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

The extreme climate of the Canadian Prairies poses a major chal enge 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 col ection of 390 accessions was genotyped with 464 simple sequence repeat markers, and phenotypic data for nine agronomic traits including yield, bol s per area, 1,000 seed weight, seeds per bol , start of flowering, end of flowering, plant height, plant branching, and lodging col ected from up to eight environments was used for association mapping. Based on a mixed model （principal component analysis （PCA） t kinship matrix （K））, 12 significant marker-trait associations for six agronomic traits were identi-fied. 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 al eles have additive effects. None of the modern cultivars carried the five favorable al eles and the maximum number of four observed in any accessions was mostly in＆amp;nbsp;breeding lines. Our results confirmed the complex genetic architecture of yield-related traits and the inherent difficulties associated with their identification while il ustrating the potential for improvement through marker-assisted selection.     

A genome‐wide association study of 23 agronomic traits in Chinese wheat landraces

Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro‐ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome‐wide association study was conducted for these traits using 52 303 DArT‐seq markers to identify marker‐trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus (QTL), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty‐five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN‐B1 and vrn‐B3 and the photoperiod response genes Ppd and PRR. Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker‐assisted selection in wheat.     

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.     

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.     

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.     

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。     

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.     

Mapping QTLs for improving grain yield using the USDA rice mini-core collection

Yield is the most important and complex trait for genetic improvement in crops, and marker-assisted selection enhances the improvement efficiency. The USDA rice mini-core collection derived from over 18,000 accessions of global origins is an ideal panel for association mapping. We phenotyped 203 O. sativa accessions for 14 agronomic traits and identified 5 that were highly and significantly correlated with grain yield per plant: plant height, plant weight, tillers, panicle length, and kernels/branch. Genotyping with 155 genome-wide molecular markers demonstrated 5 main cluster groups. Linkage disequilibrium (LD) decayed at least 20 cM and marker pairs with significant LD ranged from 4.64 to 6.06% in four main groups. Model comparisons revealed that different dimensions of principal component analysis affected yield and its correlated traits for mapping accuracy, and kinship did not improve the mapping in this collection. Thirty marker–trait associations were highly significant, 4 for yield, 3 for plant height, 6 for plant weight, 9 for tillers, 5 for panicle length and 3 for kernels/branch. Twenty-one markers contributed to the 30 associations, because 8 markers were co-associated with 2 or more traits. Allelic analysis of OSR13, RM471 and RM7003 for their co-associations with yield traits demonstrated that allele 126 bp of RM471 and 108 bp of RM7003 should receive greater attention, because they had the greatest positive effect on yield traits. Tagging the QTLs responsible for multiple yield traits may simultaneously help dissect the complex yield traits and elevate the efficiency to improve grain yield using marker-assisted selection in rice.     

Genetic dissection of drought and heat‐responsive agronomic traits in wheat

High yield and wide adaptation are principal targets of wheat breeding but are hindered by limited knowledge on genetic basis of agronomic traits and abiotic stress tolerances. In this study, 277 wheat accessions were phenotyped across 30 environments with non‐stress, drought‐stressed, heat‐stressed, and drought‐heat‐stressed treatments and were subjected to genome‐wide association study using 395 681 single nucleotide polymorphisms. We detected 295 associated loci including consistent loci for agronomic traits across different treatments and eurytopic loci for multiple abiotic stress tolerances. A total of 22 loci overlapped with quantitative trait loci identified by biparental quantitative trait loci mapping. Six loci were simultaneously associated with agronomic traits and abiotic stress tolerance, four of which fell within selective sweep regions. Selection in Chinese wheat has increased the frequency of superior marker alleles controlling yield‐related traits in the four loci during past decades, which conversely diminished favourable genetic variation controlling abiotic stress tolerance in the same loci; two promising candidate paralogous genes colocalized with such loci, thereby providing potential targets for studying the molecular mechanism of stress tolerance–productivity trade‐off. These results uncovering promising alleles controlling agronomic traits and/or multiple abiotic stress tolerances, providing insights into heritable covariation between yield and abiotic stress tolerance, will accelerate future efforts for wheat improvement.     

云南苦荞种质资源主要性状的遗传多样性分析

为了从云南苦荞种质资源中挖掘优异种质资源,拓宽苦荞遗传基础,以48份苦荞种质资源为材料研究了6个主要农艺性状和5个品质性状的遗传多样性。结果表明,云南的苦荞资源存在着丰富的遗传多样性,6个农艺性状中株粒重的变异系数为34.4%最大,品质性状中总黄酮含量的变异系数为51.72%最大。聚类结果表明,将48份材料聚为3大类,可区分为低产型、矮秆高产型和中秆高产型。6个主要农艺性状和5个品质性状的主成分分析结果表明,前3个累计贡献率分别达84.105%和80.332%,各主成分性状载荷值反映了主要数量性状的育种选择潜力。综合分析种质资源的主要农艺性状,可为云南苦荞种质资源的利用提供有效的科学依据。