ArticleBreeding science2025
LAYLA: development of a comprehensive and cross-sample program for detecting structural variants and its application to citrus cultivars.
Article in Breeding science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- AlleleMiner: a long-read pipeline for gene-wise de novo allele phasing and variant detection in diploid citrus cultivars.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026Article
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9 authors.
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Abstract
Structural variants (SVs) are genomic mutations that are typically 50 bp or larger. Given their larger scale compared to single nucleotide polymorphisms and small insertions and deletions, SVs are expected to be associated with various traits in several crops and fruit species. They can also be used to identify plant cultivars. However, it is challenging to detect SVs using short-read next-generation sequencing (NGS), which, until recently, has been the mainstream method, due to its short read length compared to SVs. In recent years, long-read NGS, which generates reads exceeding the length of SVs, has made SV detection more feasible. To take advantage of this, we developed LAYLA (Large indel AnalYzer for muLti-sAmple), a pipeline program designed to comprehensively detect and visualize SVs across multiple samples using long-read data. Here, we applied LAYLA to 13 citrus founder cultivars used in Japanese breeding and
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