Dataset Information

Microsatellites used in forensics are located in regions unusually rich in trait-associated variants.

ABSTRACT: The 20 short tandem repeat (STR) markers of the combined DNA index system (CODIS) are the basis of the vast majority of forensic genetics in the United States. One argument for permissive rules about the collection of CODIS genotypes is that the CODIS markers are thought to contain information relevant to identification only (such as a human fingerprint would), with little information about ancestry or traits. However, in the past 20 years, a quickly growing field has identified hundreds of thousands of genotype-trait associations. Here we conduct a survey of the landscape of such associations surrounding the CODIS loci as compared with non-CODIS STRs. We find that the regions around the CODIS markers are enriched for both known pathogenic variants (>90th percentile) and for SNPs identified as trait-associated in genome-wide association studies (GWAS) (≥95th percentile in 10kb and 100kb flanking regions), compared with other random sets of autosomal tetranucleotide-repeat STRs. Although it is not obvious how much phenotypic information CODIS would need to convey to strain the "DNA fingerprint" analogy, the CODIS markers, considered as a set, are in regions unusually dense with variants with known phenotypic associations.

SUBMITTER: Link V

PROVIDER: S-EPMC10028909 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microsatellites used in forensics are located in regions unusually rich in trait-associated variants.

Link Vivian V Zavaleta Yuómi Jhony A YJA Reyes Rochelle-Jan RJ Ding Linda L Wang Judy J Rohlfs Rori V RV Edge Michael D MD

bioRxiv : the preprint server for biology 20230309

The 20 short tandem repeat (STR) markers of the combined DNA index system (CODIS) are the basis of the vast majority of forensic genetics in the United States. One argument for permissive rules about the collection of CODIS genotypes is that the CODIS markers are thought to contain information relevant to identification only (such as a human fingerprint would), with little information about ancestry or traits. However, in the past 20 years, a quickly growing field has identified hundreds of thou ...[more]

PMID: 36945578

Similar Datasets

Project description:BACKGROUND: In livestock, as in humans, the number of genetic variants that can be tested for association with complex quantitative traits, or used in genomic predictions, is increasing exponentially as whole genome sequencing becomes more common. The power to identify variants associated with traits, particularly those of small effects, could be increased if certain regions of the genome were known a priori to be enriched for associations. Here, we investigate whether twelve genomic annotation classes were enriched or depleted for significant associations in genome wide association studies for complex traits in beef and dairy cattle. We also describe a variance component approach to determine the proportion of genetic variance captured by each annotation class. RESULTS: P-values from large GWAS using 700K SNP in both dairy and beef cattle were available for 11 and 10 traits respectively. We found significant enrichment for trait associated variants (SNP significant in the GWAS) in the missense class along with regions 5 kilobases upstream and downstream of coding genes. We found that the non-coding conserved regions (across mammals) were not enriched for trait associated variants. The results from the enrichment or depletion analysis were not in complete agreement with the results from variance component analysis, where the missense and synonymous classes gave the greatest increase in variance explained, while the upstream and downstream classes showed a more modest increase in the variance explained. CONCLUSION: Our results indicate that functional annotations could assist in prioritization of variants to a subset more likely to be associated with complex traits; including missense variants, and upstream and downstream regions. The differences in two sets of results (GWAS enrichment depletion versus variance component approaches) might be explained by the fact that the variance component approach has greater power to capture the cumulative effect of mutations of small effect, while the enrichment or depletion approach only captures the variants that are significant in GWAS, which is restricted to a limited number of common variants of moderate effects.

Project description:BackgroundGenome-wide association studies have identified thousands of SNP variants associated with hundreds of phenotypes. For most associations the causal variants and the molecular mechanisms underlying pathogenesis remain unknown. Exploration of the underlying functional annotations of trait-associated loci has thrown some light on their potential roles in pathogenesis. However, there are some shortcomings of the methods used to date, which may undermine efforts to prioritize variants for further analyses. Here, we introduce and apply novel methods to rigorously identify annotation classes showing enrichment or depletion of trait-associated variants taking into account the underlying associations due to co-location of different functional annotations and linkage disequilibrium.ResultsWe assessed enrichment and depletion of variants in publicly available annotation classes such as genic regions, regulatory features, measures of conservation, and patterns of histone modifications. We used logistic regression to build a multivariate model that identified the most influential functional annotations for trait-association status of genome-wide significant variants. SNPs associated with all of the enriched annotations were 8 times more likely to be trait-associated variants than SNPs annotated with none of them. Annotations associated with chromatin state together with prior knowledge of the existence of a local expression QTL (eQTL) were the most important factors in the final logistic regression model. Surprisingly, despite the widespread use of evolutionary conservation to prioritize variants for study we find only modest enrichment of trait-associated SNPs in conserved regions.ConclusionWe established odds ratios of functional annotations that are more likely to contain significantly trait-associated SNPs, for the purpose of prioritizing GWAS hits for further studies. Additionally, we estimated the relative and combined influence of the different genomic annotations, which may facilitate future prioritization methods by adding substantial information.

Project description:The invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases. Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome. These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Identifying these diseased-related regulatory elements will shed light on understanding the mechanisms of how these variants regulate gene expression and ultimately result in disease formation and progression.In this study, we curated and categorized 27,558 Mendelian disease variants, 20,964 complex disease variants, 5,809 cancer predisposing germline variants, and 43,364 recurrent cancer somatic mutations. Compared against nine different types of regulatory regions from FANTOM5 and ENCODE projects, we found that different types of disease variants show distinctive propensity for particular regulatory elements. Mendelian disease variants and recurrent cancer somatic mutations are 22-fold and 10- fold significantly enriched in promoter regions respectively (q<0.001), compared with allele-frequency-matched genomic background. Separate from these two categories, cancer predisposing germline variants are 27-fold enriched in histone modification regions (q<0.001), 10-fold enriched in chromatin physical interaction regions (q<0.001), and 6-fold enriched in transcription promoters (q<0.001). Furthermore, Mendelian disease variants and recurrent cancer somatic mutations share very similar distribution across types of functional effects. We further found that regulatory regions are located within over 50% coding exon regions. Transcription promoters, methylation regions, and transcription insulators have the highest density of disease variants, with 472, 239, and 72 disease variants per one million base pairs, respectively.Disease-associated variants in different disease categories are preferentially located in particular regulatory elements. These results will be useful for an overall understanding about the differences among the pathogenic mechanisms of various disease-associated variants.

Dataset Information

Microsatellites used in forensics are located in regions unusually rich in trait-associated variants.

Publications

Microsatellites used in forensics are located in regions unusually rich in trait-associated variants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets