Year: 2026
Type: article
Abstract: Genome-wide association studies (GWAS) identify genomic regions associated with complex traits, but interpreting these regions requires further analysis of local linkage disequilibrium (LD), marker–trait relationships and multilocus genotype patterns. In this study, a Python-based graphical user interface (GUI) was developed to integrate regional post-GWAS analyses and provide a button-driven alternative to command-line workflows. The platform includes PLINK-based regional marker extraction, LD calculation, LD decay visualisation, exploratory regional SNP–trait analysis, candidate LD region detection, graph-based LD clustering and pairwise genotype-combination analysis. As a proof of concept, the workflow was applied to publicly available genotype data from the Bengal and Assam Aus Panel and grain iron (Fe) concentration data from the same population. The analysis focused on a previously reported quantitative trait locus (QTL) located at approximately 29.28 megabase pairs (Mbp) on rice chromosome 7, near the candidate gene nicotianamine synthase 3 ( OsNAS3 ). The GUI extracted 4894 single-nucleotide polymorphisms (SNPs) from a 1-Mbp interval and generated 11,973,171 pairwise LD comparisons. Exploratory regional SNP–trait analysis evaluated 4448 eligible SNPs. Because the GUI screening procedure did not account for population structure or relatedness, the regional SNPs were additionally evaluated using a mixed linear model incorporating five genome-wide principal components and a genomic kinship matrix. The adjusted analysis identified 133 Bonferroni-significant and 1635 Benjamini–Hochberg-significant SNPs, including marginal adjusted signals within the genomic neighbourhood of OsNAS3 . At the specified clumping parameters, all 133 Bonferroni-significant SNPs were assigned to a single clump indexed by SNP 7:29285763, and no residual association remained significant after conditioning on this lead marker and correcting for multiple testing. Among 43,639 SNP pairs separated by no more than 1000 base pairs (bp), 22,952 had r 2 ≥ 0.6. These strong-LD pairs were summarised as 116 candidate LD regions using interval-based aggregation and 339 graph-based LD clusters using connected-components analysis. Of the 22,952 strong-LD SNP pairs, 21,646 met the genotype-call eligibility criteria for pairwise genotype-combination analysis. Although exploratory pairwise analysis of variance (ANOVA) identified numerous corrected genotype–phenotype differences, nested-model comparisons provided no corrected evidence that any two-locus genotype combination explained additional phenotypic variation beyond its better constituent single-marker model. These findings reflect the extensive LD within the selected QTL interval and represent regional prioritisation rather than identification of causal variants. Overall, the GUI provides a reproducible framework for characterising GWAS-derived QTL intervals, regional LD patterns and genotype–phenotype relationships. Its broader applicability should be further evaluated using additional traits, populations, genomic regions and organisms with compatible PLINK genotype data.
Source: Genomics & Informatics
Authors: Partha Talukdar, Michael Martin
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,290
OpenAlex ID: W7225738509