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.     

Evaluation of wild perennial Glycine species for resistance to soybean cyst nematode and soybean rust

The genetic base for soybean cultivars is narrow compared to most other crop species. Twenty-seven wild perennial Glycine species comprise the tertiary gene pool to soybean that may contain many genes of economic importance for soybean improvement. We evaluated 16 accessions of G. argyrea, G. clandestina, G. dolichocarpa, and G. tomentella for resistance to Heterodera glycines (HG), also known as the soybean cyst nematode, and to multiple isolates of Phakopsora pachyrhizi, the causal fungus of soybean rust. All 16 accessions were classified as resistant to H. glycines HG Type 2.5.7, based on number of cysts per root mass with plant introductions (PIs) 483227, 509501, 563892, and 573064 (all G. tomentella) void of any cysts indicating no reproduction by this pest. All 16 accessions had an immune reaction to one isolate of P. pachyrhizi. Regardless of isolate, no sporulating uredinia were observed on G. argyrea (PI 505151) and G. tomentella (PIs 483227, 509501, and 573064). These results demonstrate that some accessions within the perennial Glycine species harbour resistance to both H. glycines and P. pachyrhizi and would be good candidates for wide hybridization programs seeking to transfer potentially unique multiple resistance genes into soybean.     

Identification of quantitative trait loci underlying seed protein and oil contents of soybean across multi‐genetic backgrounds and environments

Seed protein and oil contents are important quantitative traits in soybean. Previously, quantitative trait loci (QTL) associated with seed protein and oil were mostly identified in single genetic background. The objective of this work was to identify QTL and their epistatic effects underlying seed protein and oil contents in three recombinant inbred line populations (two of them used one common female parent) across eight environments by composite interval mapping. Forty QTL underlying protein content and 35 QTL underlying oil content were identified. Among them, nine were universal QTL underlying protein content and four were universal QTL underlying oil content. Epistatic interactions between QTL underlying seed protein/oil and different genetic backgrounds were detected. Different pairs of epistatic interactions were observed in diverse genetic backgrounds across multi‐environments. Common marker intervals were observed to simultaneously underlie seed protein and oil contents with different epistatic interactions. The results in this study suggested that a specific genotype with high oil content and low protein content might significantly affect the selection of soybean lines for high seed protein.     

Identification of quantitative trait loci (QTLs) for seed protein concentration in soybean and analysis for additive effects and epistatic effects of QTLs under multiple environments

Soybean protein concentration is a key trait driver of successful soybean quality. A recombination inbred lines derived from a cross between ‘Charleston’ and ‘Dongnong594’, were planted in three environments across four years in China. Then, the genetic effects were partitioned into additive main effects, epistatic main effects and their environment interaction effects by using composite interval mapping, multiple interval mapping and composite interval mapping in a mixed linear model. Forty‐three quantitative trait loci QTLs were identified on 17 of 20 soybean chromosomes excluding Ch 7, Ch 8 and Ch 17. Two QTLs showed a good stability across multiple environments, qPRO20‐1 was detected under four environments, which explained 4.4–9.95% phenotypic variances and the allele was from ‘Charleston’ among four environments. qPRO7‐5 was detected under three environments, which explained 7.2–14.5% phenotypic variances and the allele was from ‘Dongnong 594’, three pathway genes of protein biosynthesis were detected in the interval of qPRO7‐5. The additive main‐effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. This indicated that it is feasible by marker‐assisted selection to improve soybean protein concentration.     

Quantitative trait loci analysis of soluble sugar contents in soybean

The soluble sugar content in soybean seeds, mainly sucrose, stachyose, raffinose and trace amounts of glucose and fructose, is important for the increasing global market demand for various soyfoods including tofu, soymilk, natto, bean sprouts and edamame due to their nutritional value and health benefits. The objective of this study was to conduct quantitative trait loci (QTL) analysis and identify molecular markers for soluble sugar content in soybean seeds for marker‐assisted selection (MAS) in soybean breeding. The content of the five previously mentioned sugars were measured and associated QTLs were mapped based on a F₂ population that was derived from a cross between V97‐3000 and V99‐5089. Eleven QTLs were detected for the five sugar contents: one for glucose, three each for fructose and sucrose, and two each for raffinose and stachyose. However, only one QTL for sucrose, one QTL for raffinose, and two QTLs for stachyose were identified with LOD > 3.0 and R² > 10% from this research. The QTL on chromosome 11 [linkage group (LG) B1] was identified as associated with sucrose, raffinose and stachyose in the same region as previously reported for sucrose and stachyose. The SSR marker, Satt359, on the QTL B1 region had an significant association with sucrose (LOD = 5.192; R² = 0.134), raffinose (LOD = 3.95; R² = 0.104), and stachyose (LOD = 13.572; R² = 0.314); therefore it can be used to assist breeding selection for sucrose, raffinose and stachyose contents simultaneously.     

Identification of quantitative trait loci underlying resistance of soybean to Fusarium graminearum

Fusarium graminearum could cause serious yield loss of soybean. Host resistance could offer an economical and effective way to control F. graminearum. The aims of this study were to identify and confirm quantitative trait loci (QTLs) underlying resistance to F. graminearum, and to analyse the genetic effects of pyramid resistance QTL on resistance level. A total of 140 F_2:14 recombinant inbred lines (RILs) were constructed via the cross between 'Hefeng 25' (moderate resistance to F. graminearum) and 'Conrad' (resistance to F. graminearum). The molecular genetic linkage map was constructed based on 164 simple sequence repeat (SSR) markers. A total of seven QTLs underlying F. graminearum resistance, located on six chromosomes, were identified. Among these seven identified QTLs, beneficial allele of qFG-1, qFG-2 and qFG-3 derived from 'Hefeng 25' and beneficial allele of qFG-4, qFG-5, qFG-6, qFG-7 derived from 'Conrad'. Of these seven identified QTLs, qFG-1, qFG-3, qFG-4 and qFG-5 were novel for F. graminearum resistance. Four pairs of QTLs with significant epistatic effects were found. The accumulation of resistance QTL was positively correlated with decreases in disease severity index, which was valuable for improving efficiency of marker-assistant breeding in F. graminearum resistance.     

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.     

Identification of quantitative trait loci with main and epistatic effects for plant architecture traits in Upland cotton (Gossypium hirsutum L.)

Plant architecture is important for cotton cultivation and breeding. In this study, two mapping generations/populations F₂ and F_2:3 in Upland cotton (Gossypium hirsutum L.), derived from ‘Baimian1’ and TM‐1, were used to identify quantitative trait loci (QTLs) for 10 plant architecture traits. A total of 55 main‐effect QTLs (M‐QTLs) were detected. Four common M‐QTLs, qTFB‐10(F₂/F_2:3) for total fruit branches, qFBL‐26b(F₂)/qFBL‐26(F_2:3) for fruit branch length, qFBA‐5(F₂/F_2:3) for fruit branch angle and qFBN‐26b(F₂)/qFBN‐26(F_2:3) for fruit branch nodes, were found. The synergistic alleles and the negative alleles can be utilized in cotton plant architecture breeding programmes according to specific breeding objectives. Altogether 54 pairs of epistatic QTLs (E‐QTLs) exhibiting the interactions of additive‐by‐additive (AA), additive‐by‐dominant (AD), dominant‐by‐additive (DA) and dominant‐by‐dominant (DD) were detected. The epistasis appeared to be an important contributor to genetic variation in cotton plant architecture traits. Therefore, the identified markers associated with E‐QTLs as well as M‐QTLs will be of importance in future breeding programmes to develop cotton cultivars exhibiting desirable plant architecture.     

Dissection of genetic architecture for oil content in soybean seed using two backcross populations

Soybean seed oil was valued in foods, animal feed and some industrial applications. Molecular marker‐assisted selection (MAS) for high‐oil‐content cultivars was an important method for soybean breeders. The objective of this study was to identify quantitative trait loci (QTL) and epistatic QTL underlying the seed oil content of soybeans across two backcross (BC) populations (with one common male parent ‘Dongnong47’) and two different environments. Two molecular genetic maps were constructed. They encompassed 1046.8 cM [with an average distance of 6.75 cM in the ‘Dongnong47’  ×  ‘Jiyu89’ (DJ) population] and 846.10 cM [with an average distance of 5.76 cM in the ‘Dongnong47’  ×  ‘Zaoshu18’ (DZ) population]. Nine and seven QTL were identified to be associated with oil content in the DJ and DZ populations, respectively. The phenotypic variation explained by most of the QTL was usually less than 10%. Among the identified QTL, those stable ones across multiple environments and populations often had stronger additive effects. In addition, three stable QTL in the DZ populations were identified in the similar genomic region of the three QTL in the DJ population [qDJE and qDZE‐1 were located near Satt151 of Chromosome 15 (Chr15), qDJA1 and qDZA1 were located near Satt200 of Chr15 (LG A1), and qDJD2‐1 and qDZD2‐1 were located near Sat365 of Chr17]. In conclusion, MAS will be able more effectively to combine beneficial alleles of the different donors to design new genotypes with higher soybean seed oil content using the BC populations.     

Quantitative trait loci mapping for flooding tolerance at an early growth stage of soybean recombinant inbred line population

Flooding stress causes a significant yield reduction in soybean. The early growth of soybean in Korea coincides with the rainy season, potentially exposing to flooding stress. Greenhouse experiments were conducted to map the quantitative trait loci (QTL) for flooding tolerance in soybean and to identify and investigate candidate genes near the QTL hot spots. Flood stress was imposed at V1–V2 stage on a recombinant inbred line population (‘Paldalkong’ × ‘NTS1116’), and leaf chlorophyll content (CC) and shoot dry weight (DW) were measured under control and flooded conditions. The genetic map was constructed using 180K Axiom^® SoyaSNP markers. The QTL were analysed under control and flooded conditions as well as for index (ratio of CC or DW under flooded to control, CCI and DWI) and flooding tolerance index (FTI, mean of CCI and DWI). A total of 20 QTL with LOD scores 3.59–19.73 causing 5.8%–33.3% phenotypic variation were identified on nine chromosomes. Chromosomes 10, 12 and 13 harboured relatively more stable QTL. Results of this study could be useful to further understand the genetic basis of soybean's flooding tolerance and applied in breeding programmes.     

Genetic relationships of soybean cyst nematode resistance originated in Gedenshirazu and PI84751 on Rhg1 and Rhg4 loci

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is one of the most damaging pests of soybean (Glycine max (L.) Merr.). Host plant resistance has been the most effective control method. Because of the spread of multiple SCN races in Hokkaido, the Tokachi Agricultural Experiment Station has bred soybeans for SCN resistance since 1953 by using 2 main resistance resources PI84751 (resistant to races 1 and 3) and Gedenshirazu (resistant to race 3). In this study, we investigated the genetic relationships of SCN resistance originating from major SCN resistance genes in Gedenshirazu and PI84751 by using SSR markers. We confirmed that race 1 resistance in PI84751 was independently controlled by 4 genes, 2 of which were rhg1 and Rhg4. We classified the PI84751- type allele of Rhg1 as rhg1-s and the Gedenshirazu-type allele of Rhg1 as rhg1-g. In the cross of the Gedenshirazu-derived race 3-resistant lines and the PI84751-derived races 1- and 3-resistant lines, the presence of rhg1-s and Rhg4 was responsible for race 1-resistance. These results indicated that it was possible to select race 1 resistant plants by using marker-assisted selection for the rhg1-s and Rhg4 alleles through a PI84751 origin × Gedenshirazu origin cross.     

Inheritance of resistance and genetic relationships among soybean plant introductions to races of soybean cyst nematode

Summary The objectives of this study were to determine if genes for resistance to soybean cyst nematode (SCN) in soybean PI 437654 were identical or different from the genes in Peking, and PI 90763. The F₂ plants and F₃ families were studied from crosses between PI 437654, Peking, and PI 90763. The cross PI 437654 × susceptible Essex was included to determine inheritance of resistance to SCN. For Race 3, PI 437654 was found to have genes in common with Peking and PI 90763. The segregation in PI 437654 × Essex indicated the presence of one dominant and two recessive genes. For Race 5, PI 437654 indicated the presence of similar genes as those in PI 90763 and Peking whereas, PI 437654 × Essex indicated the action of the segregation ratios of two dominant and two recessive genes. For Race 14, the data from the cross PI 437654 × PI 90763 indicated monogenic inheritance with resistance being dominant; whereas PI 437654 × Peking showed a recessive gene controlling resistance. The segregation in PI 437654(R) × Essex(S) suggested one dominant and two recessive genes for Race 14 reaction.     

Resistance to soybean cyst nematode and molecular polymorphism in various sources of Peking soybean

Summary Cultivar Peking has been extensively used as a source of resistance to Race 3 and Race 5 of soybean cyst nematode, Heterodera glycines I., and Peking genes for resistance are present in a wide range of resistant soybean cultivars. Peking is also used as a host differential in the soybean cyst nematode race classification system. Thirteen Peking lines maintained in the USDA Soybean Germplasm Collection and in several breeding programs were surveyed using RFLP and RAPD markers for genetic characterization. Based on the molecular diversity combined with reaction to soybean cyst nematode, Peking genotypes from a common original source were identified. Peking lines PI 297543 (introduction from Hungary), and PI 438496A, PI 438496B and PI 438496C (introductions from Russia) represented unrelated germplasms. Identified molecular polymorphism can be used to validate the genetic purity of Peking lines used as host differentials for soybean cyst nematode classification system as well as utilization of an individual germplasm line in genetic-breeding programs.     

Quantitative trait loci analysis in Theobroma cacao using molecular markers. Inheritance of polygenic resistance to Phytophthora palmivora in two related cacao populations

Two related segregating populations of Theobroma cacao L. were analysed for their resistance to Phytophthora palmivora. The first F₁ population was obtained by crossing two susceptible cacao clones of Catongo (a highly homozygous genotype) and Pound 12(a highly heterozygous genotype) and the second population was obtained by backcrossing a single F₁ tree with Catongo. The genetic maps obtained for each population were compared. The F₁ map includes 162 loci and the backcross has 140 loci. The two maps, F₁ and BC₁, exhibit high co-linear loci organization covering respectively, 772 and 944 cM.Phytophthora resistance was assessed by measuring the size increase of a lesion at five (DL5)and ten days (DL10) after pod inoculation. Six different QTL were detected in the F₁ and BC₁ populations. One QTL was found in both populations, and appeared to be a major component of disease resistance, and explaining nearly 48% of the phenotypic variance in the F₁ population. The absence of some yield QTL detection in the BC₁ in comparison with the F₁ population is due to the lack of transmission of the favouring alleles for these QTL from the single F₁ tree used for the backcross. The phenotypic variance explained by the action of the quantitative trait alleles indicated that genetic factors of both major and minor effects were involved in the control of the character studied. QTL conferring increased resistance to Phytophthorawere identified in both susceptible parents, suggesting the presence of transgressive traits and the possibility of selection in cacao. Pleiotropic and epistatic effects for the QTL were also detected. Finally, the use of marker assisted selection (MAS) in cacao breeding programs is discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Analysis of quantitative trait loci associated with leaflet types in two recombinant inbred lines of soybean

Leaf area, length and width affect the photosynthetic capability of a plant and so increasing the photosynthetic rate per unit leaf area may improve seed yield in soybean. In this study, simple sequence repeat (SSR) markers were used to identify the genomic regions significantly associated with the quantitative trait locus (QTL) that controls length, width and the length/width ratio of the terminal and lateral leaflet in two segregating F_2:10 recombinant inbred line (RIL) populations, ‘Keounolkong’ × ‘Shinpaldalkong’ (K/S) and ‘Keounolkong’ × ‘Iksan10’ (K/I). In the K/S population, one QTL was identified for terminal leaflet length (TLL), two for lateral leaflet length (LLL), four for terminal leaflet width (TLW), four for lateral leaflet width (LLW), two for terminal leaflet length/width ratio (TLR) and four for lateral leaflet length/width ratio (LLR), with total phenotypic variations of 7.43, 10.9, 26.57, 23.46, 20.25 and 23.31%, respectively. In the K/I population, two QTLs were identified for TLL, two for LLL, three for TLW, and two for LLW, four for TLR and two for LLR with total phenotypic variations of 29.89, 22.77, 18.5, 12.15, 22.96 and 17.85%, respectively. Only a few QTLs coincided among the leaflet traits and no relationships were observed between the two populations. Many QTLs were associated with leaflet traits but each single QTL made only a minimal contribution. Thus, pyramiding the favourable alleles for leaflet traits in soybean breeding programmes may accelerate vegetative growth and perhaps lead to higher yields by maximizing total photosynthetic performance.     

Confirmation of quantitative trait loci for resistance to multiple-HG types of soybean cyst nematode (<Emphasis Type="Italic">Heterodera glycines</Emphasis> Ichinohe)

Genetic analysis of resistance of plant introduction (PI) 438489B to soybean cyst nematode (SCN) have shown that this PI is highly resistant to many SCN HG types. However, validation of the previously detected quantitative trait loci (QTL) has not been done. In this study, 250 F_2:3 progeny of a Magellan (susceptible) × PI 438489B (resistant) cross were used for primary genetic mapping to detect putative QTL for resistance to five SCN HG types. QTL confirmation study was subsequently conducted using F_6:7 recombinant inbred lines (RILs) derived from the same cross. Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were employed for molecular genotyping. Interval mapping (IM), permutation tests, cofactor selection, and composite interval mapping (CIM) were performed to identify and map QTL. Results showed that five QTL intervals were associated with resistance to either multiple- or single-HG types of SCN. Among these, two major QTL for resistance to multiple-SCN HG types were mapped to chromosomes (Chr.) 8 and 18, consistent with the known rhg1 and Rhg4 locations. The other QTL were mapped to Chr. 4. The results of our study confirmed earlier reported SCN resistance QTL in this PI. Moreover, SSR and SNP molecular markers tightly linked to these QTL can be useful for the near-isogenic lines (NILs) development aiming to fine-mapping of these QTL regions and map-based cloning of SCN resistance candidate genes.     

Identification of QTL underlying the resistance of soybean to pod borer, <Emphasis Type="Italic">Leguminivora glycinivorella</Emphasis> (Mats.) obraztsov,and correlations with plant,pod and seed traits

Soybean (Glycine max L. Merr.) pod borer (Leguminivora glycinivorella (Mats.) Obraztsov) (SPB) results in severe loss in soybean yield and quality in certain regions of the world, especially in Northeastern China, Japan and Russia. The aim here was to evaluate the inheritance of pod borer resistance and to identify quantitative trait loci (QTL) underlying SPB resistance for the acceleration of the control of this pest. Used were the 129 recombinant inbred lines (RILs) of the F_5:6 derived population from ‘Dong Nong 1068’ × ‘Dong Nong 8004’ and 131 SSR markers. Correlations between the percentage of damaged seeds (PDS) by pod borer and plant, pod and seed traits that were potentially related to SPB resistance were analyzed. The results showed highly significant correlations between PDS by pod borer and plant height (PH), maturity date (MA), pod color (PC), pubescence density (PB), 100-seed weight (SW) and protein content existed. Soybeans with dwarf stem, light color of pod coat, small seeds, lower density of pubescence, early maturity and low content of protein seemed to have higher resistance to SPB. The correlated traits had potential to inhibit egg deposition and thereby to decrease the damage by SPB. Three QTL directly associated with the resistance to SPB judged by PDS at harvest were identified. qRspb-1 (Satt541–Satt253) and qRspb-2 (Satt253–Satt314) were both on linkage group (LG) H and qRspb-3 (Satt288–Satt199) on LG G. The three QTL explained 10.96, 9.73 and 11.59% of the phenotypic variation for PDS, respectively. In addition, 12 QTL that underlay 10 of 13 traits potentially related with SPB resistance were found. These QTL detected jointly provide potential for marker assisted selection to improve cultivar resistance to SPB. Guiyun Zhao, Jian Wang, and Yingpeng Han have equal contribution to the paper.