|
Although Nutrialerts posted abstracts about copy number variations last year From NuGO and The Division of Personalized Nutrition and Medicine at the
|
|
About 13% of the human genome may be structural variations, specifically, copy number variations. Two new articles provide a primer for structural variations and a review of functional analyses methods. |
Genomic variation is greater than the sum of all of an individual’s SNPs (see Nutrialerts – SNP Databases and Resources: Reviews). Structural changes in DNA called copy number variations (CNVs) or copy number polymorphisms (CNPs) also produce variation in the genome (see Nutrialerts - Gene Duplications in Genomes ). Current estimates indicate that about 13% of the human genome. Over 11,700 CNVs have been identified which overlap more than 1000 genes. Deletions, insertions (INDELS), duplications, triplications, and translocations can all result in CNVs.
CNVs encompass more total nucleotides and arise more frequently than SNPs . CNVs have been shown to contribute to human evolution, genetic diversity between individuals, and a rapidly increasing number of traits or susceptibility to traits, that is, genomic disorders [3-7].
Methods in Molecular Biology recently published a book on edited volume on Genetic Variation . Two of the articles are particularly useful as an introduction for structural genomics [1, 2]. Although these articles have related titles, the first deals with the biology of CNVs [1] and the second with functional characterization [2] . Current research methodology uses DNA microarrays to analyze CNVs, although these tools do not provide complete analyses since only 1 million of the estimated 25 million SNPs are on the arrays. The table below provides websites for genetic characterizations (see also the SNP Review).
In addition to analyzing SNPs, nutrigenomic researchers must also analyze the many types of structural variations in the genome , each of which may contribute to differences in response to nutrients.
_____________________________________________________________________________
Tools For Genetic Characterization
from [1]
|
Central databases (SNPs and mutations) |
||
|
|
|
|
|
|
dbSNP |
|
|
|
HapMap |
|
|
|
The SNP consortium (TSC) |
|
|
|
|
|
|
Mutation databases |
||
|
|
|
|
|
|
OMIM |
|
|
|
HGMD |
|
|
|
Locus specific mutations |
|
|
|
|
|
|
CNV databases |
||
|
|
|
|
|
|
Db of genomic variants |
|
|
|
Structural variation db |
|
|
|
Decipher |
|
|
|
|
|
|
VNTR databases |
||
|
|
|
|
|
|
Tandem repeats database |
|
|
|
uniSTS |
|
|
|
|
|
|
Linkage disequilibrium visualization and analysis |
||
|
|
|
|
|
|
SNAP |
|
|
|
HaploView |
|
|
|
|
|
|
Gene orientated SNP and mutation visualization |
||
|
|
|
|
|
|
LocusLink |
|
|
|
HUGE navigator |
|
|
|
SNPper |
|
|
|
BrainArray |
|
|
|
Biomart |
|
|
|
|
|
|
Genome orientated SNP and mutation visualization |
||
|
|
|
|
|
|
Ensembl |
|
|
|
UCSC |
|
|
|
Map viewer |
|
|
|
1,000 genomes project |
|
|
|
NHGRI catalog of GWAS |
|
References
1. Barnes MR. Genetic variation analysis for biomedical researchers: a primer. Methods Mol Biol (2010) 628: p. 1-20
2. Barnes MR and Breen G. A short primer on the functional analysis of copy number variation for biomedical scientists. Methods Mol Biol (2010) 628: p. 119-35
3. Bassett AS, Scherer SW, and Brzustowicz LM. Copy Number Variations in Schizophrenia: Critical Review and New Perspectives on Concepts of Genetics and Disease. Am J Psychiatry (2010)
4. Dhawan D and Padh H. Pharmacogenetics: technologies to detect copy number variations. Curr Opin Mol Ther (2009) 11 (6): p. 670-80
5. Fanciulli M, Petretto E, and Aitman TJ. Gene copy number variation and common human disease. Clin Genet (2010) 77 (3): p. 201-13
6. Ku CS, Loy EY, Salim A, Pawitan Y, and Chia KS . The discovery of human genetic variations and their use as disease markers: past, present and future. J Hum Genet (2010)
7. Williams HJ, Owen MJ, and O'Donovan MC. Schizophrenia genetics: new insights from new approaches. Br Med Bull (2009)
_________________________________________________
From NuGO and The Division of Personalized Nutrition and Medicine at the FDA/National Center for Toxicological Research. The contents of the posting do not necessarily reflect the views or policies of the U.S. FDA.
SUBSCRIBE to NUTRIALERT EMAIL
Michael R. Barnes and Gerome Breen (eds.), Genetic Variation: Methods and Protocols, Methods in Molecular Biology, vol. 628 , DOI 10.1007/978-1-60327-367-1_1, © Springer Science + Business Media, LLC 2010
Methods Mol Biol. 2010;628:1 - 20.
Genetic Variation Analysis for Biomedical Researchers: A Primer
Michael R. Barnes
Abstract
Biomedical researchers studying gene function should consider the impact of variation, even if genetics is
not the primary objective of an investigation. Information on genetic variation can provide a valuable
insight into the functional range and critical regions of a gene, protein or regulatory element. Genetic
variants may be diverse in nature, ranging from single nucleotide variants, tandem repeats, small insertions or deletions to large copy number variants. Until recently, information on genetic variation was
quite limited, but now a range of large scale surveys of variation have made plentiful data on common
variation and a picture is beginning to emerge from the driving forces in human evolution and population
diversification. Next-generation sequencing technologies are moving knowledge into a new phase focused on the individual genome and complete disclosure of individual variation, including the rarest of variants. The consequences of these advances in medicine are unresolved, but it is clear that biomedical researchers cannot afford to ignore this information. This review presents a broad overview of the in silico methods that will allow a researcher to quickly review known variation in a gene of interest, providing some pointers for further investigation.
Key words: SNP, CNV, VNTR, INDEL, Polymorphism, Genome, Bioinformatics, Variation,
Mutation
Methods Mol Biol. 2010;628:119-35.
A Short Primer on the Functional Analysis of Copy Number Variation for Biomedical Scientists
Michael R. Barnes and Gerome Breen
Abstract
Recent studies have highlighted the potential prevalence of copy number variation (CNV) in mammalian
genomes, including the human genome. These studies suggest that CNVs may play a potentially important role in human phenotypic diversity and disease susceptibility. Here, we consider some of the in silico challenges of characterizing genomic structural variants. While the phenotypic impact of the vast majority of CNVs is likely to be neutral, some CNVs will clearly impact phenotype. Here, we review some of the key databases hosting CNV data and discuss some of the caveats in the analysis of CNV data. The task is now to translate some of the initial associations between CNVs and disease into causal variants.
Key words: Genome, CNV, Deletion, Duplication, Copy number, Bioinformatics, Variation, CNV