ArticleBMC genomics2022
Evaluation of nine statistics to identify QTLs in bulk segregant analysis using next generation sequencing approaches.
Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Bulked Segregant Analysis Revealed the Common Resistant QTLs Associated with Fusarium Ear Rot and Gibberella Ear Rot in Maize.Plants (Basel, Switzerland) · 2026Article
- The genomic basis of local adaptation to photoperiod across altitude in a self-fertilizing monkeyflower.bioRxiv : the preprint server for biology · 2026Article
- Regulatory networks and molecular mechanisms underlying salt stress tolerance in rice.Frontiers in plant science · 2026Review
- Development of cleaved amplified polymorphic sequence marker for powdery mildew resistance in Korean malting barley using QTL-seq.Frontiers in plant science · 2025Article
- A fully phased, chromosome-scale genome of sugar beet line FC309 enables the discovery of Fusarium yellows resistance QTL.DNA research : an international journal for rapid publication of reports on genes and genomes · 2024Article
- Dissecting the genetic architecture of sunflower disc diameter using genome-wide association study.Plant direct · 2024Article
- MAPtools: command-line tools for mapping-by-sequencing and QTL-Seq analysis and visualization.Plant methods · 2024Article
- QTLs and Genes for Salt Stress Tolerance: A Journey from Seed to Seed Continued.Plants (Basel, Switzerland) · 2024Review
- Article
- QTL-Seq identified a genomic region on chromosome 1 for soil-salinity tolerance in FFrontiers in plant science · 2024Article
- Cloning of an Albino Mutation ofInternational journal of molecular sciences · 2023Article
- From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology.International journal of molecular sciences · 2023Review
- SNP-based bulk segregant analysis revealed disease resistance QTLs associated with northern corn leaf blight in maize.Frontiers in genetics · 2022Article
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2 authors.
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Abstract
backgroundBulk segregant analysis (BSA) combined with next generation sequencing is a powerful tool to identify quantitative trait loci (QTL). The impact of the size of the study population and the percentage of extreme genotypes analysed have already been assessed. But a good comparison of statistical approaches designed to identify QTL regions using next generation sequencing (NGS) technologies for BSA is still lacking.
resultsWe developed an R code to simulate QTLs in bulks of F2 contrasted lines. We simulated a range of recombination rates based on estimations using different crop species. The simulations were used to benchmark the ability of statistical methods identify the exact location of true QTLs. A single QTL led to a shift in allele frequency across a large fraction of the chromosome for plant species with low recombination rate. The smoothed version of all statistics performed best notably the smoothed Euclidean distance-based statistics was always found to be more accurate in identifying the location of QTLs. We propose a simulation approach to build confidence interval statistics for the detection of QTLs.
conclusionWe highlight the statistical methods best suited for BSA studies using NGS technologies in crops even when recombination rate is low. We also provide simulation codes to build confidence intervals and to assess the impact of recombination for application to other studies. This computational study will help select NGS-based BSA statistics that are useful to the broad scientific community.
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