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Updated: Aug 19, 2025

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Inverted genomic regions between reference genome builds in humans impact imputation accuracy and decrease the power

Xin Sheng1, Lucy Xia1, Jordan L Cahoon2,3

  • 1Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.

HGG Advances
|December 5, 2022
PubMed
Summary
This summary is machine-generated.

Bioinformatic conversion errors involving inverted genome regions between human reference builds (GRCh37/hg19 and GRCh38) impact variant accuracy. A new method using liftOver corrects these errors, improving imputation and association analyses for disease susceptibility variants.

Keywords:
bioinformaticsgenetic associationsgenome buildimputationreference genome

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Area of Science:

  • Genomics
  • Bioinformatics
  • Human Genetics

Background:

  • The human reference genome has evolved through multiple versions, primarily GRCh37/hg19 and GRCh38, necessitating accurate coordinate conversions for biomedical research.
  • Single-nucleotide variants (SNVs) in genome regions that are inverted between reference builds are prone to bioinformatic mishandling during coordinate conversion.

Purpose of the Study:

  • To identify and address the underrecognized consequences of mishandled SNVs in inverted genome regions during reference build conversions.
  • To develop a method for detecting and correcting variant conversion errors in inverted regions to improve downstream genetic analyses.

Main Methods:

  • Analysis of SNVs in approximately 2-5 Mb of the human genome affected by inversions between GRCh37/hg19 and GRCh38.
  • Evaluation of coordinate conversion accuracy using the TOPMed imputation server and in-house quality control pipelines.
  • Development of a heuristic method based on the liftOver tool to detect and correct variants in inverted regions.

Main Results:

  • Mishandled SNVs in inverted regions lead to allelic conversion errors, particularly for palindromic variants (A/T, C/G).
  • These errors destabilize local haplotype structure, reducing imputation accuracy and statistical power in association studies.
  • A known prostate cancer susceptibility locus on chromosome 10 showed a significant increase in p-value (from 2.86e-7 to 0.0011) due to these errors in a large African/African American cohort.

Conclusions:

  • Undetected allelic conversion errors in inverted genome regions pose a significant challenge for accurate genetic analysis.
  • The developed liftOver-based heuristic effectively detects and corrects these variants, enhancing imputation accuracy.
  • This method is crucial for reliable association studies, especially for disease susceptibility variants located in these affected genomic regions.