Detection of quantitative trait loci controlling soybean protein, oil and amino acid content in a recombinant inbred line population

Seed protein and oil content are the two important traits determining the quality and value of soybean. Development of improved cultivars requires detailed understanding of the genetic basis underlying the trait of interest. However, it is prerequisite to have a high-density linkage map for precisely mapping genomic regions, and therefore the present study used high-density genetic map containing 2267 recombination bin markers distributed on 20 chromosomes and spanned 2453.79 cM with an average distance of 1.08 cM between markers using restriction-site-associated DNA sequencing (RAD-seq) approach. A recombinant inbred line (RIL) population of 104 lines derived from a cross between Linhefenqingdou and Meng 8206 cultivars was evaluated in six different environments to identify main- and epistatic-effect quantitative trait loci (QTLs)as well as their interaction with environments. A total of 44 main-effect QTLs for protein and oil content were found to be distributed on 17 chromosomes, and 15 novel QTL were identified for the first time. Out of these QTLs, four were major and stable QTLs, viz., qPro-7-1, qOil-8-3, qOil-10-2 and qOil-10-4, detected in at least two environments plus combined environment with R2 values >10%. Within the physical intervals of these four QTLs, 111 candidate genes were screened for their direct or indirect involvement in seed protein and oil biosynthesis/metabolism processes based on gene ontology and annotation information. Based on RNA sequencing (RNA-seq) data analysis, 15 of the 111 genes were highly expressed during seed development stage and root nodules that might be considered as the potential candidate genes. Seven QTLs associated with protein and oil content exhibited significant additive and additive × environment interaction effects, and environment-independent QTLs revealed higher additive effects. Moreover, three digenic epistatic QTLs pairs were identified, and no main-effect QTLs showed epistasis. In conclusion, the use of a high-density map identified closely linked flanking markers, provided better understanding of genetic architecture and candidate gene information, and revealed the scope available for improvement of soybean quality through marker assisted selection (MAS).

Intumescence is a physiological disorder in tomato and other plant species that encompasses callus formation on leaves and stems. Next to a genetic predisposition, it has also been shown to be influenced by environmental factors like light spectrum. We grew tomato plants of four different recombinant inbred line (RIL) populations under high‐pressure sodium (HPS) and red/blue LED supplemental lighting in a greenhouse and determined the severity of intumescence on 4‐week‐old plants, in three subsequent replicates. The intumescence severity was scored on a scale from 0 to 3. The severity of intumescence was highly genotype dependent in three out of the four tested tomato populations, with the heritability ranging from 54% to 83%. In those three populations, two to eight QTL for intumescence were identified. One major effect quantitative trait locus (QTL) on the top of chromosome 1 was at a similar position in two genetically different RIL populations. The amount of genetic variation explained for these QTL ranged from 30% to 70% depending on the population. Next to chromosomal influences, we also identified differences in effects from maternal plastids on intumescence, by using reciprocal crosses. The cultivation of the tomato plants under HPS lamps or under red/blue LED supplemental lighting had no significant influence on intumescence score. All major QTLs appeared to be reproducible among the three replicates and among the two light conditions. Significant, though, low negative correlations were identified between the intumescence score and the area of leaves, chlorophyll content index, photosynthesis efficiency and fresh weight to dry weight ratio, which can reflect possible effects of the disorder on multiple aspects of plant performance.

Peanut (Arachis hypogaea L.) is an important row crop rich in oil, protein, vitamins and other micro-nutrients. The intensive selection of the cultigen, a cultivated plant deliberately altered by humans through cultivation, has resulted in favourable changes in yield and biochemical composition. Nevertheless, it has generated a narrow genetic basis that limits the development of new varieties with resistance to pests, diseases and environmental stresses. In this study, we address this limitation by characterizing the proximate and fatty acid composition of a multi-disease-resistant interspecific recombinant inbred line (RIL) population derived from three wild Arachis species and a cultivated elite peanut line that is being used to widen the genetic basis of the crop. The population was also genotyped with the Axiom Arachis 48K SNP array and used to detect quantitative trait loci (QTL) for oil, protein content and oleic and linoleic fatty acid percentages. A wide range of proximate composition was found in the RIL population. Eighteen and 11 individuals had high oil and protein content, respectively, and no undesirable traits related to oil quality had been introduced into the population from wild species. The fatty acid composition of oleic and linoleic acids was found to be regulated by two major QTL. The discovery of markers within the major effect QTL for the most significant chemical traits provides new opportunities for the creation of resistant and extremely nutrient-dense peanut cultivars.

Khanal, R., Navabi, A. and Lukens, L. 2015. Linkage map construction and quantitative trait loci (QTL) mapping using intermated vs. selfed recombinant inbred maize line (Zea mays L.). Can. J. Plant Sci. 95: 1133–1144. Intermating of individuals in an F2 population increases genetic recombination between markers, which is useful for linkage map construction and quantitative trait loci (QTL) mapping. The objectives of this study were to compare the linkage maps and precision of QTL detection in an intermated recombinant inbred line (IRIL) population and a selfed recombinant inbred line (RIL) population. Both, IRIL and RIL, populations were developed from Zea mays inbred lines CG60 and CG102. The populations were grown in two environments to evaluate traits, and inbred lines from each population were genotyped with SSR and SNP markers for linkage map construction and QTL identification. In addition, we simulated RIL and IRIL populations from two inbred parents to compare the precision of QTL detection between simulated RIL and IRIL populations. In the empirical study, the linkage map was longer in RIL as compared with IRIL, and the average QTL support interval was reduced by 1.37-fold in the IRIL population compared with the RIL population. We detected 16 QTL for flowering time, plant height, leaf number, and stay green in at least one recombinant inbred line population. Two out of 16 QTL were shared between two recombinant inbred line populations. In the simulation study, the QTL support interval was reduced by 1.66-fold in the IRIL population as compared with the RIL population and linked QTL were identified more frequently in IRIL population as compared with RIL population. This study supports the utility of intermated RIL populations for precise QTL mapping.

The study was undertaken to identify the quantitative trait loci (QTLs) governing yield and its related traits using a recombinant inbred line (RIL) population derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R). A genetic map spanning 294.2 cM was constructed with 126 simple sequence repeats (SSR) loci uniformly distributed across the rice genome. QTL analysis using phenotyping and genotyping information identified a total of 22 QTLs. Of these, five major effect QTLs were identified for the following traits: total grain yield/plant (qYLD3-1), panicle weight (qPW3-1), plant height (qPH12-1), flag leaf width (qFLW4-1) and panicle length (qPL3-1), explaining 20.23–22.76% of the phenotypic variance with LOD scores range of 6.5–10.59. Few genomic regions controlling several traits (QTL hotspot) were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1). Significant epistatic interactions were also observed for total grain yield per plant (YLD) and panicle length (PL). While most of these QTLs were observed to be co-localized with the previously reported QTL regions, a novel, major QTL associated with panicle length (qPL3-1) was also identified. SNP genotyping of selected high and low yielding RILs and their QTL mapping with 1,082 SNPs validated most of the QTLs identified through SSR genotyping. This facilitated the identification of novel major effect QTLs with much better resolution and precision. In-silico analysis of novel QTLs revealed the biological functions of the putative candidate gene (s) associated with selected traits. Most of the high-yielding RILs possessing the major yield related QTLs were identified to be complete restorers, indicating their possible utilization in development of superior rice hybrids.

Key messageGenomic regions associated with seed protein, oil and amino acid contents were identified by genome-wide association analyses. Geographic distributions of haplotypes indicate scope of improvement of these traits.Soybean [Glycine max (L.) Merr.] protein and oil are used worldwide in feed, food and industrial materials. Increasing seed protein and oil contents is important; however, protein content is generally negatively correlated with oil content. We conducted a genome-wide association study using phenotypic data collected from five environments for 621 accessions in maturity groups I–IV and 34,014 markers to identify quantitative trait loci (QTL) for seed content of protein, oil and several essential amino acids. Three and five genomic regions were associated with seed protein and oil contents, respectively. One, three, one and four genomic regions were associated with cysteine, methionine, lysine and threonine content (g kg−1 crude protein), respectively. As previously shown, QTL on chromosomes 15 and 20 were associated with seed protein and oil contents, with both exhibiting opposite effects on the two traits, and the chromosome 20 QTL having the most significant effect. A multi-trait mixed model identified trait-specific QTL. A QTL on chromosome 5 increased oil with no effect on protein content, and a QTL on chromosome 10 increased protein content with little effect on oil content. The chromosome 10 QTL co-localized with maturity gene E2/GmGIa. Identification of trait-specific QTL indicates feasibility to reduce the negative correlation between protein and oil contents. Haplotype blocks were defined at the QTL identified on chromosomes 5, 10, 15 and 20. Frequencies of positive effect haplotypes varied across maturity groups and geographic regions, providing guidance on which alleles have potential to contribute to soybean improvement for specific regions.

Improvement in grain yield is an important objective in high-oil maize breeding. In this study, one high-oil maize inbred was crossed with two normal maize inbreds to produce two connected recombinant inbred line (RIL) populations with 282 and 263 F7:8 families, respectively. The field experiments were conducted under four environments, and eight grain yield components and grain oil content were evaluated. Two genetic linkage maps were constructed using 216 and 208 polymorphic SSR markers. Quantitative trait loci (QTL) were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL in both populations. A total of 199 QTL were detected, 122 in population 1 and 87 in population 2. Seven, 11 and 19 QTL showed consistency across five environments, across two RIL populations and with respective F2:3 generations, respectively. 183 QTL were integrated in 28 meta-QTL (mQTL). QTL with contributions over 15% were consistently detected in 3–4 cases and integrated in mQTL. Each mQTL included 3–19 QTL related to 1–4 traits, reflecting remarkable QTL co-location for grain yield components and oil content. Further research and marker-assisted selection (MAS) should be concentrated on 37 consistent QTL and four genetic regions of mQTL with more than 10 QTL at bins 3.04–3.05, 7.02, 8.04–8.05 and 9.04–9.05. Near-isogenic lines for 100-grain-weight QTL at bin 7.02–7.03, for ear-length QTL at bin 7.02–7.03 and for rows-per-ear QTL at bin 3.08 are now in construction using MAS. Co-located candidate genes could facilitate the identification of candidate genes for grain yield in maize.

High-resolution mapping through whole-genome resequencing identifies two novel QTLs controlling oil content in peanut

The relatively low genomic variation of current U.S. soybean [Glycine max (L.) Merill] cultivars constrains the improvement of grain yield, seed quality, and other agronomic traits within soybean breeding programs. Recently, a substantial effort has been undertaken to introduce novel genetic diversity present in wild soybean (Glycine soja Siebold and Zucc.) into new elite cultivars, in both public and private applied soybean breeding programs. The objectives of this research were to evaluate the phenotypic diversity within a core collection of 80 G. soja plant introductions (PIs) in the United States Department of Agriculture National Genetic Resources Program that were collected in China, Japan, Russia, and South Korea, and to analyze the correlations between agronomic and seed composition traits. Field tests were conducted in Missouri and North Carolina during three years, 2013, 2014, and 2015, in a randomized complete block design (n=3). The phenotypic data collected included plant maturity date, seed weight, and the seed concentration of protein, oil, essential amino acid, fatty acid, and soluble carbohydrates. Analyzing the data from six environments, we found genotype was a significant (p less than 0.0001) source of variation for maturity date, seed weight, seed protein and amino acids, seed oil and fatty acids, and seed carbohydrates. Significant correlations were observed between numerous traits. The core collection had lower seed weight, higher seed content of protein, linolenic acid, raffinose and stachyose but lower seed content of oil and oleic acid than those of the cultivated soybean lines that were used as checks. The amino acid profile of the core collection was significantly different from that of the checks. An association analysis revealed 19 SNP that were significantly associated with maturity, seed weight, and seed contents of aspartic acid, glutamine, palmitic acid, oleic acid, and linoleic acid. The information and data collected in this study will be invaluable in guiding soybean breeders and geneticists in selecting promising Glycine soja plant introductions for research and cultivar improvement. In addition the identification of quantitative trait loci (QTLs) associated with the contents of seed protein and oil, maturity, branching traits, height, lodging, and yield in a recombinant inbred line (RIL) population developed from one single F2 plant from the cross between Osage and PI593983 was carried out. The mapping population in this study included 164 F4:6 recombinant inbred lines (RILs) derived from a cross between Osage, a cultivated soybean variety, and PI593983, a wild soybean accession. Field tests were carried out in Missouri for two years during 2016 and 2017, in a randomized complete block design (n=2). Both protein and oil contents showed high heritabilities. Seed protein and seed oil were negatively correlated (-0.77). A total of 4,374 polymorphic markers were used to construct a genetic linkage map, and nine QTLs for protein content, explained 7.6 to 36.7% of variance, and seven QTLs for oil content, explained for 7.8 to 29.7% of variance, were detected using composite interval mapping. addition we identified eight novel QTLs and confirmed sixteen QTLs associated with maturity (R2 = 6.4 to 26.3%), plant height (R2 = 7.4 to 15.5%), and total branch length (R2 = 9.3% and 14.5%) in individual and across environments, and the ratio of total branch length to plant height (R2 = 11.8%), yield (R2 =12.8 and 15.7), and lodging (R2 = 12.1 and 13.4) in individual studied environments. Sixteen QTLs for maturity, yield, and plant height confirmed previously reported QTLs, and eight QTLs have not been reported before. The results of this study will facilitate the identification of the causative genes for seed protein and oil, maturity, height, lodging, and branching traits, and will help soybean breeder improve soybean performance by developing markers for marker-assisted selection.

Partial resistance to Phytophthora sojae in soybean is controlled by multiple quantitative trait loci (QTL). With traditional QTL mapping approaches, power to detect such QTL, frequently of small effect, can be limited by population size. Joint linkage QTL analysis of nested recombinant inbred line (RIL) populations provides improved power to detect QTL through increased population size, recombination, and allelic diversity. However, uniform development and phenotyping of multiple RIL populations can prove difficult. In this study, the effectiveness of joint linkage QTL analysis was evaluated on combinations of two to six nested RIL populations differing in inbreeding generation, phenotypic assay method, and/or marker set used in genotyping. In comparison to linkage analysis in a single population, identification of QTL by joint linkage analysis was only minimally affected by different phenotypic methods used among populations once phenotypic data were standardized. In contrast, genotyping of populations with only partially overlapping sets of markers had a marked negative effect on QTL detection by joint linkage analysis. In total, 16 genetic regions with QTL for partial resistance against P. sojae were identified, including four novel QTL on chromosomes 4, 9, 12, and 16, as well as significant genotype-by-isolate interactions. Resistance alleles from PI 427106 or PI 427105B contributed to a major QTL on chromosome 18, explaining 10-45% of the phenotypic variance. This case study provides guidance on the application of joint linkage QTL analysis of data collected from populations with heterogeneous assay conditions and a genetic framework for partial resistance to P. sojae.

Chromosome segment substitution lines (CSSLs) are a powerful alternative for locating quantitative trait loci (QTL), analyzing gene interactions, and providing starting materials for map-based cloning projects. We report the development and characterization of a CSSL library of a U.S. weedy rice accession ‘PSRR-1’ with genome-wide coverage in an adapted rice cultivar ‘Bengal’ background. The majority of the CSSLs carried a single defined weedy rice segment with an average introgression segment of 2.8 % of the donor genome. QTL mapping results for several agronomic and domestication traits from the CSSL population were compared with those obtained from two recombinant inbred line (RIL) populations involving the same weedy rice accession. There was congruence of major effect QTLs between both types of populations, but new and additional QTLs were detected in the CSSL population. Although, three major effect QTLs for plant height were detected on chromosomes 1, 4, and 8 in the CSSL population, the latter two escaped detection in both RIL populations. Since this was observed for many traits, epistasis may play a major role for the phenotypic variation observed in weedy rice. High levels of shattering and seed dormancy in weedy rice might result from an accumulation of many small effect QTLs. Several CSSLs with desirable agronomic traits (e.g. longer panicles, longer grains, and higher seed weight) identified in this study could be useful for rice breeding. Since weedy rice is a reservoir of genes for many weedy and agronomic attributes, the CSSL library will serve as a valuable resource to discover latent genetic diversity for improving crop productivity and understanding the plant domestication process through cloning and characterization of the underlying genes.

Protein content (PC) and oil content (OC) are important breeding traits of soybean [Glycine max(L.) Merr.]. Quantitative trait locus (QTL) mapping for PC and OC is important for molecular breeding in soybean; however, the negative correlation between PC and OC influences the accuracy of QTL mapping. In the current study, a four-way recombinant inbred lines (FW-RILs) population comprising 160 lines derived from the cross (Kenfeng14 × Kenfeng15) × (Heinong48 × Kenfeng19) was planted in eight different environments and PC and OC measured. Conditional and unconditional QTL analyses were carried out by interval mapping (IM) and inclusive complete IM based on linkage maps of 275 simple sequences repeat markers in a FW-RILs population. This analysis revealed 59 unconditional QTLs and 52 conditional QTLs among the FW-RILs. An analysis of additive effects indicated that the effects of 13 protein QTLs were not related to OC, whereas OC affected the expression of 13 and eight QTLs either partially or completely, respectively. Eight QTLs affecting OC were not influenced by PC, whereas six and 26 QTLs were partially and fully affected by PC, respectively. Among the QTLs detected in the current study, two protein QTLs and five oil QTLs had not been previously reported. These findings will facilitate marker-assisted selection and molecular breeding of soybean.

Improving seed composition and quality, including protein, oil, fatty acid, and amino acid contents, is an important goal of soybean farmers and breeders. The aim of this study was to map the quantitative trait loci (QTL) underlying the contents of protein, oil, fatty acids, and amino acids with 1510 single nucleotide polymorphism (SNP) markers using the ‘Hamilton’ × ‘Spencer’ recombinant inbred line population (H × S; n = 93). A total of 13 QTL for the traits studied have been mapped on 3 chromosomes (Chr.) of the soybean genome. Three major QTL have been mapped to a 7–13 cM region on Chr. 6. One major QTL for oil content (qOIL001) explained approximately 76% of the total phenotypic variation in this population; the second major QTL for amino acid alanine (Ala; qALA001) explained approximately 74% of the total variation in Ala content; moreover, two major QTL for palmitic acid (qPAL001 and qPAL002) were identified on Chr. 6 and explained approximately 21% of the phenotypic variation in this population. The SNP markers flanking the QTL identified here will be very useful for soybean breeders to develop and select soybean lines with higher seed composition qualities using marker-assisted selection.

Seed size and shape traits are important determinants of seed yield and appearance quality in soybean [Glycine max (L.) Merr.]. Understanding the genetic architecture of these traits is important to enable their genetic improvement through efficient and targeted selection in soybean breeding, and for the identification of underlying causal genes. To map seed size and shape traits in soybean, a recombinant inbred line (RIL) population developed from K099 (small seed size) × Fendou 16 (large seed size), was phenotyped in three growing seasons. A genetic map of the RIL population was developed using 1,485 genotyping by random amplicon sequencing-direct (GRAS-Di) and 177 SSR markers. Quantitative trait locus (QTL) mapping was conducted by inclusive composite interval mapping. As a result, 53 significant QTLs for seed size traits and 27 significant QTLs for seed shape traits were identified. Six of these QTLs (qSW8.1, qSW16.1, qSLW2.1, qSLT2.1, qSWT1.2, and qSWT4.3) were identified with LOD scores of 3.80–14.0 and R2 of 2.36%–39.49% in at least two growing seasons. Among the above significant QTLs, 24 QTLs were grouped into 11 QTL clusters, such as, three major QTLs (qSL2.3, qSLW2.1, and qSLT2.1) were clustered into a major QTL on Chr.02, named as qSS2. The effect of qSS2 was validated in a pair of near isogenic lines, and its candidate genes (Glyma.02G269400, Glyma.02G272100, Glyma.02G274900, Glyma.02G277200, and Glyma.02G277600) were mined. The results of this study will assist in the breeding programs aiming at improvement of seed size and shape traits in soybean.

Two genetic linkage maps based on doubled haploid (DH) and recombinant inbred lines (RILs) populations, derived from the same indica-japonica cross ‘Samgang × Nagdong’, were constructed to analyze the quantitative trait loci (QTLs) affecting agronomic traits in rice. The segregations of agronomic traits in RILs population showed larger variations than those in DH population. A total of 10 and 12 QTLs were identified on six chromosomes using DH population and seven chromosomes using RILs population, respectively. Three stable QTLs including pl9.1, ph1.1, and gwp11.1 were detected through different years. The percentages of phenotypic variation explained by individual QTLs ranged from 8 to 18% in the DH population and 9 to 33% in the RILs population. Twenty-three epistatic QTLs were identified in the DH population, while 21 epistatic QTLs were detected in the RILs population. Epistatic interactions played an important role in controlling the agronomic traits genetically. Four significant main-effect QTLs were involved in the digenic interactions. Significant interactions between QTLs and environments (QE) were identified in two populations. The QTLs affecting grain weight per panicle (GWP) were more sensitive to the environmental changes. The comparison and QTLs analysis between two populations across different years should help rice breeders to comprehend the genetic mechanisms of quantitative traits and improve breeding programs in marker-assisted selection (MAS).