bioRxivPlant Biology
Finding genetic variants in plants without complete genomes
Abstract
Structural variants and presence/absence polymorphisms are common in plant genomes, yet they are routinely overlooked in genome-wide association studies (GWAS). Here, we expand the genetic variants detected in GWAS to include major deletions, insertions, and rearrangements. We first use raw sequencing data directly to derive short sequences, k-mers, that mark a broad range of polymorphisms independently of a reference genome. We then link k-mers associated with phenotypes to specific genomic regions. Using this approach, we re-analyzed 2,000 traits measured in Arabidopsis thaliana, tomato, and maize populations. Associations identified with k-mers recapitulate those found with single-nucleotide polymorphisms (SNPs), however, with stronger statistical support. Moreover, we identified new associations with structural variants and with regions missing from reference genomes. Our results demonstrate the power of performing GWAS before linking sequence reads to specific genomic regions, which allow detection of a wider range of genetic variants responsible for phenotypic variation.
- organism: Arabidopsis
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- k-mer-based GWAS enhances the discovery of causal variants and candidate genes in soybean
Marc‐André Lemay, Maxime de Ronne, … Francois J. Belzile·The Plant GenomePeer-reviewed·Aug 18, 2023
- Structural variants contribute to phenotypic variation in maize
Nathan S. Catlin, Husain I. Agha, … Emily B. Josephs·Molecular EcologyPeer-reviewed·Feb 13, 2025
- Association Mapping From Sequencing Reads Using K-mers
Atif Hasan Rahman, Ingileif B. Hallgrímsdóttir, … Lior S. Pachter·eLifePeer-reviewed·Jun 13, 2018
- PlantOmicsGWAS: An end-to-end, reproducible framework for plant genome-wide association and genomic prediction using linear and pan-genome references
Falak Sher Khan, Ahmed yassin, … Wenxiu Ye·bioRxiv·Aug 20, 2026
- Trait Association and Prediction Through Integrative K-mer Analysis
Cheng He, Jacob D. Washburn, … Sanzhen Liu·The Plant JournalPeer-reviewed·Sep 11, 2024
- A Whole-Genome Association Approach for Large-scaled Inter-species Trait
Qi Wu, Huizhong Fan, … Fuwen Wei·bioRxiv·Oct 26, 2018