Association analysis of fiber quality traits and exploration of elite alleles in Upland cotton cultivars/accessions （Gossypium hirsutum L.）

Exploring the elite al eles and germplasm acces-sions related to fiber quality traits wil accelerate the breeding of cotton for fiber quality improvement. In this study, 99 Gossypium hirsutum L. accessions with diverse origins were used to perform association analysis of fiber quality traits using 97 polymorphic microsatel ite marker primer pairs. A total of 107 significant marker-trait associations were detected for three fiber quality traits under three different environments, with 70 detected in two or three environments and 37 detected in only one environment. Among the 70 significant marker-trait associations, 52.86% were reported previously, implying that these are stable loci for target traits. Furthermore, we detected a large number of elite al eles associated simulta-neously with two or three traits. These elite al eles were mainly from accessions col ected in China, introduced to China from the United States, or rare al eles with a frequency of less than＆amp;nbsp;5%. No one cultivar contained more than half of the elite al eles, but 10 accessions were col ected from China and the two introduced from the United States did contain more than half of these al eles. Therefore, there is great potential for mining elite al eles from germplasm accessions for use in fiber quality improvement in modern cotton breeding.     

Diversity characterization and association analysis of agronomic traits in a Chinese peanut （Arachis hypogaea L.） mini-core collection

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A peanut （Arachis hypogaea L.） mini-core collection in China comprising 298 accessions was genotyped using lo9 simple sequence repeat （SSR） markers, which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments, exhibiting abundant genetic and phenotypic diversity within the panel. A model-based structure analysis assigned all accessions to three groups. Most of the accessions had the relative kinship of less than o.05, indicating that there were no or weak relationships between accessions of the mini- core collection. For 15 agronomic traits in the peanut panel, generally the Q ＋ K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model. In total, 89 SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q＋K model-based association analysis. Of these, eight alleles were repeatedly detected in two or three environments, and 15 alleles were commonly detected to be associated with multiple agronomic traits. Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers. Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.     

Variation in the Agronomic and Morphological Traits of Iranian Chickpea Accessions

Landraces of chickpea (Cicer arietinum L.) in Iran have not been adequately characterized for their agronomic and morphological traits. Such characterization would be helpful in the development of improved cultivars, so in this study 362 chickpea accessions, collected from the major chickpea growing areas of Iran, were evaluated to determine their phenotypic diversity. High coefficients of variation (CVs) were recorded in pods/branch, seeds/pod, yield/plant, seeds/plant, pods/plant and branches/plant. Using principal component (PC) analysis, the first four PCs with eigenvalues more than 1 contributed 84.10% of the variability among accessions, whereas PC5 to PC10 were less than unity. PC1 was positively related to days to first maturity, days to 50% flowering and days to 50% maturity. The characters with the greatest weight on PC2 were seeds/plant and yield/plant, whereas PC3 was mainly related to pods/plant, seeds/pod and 100seed weight, and PC4 was positively related to pods/branch and negatively to branches/plant. The germplasm was grouped into four clusters using cluster analysis. Each cluster had some specific characteristics of its own and the cluster I was clearly separated from clusters II, III and IV. These accessions are an important resource for the establishment of a core collection of chickpeas in the world.     

Development of Oryza rufipogon and O. sativa Introgression Lines and Assessment for Yield-related Quantitative Trait Loci

Introgression lines population was effectively used in mapping quantitative trait loci （QTLs）, identifying favorable genes, discovering hidden genetic variation, evaluating the action or interaction of QTLs in multiple conditions and providing the favorable experimental materials for plant breeding and genetic research. In this study, an advanced backcross and consecutive selfing strategy was used to develop introgression lines （ILs）, which derived from an accession of Oryza rufipogon Griff. collected from Yuanjiang County, Yunnan Province of China, as the donor, and an elite indica cultivar Teqing （O. sativa L.）, as the recipient. Introgression segments from O. rufipogon were screened using 179 polymorphic simple sequence repeats （SSR） markers in the genome of each IL. Introgressed segments carried by the introgression lines population contained 120 ILs covering the whole O. rufipogon genome. The mean number of homozygous O. rufipogon segments per introgression line was about 3.88. The average length of introgressed segments was approximate 25.5 cM, and about 20.8% of these segments had sizes less than 10 cM. The genome of each IL harbored the chromosomal fragments of O. rufipogon ranging from 0.54% to 23.7%, with an overall average of 5.79%. At each locus, the ratio of substitution of O. rufipogon alleles had a range of 1.67-9.33, with an average of 5.50. A wide range of alterations in morphological and yield-related traits were also found in the introgression lines population. Using single-point analysis, a total of 37 putative QTLs for yield and yield components were detected at two sites with 7%-20% explaining the phenotypic variance. Nineteen QTLs （51.4%） were detected at both sites, and the alleles from O. rufipogon at fifteen loci （40.5%） improved the yield and yield components in the Teqing background. These O. rufipogon-O, sativa introgression lines will serve as genetic materials for identifying and using favorable genes from common wild rice.     

Index selection on seed traits under direct, cytoplasmic and maternal effects in multiple environments

Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.     

Detection of Quantitative Trait Loci for Yield and Drought Tolerance Traits in Soybean Using a Recombinant Inbred Line Population

To investigate the genetic basis of drought tolerance in soybean （Glycine max L. Merr.） a recombinant inbred population with 184 F2：7：11 lines developed from a cross between Kefengl （drought tolerant） and Nannong1138-2 （drought sensitive） were tested under water-stressed and well-watered conditions in field and greenhouse trials. Traits measured included leaf wilting coefficient, excised leaf water loss and relative water content as indicators of plant water status and seed yield. A total of 40 quantitative trait loci （QTLs） were identified： 17 for leaf water status traits under drought stress and 23 for seed yield under well-watered and drought-stressed conditions in both field and greenhouse trials. Two seed yield QTLs were detected under both well-watered and drought-stressed conditions in the field on molecular linkage group H and Dlb, while two seed yield QTLs on molecular linkage group C2 were found under greenhouse conditions. Several QTLs for traits associated with plant water status were identified in both field and greenhouse trials, including two leaf wilting coefficient QTLs on molecular linkage group A2 and one excised leaf water loss QTL on molecular linkage group H. Phenotypic correlations of traits suggested several QTLs had pleiotropic or location-linked associations. These results will help to elucidate the genetic basis of drought tolerance in soybean, and could be incorporated into a marker-assisted selection breeding program to develop high-yielding soybean cultivars with improved tolerance to drought stress.     

Mapping QTLs for seed yield and drought susceptibility index in soy-bean（Glycine max L.） across different environments

Drought stress has long been a major constraint in maintaining yield stability of soybean （Glycine max （L.） Merr.） in rainfed ecosystems. The identification of consistent quantitative trait loci （QTL） involving seed yield per plant （YP） and drought susceptibility index （DSI） in a population across different environments would therefore be important in molecular marker-assisted breeding of soybean cultivars suitable for rainfed regions. The YP of a recombinant line population of 184 F2：7：11 lines from a cross of Kefengl and Nannong1138-2 was studied under water-stressed （WS） and well-watered （WW） conditions in field （F） and greenhouse （G） trials, and DSI for yield was calculated in two trials. Nineteen QTLs associated with YP-WS and YP-WW, and 10 QTLs associated with DSI, were identi- fied. Comparison of these QTL locations with previous findings showed that the majority of these regions control one or more traits re- lated to yield and other agronomic traits. One QTL on molecular linkage group （MLG） K for YP-F, and two QTLs on MLG C2 for YP-G, remained constant across different water regimes. The regions on MLG C2 for YP-WW-F and MLG H for YP-WS-F had a pleiotropic effect on DSI-F, and MLG A1 for YP-WS-G had a pleiotropic effect on DSI-G. The identification of consistent QTLs for YP and DSI across different environments will significantly improve the efficiency of selecting for drought tolerance in soybean.     

The Genetic Architecture of Flowering Time and Photoperiod Sensitivity in Maize as Revealed by QTL Review and Meta Analysis

The control of flowering is not only important for reproduction,but also plays a key role in the processes of domestication and adaptation.To reveal the genetic architecture for flowering time and photoperiod sensitivity,a comprehensive evaluation of the relevant literature was performed and followed by meta analysis.A total of 25 synthetic consensus quantitative trait loci(QTL)and four hot-spot genomic regions were identified for photoperiod sensitivity including 11 genes related to photoperiod response or flower morphogenesis and development.Besides,a comparative analysis of the QTL for flowering time and photoperiod sensitivity highlighted the regions containing shared and unique QTL for the two traits.Candidate genes associated with maize flowering were identified through integrated analysis of the homologous genes for flowering time in plants and the consensus QTL regions for photoperiod sensitivity in maize(Zea mays L.).Our results suggest that the combination of literature review,meta-analysis and homologous blast is an efficient approach to identify new candidate genes and create a global view of the genetic architecture for maize photoperiodic flowering.Sequences of candidate genes can be used to develop molecular markers for various models of marker-assisted selection,such as marker-assisted recurrent selection and genomic selection that can contribute significantly to crop environmental adaptation.     

Genetics of barley tiller and leaf development

In cereals, tillering and leaf development are key factors in the concept of crop ideotype, introduced in the 1960 s to enhance crop yield, via manipulation of plant architecture. In the present review, we discuss advances in genetic analysis of barley shoot architecture,focusing on tillering, leaf size and angle. We also discuss novel phenotyping techniques, such as 2 D and 3 D imaging, that have been introduced in the era of phenomics, facilitating reliable trait measurement. We discuss the identification of genes and pathways that are involved in barley tillering and leaf development,highlighting key hormones involved in the control of plant architecture in barley and rice. Knowledge on genetic control of traits related to plant architecture provides useful resources for designing ideotypes for enhanced barley yield and performance.     

Novel pleiotropic loci controlling panicle architecture across environments in japonica rice （Oryza sativa L.）

To identify quantitative trait loci (QTLs) controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat (SSR) markers and 254 recombinant inbred lines (RILs) derived from a cross between cultivars Xiushui 79 and C Bao. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%-35% of phenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle (NPB), two for panicle length (PL), two for spikelet density (SD), one for the number of secondary branches per panicle (NSB), one for secondary branch distribution density (SBD), and one for the number of spikelets per panicle (NS), respectively. qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously. qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively. qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTL × environment interactions were not significant for additive QTLs and additive × additive QTL pairs.     

Genomic regions underlying agronomic traits in linseed (Linum usitatissimum L.) as revealed by association mapping OA简

The extreme climate of the Canadian Prairies poses a major challenge to improve yield. Although it is possible to breed for yield per se, focusing on yield‐related traits could be advantageous because of their simpler genetic architecture. The Canadian flax core collection of 390 accessions was genotyped with 464 simple sequence repeat markers, and phenotypic data for nine agronomic traits including yield, bolls per area, 1,000 seed weight, seeds per boll, start of flowering, end of flowering, plant height, plant branching, and lodging collected from up to eight environments was used for association mapping. Based on a mixed model (principal component analysis (PCA) + kinship matrix (K)), 12 significant marker‐trait associations for six agronomic traits were identified. Most of the associations were stable across environments as revealed by multivariate analyses. Statistical simulation for five markers associated with 1000 seed weight indicated that the favorable alleles have additive effects. None of the modern cultivars carried the five favorable alleles and the maximum number of four observed in any accessions was mostly in breeding lines. Our results confirmed the complex genetic architecture of yield‐related traits and the inherent difficulties associated with their identification while illustrating the potential for improvement through marker‐assisted selection.     

陆地棉主要产量相关性状的SSR标记关联分析

高产优质育种是我国棉花育种的主要目标。寻找与目标性状关联的分子标记,可克服常规育种的盲目性,提高分子标记辅助选择育种的准确性。本研究对118份陆地棉种质资源的衣分、单铃重、单株铃数及子指等4个产量相关性状进行2年2点的表型鉴定,并利用覆盖全基因组的、有多态性的214对SSR标记进行标记与性状的关联分析。结果表明:118份材料的4个产量相关性状表型变异丰富,平均变异系数的变幅在6.1%~19.1%之间,且在各环境中表现较为稳定;基因型分析表明,214对标记共检测到460个等位变异,基因多样性指数平均为0.5151,PIC值平均为0.4587,表明该批标记具有较多的等位变异数和较高的基因多样性;群体结构分析表明该批材料可分为4个亚群,且各类群中材料与地理来源无对应关系;关联分析结果显示,在显著条件下(-log10P1.3,P0.05),共有39个标记位点能够在2个及2个以上的环境中同时检测到,其中有4个标记位点同时与2个以上性状相关联,进一步比较发现,有7个位点与前人研究结果一致,其余32个位点为新发现的位点。研究结果可为陆地棉产量性状遗传改良的分子标记辅助选择提供理论依据。     

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.     

Detection of favorable alleles for yield and yield components by association mapping in upland cotton

Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(??lgP?>?1.30, P?<?0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.     

Association mapping of six yield-related traits in rapeseed (Brassica napus L.)

Yield is one of the most important traits for rapeseed (Brassica napus L.) breeding, but its genetic basis remains largely ambiguous. Association mapping has provided a robust approach to understand the genetic basis of complex agronomic traits in crops. In this study, a panel of 192 inbred lines of B. napus from all over the world was genotyped using 451 single-locus microsatellite markers and 740 amplified fragment length polymorphism markers. Six yield-related traits of these inbred lines were investigated in three consecutive years with three replications, and genome-wide association studies were conducted for these six traits. Using the model controlling both population structure and relative kinship (Q + K), a total of 43 associations (P < 0.001) were detected using the means of the six yield-related traits across 3 years, with two to fourteen markers associated with individual traits. Among these, 18 markers were repeatedly detected in at least 2 years, and 12 markers were located within or close to QTLs identified in previous studies. Six markers commonly associated with correlated traits. Conditional association analysis indicated that five of the associations between markers and correlated traits are caused by one QTL with pleiotropic effects, and the remaining association is caused by linked but independent QTLs. The combination of favorable alleles of multiple associated markers significantly enhances trait performance, illustrating a great potential of utilization of the associations in rapeseed breeding programs.     

QTL analysis of yield traits in an advanced backcross population derived from a cultivated Andean × wild common bean (Phaseolus vulgaris L.) cross

Advanced backcross QTL analysis was used to identify quantitative trait loci (QTL) for agronomic performance in a population of BC₂F_3:5 introgression lines created from the cross of a Colombian large red-seeded commercial cultivar, ICA Cerinza, and a wild common bean accession, G24404. A total of 157 lines were evaluated for phenological traits, plant architecture, seed weight, yield and yield components in replicated trials in three environments in Colombia and genotyped with microsatellite, SCAR, and phaseolin markers that were used to create a genetic map that covered all 11 linkage groups of the common bean genome with markers spaced at an average distance of every 10.4 cM. Segregation distortion was most significant in regions orthologous for a seed coat color locus (R-C) on linkage group b08 and two domestication syndrome genes, one on linkage group b01 at the determinacy (fin) locus and the other on linkage group b02 at the seed-shattering (st) locus. Composite interval mapping analysis identified a total of 41 significant QTL for the eight traits measured of which five for seed weight, two for days to flowering, and one for yield were consistent across two or more environments. QTL were located on every linkage group with b06 showing the greatest number of independent loci. A total of 13 QTL for plant height, yield and yield components along with a single QTL for seed size showed positive alleles from the wild parent while the remaining QTL showed positive alleles from the cultivated parent. Some QTL co-localized with regions that had previously been described to be important for these traits. Compensation was observed between greater pod and seed production and smaller seed size and may have resulted from QTL for these traits being linked or pleiotropic. Although wild beans have been used before to transfer biotic stress resistance traits, this study is the first to attempt to simultaneously obtain a higher yield potential from wild beans and to analyze this trait with single-copy markers. The wild accession was notable for being from a unique center of diversity and for contributing positive alleles for yield and other traits to the introgression lines showing the potential that advanced backcrossing has in common bean improvement.     

Diversity characterization and association analysis of agronomic traits in a Chinese peanut (Arachis hypogaea L.) mini-core collection

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants.A peanut(Arachis hypogaea L.)mini-core collection in China comprising 298 accessions was genotyped using 109 simple sequence repeat(SSR)markers,which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments,exhibiting abundant genetic and phenotypic diversity within the panel.A model-based structure analysis assigned all accessions to three groups.Most of the accessions had the relative kinship of less than 0.05,indicating that there were no or weak relationships between accessions of the mini-core collection.For 15 agronomic traits in the peanut panel,generally the Q t K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model.In total,89SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q t K model-based association analysis.Of these,eight alleles were repeatedly detected in two or three environments,and 15 alleles were commonly detected to be associated with multiple agronomic traits.Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers.Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.     

Association mapping in durum wheat grown across a broad range of water regimes

Association mapping was used to dissect the genetic basis of drought-adaptive traits and grain yield (GY) in a collection of 189 elite durum wheat accessions evaluated in 15 environments highly different for water availability during the crop cycle (from 146 to 711 mm) and GY (from 9.9 to 67.3 q ha(-1)). For highly heritable traits (e.g. heading date, kernel weight, etc.) several significant experiment-wise marker-trait associations were detected across five or more (up to 13 for kernel weight) environments, with R(2) values ranging from ca. 5 to 10%. As to GY, significant associations (R(2) from 2.5 to 4.2%) were mostly detected in one environment only (56 markers), while decreasing rapidly from two to five environments (from 20 to three markers, respectively) and with only one marker (Xbarc197 on chr. 5A) found significant in six environments (ranging from low- to high-yielding). These results are probably due to the complex genetic basis of GY and its interaction with environmental conditions. The number of markers significantly affecting GY decreased considerably under drought conditions, suggesting a limited effectiveness of association mapping to identify loci for GY under low-moisture conditions, most likely because different genotypes can attain similar phenotypes via different morpho-physiological traits and corresponding gene networks. Our study confirmed the role of major loci for phenology previously described in biparental mapping populations, highlighted a novel set of loci for drought-adaptive traits, and provided information on the agronomic value of the alleles at such loci across a broad range of soil moisture conditions.     

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.