Evidence map›Paper›PMID 37841589›Full record

ArticleiScience2023

Microsatellites used in forensics are in regions enriched for trait-associated variants.

Vivian Link, Yuómi Jhony A Zavaleta, Rochelle-Jan Reyes, Linda Ding, Judy Wang, Rori V Rohlfs, Michael D Edge

Abstract read
In one paragraph

Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Vivian LinkDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Yuómi Jhony A ZavaletaDepartment of Biology, San Francisco State University, San Francisco, CA, USA.
Rochelle-Jan ReyesDepartment of Biology, San Francisco State University, San Francisco, CA, USA.
Linda DingDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Judy WangDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Rori V RohlfsDepartment of Biology, San Francisco State University, San Francisco, CA, USA.
Michael D EdgeDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.

Funding

SFSU MA-MS/PHD BRIDGE TO THE FUTURER25GM048972 · NIGMS · SAN FRANCISCO STATE UNIVERSITY · PI BAYLISS, FRANK T, FUSE, MEGUMI M. · 1992 to 2020
$5.6M
Traits on trees: Population genomics for understanding complex phenotypesR35GM137758 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Michael Donald Edge · 2020 to 2026
$2.5M
NIGMS NIH HHS R25 GM048972NIGMS NIH HHS R35 GM137758
6 · The paper itself

Abstract

The 20 short tandem repeat (STR) loci 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 loci are thought to contain little information about ancestry or traits. However, in the past 20 years, a 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. Although this study cannot establish or quantify associations between CODIS genotypes and phenotypes, we find that the regions around the CODIS loci are enriched for both known pathogenic variants (> 90th percentile) and for trait-associated SNPs identified in genome-wide association studies (GWAS) (≥ 95th percentile in 10kb and 100kb flanking regions), compared with other random sets of autosomal tetranucleotide-repeat STRs.

Indexed as

Biological sciencesGeneticsGenomics

Identifiers

PMID37841589
PMCPMC10570123

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.