Additive Effect Quantitative Trait Loci Research Articles

Detection of quantitative trait loci (QTL) associated with spring regrowth in alfalfa (Medicago sativa L.)

Spring regrowth is an important trait for perennial plants including alfalfa, the most cultivated forage legume worldwide. However, the genetic and genomic basis of the trait is largely unknown in alfalfa due to its complex genetic background of the tetroploid genome. The objective of this study was to identify quantitative trait loci (QTLs) associated with spring regrowth using high-resolution genetic linkage maps we constructed previously. In total, 36 significant additive effect QTLs for the trait were detected. Among them, 10 QTLs individually explained more than 10% of the phenotypic variation (PVE) with four in P1 and six in P2. Six overlapped QTLs intervals were detected with two and four intervals distributed in P1 and P2, respectively. In P1, both overlapped genomic regions were located on homolog 7D. In P2, the four QTLs with PVE>10% were co-localized on homolog 6D. Meanwhile, six pairs of significant epistatic QTLs were identified in P2. Screening of potential candidate genes associated with four overlapped QTLs (qCP2019-8, qLF2019-5, qLF2020-4, and qBLUP-3) narrowed down one candidate annotated as MAIL1. The Arabidopsis homolog gene has been reported to play an important role in plant growth. Therefore, the detected QTLs are valuable resources for genetic improvement of alfalfa spring vigor using marker-assisted selection (MAS), and further identification of the associated genes would provide insights into genetic control of spring regrowth in alfalfa.

Mapping additive and epistatic QTLs for forage quality and yield in soybean [Glycine max (L.) Merri.] in two environments

Soybean plants have high protein content and can be used as a supplementary source of high-protein feed. To map quantitative trait loci (QTL) for the content of crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and dry weight of plant (DWP) in R2 stage of soybean, two recombinant inbred lines, RIL3613 and RIL6013, containing 134 and 156 RILs, derived from the cross of Dongnong L13 × Heihe 36 and Dongnong L13 × Henong 60, were planted for two consecutive years. Based on a simple sequence repeat (SSR) linkage map, QTLs of CP, NDF, ADF and DWP were mapped by interval mapping (IM) and inclusive composite interval mapping method (ICIM) using additive effect, epistatic effect and environmental interaction model. The variance components of genotype, environment and genotype × environment (G × E) interaction for quality and yield traits in the two RIL populations were significant under multiple environmental conditions. Eighteen additive effect QTLs on 10 of 20 soybean chromosomes explained 7.02%–15.67% and 2.13%–11.42% of the phenotypic variation in RIL3613 and RIL6013, respectively. Three epistatic QTL pairs related to CP and six ones for DWP were identified. Eight additive effect QTLs for CP, eight ones for NDF, three ones for ADF, and another three ones for DWP were identified by genotype × environment interaction analysis. One epistatic QTL for CP, 11 epistatic QTL pairs for ADF and 38 ones for NDF were identified. These results can provide better understanding of the genetic basis of soybean feed quality and yield.

Deciphering the Genetic Architecture of Plant Height in Soybean Using Two RIL Populations Sharing a Common M8206 Parent.

Plant height (PH) is an important agronomic trait that is closely related to soybean yield and quality. However, it is a complex quantitative trait governed by multiple genes and is influenced by environment. Unraveling the genetic mechanism involved in PH, and developing soybean cultivars with desirable PH is an imperative goal for soybean breeding. In this regard, the present study used high-density linkage maps of two related recombinant inbred line (RIL) populations viz., MT and ZM evaluated in three different environments to detect additive and epistatic effect quantitative trait loci (QTLs) as well as their interaction with environments for PH in Chinese summer planting soybean. A total of eight and 12 QTLs were detected by combining the composite interval mapping (CIM) and mixed-model based composite interval mapping (MCIM) methods in MT and ZM populations, respectively. Among these QTLs, nine QTLs viz., QPH-2, qPH-6-2MT, QPH-6, qPH-9-1ZM, qPH-10-1ZM, qPH-13-1ZM, qPH-16-1MT, QPH-17 and QPH-19 were consistently identified in multiple environments or populations, hence were regarded as stable QTLs. Furthermore, Out of these QTLs, three QTLs viz., qPH-4-2ZM, qPH-15-1MT and QPH-17 were novel. In particular, QPH-17 could detect in both populations, which was also considered as a stable and major QTL in Chinese summer planting soybean. Moreover, eleven QTLs revealed significant additive effects in both populations, and out of them only six showed additive by environment interaction effects, and the environment-independent QTLs showed higher additive effects. Finally, six digenic epistatic QTLs pairs were identified and only four additive effect QTLs viz., qPH-6-2MT, qPH-19-1MT/QPH-19, qPH-5-1ZM and qPH-17-1ZM showed epistatic effects. These results indicate that environment and epistatic interaction effects have significant influence in determining genetic basis of PH in soybean. These results would not only increase our understanding of the genetic control of plant height in summer planting soybean but also provide support for implementing marker assisted selection (MAS) in developing cultivars with ideal plant height as well as gene cloning to elucidate the mechanisms of plant height.

QTL analysis for wheat falling number in a recombinant inbred line population segregated with 1BL/1RS translocation in a rainfed agricultural area of China

Falling number (FN) is an inner quality trait in wheat (Triticum aestivum L.) ultimately determining the end use of wheat kernels. In this 3-year study, 171 recombinant inbred lines derived from Chuannong17 (a 1BL/1RS tranlocation parent) × Mianyang11 were planted in the Sichuan Basin, a rainfed agricultural area in southwestern China. In this climate, we found that FN had significant differences between 1BL/1RS translocation lines and non-1BL/1RS translocation lines in two of the 3 years and the heavy fluctuation of rainfall and temperature resulted in decreasing FN in grain filling period. We used 191 simple sequence repeats markers to construct a genetic linkage map and then detected 11 additive effect FN quantitative trait loci (QTL) on chromosomes 2B, 3D, 4A, 4D, 6B and 7D, explaining 5.48–31.91% of the phenotypic variance. The FN QTL on chromosomes 4A, 4D and 6B were major or stable and detected at least in 2 years, whereas the Qfn.sicau-3D.1 in 2015 year explained the maximum phenotypic variation (about 31.91%). Furthermore, FN QTLs additive and epistatic effects as well as their interactions with environment were estimated by a mixed linear model approach. We found that the additive effect QTLs had no significant additive × environment interaction, while the paired QTLs had significant additive × additive epistatic effects however none had a significant additive × additive epistasis × environment interaction effect, excluding the paired QTLs Qfn.sicau-3B/Qfn.sicau-5B.

Mapping of QTLs associated with important agronomic traits using three populations derived from a super hybrid rice Xieyou9308

Xieyou9308 is the first commercial super hybrid rice released in 1996 in China. To clarify its genetic mechanism underlying high yield potential, a recombinant inbred line (RIL) population derived from the cross between the maintainer line XieqingzaoB (XQZB) and the restorer line Zhonghui9308 (ZH9308) and two derived backcross F1 (BCF1) populations were developed for the identification of quantitative trait loci (QTLs) related to ten important agronomic traits (tiller number (TN), heading date (HD), and grain yield per plant (GYPP), etc.). The BCF1 performance was closely correlated with the performance of their parental RILs according to both the analysis of broad-sense heritability (h B 2 ) and phenotypic correlation coefficient (PCC) in the two BCF1 populations, but not proved by QTL analysis. A total of 21 additive-effect main QTLs (M-QTLs), 22 dominant-effect M-QTLs, and 19 dominant-effect M-QTLs were detected with the WinQTLCart 2.50 software for the ten traits in the RIL and two BCF1 populations, respectively. Of theses, three QTLs (qHD7a, qPPP3a, and qPL10) of 21 were detected repeatedly in the RIL and one BCF1 populations, ten QTLs underlying four traits were only detected repeatedly in two BCF1 populations, and nine QTLs controlling more than two traits were detected repeatedly, the additive-effect QTLs and dominant-effect QTLs play an important role in the performance of agronomic traits and no epistatic QTL of additive by additive effect and dominant by dominant-effect was detected for all traits in three populations. This research is valuable for M-QTL related to important agronomic trait in future fine mapping and positional cloning.

A comparison of grain protein content QTLs and flour protein content QTLs across environments in cultivated wheat

The protein content of cultivated wheat (Triticum aestivum L.) is an important determinant factor of the nutritional value of the grain and the technological properties and rheological properties of flour. In order to examine the genetic basis of protein content, we searched for grain protein content quantitative trait loci (QTLs) and flour protein content QTLs in a newly developed doubled haploid (DH) line and identified the genetic correlation between grain protein content and flour protein content in the same DH population. Both the DH population and its parental lines were evaluated for grain protein content and flour protein content in three field trials. Four additive effect QTLs, two pairs of epistatic QTLs, and two QTLs × environment (QE) interaction for grain protein content were identified. The model explained 51.52% of the phenotypic variation (PVE), with epistatic effects being better explained by the higher PVE than additive effects. Four additive effect QTLs, five pairs of epistatic QTLs, and one QE were detected for flour protein content. The model explained 45.8% of the PVE. Of the 15 QTLs identified, three additive QTLs and one pair of epistatic QTLs were determined for both grain protein content and flour protein content; of these, the QTLs for protein content were considered to be more 'stable' than those detected for only grain protein content or for only flour protein content. The data reported here may be useful for manipulating the QTLs for protein content by marker-assisted selection in future wheat breeding programs.

Quantitative trait loci (QTL) analysis for rice grain width and fine mapping of an identified QTL allele gw-5 in a recombination hotspot region on chromosome 5.

Rice grain width and shape play a crucial role in determining grain quality and yield. The genetic basis of rice grain width was dissected into six additive quantitative trait loci (QTL) and 11 pairs of epistatic QTL using an F(7) recombinant inbred line (RIL) population derived from a single cross between Asominori (japonica) and IR24 (indica). QTL by environment interactions were evaluated in four environments. Chromosome segment substitution lines (CSSLs) harboring the six additive effect QTL were used to evaluate gene action across eight environments. A major, stable QTL, qGW-5, consistently decreased rice grain width in both the Asominori/IR24 RIL and CSSL populations with the genetic background Asominori. By investigating the distorted segregation of phenotypic values of rice grain width and genotypes of molecular markers in BC(4)F(2) and BC(4)F(3) populations, qGW-5 was dissected into a single recessive gene, gw-5, which controlled both grain width and length-width ratio. gw-5 was narrowed down to a 49.7-kb genomic region with high recombination frequencies on chromosome 5 using 6781 BC(4)F(2) individuals and 10 newly developed simple sequence repeat markers. Our results provide a basis for map-based cloning of the gw-5 gene and for marker-aided gene/QTL pyramiding in rice quality breeding.

Identifying loci under selection across contrasting environments inAvena barbatausing quantitative trait locus mapping

We constructed recombinant inbred lines of a cross between naturally occurring ecotypes of Avena barbata (Pott ex Link), Poaceae, associated with contrasting moisture environments. These lines were assessed for fitness in common garden reciprocal transplant experiments in two contrasting field sites in each of two years, as well as a novel, benign greenhouse environment. An AFLP (amplified fragment length polymorphism) linkage map of 129 markers spanned 644 cM in 19 linkage groups, which is smaller, with more linkage groups, than expected. Therefore parts of the A. barbata genome remain unmapped, possibly because they lack variation between the ecotypes. Nevertheless, we identified QTL (quantitative trait loci) under selection in both native environments and in the greenhouse. Across years at the same site, the same loci remain under selection, for the same alleles. Across sites, an overlapping set of loci are under selection with either (i) the same alleles favoured at both sites or (ii) loci under selection at one site and neutral at the other. QTL under selection in the greenhouse were generally unlinked to those under selection in the field because selection acted on a different trait. We found little evidence that selection favours alternate alleles in alternate environments, which would be necessary if genotype by environment interaction were to maintain genetic variation in A. barbata. Additive effect QTL were best able to explain the genetic variation among recombinant inbred lines for the greenhouse environment where heritability was highest, and past selection had not eliminated variation.