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Updated: Jan 9, 2026

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Genome-wide selection inference at short tandem repeats.

Bonnie Huang¹, Arun Durvasula^2,3, Nima Mousavi⁴

¹Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.

|December 1, 2025

Summary

This summary is machine-generated.

Short tandem repeats (STRs) cause genetic variation and disease. A new method, SISTR2, analyzes selection on STRs, revealing their mutation rates and disease burden, which is higher for de novo mutations than single nucleotide variants.

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Area of Science:

Population genetics
Human genetics
Evolutionary biology

Background:

Short tandem repeats (STRs) are a major source of human genetic variation.
STRs contribute to various diseases, including Mendelian disorders, complex traits, and cancer.
Mutations in STRs can negatively impact reproductive fitness over evolutionary timescales.

Purpose of the Study:

To extend the SISTR framework (SISTR2) for joint estimation of selection coefficients across multiple STRs.
To enable more accurate analysis of a broader range of STRs, including those with low mutation rates.
To estimate the relative burden of de novo and inherited variation at STRs compared to single nucleotide variants (SNVs).

Main Methods:

Development of SISTR2, an extension of the SISTR population genetics framework.
Joint estimation of selection coefficient distributions across sets of STRs.
Exploration of mutation parameters and comparison of variation burden between STRs and SNVs.

Main Results:

SISTR2 allows for more accurate analysis of diverse STRs, including low-mutation-rate loci.
Substantial variation in mutation and selection parameters was observed across different STR classes.
De novo mutations at STRs contribute a greater burden than those at SNVs, while SNVs contribute more inherited variation.

Conclusions:

SISTR2 provides a more robust framework for analyzing selection at STRs.
STRs exhibit significant variation in mutation and selection parameters.
The burden of de novo STR mutations is higher than de novo SNVs, impacting evolutionary and disease studies.