Quantitative trait loci controlling sulfur containing amino acids, methionine and cysteine, in soybean seeds

Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, a major limitation of soy proteins is their deficiency in sulfur-containing amino acids, methionine (Met) and cysteine (Cys). The objective of this study was to identify quantitative trait loci (QTL) associated with Met and Cys concentration in soybean seed. 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. Ground soybean seed samples were analyzed for Met and Cys concentration using a near infrared spectroscopy instrument. Data were analyzed using SAS software and QTL Cartographer. RIL differed (P<0.01) in Met and Cys concentrations, with a range of 5.1–7.3 (g kg⁻¹ seed dry weight) for Cys and 4.4–8.8 (g kg⁻¹ seed dry weight) for Met. Heritability estimates on an entry mean basis were 0.14 and 0.57 for Cys and Met, respectively. A total of 94 polymorphic simple sequence repeat molecular genetic markers were screened in the RIL. Single factor ANOVA was used to identify candidate QTL, which were confirmed by composite interval mapping using QTL Cartographer. Four QTL linked to molecular markers Satt235, Satt252, Satt427 and Satt436 distributed on three molecular linkage groups (MLG) D1a, F and G were associated with Cys and three QTL linked to molecular markers Satt252, Satt564 and Satt590 distributed on MLG F, G and M were associated with Met concentration in soybean seed. QTL associated with Met and Cys in soybean seed will provide important information to breeders targeting improvements in the nutritional quality of soybean.     

QTL in mega-environments: I. Universal and specific seed yield QTL detected in a population derived from a cross of high-yielding adapted × high-yielding exotic soybean lines

Modern soybean [(Glycine max (L.) Merrill] breeding programs rely primarily on the use of elite × elite line crosses to develop high-yielding cultivars. Favorable alleles for traits of interest have been found in exotic germplasm but the successful introduction of such alleles has been hampered by the lack of adaptation of the exotic parent to local mega-environment and difficulties in identifying superior progeny from elite × exotic crosses. The objective of this study was to use a population derived from a cross between an adapted and an exotic elite line to understand the genetic causes underlying adaptation to two mega-environments (China and Canada). A cross between a high-yielding Canadian cultivar ‘OAC Millennium’ and an elite Chinese cultivar ‘Heinong 38’ was performed to develop a recombinant inbred line (RIL) population. The RIL population was evaluated in China and Canada in multiple environments from 2004 to 2006. Significant variation for seed yield was observed among the RILs in both the Chinese and Canadian environment. Individual RILs performed differently between the Chinese and Canadian environments suggesting differential adaptation to intercontinental mega-environments. Seven seed yield quantitative trait loci (QTL) were identified of which five were mega-environment universal QTL (linked to markers Satt100, Satt162, Satt277, Sat_126, and the interval of Satt139-Sat_042) and two were mega-environment-specific QTL (at marker intervals, Satt194-SOYGPA and Satt259-Satt576). Seed yield QTL located near Satt277 has been confirmed and new QTL have been identified explaining between 9 and 37% of the phenotypic variation in seed yield. The QTL located near Satt100 explained the greatest amount of variation ranging from 18 to 37% per environment. Broad sense heritability ranged from 89 to 64% among environments. Epistatic effects have been identified in both mega-environments with pairs of markers explaining between 9 and 14% of the phenotypic variation in seed yield. An improved understanding of the type of QTL action as either universal or mega-environment-specific QTL as well as their interaction may facilitate the development of strategies to introgress specific high-yielding alleles from Chinese to North American germplasm and vice versa to sustain efforts in breeding of high-yielding soybean cultivars.     

Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses

One of the goals of plant breeding is to increase yield with improved quality characters. Plant introductions (PI) are a rich source of favorable alleles that could improve different characters in modern soybean [Glycine max (L.) Merril] including yield. The objectives of this study were to identify yield QTL underlying the genetic basis for differential adaptation of soybeans to the Canadian, United States or Chinese mega-environments (ME) and to evaluate the relationship and colocalization between yield and agronomic traits QTL. Two crosses between high-yielding Canadian cultivars and elite Chinese cultivars, OAC Millennium × Heinong 38 and Pioneer 9071 × #8902, were used to develop two recombinant inbred line (RIL) populations. Both populations were evaluated at different locations in Ontario, Canada; Minnesota, United States (US), Heilongjiang and Jilin, China, in 2009 and 2010. Significant variation for yield was observed among the RILs of both populations across the three hypothetical ME. Two yield QTL (linked to the interval Satt364–Satt591 and Satt277) and one yield QTL (linked to marker Sat_341) were identified by single-factor ANOVA and interval mapping across all ME in populations 1 and 2, respectively. The most frequent top ten high-yielding lines across all ME carried most of the high-yielding alleles of the QTL that were identified in two and three ME. Both parents contributed favorable alleles, which suggests that not only the adapted parent but also the PI parents are potential sources of beneficial alleles in reciprocal environments. Other QTL were detected also at two and one ME. Most of the yield QTL were co-localized with a QTL associated with an agronomic trait in one, two, or three ME in just one or in both populations. Results suggested that most of the variation observed in seed yield can be explained by the variation of different agronomic traits such a maturity, lodging and height. Novel alleles coming from PI can favorably contribute, directly or indirectly, to seed yield and the utilization of QTL detected across one, two or three ME would facilitate the new allele introgression into breeding populations in both North America and China.     

QTLs for resistance to Phomopsis seed decay are associated with days to maturity in soybean (Glycine max)

Phomopsis seed decay (PSD), primarily caused by Phomopsis longicolla, is a major contributor to poor soybean seed quality and significant yield loss, particularly in early maturing soybean genotypes. However, it is not yet known whether PSD resistance is associated with early maturity. This study was conducted to identify quantitative trait loci (QTLs) for resistance to PSD and days to maturity using a recombinant inbred line (RIL) population derived from a cross between the PSD-resistant Taekwangkong and the PSD-susceptible SS2-2. Based on a genetic linkage map incorporating 117 simple sequence repeat markers, QTL analysis revealed two and three QTLs conferring PSD resistance and days to maturity, respectively, in the RIL population. Two QTLs (PSD-6-1 and PSD-10-2) for PSD resistance were identified in the intervals of Satt100–Satt460 and Sat_038–Satt243 on chromosomes 6 and 10, respectively. Two QTLs explained phenotypic variances in PSD resistance of 46.3 and 14.1 %, respectively. At the PSD-6-1 QTL, the PSD-resistant cultivar Taekwangkong contributed the allele with negative effect decreasing the infection rate of PSD and this QTL does not overlap with any previously reported loci for PSD resistance in other soybean genotypes. Among the three QTLs for days to maturity, two (Mat-6-2 and Mat-10-3) were located at positions similar to the PSD-resistance QTLs. The identification of the QTLs linked to both PSD resistance and days to maturity indicates a biological correlation between these two traits. The newly identified QTL for resistance to PSD associated with days to maturity in Taekwangkong will help improve soybean resistance to P. longicolla.     

QTL in mega-environments: II. Agronomic trait QTL co-localized with seed yield QTL detected in a population derived from a cross of high-yielding adapted × high-yielding exotic soybean lines

Seed yield mega-environment-universal and specific QTL (QTL_U and QTL_SP, respectively) linked to Satt100, Satt130, Satt162, Satt194, Satt259 Satt277 and Sat_126, have been identified in a population derived from a cross between a Chinese and a Canadian soybean [Glycine max (L.) Merrill] elite line. The variation observed in yield could be the consequence of the variation of agronomic traits. Yield-component traits have been reported in the literature, but a better understanding of their impact at the molecular level is still lacking. Therefore, the objectives of this study were to identify traits correlated with yield and to determine if the yield QTL_U and QTL_SP were co-localized with QTL_U and QTL_SP associated with an agronomic trait. A recombinant inbred line (RIL) population was developed from a cross between a high-yielding adapted Canadian and a high-yielding exotic Chinese soybean elite line. The RIL were evaluated in multiple environments in China and Canada during the period from 2004 to 2006. Four yield QTL_U, tagged by markers Satt100, Satt277, Satt162 and Sat_126, were co-localized with a QTL associated with an agronomic trait, behaving as either QTL_U or QTL_SP for the agronomic trait. For example, the yield QTL_U, tagged by marker Satt100 was associated also with 100 seed weight, pods per plant, pods per node, plant height, R1, R5, R8, oil content and protein content in all Canadian environments, but only with pods per plant, pods per node, plant height, R1, R5, R8 and oil content in two or more Chinese environments. No agronomic traits QTL were co-localized with the yield QTL_U tagged by the marker Satt139 or the yield QTL_SP tagged by Satt259, suggesting a physiological basis of the yield in these QTL. The results suggest that a successful introgression of crop productivity alleles from plant introductions into an adapted germplasm could be facilitated by the use of both the QTL_U and QTL_SP because each type of QTL contributed either directly or indirectly through yield-component traits to seed yield of RILs.     

Mapping Isoflavone QTL with Main,Epistatic and QTL × Environment Effects in Recombinant Inbred Lines of Soybean

Soybean (Glycine max (L.) Merr.) isoflavone is important for human health and plant defense system. To identify novel quantitative trait loci (QTL) and epistatic QTL underlying isoflavone content in soybean, F_5:6, F_5:7 and F_5:8 populations of 130 recombinant inbred (RI) lines, derived from the cross of soybean cultivar ‘Zhong Dou 27′ (high isoflavone) and ‘Jiu Nong 20′ (low isoflavone), were analyzed with 95 new SSR markers. A new linkage map including 194 SSR markers and covering 2,312 cM with mean distance of about 12 cM between markers was constructed. Thirty four QTL for both individual and total seed isoflavone contents of soybean were identified. Six, seven, ten and eleven QTL were associated with daidzein (DZ), glycitein (GC), genistein (GT) and total isoflavone (TI), respectively. Of them 23 QTL were newly identified. The qTIF_1 between Satt423 and Satt569 shared the same marker Satt569 with qDZF_2, qGTF_1 and qTIF_2. The qGTD2_1 between Satt186 and Satt226 was detected in four environments and explained 3.41%-10.98% of the phenotypic variation. The qGTA2_1, overlapped with qGCA2_1 and detected in four environments, was close to the previously identified major QTL for GT, which were responsible for large a effects. QTL (qDZF_2, qGTF_1 and qTIF_2) between Satt144-Satt569 were either clustered or pleiotropic. The qGCM_1, qGTM_1 and qTIM_1 between Satt540-Sat_244 explained 2.02%–9.12% of the phenotypic variation over six environments. Moreover, the qGCE_1 overlapped with qGTE_1 and qTIE_1, the qTIH_2 overlapped with qGTH_1, qGCI_1 overlapped with qDZI_1, qTIL_1 overlapped with qGTL_1, and qTIO_1 overlapped with qGTO_1. In this study, some of unstable QTL were detected in different environments, which were due to weak expression of QTL, QTL by environment interaction in the opposite direction to a effects, and/or epistasis. The markers identified in multi-environments in this study could be applied in the selection of soybean cultivars for higher isoflavone content and in the map-based gene cloning.     

Genomic Regions Associated with Amino Acid Composition in Soybean

Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, few studies have been conducted to evaluate genomic regions controlling amino acid composition in soybean. It is important to study the genetics of amino acid composition to achieve improvements through breeding. The objectives of this study were to determine the ratios between essential to non-essential (E:NE) and essential to total (E:T) amino acids, and to identify genomic regions controlling essential and non-essential amino acid composition in soybean seed. To achieve these objectives, 101 F₆-derived recombinant inbred lines (RIL) developed from a cross of N87-984-16 × TN93-99 were used. Ground soybean seed samples were analyzed for amino acids using a near infrared spectroscopy (NIRS) instrument. A significant (p < 0.01) difference among the RIL was found for amino acid composition. Heritability estimates on an entry mean basis ranged from 0.13 for His to 0.67 for Tyr. A total of 94 polymorphic simple sequence repeat (SSR) molecular genetic markers were screened in DNA from progenies. Single factor ANOVA was used to identify candidate quantitative trait loci (QTL), which were then confirmed by QTL Cartographer. At least one QTL for each amino acid was detected in this population. QTL linked to molecular markers Satt143, Satt168, Satt203, Satt274 and Satt495 were associated with most of the amino acids. Phenotypic variation explained by an individual QTL ranged from 9.4 to 45.3%. QTL detected for amino acids in soybean in this experiment are expected to be useful for future breeding programs targeting development of improved soybean amino acid composition for human and animal nutrition.     

Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents

Soybean seed is a major source of oil for human consumption worldwide and the main renewable feedstock for biodiesel production in North America. Increasing seed oil concentration in soybean [Glycine max (L.) Merrill] with no or minimal impact on protein concentration could be accelerated by exploiting quantitative trait loci (QTL) or gene-specific markers. Oil concentration in soybean is a polygenic trait regulated by many genes with mostly small effects and which is negatively associated with protein concentration. The objectives of this study were to discover and validate oil QTL in two recombinant inbred line (RIL) populations derived from crosses between three moderately high-oil soybean cultivars, OAC Wallace, OAC Glencoe, and RCAT Angora. The RIL populations were grown across several environments over 2 years in Ontario, Canada. In a population of 203 F_3:6 RILs from a cross of OAC Wallace and OAC Glencoe, a total of 11 genomic regions on nine different chromosomes were identified as associated with oil concentration using multiple QTL mapping and single-factor ANOVA. The percentage of the phenotypic variation accounted for by each QTL ranged from 4 to 11 %. Of the five QTL that were tested in a population of 211 F_3:5 RILs from the cross RCAT Angora × OAC Wallace, a “trait-based” bidirectional selective genotyping analysis validated four QTL (80 %). In addition, a total of seven two-way epistatic interactions were identified for oil concentration in this study. The QTL and epistatic interactions identified in this study could be used in marker-assisted introgression aimed at pyramiding high-oil alleles in soybean cultivars to increase oil concentration for biodiesel as well as edible oil applications.     

Identification of QTLs for seed germination capability after various storage periods using two RIL populations in rice

Seed germination capability of rice is one of the important traits in the production and storage of seeds. Quantitative trait loci (QTL) associated with seed germination capability in various storage periods was identified using two sets of recombinant inbred lines (RILs) which derived from crosses between Milyang 23 and Tong 88-7 (MT-RILs) and between Dasanbyeo and TR22183 (DT-RILs). A total of five and three main additive effects (QTLs) associated with seed germination capability were identified in MT-RILs and DT-RILs, respectively. Among them, six QTLs were identified repeatedly in various seed storage periods designated as qMT-SGC5.1, qMT-SGC7.2, and qMT-SGC9.1 on chromosomes 5, 7, and 9 in MT-RILs, and qDT-SGC2.1, qDT-SGC3.1, and qDT-SGC9.1 on chromosomes 2, 3, and 9 in DT-RILs, respectively. The QTL on chromosome 9 was identified in both RIL populations under all three storage periods, explaining up to 40% of the phenotypic variation. Eight and eighteen pairs additive × additive epistatic effect (epistatic QTL) were identified in MT-RILs and DT-RILs, respectively. In addition, several near isogenic lines (NILs) were developed to confirm six repeatable QTL effects using controlled deterioration test (CDT). The identified QTLs will be further studied to elucidate the mechanisms controlling seed germination capability, which have important implications for long-term seed storage.     

Identification of QTL in soybean underlying resistance to herbivory by Japanese beetles (Popillia japonica, Newman)

Soybean [Glycine max (L.) Merr.] was one of the most important legume crops in the world in 2010. Japanese beetles (JB; Popillia japonica, Newman) in the US were an introduced and potentially damaging insect pest for soybean. JBs are likely to spread across the US if global warming occurs. Resistance to JB in soybean was previously reported only in plant introductions. The aims here were to identify loci underlying resistance to JB herbivory in recombinant inbred lines (RILs) derived from the cross of Essex × Forrest cultivars (EF94) and to correlate those with loci with factors that confer insect resistance in soybean cultivars. The RIL population was used to map 413 markers, 238 satellite markers and 177 other DNA markers. Field data were from two environments over 2 years. Pest severity (PS) measured defoliation on a 0–9 scale. Pest incidence (PI) was the percentage of plants within each RIL with beetles on them. Antibiosis and antixenosis data were from feeding assays with detached leaves in petri plates. Five QTL were detected for the mean PS field trait (16% < R ² < 27%). The loci were within the intervals Satt632–A2D8 on linkage group (LG) A2 (chromosome 8); Satt583–Satt415 on LG B1 (11); Satt009–Satt530 on LG N (3); and close to two markers OB02_140 (LG E; 20 cM from Satt572) and OZ15_150 LG (19 cM from Satt291 C2). Two QTL were detected for the mean PI field trait (16% < R ² < 18%) close to Satt385 on LG A1 and Satt440 on LG I. The no choice feeding studies detected three QTL that were significant; two for antixenosis (22% < R ² < 24%) between Satt632–A2D8 on LG A2 (8) and Sat_039–Satt160 on LG F (13); and a major locus effect (R ² = 54%) for antibiosis on LG D2 (17) between Satt464–Satt488. Therefore, loci underlying resistance to JB herbivory were a mixture of major and minor gene effects. Some loci were within regions underlying resistance to soybean cyst nematode (LGs A2 and I) and root knot nematode (LG F) but not other major loci underlying resistance to nematode or insect pests (LGs G, H and M).     

Validation of mega-environment universal and specific QTL associated with seed yield and agronomic traits in soybeans

The value of quantitative trait loci (QTL) is dependant on the strength of association with the traits of interest, allelic diversity at the QTL and the effect of the genetic background on the expression of the QTL. A number of recent studies have identified QTL associated with traits of interest that appear to be independent of the environment but dependant on the genetic background in which they are found. Therefore, the objective of this study was to validate universal and/or mega-environment-specific seed yield QTL that have been previously reported in an independent recombinant inbred line (RIL) population derived from the cross between an elite Chinese and Canadian parent. The population was evaluated at two field environments in China and in five environments in Canada in 2005 and 2006. Of the seven markers linked to seed yield QTL reported by our group in a previous study, four were polymorphic between the two parents. No association between seed yield and QTL was observed. The result could imply that seed yield QTL were either not stable in this particular genetic background or harboured different alleles than the ones in the original mapping population. QTL_U Satt162 was associated with several agronomic traits of which lodging was validated. Both the non-adapted and adapted parent contributed favourable alleles to the progeny. Therefore, plant introductions have been validated as a source of favourable alleles that could increase the genetic variability of the soybean germplasm pool and lead to further improvements in seed yield and other agronomic traits.     

SSR- and SNP-related QTL underlying linolenic acid and other fatty acid contents in soybean seeds across multiple environments

Soybean fatty acids (FAs) are major sources of vegetable oil in the world. The FA composition of soybean is associated with the quality and nutritional value of its oil and food products. The polyunsaturated FAs, particularly linolenic acid (LN), are prone to oxidation by lipoxygenase isozymes and negatively affect the flavor and shelf-life of soybean products. The improvement of FA composition and the increase of oxidative stability has been a major goal of soybean breeding for decades. The objective of the present study was to identify quantitative trait loci (QTL) associated with the low LN and other FA contents in six environments. One hundred and twenty-five recombinant inbred lines (RILs) of F5:7, F5:8 and F5:9 generations derived by the single-seed-descent method from the cross of Hefeng 25 [LN 6.20%; linoleic acid (LI) 53.06%; oleic acid (OL) 19.75%; palmitic acid (PA) 12.16%; stearic acid (ST) 4.97%] and Dongnong L-5 (LN 2.53%; LI 59.30%; OL 24.24%; PA 10.0%; ST 3.99%) were used in this study. A total of 112 simple sequence repeat markers were used to construct a genetic linkage map. Six QTL associated with LN content, four QTL associated with LI content, four QTL associated with OL content, four QTL associated with PA content and one QTL associated with ST content were identified, and mapped onto different linkage groups (LGs). The QTL detected here explained 2.53?C37.30% of phenotypic variation for individual FA in different environments or individual FA means. Of them, the beneficial alleles of QLNB2_1 (close to Satt726), QLNB2_2 (close to Fad3a-4) and QLND1b_1 (close to Satt701), which were associated with low LN content across various environments and LN means, were derived from Dongnong L-5. These three QTL might have great potential value in marker-assisted selection for low LN content in soybean seed.     

QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.)

At harvest traits such as seed weight are the sum of development and responses to stresses over the growing season and particularly during the reproductive phase of growth. The aim here was to measure quantitative trait loci (QTL) underlying the seed weight from early development to drying post harvest. One hundred forty-three F(5) derived recombinant inbred lines (RILs) developed from the cross of soybean cultivars 'Charleston' and 'Dongnong 594' were used for the analysis of QTL underlying mean 100-seed weight at six different developmental stages. QTL x Environment interactions (QE) were analyzed by a mixed genetic mode based on 3 years' data. At an experiment-wise threshold of a=0.05 and by single-point analysis 94 QTL unaffected by QE underlay the mean seed weight at different developmental stages. Sixty-eight QTL affected by QE that also underlay mean seed weight were identified. From the 162 QTL 42 could be located on 12 linkage groups by composite interval mapping (LOD>2.0). The numbers, locations and types of the QTL and the genetic effects were different at each developmental stage. On linkage group C2 the distantly linked QTL swC2-1, swC2-2 and swC2-3 each affected mean seed weight throughout the different developmental stages. The DNA markers linked to the QTL possessed potential for use in marker-assisted selection for soybean seed size. The identification of QTL with genetic main effects and QE interaction effects suggested that such interactions might significantly alter seed weight during seed development.     

Quantitative trait locus analysis of a recombinant inbred line population derived from a Lycopersicon esculentum x Lycopersicon cheesmanii cross

Quantitative trait loci influencing fruit traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato, Lycopersicon esculentum with a related wild species Lycopersicon cheesmanii. One hundred thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 F₈ RIL families. Fruit weight and soluble solids were measured in replicated trials during 1991 and 1992. Seed weight was measured in 1992. Significant (P<0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. A total of 73 significant marker locus-trait associations were detected for the three traits measured. Fifty-three of these associations were for fruit weight and soluble solids, many of which involved marker loci signficantly associated with both traits. QTL with large effects on all three traits were detected on chromosome 6. Greater homozygosity at many loci in the RIL population as compared to F₂ populations and greater genomic coverage resulted in increased precision in the estimation of QTL effects, and large proportions of the total phenotypic variance were explained by marker class variation at significant marker loci for many traits. The RIL population was effective in detecting and discriminating among QTL for these traits previously identified in other investigations despite skewed segregation ratios at many marker loci. Large additive effects were measured at significant marker loci. Lower fruit weight, higher soluble solids, and lower seed weight were generally associated with RFLP alleles from theL. cheesmanii parent.     

Dynamic QTL analysis of linolenic acid content in different developmental stages of soybean seed

Linolenic acid (LN) in soybean (Glycine max L. Merr.) seed mainly contributes to the undesirable odors and flavors commonly associated with poor oil quality. LN deposition at various stages of soybean seed development had not been reported by 2010. The objects of this study were (1) to identify and measure quantitative trait loci (QTL) underlying LN content and (2) to estimate the QTL effects expressed from earlier seed developmental stages to drying seed of soybean. One hundred and twenty-five F_5:8 and F_5:9 recombinant inbred lines derived from the cross of soybean cultivars ‘Hefeng 25’ and ‘Dongnong L5’ were used for the identification of QTL underlying LN content from the 37 day (D) to 86D stages after flowering, at Harbin in 2008 and 2009. QTL × Environment interactions (QE) effects were evaluated using a mixed genetic model (Zhu in J Zhejiang Univ (Natural Science) 33:327–335, 1999). Twelve unconditional QTL and 12 conditional QTL associated with LN content were identified at different developmental stages. Most of the QTL explained <10% of phenotypic variation of LN content. Unconditional QTL QLNF-1, QLNC2-1, QLND1b-1, QLNA2-1 and QLNH-1 influenced LN content across different development stages and environments. Conditional QTL QLNF-1, QLNC2-1 and QLNH-1 were identified in multiple developmental stages and environments. Conditional and unconditional QTL clustered in neighboring intervals on linkage groups A2, C2 and D1b. Ten QTL with conditional additive main effects (a) and/or conditional additive × environment interaction effects (ae) at specific developmental stage were identified on nine linkage groups. Of them, six QTL only possessed additive main effects and seven QTL had significant ae effects in different developmental stages. A total of 13 epistatic pairwise QTL were identified by conditional mapping in different developmental stages. Two pairs of QTL only showed aa effects and five pairs of QTL only showed aae effects at different developmental stages. QTL with aa effects, as well as their environmental interaction effects, appeared to vary at different developmental stages.     

Genetic control of soybean seed oil: II. QTL and genes that increase oil concentration without decreasing protein or with increased seed yield

Soybean [Glycine max (L.) Merrill] seed oil is the primary global source of edible oil and a major renewable and sustainable feedstock for biodiesel production. Therefore, increasing the relative oil concentration in soybean is desirable; however, that goal is complex due to the quantitative nature of the oil concentration trait and possible effects on major agronomic traits such as seed yield or protein concentration. The objectives of the present study were to study the relationship between seed oil concentration and important agronomic and seed quality traits, including seed yield, 100-seed weight, protein concentration, plant height, and days to maturity, and to identify oil quantitative trait loci (QTL) that are co-localized with the traits evaluated. A population of 203 F_4:6 recombinant inbred lines, derived from a cross between moderately high oil soybean genotypes OAC Wallace and OAC Glencoe, was developed and grown across multiple environments in Ontario, Canada, in 2009 and 2010. Among the 11 QTL associated with seed oil concentration in the population, which were detected using either single-factor ANOVA or multiple QTL mapping methods, the number of QTL that were co-localized with other important traits QTL were six for protein concentration, four for seed yield, two for 100-seed weight, one for days to maturity, and one for plant height. The oil-beneficial allele of the QTL tagged by marker Sat_020 was positively associated with seed protein concentration. The oil favorable alleles of markers Satt001 and GmDGAT2B were positively correlated with seed yield. In addition, significant two-way epistatic interactions, where one of the interacting markers was solely associated with seed oil concentration, were identified for the selected traits in this study. The number of significant epistatic interactions was seven for yield, four for days to maturity, two for 100-seed weight, one for protein concentration, and one for plant height. The identified molecular markers associated with oil-related QTL in this study, which also have positive effects on other important traits such as seed yield and protein concentration, could be used in the soybean marker breeding programs aimed at developing either higher seed yield and oil concentration or higher seed protein and oil concentration per hectare. Alternatively, selecting complementary parents with greater breeding values due to positive epistatic interactions could lead to the development of higher oil soybean cultivars.     

Quantitative trait loci involved in regulating seed oil composition in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis> and their evolutionary implications

Fatty acid composition is an important determinant of seed oil quality. Overall, 72 QTL for 12 fatty acid traits that control seed oil composition were identified in four recombinant inbred line (RIL) populations (Ler-0 × Sha, Ler-0 × Col-4, Ler-2 × Cvi, Ler-0 × No-0) of Arabidopsis thaliana. The identified QTL explained 3.2–79.8% of the phenotypic variance; 33 of the 59 QTL identified in the Ler-0 × Sha and the Ler-0 × Col RIL populations co-located with several a priori candidate genes for seed oil composition. QTL for fatty acids 18:1, 18:2, 22:1, and fatty acids synthesized in plastids was identified in both Ler-0 × Sha and Ler-0 × Col-4 RIL populations, and QTL for 16:0 was identified in the Ler-0 × Sha and Ler-0 × No-0 RIL populations providing strong support for the importance of these QTL in determining seed oil composition. We identified melting point QTL in three RIL populations, and fatty acid QTL collocated with two of them, suggesting that the loci could be under selection for altering the melting point of seed oils to enhance adaptation and could be useful for breeding purposes. Nuclear-cytoplasmic interactions and epistasis were rare. Analysis of the genetic correlations between these loci and other fatty acids indicated that these correlations would tend to strongly enhance selection for desirable fatty acids.     

大豆小区产量及其相关性状QTL间的上位性和环境互作效应

以晋豆23栽培大豆(Glycine max)为母本、灰布支黑豆(ZDD2315,半野生大豆)为父本衍生出447个RIL群体,通过构建SSR遗传图谱及利用混合线性模型分析方法,对2年大豆小区产量及主要植物学性状进行QTL定位,并作加性效应、加性×加性上位互作效应及环境互作效应分析。结果显示,共检测到12个与小区产量、单株粒重、单株茎重、单株粒茎比、有效分枝、主茎节数、株高和结荚高度相关的QTL,分别位于A1、A2、H_1、I、J_2和M连锁群上。其中小区产量、株高、单株粒重、有效分枝和主茎节数均表现为遗传正效应,即增加其性状的等位基因来源于母本晋豆23。同时,检测到11对影响小区产量、单株粒重、单株茎重、株高和结荚高度的加性×加性上位互作效应及环境互作效应的QTL,发现22个QTL与环境存在互作。实验结果表明,上位效应和QE互作效应对大豆小区产量及主要农艺性状的遗传影响很大。进行大豆分子标记辅助育种时,既要考虑效应起主要作用的QTL,又要注重上位性QTL,这样有利于性状的稳定表达和遗传。     

Quantitative trait locus analysis and construction of consensus genetic map for drought tolerance traits based on three recombinant inbred line populations in cultivated groundnut (Arachis hypogaea L.)

Groundnut (Arachis hypogaea L.) is an important food and cash crop grown mainly in semi-arid tropics (SAT) regions of the world where drought is the major constraint on productivity. With the aim of understanding the genetic basis and identification of quantitative trait loci (QTL) for drought tolerance, two new recombinant inbred line (RIL) mapping populations, namely ICGS 76?×?CSMG 84-1 (RIL-2) and ICGS 44?×?ICGS 76 (RIL-3), were used. After screening of 3,215 simple sequence repeat (SSR) markers on the parental genotypes of these populations, two new genetic maps were developed with 119 (RIL-2) and 82 (RIL-3) SSR loci. Together with these maps and the reference map with 191 SSR loci based on TAG 24?×?ICGV 86031 (RIL-1), a consensus map was constructed with 293 SSR loci distributed over 20 linkage groups, spanning 2,840.8?cM. As all these three populations segregate for drought-tolerance-related traits, a comprehensive QTL analysis identified 153 main effect QTL (M-QTL) and 25 epistatic QTL (E-QTL) for drought-tolerance-related traits. Localization of these QTL on the consensus map provided 16 genomic regions that contained 125 QTL. A few key genomic regions were selected on the basis of the QTL identified in each region, and their expected role in drought adaptation is also discussed. Given that no major QTL for drought adaptation were identified, novel breeding approaches such as marker-assisted recurrent selection (MARS) and genomic selection (GS) approaches are likely to be the preferred approaches for introgression of a larger number of QTL in order to breed drought-tolerant groundnut genotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-011-9660-0) contains supplementary material, which is available to authorized users.     

A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds

Key message

We detected a QTL for single seed weight in soybean that was stable across multiple environments and genetic backgrounds with the use of two recombinant inbred line populations.

Abstract

Single seed weight (SSW) in soybean is a key determinant of both seed yield and the quality of soy food products, and it exhibits wide variation. SSW is under genetic control, but the molecular mechanisms of such control remain unclear. We have now investigated quantitative trait loci (QTLs) for SSW in soybean and have identified such a QTL that is stable across multiple environments and genetic backgrounds. Two populations of 225 and 250 recombinant inbred lines were developed from crosses between Japanese and US cultivars of soybean that differ in SSW by a factor of ~2, and these populations were grown in at least three different environments. A whole-genome panel comprising 304 simple sequence repeat (SSR) loci was applied to mapping in each population. We identified 15 significant QTLs for SSW dispersed among 11 chromosomes in the two populations. One QTL located between Sat_284 and Sat_292 on chromosome 17 was detected (3.6 < LOD < 14.1) in both populations grown in all environments. This QTL, tentatively designated qSw17-1, accounted for 9.4–20.9 % of phenotypic variation in SSW, with a dominant allele being associated with increased SSW. Given its substantial effect on SSW, qSw17-1 is an attractive target for positional cloning, and SSR markers closely associated with this locus may prove useful for marker-assisted selection for SSW control in soybean.