Quantitative Trait Loci For Content Research Articles

Genetic Loci Mining and Candidate Gene Analysis for Determining Fatty Acid Composition in Rice

Fatty acid composition and its proportions are critical to the nutritional value and storage quality of rice (Oryza sativa L.) as the third major nutrient component in this staple food. This study involved crossing an indica rice variety, Huazhan (HZ), as the male parent, with a japonica variety, Nekken2, as the female parent, to produce the F1 generation. Subsequently, a population of 120 recombinant inbred lines (RILs) was developed through multiple generations of self-breeding. By utilizing a high-density molecular genetic linkage map and phenotypic data of four fatty acid components, we identified a total of 14 quantitative trait loci (QTLs) related to fatty acid composition across chromosomes 1, 3, 4, 6, 8, and 9. These included two QTLs for C14 content, three for C16:0 content, six for C18:1 content, and three for C18:2 content. Notably, the QTL qCOPT4.2 exhibited a high LOD score of 5.22. Within QTL intervals, genes such as OsACX3 and SLG affecting grain length were identified. The expression of candidate genes within these intervals was assessed and further analyzed by using quantitative real-time PCR. Genes such as LOC_Os01g15000, LOC_Os04g47120, LOC_Os04g49194, LOC_Os06g22080, LOC_Os06g23870, LOC_Os06g24704, LOC_Os06g30780, LOC_Os08g44840, and LOC_Os09g36860 were found to regulate fatty acid synthesis or metabolic pathways, potentially enhancing fatty acid content in rice. These QTLs are indispensable for breeding rice varieties with improved fatty acid profiles, offering new genetic resources for enhancing the nutritional and storage qualities of rice.

Validation and identification of new QTLs for plant and fruit developmental and composition traits in eggplant under low N conditions

Enhancing plant adaptation to low input conditions is a fundamental goal for implementing sustainable agriculture. In the present study, two eggplant (Solanum melongena) accessions (MEL1 and MEL5), two introgression lines (ILs) derived from eggplant wild relatives S. dasyphyllum (IL-M1-D1) and S. insanum (IL-M5-I9), and a heterozygous version of this last IL (ILHet-M5-I9), along with hybrids among them were evaluated under low N (LN) conditions. IL-M1-D1 carries an introgressed fragment of 4.9 Mb in homozygosis from S. dasyphyllum on chromosome 2, while IL-M5-I9 and ILHet-M5-I9 carry an introgression of 21.5 Mb on chromosome 9 in homozygosis and heterozygosis, respectively, from S. insanum. Multiple quantitative trait loci (QTLs) for several traits of interest were associated with both introgressions under LN conditions in a previous study with segregating advanced backcrosses. Here we evaluated the performance of these materials for 22 agronomic and developmental traits under low N fertilization (LN) conditions. Hybrids with the ILs enabled the study of genetic background effects on QTLs expression. The materials evaluated showed a significant phenotypic variation, particularly within hybrids segregating for the introgression from S. insanum in chromosome 9. Statistical analysis revealed no significant differences among hybrids carrying or not the introgression on chromosome 2 of S. dasyphyllum, and only slight differences were observed between the IL-M1-D1 and its recurrent parent S. melongena MEL1, suggesting a limited impact of this introgression on chromosome 2 on the phenotype variation. However, the differences observed between IL-M5-I9 and its recurrent parent S. melongena MEL5, together with the association between genotypic and phenotypic variation in hybrids segregating for this introgression, allowed the identification of 13 QTLs on chromosome 9. These results successfully validated the previously identified QTLs for flavonol content in leaves, nitrogen balanced index, fruit mean weight, and nitrogen content in leaves and, also revealed nine new QTLs associated with the introgressed genomic region in chromosome 9. This study emphasizes the influence of environmental conditions, genotypes, and genetic backgrounds on the phenotypic expression of eggplant QTLs introgressed from wild relatives and highlights the importance of QTL validation. These findings contribute valuable insights for developing new eggplant cultivars for a more sustainable agriculture, particularly with adaptation to LN conditions.

Genetic analysis of QTLs for lysine content in four maize DH populations

BackgroundLow levels of the essential amino acid lysine in maize endosperm is considered to be a major problem regarding the nutritional quality of food and feed. Increasing the lysine content of maize is important to improve the quality of food and feed nutrition. Although the genetic basis of quality protein maize (QPM) has been studied, the further exploration of the quantitative trait loci (QTL) underlying lysine content variation still needs more attention.ResultsEight maize inbred lines with increased lysine content were used to construct four double haploid (DH) populations for identification of QTLs related to lysine content. The lysine content in the four DH populations exhibited continuous and normal distribution. A total of 12 QTLs were identified in a range of 4.42–12.66% in term of individual phenotypic variation explained (PVE) which suggested the quantitative control of lysine content in maize. Five main genes involved in maize lysine biosynthesis pathways in the QTL regions were identified in this study.ConclusionsThe information presented will allow the exploration of candidate genes regulating lysine biosynthesis pathways and be useful for marker-assisted selection and gene pyramiding in high-lysine maize breeding programs.

Characterisation of a major QTL for sodium accumulation in tomato grown in high salinity.

Soil salinity is a serious concern for tomato culture, affecting both yield and quality parameters. Although some genes involved in tomato salt tolerance have been identified, their genetic diversity has been rarely studied. In the present study, we assessed salt tolerance-related traits at juvenile and adult stages in a large core collection and identified salt tolerance quantitative trait loci (QTLs) by genome-wide association study (GWAS). The results suggested that a major QTL is involved in leaf sodium accumulation at both physiological stages. We were able to identify the underlying candidate gene, coding for a well-known sodium transporter, called SlHKT1.2. We showed that an eQTL for the expression of this gene in roots colocalized with the above ground sodium content QTL. A polymorphism putatively responsible for its variation was identified in the gene promoter. Finally, to extend the applicability of these results, we carried out the same analysis on a test-cross panel composed of the core collection crossed with a distant line. The results indicated that the identified QTL retained its functional impact even in a hybrid genetic context: this paves the way for its use in breeding programs aimed at improving salinity tolerance in tomato cultivars.

Two dwarfing genes Rht-B1b and Rht-D1b show pleiotropic effects on grain protein content in bread wheat (Triticum aestivum L.).

Five QTL for wheat grain protein content were identified, and the effects of two dwarfing genes Rht-B1b and Rht-D1b on grain protein content were validated in multiple populations. Grain protein content (GPC) plays an important role in wheat quality. Here, a recombinant inbred line (RIL) population derived from a cross between Yangmai 12 (YM12) and Yanzhan 1 (YZ1) was used to identify quantitative trait loci (QTL) for GPC. Two hundred and five RILs and their parents were grown in three years in randomized complete blocks each with two replications, and genotyped using the wheat 55K SNP array. Five QTL were identified for GPC on chromosomes 1A, 1B, 2D, 4B, and 4D. Notably, QGpc.yaas-4B (co-located with Rht-B1) and QGpc.yaas-4D (co-located with Rht-D1) were consistently detected across all experiments and best linear unbiased estimating, accounting for 6.61-8.39% and 6.05-10.21% of the phenotypic variances, respectively. The effects of these two dwarfing alleles Rht-B1b and Rht-D1b on reducing GPC and plant height were validated in two additional RIL populations and one natural population. This study lays a foundation for further investigating the effects of dwarfing genes Rht-B1b and Rht-D1b on wheat GPC.

Identification of QTLs and candidate genes for water-soluble protein content in soybean seeds

Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15–11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

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

Increasing oil content is a key objective in peanut breeding programs. Accurate identification of quantitative trait loci (QTLs) with linked markers for oil content can greatly aid in marker-assisted selection for high-oil breeding. In this study, a high-density bin map was constructed by resequencing a recombinant inbred line (RIL) population (ZH16×J11) consisting of 295 lines. The bin map contained 4,212 loci and had a total length of 1,162.3 cM. Ten QTLs for oil content were identified in six linkage groups. Notably, two of these QTLs, qOCB03.1 and qOCB06.1, were consistently detected in a minimum of three environments and explained up to 13.62% of phenotypic variation. They have not been reported in previous studies and thus are novel QTLs. The combination of favorable alleles from the qOCB03.1 and qOCB06 in the RIL population could increase oil content across multiple environments from 1.50 to 2.46%. Two InDel markers linked to qOCB03.1 and qOCB06.1 were developed and validated to be associated with oil content in another RIL population (ZH10×ICG12625) with diverse phenotypes. Additionally, the high-resolution map allowed for the precise positioning of qOCB03.1 and qOCB06.1 within a 1.77 Mb-interval on chromosome B03 and a 1.51 Mb- interval on chromosome B06, respectively. Annotation of genomic variants, analysis of transcriptome sequencing, and evaluation of the allelic effects in 292 peanut varieties revealed two candidate genes associated with oil content for each of the two QTLs. The identification of candidate genes in this study can enable the map-based cloning of key genes controlling oil content in peanut. Furthermore, these novel and stable QTLs and their tightly linked markers are valuable for marker-assisted breeding for increased oil content in peanut.

QTL Analysis of β-Glucan Content and Other Grain Traits in a Recombinant Population of Spring Barley.

Barley with high grain β-glucan content is valuable for functional foods. The identification of loci for high β-glucan content is, thus, of great importance for barley breeding. Segregation mapping for the content in β-glucan and other barley grain components (starch, protein, lipid, ash, phosphorous, calcium, sodium) was performed using the progeny of the cross between Glacier AC38, a mutant with high amylose, and CDC Fibar, a high β-glucan waxy cultivar. The offspring of this cross showed transgressive segregation for β-glucan content. Linkage analysis based on single-nucleotide polymorphism (SNP) molecular markers was used for the genotyping of the parents and recombinant inbred lines (RILs). Two Quantitative Trait Loci (QTL) for β-glucan content and several QTL for other grain components were found. The former ones, located on chromosomes 1H and 7H, explained 27.9% and 27.4% of the phenotypic variance, respectively. Glacier AC38 provided the allele for high β-glucan content at the QTL on chromosome 1H, whereas CDC Fibar contributed the allele at the QTL on chromosome 7H. Their recombination resulted in a novel haplotype with higher β-glucan content, up to 18.4%. Candidate genes are proposed for these two QTL: HvCslF9, involved in β-glucan biosynthesis, for the QTL on chromosome 1H; Horvu_PLANET_7H01G069300, a gene encoding an ATP-Binding Cassette (ABC) transporter, for the QTL on chromosome 7H.

Selective allele stacking of a novel quantitative trait locus facilitates the enhancement of seed epicatechin content in soybean (Glycine max (L.) Merr.)

(-)-Epicatechin (EC), a primary form of flavan-3ol and a building block of proanthocyanidins, has health benefits as it is a potent antioxidant. So far, no quantitative trait loci (QTLs) associated with EC have yet been identified in soybean. In this study, QTLs for EC and hilum color were identified in recombinant inbred lines (RILs) derived from the varieties Jinpung and IT109098 using high-resolution single nucleotide polymorphism linkage mapping. This revealed two major QTLs for EC content, qEC06 and qEC08. qEC06 spanned the Tawny (T) locus encoding flavonoid 3′-hydroxylase. qEC08, located near the Inhibitor (I) locus on Chr08, was also a major QTL for hilum color; however, allelic stacking of qEC08 and I revealed no relationship between I and EC content. RILs with IT109098 alleles at both qEC06 and qEC08 had higher EC content than other lines. These results will enable the production of soybean varieties with high EC content via marker-assisted selection.

Detection of two homologous major QTLs and development of diagnostic molecular markers for sucrose content in peanut.

We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.

Identification of Quantitative Trait Loci (QTL) for Sucrose and Protein Content in Soybean Seed.

Protein and sugar content are important seed quality traits in soybean because they improve the value and sustainability of soy food and feed products. Thus, identifying Quantitative Trait Loci (QTL) for soybean seed protein and sugar content can benefit plant breeders and the soybean market by accelerating the breeding process via marker-assisted selection. For this study, a population of recombinant inbred lines (RILs) was developed from a cross between R08-3221 (high protein and low sucrose) and R07-2000 (high sucrose and low protein). Phenotypic data for protein content were taken from the F2:4 and F2:5 generations. The DA7250 NIR analyzer and HPLC instruments were used to analyze total seed protein and sucrose content. Genotypic data were generated using analysis via the SoySNP6k chip. A total of four QTLs were identified in this study. Two QTLs for protein content were located on chromosomes 11 and 20, and two QTLs associated with sucrose content were located on chromosomes 14 and. 11, the latter of which co-localized with detected QTLs for protein, explaining 10% of the phenotypic variation for protein and sucrose content in soybean seed within the study population. Soybean breeding programs can use the results to improve soybean seed quality.

Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.).

The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.

Identification of oil content QTL on Arahy12 and Arahy16 and development of KASP markers in cultivated peanut (Arachis hypogaea L.)

Peanut kernels rich in oil, particularly those with oleic acid as their primary fatty acid, are sought after by consumers, the food industry, and farmers due to their superior nutritional content, extended shelf life, and health benefits. The oil content and fatty acid composition are governed by multiple genetic factors. Identifying the quantitative trait loci (QTL) related to these attributes would facilitate marker-assisted selection or genomic selection, thus enhancing the quality-focused peanut breeding program. For this purpose, we developed a population of 521 recombinant inbred lines (RIL) and tested their kernel quality traits across five different environments. We identified two major and stable QTLs for oil content (qOCAh12.1 and qOCAh16.1). The markers linked to these QTLs were designed by competitive allele-specific PCR (KASP) and were subsequently validated. Moreover, we found that the superior haplotype of oil content in the qOCAh16.1 region was conserved within the PI germplasm cluster, as evidenced by a diverse peanut accession panel. In addition, we determined that qAh09 and qAh19.1, which harbor the key gene encoding fatty acid desaturase 2 (FAD2), influence all seven fatty acids, including palmitic, stearic, oleic, linoleic, arachidic, gadoleic, and behenic acids. As for protein content and the long-chain saturated fatty acid behenic acid, qAh07 emerged as the major and stable QTLs, accounting for over 10% of the phenotypic variation explained (PVE). These findings would enhance marker-assisted selection in peanut breeding, aiming to improve oil content, and deepen our understanding of the genetic mechanisms that shape fatty acid composition.

Integrated analysis of transcriptomic and small RNA sequencing data provides miRNA candidates for engineering agronomically important seed traits in Brassica juncea

Brassica juncea L. is an important oilseed crop that yields edible oil and biofuel. Improving B. juncea seed traits is a primary breeding target, but these traits are genetically complex. MicroRNAs (miRNAs) regulate seed development by modulating gene expression at the post-transcriptional or translational level and are excellent candidates for improving seed traits. However, the roles of miRNAs in B. juncea seed development are yet to be investigated. Here, we report small RNA profiling and miRNA identification from developing seeds of two contrasting varieties of B. juncea, Early Heera2 (EH2) and Pusa Jaikisan (PJK). We identified 326 miRNAs, including 127 known and 199 novel miRNAs, of which 103 exhibited inter-varietal differential expression. Integrating miRNAome and our previous transcriptome data identified 13,683 putative miRNA-target modules. Segregation of differentially expressed miRNAs into different groups based on variety-wise upregulation, followed by comprehensive functional analysis of targets using pathway mapping, gene ontology, transcription factor mapping, and candidate gene analysis, revealed at least 11, 6, and 7 miRNAs as robust candidates for the regulation of seed size, seed coat color, and oil content, respectively. Further, co-localization with previously reported quantitative trait loci (QTL) proffered 29 and 15 miRNAs overlapping with seed weight and oil content QTLs, respectively. Our study is the first comprehensive report of miRNAome expression dynamics from developing seeds and provides candidate miRNAs and target genes for engineering seed traits in B. juncea.

QTL Mining and Validation of Grain Nutritional Quality Characters in Rice (Oryza sativa L.) Using Two Introgression Line Populations

Nutritional grain quality is mainly influenced by the protein fraction content and grain protein content. Quantitative trait loci (QTL) mining for five traits, about 245 and 284 BC3F3 individual families of two introgression line (IL) populations were derived from Kongyu 131/Cypress (population-I) and Kongyu 131/Vary Tarva Osla (population-II), respectively. A genetic linkage map was developed using 127 simple sequence repeat (SSR) markers in population-I and 119 SSR markers in population-II. In total, 20 and 5 QTLs were detected in population-I and population-II, respectively. About twenty QTLs were mapped in population-I: five QTLs for albumin, seven QTLs for globulin, six QTLs for prolamin, one QTL for glutelin, and one QTL for grain protein content. In total, five QTLs were mapped in population-II: one QTL for albumin and four QTLs for grain protein content. Out of 25 QTLs, 19 QTLs exhibit co-localization with the previously reported QTLs. QTL-like qGPC7.3 was delineated for total protein content. This QTL was derived from population-I and was successfully validated in NILs (near-isogenic lines). The grain protein phenotype showed a significant variation between two NILs. This investigation serves as groundwork for additional cloning of nutritional quality-related genes in rice grains.

Genetic dissection of QTLs for oil content in four maize DH populations.

Oil is one of the main components in maize kernels. Increasing the total oil content (TOC) is favorable to optimize feeding requirement by improving maize quality. To better understand the genetic basis of TOC, quantitative trait loci (QTL) in four double haploid (DH) populations were explored. TOC exhibited continuously and approximately normal distribution in the four populations. The moderate to high broad-sense heritability (67.00-86.60%) indicated that the majority of TOC variations are controlled by genetic factors. A total of 16 QTLs were identified across all chromosomes in a range of 3.49-30.84% in term of phenotypic variation explained. Among them, six QTLs were identified as the major QTLs that explained phenotypic variation larger than 10%. Especially, qOC-1-3 and qOC-2-3 on chromosome 9 were recognized as the largest effect QTLs with 30.84% and 21.74% of phenotypic variance, respectively. Seventeen well-known genes involved in fatty acid metabolic pathway located within QTL intervals. These QTLs will enhance our understanding of the genetic basis of TOC in maize and offer prospective routes to clone candidate genes regulating TOC for breeding program to cultivate maize varieties with the better grain quality.

Quantitative Trait Loci Mapping of Grain Lipid Content in Rice Variety ‘Goudang 3’ Using Genome Re-Sequencing

Fat is the third largest substance in rice seeds, and its content has a great impact on rice cooking, taste and storage qualities. However, few genes related to seed fat content have been cloned, which seriously restricts the application of fat traits in high-quality rice breeding. ‘Goudang 3’ is a representative aromatic rice landrace of Guizhou He, a characteristic rice species resource in Guizhou Province, China. It has the advantages of high fat content, rich flavor, soft and glutinous taste, etc. In this work, to address this issue, from a high-fat content rice variety, Goudang 3, and a low-fat content rice variety, Huazhan, a 148 recombinant inbred lines (RILs) population were derived. A high-density genetic map with 4063 Bin Markers covering 12 chromosomes were constructed through simplified genotyping-by-sequencing (GBS) technology. In combination with fat content, a brown rice fat content quantitative trait loci (QTL) qCFC3 was mapped within the 492 kb interval on chromosome 3. The qCFC3 was consistent with the previous reporting site, and no cloned fat content-related genes have been reported. LOC_Os03g13630 was identified. In conclusion, these QTL and candidate gene can be used for improving rice quality and can lay a foundation for further cloning and functional analysis.

Genetic Dissection and Germplasm Selection of the Low Crude Fiber Component in Brassica napus L. Shoots.

Brassica napus is one of the most important oil crops in the world, and B. napus shoots are nutrient-rich fresh vegetables. The crude fiber (CF) component is one of the most important factors affecting the taste quality of B. napus shoots, but the factors underlying the desirable low-CF trait remain poorly understood. In this study, a high-density single-nucleotide polymorphism (SNP) map was used to map quantitative trait loci (QTLs) for five CF-related traits in a recombinant inbred population. A total of 49 QTLs were obtained in four environments, including eleven, twelve, eight, twelve and six QTLs for content of neutral detergent fiber, acid detergent fiber, acid detergent lignin, hemicellulose and cellulose, respectively. The phenotypic variation explained by single QTL ranged from 4.62% to 14.76%. Eight of these QTLs were further integrated into four unique QTLs, which controlled two different traits simultaneously. Five CF-component-related candidate genes were identified, among which BnaC03g07110D and BnaC07g21271D were considered to be the most likely candidate genes. In addition, five lines with low CF content were selected, which can be used as excellent germplasm resources in breeding. The QTLs identified in this study will contribute to our understanding of the genetic mechanism of CF and can be used as targets for reducing CF content in B. napus shoots. In addition, this study also provided excellent germplasm resources for low CF content breeding.

Genetic dissection of QTLs for starch content in four maize DH populations.

Starch is the principal carbohydrate source in maize kernels. Understanding the genetic basis of starch content (SC) benefits greatly in improving maize yield and optimizing end-use quality. Here, four double haploid (DH) populations were generated and were used to identify quantitative trait loci (QTLs) associated with SC. The phenotype of SC exhibited continuous and approximate normal distribution in each population. A total of 13 QTLs for SC in maize kernels was detected in a range of 3.65–16.18% of phenotypic variation explained (PVE). Among those, only some partly overlapped with QTLs previously known to be related to SC. Meanwhile, 12 genes involved in starch synthesis and metabolism located within QTLs were identified in this study. These QTLs will lay the foundation to explore candidate genes regulating SC in maize kernel and facilitate the application of molecular marker-assisted selection for a breeding program to cultivate maize varieties with a deal of grain quality.

Stable sorghum grain quality QTL were identified using SC35 × RTx430 mapping population.

Understanding the genetic control and inheritance of grain quality traits is instrumental in facilitating end-use quality improvement. This study was conducted to identify and map quantitative trait loci (QTL) controlling protein, starch, and amylose content in grain sorghum [Sorghum bicolor (L.) Moench] grown under variable environmental conditions. A recombinant inbred line (RIL) population derived from a cross between RTx430 and SC35 was evaluated in six environments across Hays and Manhattan, KS. Significant variation was observed in genotype, environment, and genotype × environment interaction for all three quality traits. Unlike the RILs, the two parental lines did not show significant differences for these traits. However, significant transgressive segregation was observed for all traits resulting in phenotypic performance extending beyond the two parents. A total of seven protein, 10 starch, and 10 amylose content QTL were identified. Chromosomal regions and phenotypic variation (PVE) of QTL were variable across growing conditions. Quantitative trait loci hotspots for all three traits were detected on chromosomes 1 (115.2-119.2 cM) and 2 (118.2-127.4 cM). Candidate gene analysis indicated that these QTL hotspots were conditioned by several transcription factors, such as Cytochrome P450 and basic helix-loop-helix DNA binding protein, which regulate starch and protein accumulation in the grain. The identified genomic regions and underlying candidate genes provide a starting point for further validation and marker-assisted gene pyramiding to improve sorghum grain quality.