Search

Plant structure type (PT) is an important complex and quantitative trait to regulating yield potential and stress tolerance in wheat (Triticum aestivum L.). In this study, a recombinant inbred line (RIL) population genotyped by wheat 50 K SNP chip was employed to detect quantitative trait loci (QTL) controlling plant structure type and seed-related eight traits in seven environments. A total of 13 QTL were detected in multiple environments. By comparing previous studies, QKw-5D-2-2 (kernel width) and QSnl-6B (spike neck length), on chromosomes 5D and 6B, respectively, were regarded as two new multi-environmental stable QTLs explaining 5.01–11.51% and 9.79–15.01% of the phenotypic variation, correspondingly. In addition, we predicted two genes associated with grain width in the interval QKw-5D-2-2, and seven multi-environmentally stable QTLs on chromosome 4D were found to be distributed in clusters; significant correlations were found between plant height (PH) and, PT, spike neck length (SNL), basal two internode length (BL), kernel width (KW) and thousand kernel weights (TKW) by genetic and correlation analyses. In summary, our results will provide help to understand the genetic relationship between plant structure type and yield potential. And the newly identified QTLs and QTL clusters lay the genetic foundation for fine localization of plant structure type related traits and molecular marker-assisted breeding in wheat genetic improvement. [ABSTRACT FROM AUTHOR]

Copyright of Acta Agronomica Sinica is the property of Crop Science Society of China and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Agronomic traits are usually determined by multiple quantitative trait loci (QTLs) that can have pleiotropic effects. A multiparent advanced generation intercross (MAGIC) population is well suited for genetically analysing the effects of multiple QTLs on the traits of interest because it contains more QTL alleles than a biparental population and can overcome the problem of confounding the population structure of the natural germplasm population. We previously developed the B. juncea MAGIC population, derived from eight B. juncea lines with great diversity in agronomic and quality traits. In this study, we show that the B. juncea MAGIC population is also effective for the evaluation of multiple QTLs for complex agronomic traits in B. juncea. A total of twenty-two QTLs for nine seed-related traits were identified, including one QTL for each oil content, seed number per silique and thousand-seed weight; two QTLs for each acid detergent lignin and neutral detergent fibre; three QTLs for each acid detergent fibre and protein content; four QTLs for the seed maturity time; and five QTLs for the white index. Some of these QTLs overlapped. These results should be helpful for further fine mapping, gene cloning, plant breeding and marker-assisted selection (MAS) in B. juncea.

Seed traits are agronomically important for Cucurbita breeding, but the genes controlling seed size, seed weight and seed number have not been mapped in Cucurbita maxima (C. maxima). In this study, 100 F2 individual derived from two parental lines, “2013-12” and “9-6”, were applied to construct a 3,376.87-cM genetic map containing 20 linkage groups (LGs) with an average genetic distance of 0.47 cM using a total of 8,406 specific length amplified fragment (SLAF) markers in C. maxima. Ten quantitative trait loci (QTLs) of seed width (SW), seed length (SL) and hundred-seed weight (HSW) were identified using the composite interval mapping (CIM) method. The QTLs affecting SW, SL and HSW explained a maximum of 38.6%, 28.9% and 17.2% of the phenotypic variation and were detected in LG6, LG6 and LG17, respectively. To validate these results, an additional 150 F2 individuals were used for QTL mapping of SW and SL with cleaved amplified polymorphic sequence (CAPS) markers. We found that two major QTLs, SL6-1 and SW6-1, could be detected in both SLAF-seq and CAPS markers in an overlapped region. Based on gene annotation and non-synonymous single-nucleotide polymorphisms (SNPs) in the major SWand SL-associated regions, we found that two genes encoding a VQ motif and an E3 ubiquitin-protein ligase may be candidate genes influencing SL, while an F-box and leucinerich repeat (LRR) domain-containing protein is the potential regulator for SW in C. maxima. This study provides the first high-density linkage map of C. maxima using SNPs developed by SLAF-seq technology, which is a powerful tool for associated mapping of important agronomic traits, map-based gene cloning and marker-assisted selection (MAS)-based breeding in C. maxima.

Seed traits are agronomically important for Cucurbita breeding, but the genes controlling seed size, seed weight and seed number have not been mapped in Cucurbita maxima (C. maxima). In this study, 100 F2 individual derived from two parental lines, "2013-12" and "9-6", were applied to construct a 3,376.87-cM genetic map containing 20 linkage groups (LGs) with an average genetic distance of 0.47 cM using a total of 8,406 specific length amplified fragment (SLAF) markers in C. maxima. Ten quantitative trait loci (QTLs) of seed width (SW), seed length (SL) and hundred-seed weight (HSW) were identified using the composite interval mapping (CIM) method. The QTLs affecting SW, SL and HSW explained a maximum of 38.6%, 28.9% and 17.2% of the phenotypic variation and were detected in LG6, LG6 and LG17, respectively. To validate these results, an additional 150 F2 individuals were used for QTL mapping of SW and SL with cleaved amplified polymorphic sequence (CAPS) markers. We found that two major QTLs, SL6-1 and SW6-1, could be detected in both SLAF-seq and CAPS markers in an overlapped region. Based on gene annotation and non-synonymous single-nucleotide polymorphisms (SNPs) in the major SWand SL-associated regions, we found that two genes encoding a VQ motif and an E3 ubiquitin-protein ligase may be candidate genes influencing SL, while an F-box and leucinerich repeat (LRR) domain-containing protein is the potential regulator for SW in C. maxima. This study provides the first high-density linkage map of C. maxima using SNPs developed by SLAF-seq technology, which is a powerful tool for associated mapping of important agronomic traits, map-based gene cloning and marker-assisted selection (MAS)-based breeding in C. maxima. [ABSTRACT FROM AUTHOR]

Cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB, 2n = 4x = 40), valued for its edible oil and digestible protein. Seed size and weight are important agronomical traits significantly influence the yield and nutritional composition of peanut. However, the genetic basis of seed-related traits remains ambiguous. Association mapping is a powerful approach for quickly and efficiently exploring the genetic basis of important traits in plants. In this study, a total of 104 peanut accessions were used to identify molecular markers associated with seed-related traits using 554 single-locus simple sequence repeat (SSR) markers. Most of the accessions had no or weak relationship in the peanut panel. The linkage disequilibrium (LD) decayed with the genetic distance of 1cM at the genome level and the LD of B subgenome decayed faster than that of the A subgenome. Large phenotypic variation was observed for four seed-related traits in the association panel. Using mixed linear model with population structure and kinship, a total of 30 significant SSR markers were detected to be associated with four seed-related traits (P < 1.81 × 10-3) in different environments, which explained 11.22–32.30% of the phenotypic variation for each trait. The marker AHGA44686 was simultaneously and repeatedly associated with seed length and hundred-seed weight in multiple environments with large phenotypic variance (26.23 ∼ 32.30%). The favorable alleles of associated markers for each seed-related trait and the optimal combination of favorable alleles of associated markers were identified to significantly enhance trait performance, revealing a potential of utilization of these associated markers in peanut breeding program.