Quantitative trait loci underlying soybean seed tocopherol content with main additive,epistatic and QTL × environment effects

Soybean (Glycine max [L.] Merrill) seeds are a major source of tocopherols (Toc), which could significantly improve immune system health of human and prevent or treat many serious diseases. Selection for higher Toc contents of seeds could increase nutritional value of soybean‐derived food, laying on an important breeding goal for many soybean breeders. The present objectives of the work were to evaluate various genetic effects of QTL associated with individual and total Toc content based on a RIL population (“Beifeng 9” × “Freeborn”) in six environments to improve the efficiency of molecular marker‐assisted selection (MAS) for high‐Toc breeding. The results described that eighteen, thirteen, eleven and thirteen QTL were associated with α‐Toc, γ‐Toc, δ‐Toc and total Toc content, respectively, and have additive main effects (a) and/or additive × environment interaction effects (ae) in certain environments. Among them, four QTL for α‐Toc, two QTL for γ‐Toc, one QTL for δ‐Toc and four QTL for total Toc could increase α‐Toc, γ‐Toc, δ‐Toc and total Toc content via significant a effect, respectively, which have stronger stability in different years and locations. It implied a value for MAS. Additionally, twenty‐five, fifteen, eleven and twenty epistatic pairwise QTL associated with α‐Toc, γ‐Toc, δ‐Toc and total Toc contents, respectively, were detected. The genetic information of the QTL effects obtained here would be beneficial for breeding soybean variety with high‐Toc content by MAS.     

Identification of quantitative trait loci underlying soybean (Glycine max [L.] Merr.) seed weight including main,epistatic and QTL × environment effects in different regions of Northeast China

Seed weight (SW) is the important soybean (Glycine max [L.] Merr.), yield component and also affected the quality of soybean‐derived foods. The aim of this study was to identify the quantitative trait loci (QTL) underlying SW through 112 recombinant inbred lines (RILs) derived from the cross between “Zhongdou27” (G. max, designated by its bigger seed size, 21.9 g/100 seeds) and “Jiunong 20” (G. max, smaller seed size, 17.5 g/100 seeds). Phenotypic data were collected from this RIL population after it was grown in the sixteen tested environments. A total of eight QTL (QSW1‐1, QSW2‐1, QSW2‐2, QSW5‐1, QSW15‐1, QSW17‐1, QSW19‐1 and QSW20‐1) were identified, and they could explain 4.23%–14.65% of the phenotypic variation. Among these eight QTL, three QTL (QSW1‐1 located on the interval of Sat_159‐Satt603 of chromosome (Chr) 1 (LGD1a), QSW19‐1 located on the interval of Sat_340‐Satt523 of Chr 19 (LGL) and QSW20‐1 located on Sat_418‐Sat_105 of Chr 20 (LGI)) were newly identified and could explain 4.235%–10.08%, 8.45%–13.49% and 8.08%–10.18% of the phenotypic variation, respectively. Six of the eight identified QTL including QSW2‐2, QSW5‐1, QSW15‐1, QSW17‐1, QSW19‐1 and QSW20‐1 exhibited a significant additive (a) effect, while two QTL (QSW2‐1 and QSW19‐1) only displayed significant additive‐by‐environment (ae) effects. A total of four epistatic pairwise QTL for SW were identified in the different environments. These eight QTL and their genetic information obtained here were valuable for molecular marker‐assisted selection and the realization of a reasonable SW breeding programme in soybean.     

QTL mapping for capsaicin and dihydrocapsaicin content in a population of Capsicum annuum ‘NB1’ × Capsicum chinense ‘Bhut Jolokia’

Capsaicinoids are pungent compounds used for industrial and medical purposes including food, medicine and cosmetics. The Indian local variety ‘Bhut Jolokia’ (Capsicum chinense Jacq.) is one of the world's hottest chilli peppers. It produces more than one million Scoville heat units (SHUs) in total capsaicinoids. In this study, our goal was to identify quantitative trait loci (QTLs) responsible for the high content of capsaicin and dihydrocapsaicin in ‘Bhut Jolokia’. Capsicum annuum ‘NB1’, a Korean pepper inbred line containing 14 000 SHUs, was used as a maternal line. An F₂ population derived by crossing between ‘NB1’ and ‘Bhut Jolokia’ was generated to map QTLs for capsaicinoids content. A total of 234 markers, including 201 HRM, 21 SSR, 2 CAPS and 10 gene‐based markers of the capsaicinoid synthesis pathway, were mapped. The final map covered a total distance of 1175.2 cM and contained 12 linkage groups corresponding to the basic chromosome number of chilli pepper. Capsaicin and dihydrocapsaicin content were analysed in 175 F₂ pepper fruits using the HPLC method. The maximum total capsaicinoids content was 1389 mg per 100g DW (dry weight), and the minimum content was 11 mg per 100g DW. Two QTLs (qcap3.1 and qcap6.1) for capsaicin content were identified on LG3 and LG6, and two QTLs (qhdc2.1 and qdhc2.2) for dihydrocapsaicin content were located on LG2. We did not detect QTLs for total capsaicinoids content. The QTL positions for capsaicin content were different from those for dihydrocapsaicin content. These results indicate that the complexity of selecting for more pungent chilli peppers must be considered in a chilli pepper breeding programme. The QTL‐linked markers identified here will be helpful to develop more pungent pepper varieties from ‘Bhut Jolokia’, a very hot pepper.     

A SNP genetic linkage map based on the ‘Hamilton’ by ‘Spencer’ recombinant inbred line population identified QTL for seed isoflavone contents in soybean

Soybean is one of the most important crops worldwide for its protein and oil as well as the health beneficial phytoestrogens or isoflavone. This study reports a relatively dense single nucleotide polymorphism (SNP)‐based genetic map based on ‘Hamilton’ by ‘Spencer’ recombinant inbred line population and quantitative trait loci (QTL) for seed isoflavone contents. The genetic map is composed of 1502 SNP markers and covers about 1423.72 cM of the soybean genome. Two QTL for seed isoflavone contents have been identified in this population. One major QTL that controlled both daidzein (qDZ1) and total isoflavone contents (qTI1) was found on LG C2 (Chr 6). And a second QTL for glycitein content (qGT1) was identified on the LG G (Chr 18). These two QTL in addition to others identified in soybean could be used in soybean breeding to optimize isoflavone content. This newly assembled soybean linkage map is a useful tool to identify and map QTL for important agronomic traits and enhance the identification of the genes involved in these traits.     

Mapping quantitative trait loci (QTLs) underlying seed vitamin E content in soybean with main,epistatic and QTL × environment effects

Soybean (Glycine max (L.) Merr.) seed contains small amounts of tocopherol, a non‐enzymatic antioxidant known as lipid‐soluble vitamin E (VE). Dietary VE contributes to a decreased risk of chronic diseases in humans and has several beneficial effects on resistance to stress in plants, and increasing VE content is an important breeding goal for increasing the nutritional value of soybean. In this study, quantitative trait loci (QTLs) underlying VE content with main, epistatic and QTL × environment effects were identified in a population of F_5 : 6 recombinant inbred lines from a cross between ‘Hefeng 25’ (a low‐VE cultivar) and ‘OAC Bayfield’ (a high‐VE cultivar). A total of 18 QTLs were detected that showed additive main effects (a) and/or additive × environment interaction effects (ae) in different environments. Moreover, 19 epistatic pairs of QTLs were found to be associated with α‐tocopherol (α‐Toc), γ‐tocopherol (γ‐Toc), δ‐tocopherol (δ‐Toc) and total VE (TE) contents. The QTLs identified in multienvironments could provide more information about QTL by environment interactions and could be useful for the marker‐assistant selection of soybean cultivars with high seed VE contents.     

QTL mapping of adult‐plant resistance to stripe rust in a ‘Lumai 21 × Jingshuang 16’ wheat population

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a devastating fungal disease in common wheat (Triticum aestivum L.) worldwide. Chinese wheat cultivars ‘Lumai 21’ and ‘Jingshuang 16’ show moderate levels of adult‐plant resistance (APR) to stripe rust in the field, and they showed a mean maximum disease severity (MDS) ranging from 24 to 56.7% and 26 to 59%, respectively, across different environments. The aim of this study was to identify quantitative trait loci (QTL) for resistance to stripe rust in an F₃ population of 199 lines derived from ‘Lumai 21’ × ‘Jingshuang 16’. The F₃ lines were evaluated for MDS in Qingshui, Gansu province, and Chengdu, Sichuan province, in the 2009–2010 and 2010–2011 cropping seasons. Five QTL for APR were detected on chromosomes 2B (2 QTL), 2DS, 4DL and 5DS based on mean MDS in each environment and averaged values from all three environments. These QTL were designated QYr.caas‐2BS.2, QYr.caas‐2BL.2, QYr.caas‐2DS.2, QYr.caas‐4DL.2 and QYr.caas‐5DS, respectively. QYr.caas‐2DS.2 and QYr.caas‐5DS were detected in all three environments, explaining 2.3–18.2% and 5.1–18.0% of the phenotypic variance, respectively. In addition, QYr.caas‐2BS.2 and QYr.caas‐2BL.2 colocated with QTL for powdery mildew resistance reported in a previous study. These APR genes and their linked molecular markers are potentially useful for improving stripe rust and powdery mildew resistances in wheat breeding.     

Mapping quantitative trait loci controlling soybean seed starch content in an interspecific cross of ‘Williams 82’ (Glycine max) and ‘PI 366121’ (Glycine soja)

Seed starch content (SSC) greatly affects the taste, flavour and processing properties of soy foods. The objective in this study was to identify quantitative trait loci (QTL) for SSC in soybean. A total in 169 recombinant inbred lines (RILs) derived from a cross in ‘Williams 82’ and ‘PI 366121’ were grown for three consecutive years. The SSC of the RILs displayed continuous variation with transgressive segregation and hence amenable for QTL mapping. Nine significant QTL exhibiting 5.6–11.3% of the total phenotypic variation (PVE) were identified. The QTL qSTR06_2 showed highest PVE (9.1–11.3%) at LOD values of 4.25–5.39. No stable QTL over 3 years were identified, indicating strong environmental influence on SSC. The QTL qSTR11_1 and qSTR20_1 were found to colocalize with some of the previously reported QTL for sucrose content in soybean, implying the interrelationship between starch and sucrose biosynthesis. As the carbohydrate components may affect key constituents such as oil and protein in soybean seed, findings of the study may be useful in breeding soybeans with improved seed composition.     

Identification of the QTL underlying the vitamin E content of soybean seeds

Vitamin E (VE) is an important antioxidant supplement for human health. Soybean seed extracts are the main source of VE supplements. Therefore, increasing the VE content of soybean seeds is important issue in breeding programmes. To detect quantitative trait loci (QTL) associated with VE in soybean seeds, 238 F_6:7 recombinant inbred lines (RILs) were created by crossing a high VE cultivar, ‘Beifeng 9’, with a low VE cultivar, ‘Freeborn’. A genetic map was constructed using 218 polymorphic simple sequence repeat (SSR) markers. Composite interval mapping analysis detected 66 QTLs for contents of individual and total VE, 21 for α‐tocopherol, seventeen for γ‐tocopherol, thirteen for δ‐tocopherol and fifteen for total VE. The QTLs were located on chromosomes 9, 10, 15, 18 and 19. Phenotypic variance underlain by each QTL ranged from 2.4% to 32.6%. Two major QTLs (BARCSOYSSR_10_1140–BARCSOYSSR_10_1188 and BARCSOYSSR_15_0855 to BARCSOYSSR_15_0887) associated with α‐Toc, γ‐Toc, δ‐Toc and total VE contents were mapped on chromosomes 10 and 15. They explained 12.0% and 32.6% of phenotypic variance for α‐Toc; 5.5% and 13.0% for γ‐Toc; 6.6% and 23.6% for δ‐Toc; and 19.6% and 21.8% for total VE. QTL intervals BARCSOYSSR_15_0790–BARCSOYSSR_15_0855 (Qα15_1, Qγ15_1), BARCSOYSSR_15_1113–BARCSOYSSR_15_1159 (Qα15_3, Qδ15_2, QTVE15_4) and BARCSOYSSR_15_1159–BARCSOYSSR_15_1190 (Qα15_4, Qγ15_5, QTVE15_5) were associated with α‐Toc and explained 22.2%, 23.8% and 24.4% of the phenotypic variation in multiple environments. BARCSOYSSR_09_1098–BARCSOYSSR_09_1128 (QTVE9_1) and BARCSOYSSR_15_0887–BARCSOYSSR_15_0935 (QTVE15_2, Qγ15_3) associated with total VE content explained 21.8% and 16.4% of the phenotypic variation in two environments. These QTLs allow for marker‐assisted selection for cultivars with high VE contents.     

Identification and mapping of adult‐plant stripe rust resistance in soft red winter wheat cultivar ‘USG 3555’

Little is known about the extent or diversity of resistance in soft red winter wheat (Triticum aestivum L.) to stripe rust, caused by the fungal pathogen Puccinia striiformis f.sp. tritici. The soft red winter (SRW) wheat cultivar ‘USG 3555’ has effective adult‐plant resistance to stripe rust, which was characterized in a population derived from ‘USG 3555’/‘Neuse’. The mapping population consisted of 99 recombinant inbred lines, which were evaluated for stripe rust infection type (IT) and severity to race PST‐100 in field trials in North Carolina in 2010 and 2011. Genome‐wide molecular‐marker screenings with 119 simple sequence repeats and 560 Diversity Arrays Technology (DArT) markers were employed to identify quantitative trait loci (QTL) for stripe rust resistance. QTL on chromosomes 1AS, 4BL and 7D of ‘USG 3555’ explained 12.8, 73.0 and 13.6% of the variation in stripe rust IT, and 13.5, 72.3 and 10.5% of the variation in stripe rust severity, respectively. Use of these and additional diagnostic markers for these QTL will facilitate the introgression of this source of stripe rust resistance into SRW wheat lines via marker‐assisted selection.     

Quantitative trait loci for agronomic traits in soybean

There continues to be improvement in seed yields of soybean by conventional breeding, but molecular techniques may provide faster genetic gains. The objective of this study was to identify quantitative trait loci (QTL) associated with the agronomic traits seed yield, lodging, plant height, seed filling period and plant maturity in soybean. To achieve this objective, 101 F₆‐derived recombinant inbred lines (RIL) from a population developed from a cross of N87‐984‐16 × TN93‐99 were used. Experiments were conducted in six environments during 2002–2003. Heritability estimates on an entry mean basis from data combined across environments ranged from 0.12 to 0.65 for seed yield and seed filling period, respectively. Composite interval mapping detected one QTL for yield (near Satt076), two for lodging (near Satt225 and Satt593) and four for maturity (near Satt263, Satt292, Satt293 and Satt591) in this population. Additional environmentally sensitive QTL for these traits, and for seed filling period and plant height are also reported. The QTL associated with agronomic traits that we report and the recently released germplasm (PI 636460) from this population may be useful in soybean breeding programmes.     

Identification of quantitative trait loci controlling soybean seed weight in recombinant inbred lines derived from PI 483463 (Glycine soja) × ‘Hutcheson’ (G. max)

The objective of this study was to identify quantitative trait loci (QTLs) controlling 100‐seed weight in soybean using 188 recombinant inbred lines (RIL) derived from a cross of PI 483463 and ‘Hutcheson’. The parents and RILs were grown for 4 years (2010–2013), and mature, dry seeds were used for 100‐seed weight measurement. The variance components of genotype (a), environment (e) and a × e interactions for seed weight were highly significant. The QTL analysis identified 14 QTLs explaining 3.83–12.23% of the total phenotypic variation. One of the QTLs, qSW17‐2, was found to be the stable QTL, being identified in all the environments with high phenotypic variation as compared to the other QTLs. Of the 14 QTLs, 10 QTLs showed colocalization with the seed weight QTLs identified in earlier reports, and four QTLs, qSW5‐1, qSW14‐1, qSW15‐1 and qSW15‐2, found to be the novel QTLs. A two‐dimensional genome scan revealed 11 pairs of epistatic QTLs across 11 chromosomes. The QTLs identified in this study may be useful in genetic improvement of soybean seed weight.     

Quantitative trait loci mapping of adult‐plant resistance to leaf rust in a Fundulea 900 × ‘Thatcher’ wheat cross

Wheat leaf rust (LR), caused by the obligate biotrophic fungus Puccinia triticina (Pt), is a destructive foliar disease of common wheat (Triticum aestivum L.) worldwide. The most effective, economic means to control the disease is resistant cultivars. The Romanian wheat line Fundulea 900 showed high resistance to LR in the field. To identify the basis of resistance to LR in Fundulea 900, a population of 188 F_2:3 lines from the cross Fundulea 900/‘Thatcher’ was phenotyped for LR severity during the 2010–2011, 2011–2012 and 2012–2013 cropping seasons in the field at Baoding, Hebei Province. Bulked segregant analysis and simple sequence repeat markers were used to identify the quantitative trait loci (QTLs) for LR adult‐plant resistance in the population. Three QTLs were detected and designated as QLr.hebau‐1BL, QLr.hebau‐2DS and QLr.hebau‐7DS. Based on the chromosome positions and molecular marker tests, QLr.hebau‐1BL is Lr46, and QLr.hebau‐7DS is Lr34. QLr.hebau‐2DS was derived from ‘Thatcher’ and was close to Lr22. This result suggests that Lr22b may confer residual resistance on field nurseries when challenged with isolates virulent on Lr22b, or another gene linked to Lr22b confers this resistance from ‘Thatcher’. This study confirms the value of Lr34 and Lr46 in breeding for LR resistance in China; the contribution of the QTL to chromosome 2D needs further validation.     

Identification of QTLs for growth period traits in soybean using association analysis and linkage mapping

The growth period traits of soybean (Glycine max L. Merr.) are quantitatively inherited and crucial for its adaptation to different environments. Association analysis and linkage mapping were used to identify the quantitative trait loci (QTLs) for days to flowering (DF), days from flowering to maturity (DFM) and days to maturity (DM). Considering the effect of sowing date, the phenotypes were evaluated in three or four sowing‐date‐experiments in each year. A total of 96 associations, involving 19 SSRs corresponding to DF, DFM and/or DM, were identified by association mapping. Six, eight and two QTLs were observed relating to DF, DFM and DM by linkage mapping, respectively, and some QTLs were shared by DF, DFM and DM. Four SSRs (Satt150, Satt489, Satt172 and Sat_312) were found to be related to the growth period traits using the two mapping methods. In summary, association analysis and linkage mapping can complement and verify results from both methods to identify QTLs in soybean, and these findings may be useful in facilitating the selection of growth period–related traits via marker‐assisted selection.     

Molecular marker analysis of kernel size and shape in bread wheat

The economic value of wheat grain is determined by the kernel morphology which is an important parameter for manufacturing different food products requiring specific grain characteristics. Although kernel size and shape have emerged as important breeding objectives, not much information is available about the number or location of associated gene(s)/quantitative trait loci. In the present study, a recombinant inbred line population of 106 plants (F₇) was phenotyped for four traits, namely kernel length, width, weight and factor form density (FFD) and genotyped with different polymerase chain reaction‐based markers. Transgressive segregants were observed for all the traits and genetic correlation studies showed positive correlations between the majority of the traits. The number of markers associated with each trait ranged from two to nine and the phenotypic contribution by an individual marker ranged from 3.3 to 16.6%. Many of the markers showed linkage to more than one trait. Strategies for improving the wheat grain quality traits and the utility of such markers in marker‐assisted selection (MAS) efforts are discussed.     

The transition time from the juvenile phase to the adult phase differs in soybean cultivars ‘Enrei’ and ‘Peking’

Plants develop juvenile phase to adult phase in vegetative stage. Although soybean is a very important crop worldwide, there has been only one study of the juvenile–adult phase change. In this study, we determined that the juvenile–adult phase change occurred at different stages in two soybean cultivars that differ in their photosensitivity. Cultivar ‘Enrei’ (E1e2e3E4) is weakly photosensitive and cultivar ‘Peking’ (E1E2E3E4) is strongly photosensitive. In ‘Enrei’, the leaf size gradually increased at a constant leaf position regardless of the difference in day length. In ‘Peking’ plants transferred to short‐day conditions at several leaf development stages, leaf size gradually increased at different leaf positions. Expression of miR156 by ‘Enrei’ transferred to short‐day conditions had nearly the same pattern as that of ‘Enrei’ grown under long‐day conditions. In ‘Peking’, the expression of miR156 had different patterns in younger leaves of plants subjected to either a short‐day treatment or long‐day conditions. These results indicate that the E2 and E3 loci that regulate photosensitivity also regulate the expression of miR156 and the juvenile–adult phase change in soybean.     

Genetic analysis and map-based delimitation of a major locus qSS3 for seed size in soybean

Seed size is a major determinant of grain yield in soybean, however their genetic basis remains largely unknown. In order to delimit map-based position of a major locus qSS3 , we evaluated three mapping populations, including RILs, NILs and a sub-F₂ in three environments for six seed size-related traits. For these traits, the kurtosis and skewness ranged between 0.0 and 1.16, while h²_b ranged from 0.75 to 0.96, indicating that this RIL population is suitable for QTL analysis. QTL analysis identified 12 loci which consist of 30 significant QTLs with PVE% and LOD values of 6.6%–26.2% and 2.50–5.61, respectively. Among them, qSS3 was a major and stable locus explaining 7.3%–26.2% of the variation in 5 of the 6 traits, with the respective LOD values falling in the range of 2.72–5.61. Additionally, qSS3 effects were confirmed in NILs and delimited to an interval of ~1,126 kb containing 123 annotated genes. Overall, this study may assist efforts aiming to improve soybean seed traits by identifying valuable genetic resources which can be used in future MAS breeding programmes.