ArticleJournal of applied genetics2017
Comparative analysis of genetic architectures for nine developmental traits of rye.
Article in Journal of applied genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Genome-Wide Association Study Identified Novel SNPs Associated with Chlorophyll Content in Maize.Genes · 2023Article
- A complex network of QTL for thousand-kernel weight in the rye genome.Journal of applied genetics · 2020Article
- The GAMYB gene in rye: sequence, polymorphisms, map location, allele-specific markers, and relationship with α-amylase activity.BMC genomics · 2020Article
- Putative candidate genes responsible for leaf rolling in rye (Secale cereale L.).BMC genetics · 2018Article
- Identification of a novel, dominant dwarfing gene (Ddw4) and its effect on morphological traits of rye.PloS one · 2018Article
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3 authors.
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Abstract
Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1-3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1-5 loci of the epistatic D class and 10-28 loci of the hypostatic, mostly R and E classes controlling traits variation through D-E or D-R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2-8 traits. Detection of considerable numbers of the reversed (D', E' and R') classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies.
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