QTL identification for nine seed-related traits in Brassica juncea using a multiparent advanced generation intercross (MAGIC) population

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.

Pod and seed trait QTL identification to assist breeding for peanut market preferences

ABSTRACTAlthough seed and pod traits are important for peanut breeding, little is known about the inheritance of these traits. A recombinant inbred line (RIL) population of 156 lines from a cross of Tifrunner x NC 3033 was genotyped with the Axiom_Arachis1 SNP array and SSRs to generate a genetic map composed of 1524 markers in 29 linkage groups (LG). The genetic positions of markers were compared with their physical positions on the peanut genome to confirm the validity of the linkage map and explorethe distribution of recombination and potential chromosomal rearrangements. These traits were phenotyped over three consecutive years for the purpose of developing trait-associated markers for breeding. Forty-nine QTL were identified in 14 LG for seed size index, kernel percentage, seed weight, pod weight, single-kernel, double-kernel, pod area and pod density. Twenty QTL demonstrated phenotypic variance explained (PVE) greater than 10% and eight more than 20%. Of note, seven of the eight major QTL for pod area, pod weight and seed weight (PVE >20% variance) were attributed to NC 3033 and located in a single linkage group, LG B06_1. In contrast, the most consistent QTL for kernel percentage were located on A07/B07 and derived from Tifrunner.

First Attempt to Identify and Map QTLs Associated with Promiscuous Nodulation in Soybean

ABSTRACTTo inform possibility of conducting marker assisted breeding of promiscuous soybean varieties, this study used 92 F2 lines from biparental cross to identify QTLs associated with promiscuous nodulation in soybean. GBS; genotyping by sequencing platform was used to generate SNPs through the pipeline 2 in TASSEL 5.0, Bowtie2 version 2.2.8 for tag alignment, Beagle version 4.1 to impute missing SNPs and R-QTL package in R for QTL identification. Four nodulation traits were assessedviznumber of nodules (NN), percent of effective nodules (NE), fresh weight and dry weight of nodules (NFW and NDW). Two QTLs were identified on chromosomes 10 and 13. Both QTLs were associated with NN, only QTL13 was associated NE and only QTL10 was associated with nodule ‘weights. It was observed that NN, NFW and NDW shared QTL10 and NN and NE share QTL13 allowing hypothetize on the existence of pleiotropic genes in those those two regions. Over dominance effect was observed for QTL10 and non additive effect for QTL13. The paper recommend investigations be pursued to validate those QTLs and set foundation for marker assisted selection of promiscuous soybean varieties. Also these findings could serve as starting point for gene cloning to better understand nodulation trait in soybean.