ArticleBMC plant biology2025
Genetic dissection of plant height-related traits by combined methods in wheat (Triticum aestivum L.).
Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Blind genomic tree scans identify loci underlying adaptive peaks in Antirrhinum.bioRxiv : the preprint server for biology · 2026Article
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Abstract
backgroundPlant height-related traits are important for optimal architecture and grain yield in wheat (Triticum aestivum L.). In this study, association analysis based on single nucleotide polymorphisms (SNPs) and structural chromosome variations (SCVs) was performed on eight plant height-related traits in a natural population of 281 accessions. Linkage analysis was applied to two populations: a doubled haploid (DH) population of 180 lines derived from the cross 'Jinchun 7 × Jinmai 919' and a recombinant inbred line (RIL) population of 165 F
resultsIn the natural population, plant height (PH) varied from 69.6 cm to 136.6 cm. PH and internode length decreased gradually across years of release, but the selection pressure varied among PH components. The uppermost internode length decreased the fastest across years of release, while spike length (SL) increased across the same timeframe. A total of 22 SNP loci and 19 SCV loci were detected by association mapping, which collectively explaining 3.8-12.5% variation, including five novel loci (QPH.sxau-2A, QSL.sxau-7B.2, QSEL.sxau-5A, QLI3.sxau-7A, and QLI5.sxau-2B). SNPs and SCVs co-localized to 14 marker-trait associations (MTAs), which explained 3.2-12.5% of the phenotypic variation, including QSL.sxau-7B.1 (SCV locus Mr7B-13), which was verified in the DH population. The phenotypic values for PH and internode length decreased and SL increased with an increasing number of favorable SNPs and SCVs allelic variation. In particular, QPH.sxau-2A was identified by using association and linkage analysis, with its fine mapping narrowing the functional region down to a 41.8 Mb genomic interval, containing three candidate genes TraesCS2A02G309300, TraesCS2A02G288000, and TraesCS2A02G288300.
conclusionGenotype emerged as the primary factor influencing plant-height-related trait variation. Association mapping detected 22 SNP loci and 19 SCV loci, and these loci exhibited additive effects. This study identifies novel loci for the genetic basis of plant height-related traits.
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