Individual Quantitative Trait Loci Level Research Articles

Unraveling the genetic basis of grain number-related traits in a wheat-Agropyron cristatum introgressed line through high-resolution linkage mapping

BackgroundGrain number per spike (GNS) is a pivotal determinant of grain yield in wheat. Pubing 3228 (PB3228), a wheat-Agropyron cristatum germplasm, exhibits a notably higher GNS.ResultsIn this study, we developed a recombinant inbred line (RIL) population derived from PB3228/Gao8901 (PG-RIL) and constructed a high-density genetic map comprising 101,136 loci, spanning 4357.3 cM using the Wheat 660 K SNP array. The genetic map demonstrated high collinearity with the wheat assembly IWGSC RefSeq v1.0. Traits related to grain number and spikelet number per spike were evaluated in seven environments for quantitative trait locus (QTL) analysis. Five environmentally stable QTLs were detected in at least three environments. Among these, two major QTLs, QGns-4A.2 and QGns-1A.1, associated with GNS, exhibited positive alleles contributed by PB3228. Further, the conditional QTL analysis revealed a predominant contribution of PB3228 to the GNS QTLs, with both grain number per spikelet (GNSL) and spikelet number per spike (SNS) contributing to the overall GNS trait. Four kompetitive allele-specific PCR (KASP) markers that linked to QGns-4A.2 and QGns-1A.1 were developed and found to be effective in verifying the QTL effect within a diversity panel. Compared to previous studies, QGns-4A.2 exhibited stability across different trials, while QGns-1A.1 represents a novel QTL. The results from unconditional and conditional QTL analyses are valuable for dissecting the genetic contribution of the component traits to GNS at the individual QTL level and for understanding the genetic basis of the superior grain number character in PB3228. The KASP markers can be utilized in marker-assisted selection for enhancing GNS.ConclusionsFive environmentally stable QTLs related to grain number and spikelet number per spike were identified. PB3228 contributed to the majority of the QTLs associated with GNS.

The contribution of photosynthesis traits and plant height components to plant height in wheat at the individual quantitative trait locus level

Plant height is an important agronomic trait for morphogenesis and grain yield formation in wheat. In this study, we performed both normal and multivariate conditional quantitative trait locus (QTL) analyses for plant height with spike length, internode number, length of the first internode to the sixth internode from the top during harvest, and photosynthesis traits at the seedling stage and heading stage based on a recombinant inbred line population. A total of 49 normal QTLs were detected, as well as 312 conditional QTLs. The genetic region Xbcd1970-Xbcd262 on chromosome 2D harbored the most QTLs, with 6 normal QTLs and 39 conditional QTLs. A comparison between the normal and conditional QTL mapping analyses suggested that the length of the third internode, fourth internode, and fifth internode from the top showed a high genetic association with plant height, whereas all photosynthesis traits showed weaker associations. This comparative analysis could serve as a platform for dissecting the genetic relation between objective traits and other phenotypic traits before manipulation of genes collocated with QTL clusters.

Contribution of photosynthetic- and yield-related traits towards grain yield in wheat at the individual quantitative trait locus level

Grain yield improvement in wheat (Triticum aestivum L) requires understanding of the genetic control of grain yield components and other related traits. In this study, a total of 82 and 314 quantitative trait loci (QTLs) were associated with grain yield and grain yield components after harvest and photosynthetic traits at the seedling, heading and grain filling stages from a recombinant inbred line population by normal and multivariate QTLs analysis, respectively. Sixty-one QTL clusters explained from 4.42% to 27.72% of phenotypic variances for 2–76 traits. A comparison between the normal and conditional QTL mapping found that grain yield showed significant genetic correlation with grain yield components and photosynthetic traits on five QTLs. In the genetic region between Xbarc99 and Xbarc169 on chromosome 1D, grain yield was entirely contributed by thousand kernel weight and harvest index. At the same region, harvest index was contributed by transpiration rate at seedling stage, intercellular CO2 concentration, stomatal conductance, net photosynthetic rate and transpiration rate at heading stage; and intercellular CO2 concentration, net photosynthetic rate and transpiration rate at grain filling stage, whereas thousand kernel weight was suppressed by a normal QTL for chlorophyll content at grain filling stage in this region. The direct comparison analyses between grain yield with photosynthetic traits showed similar genetic relationships in this region. Manipulation of genes found within these QTL clusters might improve important agronomic traits and grain yield.

Stable, Environmental Specific and Novel QTL Identification as Well as Genetic Dissection of Fatty Acid Metabolism in Brassica napus.

Fatty acid (FA) composition is the typical quantitative trait in oil seed crops, of which study is not only closely related to oil content, but is also more critical for the quality improvement of seed oil. The double haploid (DH) population named KN with a high density SNP linkage map was applied for quantitative trait loci (QTL) analysis of FA composition in this study. A total of 406 identified QTL were detected for eight FA components with an average confidence interval (CI) of 2.92 cM, the explained phenotypic variation (PV) value ranged from 1.49 to 45.05%. Totally, 204 consensus and 91 unique QTL were further obtained via meta-analysis method for the purpose of detecting multiple environment expressed and pleiotropic QTL, respectively. Of which, 74 stable expressed and 22 environmental specific QTL were also revealed, respectively. In order to make clear the genetic mechanism of FA metabolism at individual QTL level, conditional QTL analysis was also conducted and more than two thousand conditional QTL which could not be detected under the unconditional mapping were detected, which indicated the complex interrelationship of the QTL controlling FA content in rapeseed. Through comparative genomic analysis and homologous gene annotation, 61 candidates related to acyl lipid metabolism were identified underlying the CI of FA QTL. To further visualize the genetic mechanism of FA metabolism, an intuitive and meticulous network about acyl lipid metabolism was constructed and some closely related candidates were positioned. This study provided a more accurate localization for stable and pleiotropic QTL, and a deeper dissection of the molecular regulatory mechanism of FA metabolism in rapeseed.

Analysis of contributors to grain yield in wheat at the individual quantitative trait locus level

AbstractIn wheat, strong genetic correlations have been found between grain yield (GY) and tiller number per plant (TN), fertile spikelet number per spike (FSN), kernel number per spike (KN) and thousand‐kernel weight (TKW). To investigate their genetic relationships at the individual quantitative trait locus (QTL) level, we performed both normal and multivariate conditional QTL analysis based on two recombinant inbred lines (RILs) populations. A total of 79 and 48 normal QTLs were identified in the International Triticeae Mapping Initiative (ITMI)/SHW‐L1 × Chuanmai 32 (SC) populations, respectively, as well as 55 and 35 conditional QTLs. Thirty‐two QTL clusters in the ITMI population and 18 QTL clusters in the SC population explained 0.9%–46.2% of phenotypic variance for two to eight traits. A comparison between the normal and conditional QTL mapping analyses indicated that FSN made the smallest contribution to GY among the four GY components that were considered at the QTL level. The effects of TN, KN and TKW on GY were stronger at the QTL level.

QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P N, and C i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.

Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize

Improving grain yield is the ultimate goal of the maize-breeding programs. In this study, analyses of conditional and unconditional quantitative trait locus (QTL) and epistatic interactions were used to elucidate the genetic architecture of yield and its related traits. A total of 15 traits of a recombinant inbred line population, including yield per plant (YPP), seven ear-related traits, and seven kernel-related traits, were measured in six different environments. Based on the genetic linkage map constructed using 2091 bins as markers, 56 main-effect QTLs for these traits were identified. These QTLs were distributed across eight genomic regions (bin 1.06, bin 4.02/4.05/4.08, bin 5.04, bin 7.04, bin 8.08, and bin 9.04), within the marker intervals of 85.45–6260.66 kb, and the phenotypic variance explained ranging from 5.69 to 11.56 %. One gene (GRMZM2G168229) encoding SBP-box domain protein was located in the small interval of qKRN4-3 and may be involved in patterning of kernel row number. Seventeen conditional QTLs identified for YPP were conditioned on its related traits and explained 6.18–23.15 % of the phenotypic variance. Conditional mapping analysis revealed that qYPP4-1, qYPP6-1, and qYPP8-1 are partially influenced by YPP-related traits at the individual QTL level. Digenic epistatic analysis identified 12 digenic interactions involving 22 loci across the whole genome. In addition, conditional digenic epistatic analysis identified 14 digenic interactions involving 21 loci. This study provides valuable information for understanding the genetic relationship between YPP and related traits and constitutes the first step toward the cloning of the relevant genes.

QTLs for uppermost internode and spike length in two wheat RIL populations and their affect upon plant height at an individual QTL level

Spike length (SL) is one of the most important components of spike morphology, and the uppermost internode represents an ideal organ to study the transportation system. We performed conditional and unconditional quantitative trait locus (QTL) mapping in two unrelated recombinant inbred line populations to precisely detect QTLs for uppermost internode length (UIL) and SL, and to dissect the genetic relationship between these two factors with plant height (PH). Both of the populations were derived from crosses with synthetic wheat. Ten repetitive QTLs for UIL and six environment-independent QTLs for SL were identified in this study, and twelve of these were completely independent of PH. Conditional QTL mapping analysis indicated that SL was more independent to PH than UIL was. The results indicated that the conditional QTL mapping method could evaluate PH component effects on PH, and thus accelerate the selection of suitable loci that improve commercial wheat morphology yet avoid changes to PH.

QTL Analysis of Kernel-Related Traits in Maize Using an Immortalized F2 Population

Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04–6.06, 7.02–7.03, and 10.06–10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%).

Length of internode and spike: How do they contribute to plant height of wheat at an individual QTL level?

A recombinant inbred line (RIL) population with 302 lines derived from a cross of Weimai 8 × Luohan 2 was used to identify the quantitative trait loci (QTL) for plant height (PH) in wheat (Triticum aestivum L.). Possible genetic relationships between PH and PH components (PHC), including spike length (SL) and internode length from the first to the fourth node counted from the top, abbreviated as FIITL, SITL, TITL and FOITL, respectively, were evaluated at the QTL level. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using the IciMapping V3.0 software. Conditional QTL mapping proved that, at the QTL level, SL contributed the least to PH, followed by FIITL and FOITL, while TITL had the strongest influence on PH, followed by SITL. These results indicate that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and that it can efficiently and precisely reveal counteracting QTL, which will enhance our understanding of the genetic basis of PH in wheat.

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.

Kernel weight per spike: what contributes to it at the individual QTL level?

Spike length (SL), spikelet number (SPN) per spike, kernel number per spike (KNPS), and thousand-kernel weight (TKW) have strong genetic associations with kernel weight per spike (KWPS) in wheat. To investigate their genetic relationships at the individual quantitative trait locus (QTL) level, both unconditional and conditional QTL mapping for KWPS with respect to SL, SPN, KNPS, and TKW were conducted. Two related F8:9 recombinant inbred line populations, comprising 485 and 229 lines, respectively, were used. The trait phenotypic performances of each population were evaluated in four different environments. Unconditional QTL mapping analysis identified 22 putative additive QTL for KWPS, five of which were stable QTL, and only QKwps-WJ-1B.2 showed significant additive-by-environment interaction effects. In comparison with unconditional QTL mapping analysis, conditional QTL mapping analysis indicated that, at the QTL level, KNPS and TKW contributed more to KWPS than did SL and SPN. Any unconditional QTL for KWPS detected in this study was associated with at least one of its four related traits. The present study will provide assistance in the understanding of the genetic relationships between KWPS and its related traits.

Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?

Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F(8:9) recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.

Design III with marker loci.

Design III is an experimental design originally proposed by R.E. COMSTOCK and H.F. ROBINSON for estimating genetic variances and the average degree of dominance for quantitative trait loci (QTL) and has recently been extended for mapping QTL. In this paper, we first extend COMSTOCK and ROBINSON's analysis of variance to include linkage, two-locus epistasis and the use of F3 parents. Then we develop the theory and statistical analysis of orthogonal contrasts and contrast x environment interaction for a single marker locus to characterize the effects of QTL. The methods are applied to the maize data of C.W. STUBER. The analyses strongly suggest that there are multiple linked QTL in many chromosomes for several traits examined. QTL effects are largely environment-independent for grain yield, ear height, plant height and ear leaf area and largely environment dependent for days to tassel, grain moisture and ear number. There is significant QTL epistasis. The results are generally in favor of the hypothesis of dominance of favorable genes to explain the observed heterosis in grain yield and other traits, although epistasis could also play an important role and overdominance at individual QTL level can not be ruled out.