coding and noncoding soybean (Glycine max L. Merr.) DNA sequence amplified from genomic DNA using PCR primers designed to complete genes, cDNAs, and random genomic sequence; (2) to characterize haplotype variation in these sequences; and (3) to provide initial estimates of linkage disequilibrium (LD) in soybean. Approximately 28.7 kbp of coding sequence, 37.9 kbp of noncoding perigenic DNA, and 9.7 kbp of random noncoding genomic DNA were sequenced in each of 25 diverse soybean genotypes. Over the >76 kbp, mean nucleotide diversity expressed as Watterson's theta was 0.00097. Nucleotide diversity was 0.00053 and 0.00111 in coding and in noncoding perigenic DNA, respectively, lower than estimates in the autogamous model species Arabidopsis thaliana. Haplotype analysis of SNP-containing fragments revealed a deficiency of haplotypes vs. the number that would be anticipated at linkage equilibrium. In 49 fragments with three or more SNPs, five haplotypes were present in one fragment while four or less were present in the remaining 48, thereby supporting the suggestion of relatively limited genetic variation in cultivated soybean. Squared allele-frequency correlations (r(2)) among haplotypes at 54 loci with two or more SNPs indicated low genome-wide LD. The low level of LD and the limited haplotype diversity suggested that the genome of any given soybean accession is a mosaic of three or four haplotypes. To facilitate SNP discovery and the development of a transcript map, subsets of four to six diverse genotypes, whose sequence analysis would permit the discovery of at least 75% of all SNPs present in the 25 genotypes as well as 90% of the common (frequency >0.10) SNPs, were identified.

Dataset Information

New insights of CYP1A in endogenous metabolism: a focus on single nucleotide polymorphisms and diseases.

Publications

New insights of CYP1A in endogenous metabolism: a focus on single nucleotide polymorphisms and diseases.

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