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。     

From the editor’s desk

Improving cotton fibre quality is a major breeding goal for Upland cotton in China. To investigate the genetic mechanisms of fibre quality, a diverse panel of 403 Upland cotton accessions was grown, and the fibre quality traits were measured in six different environments. Genotyping was performed with genomewide simple sequence repeats. A total of 201 markers were polymorphic and generated 394 allele loci, and 403 accessions were arranged into two subgroups using Structure software. Of the marker loci, 18.94% showed significant linkage disequilibrium (\(P< 0.05\)). A mixed linear model in association mapping showed that 51 associations were significant between 39 polymorphic loci and five fibre quality traits, according to best linear unbiased prediction, and in at least three of six environments. Of the 39 associated marker loci, 12 were coincident with previous studies. There were 41 typical accessions identified as containing favourable allele loci related to fibre quality traits. The identified favourable QTL alleles and typical accessions for fibre quality are excellent genetic resources for future cotton breeding in China.     

Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r²?≥?0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.     

Genomic divergence in cotton germplasm related to maturity and heterosis

Commercial varieties of upland cotton(Gossypium hirsutum) have undergone extensive breeding for agronomic traits, such as fiber quality, disease resistance,and yield. Cotton breeding programs have widely used Chinese upland cotton source germplasm(CUCSG) with excellent agronomic traits. A better understanding of the genetic diversity and genomic characteristics of these accessions could accelerate the identification of desirable alleles. Here, we analyzed 10,522 high-quality singlenucleotide polymorphisms(SNP) with the CottonSNP63 K microarray in 137 cotton accessions(including 12 hybrids of upland cotton). These data were used to investigate the genetic diversity, population structure,and genomic characteristics of each population and the contribution of these loci to heterosis. Three subgroups were identified, in agreement with their knownpedigrees, geographical distributions, and times since introduction. For each group, we identified lineagespecific genomic divergence regions, which potentially harbor key alleles that determine the characteristics of each group, such as early maturity-related loci. Investigation of the distribution of heterozygous loci, among 12 commercial cotton hybrids, revealed a potential role for these regions in heterosis. Our study provides insight into the population structure of upland cotton germplasm. Furthermore, the overlap between lineagespecific regions and heterozygous loci, in the high-yield hybrids, suggests a role for these regions in cotton heterosis.     

Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome‐wide association study using high‐density SNPs

Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.     

Association Mapping for Epistasis and Environmental Interaction of Yield Traits in 323 Cotton Cultivars under 9 Different Environments

Improving yield is a major objective for cotton breeding schemes, and lint yield and its three component traits (boll number, boll weight and lint percentage) are complex traits controlled by multiple genes and various environments. Association mapping was performed to detect markers associated with these four traits using 651 simple sequence repeats (SSRs). A mixed linear model including epistasis and environmental interaction was used to screen the loci associated with these four yield traits by 323 accessions of Gossypium hirsutum L. evaluated in nine different environments. 251 significant loci were detected to be associated with lint yield and its three components, including 69 loci with individual effects and all involved in epistasis interactions. These significant loci explain ∼ 62.05% of the phenotypic variance (ranging from 49.06% ∼ 72.29% for these four traits). It was indicated by high contribution of environmental interaction to the phenotypic variance for lint yield and boll numbers, that genetic effects of SSR loci were susceptible to environment factors. Shared loci were also observed among these four traits, which may be used for simultaneous improvement in cotton breeding for yield traits. Furthermore, consistent and elite loci were screened with −Log₁₀ (P-value) >8.0 based on predicted effects of loci detected in different environments. There was one locus and 6 pairs of epistasis for lint yield, 4 loci and 10 epistasis for boll number, 15 loci and 2 epistasis for boll weight, and 2 loci and 5 epistasis for lint percentage, respectively. These results provided insights into the genetic basis of lint yield and its components and may be useful for marker-assisted breeding to improve cotton production.     

QTL mapping of yield and fiber traits based on a four-way cross population in <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.

Four-way cross (4WC) involving four different inbred lines frequently appears in the cotton breeding programs. However, linkage analysis and quantitative trait loci (QTL) mapping with molecular markers in cotton has largely been applied to populations derived from a cross between two inbred lines, and few results of QTL dissection were conducted in a 4WC population. In this study, an attempt was made to construct a linkage map and identify QTL for yield and fiber quality traits in 4WC derived from four different inbred lines in Gossypium hirsutum L. A linkage map was constructed with 285 SSR loci and one morphological locus, covering 2113.3 cM, approximately 42% of the total recombination length of the cotton genome. A total of 31 QTL with 5.1–25.8% of the total phenotypic variance explained were detected. Twenty-four common QTL across environments showed high stability, and six QTL were environment-specific. Several genomic segments affecting multiple traits were identified. The advantage of QTL mapping using a 4WC were discussed. This study presents the first example of QTL mapping using a 4WC population in upland cotton. The results presented here will enhance the understanding of the genetic basis of yield and fiber quality traits and enable further marker-assisted selection in cultivar populations in upland cotton.     

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.     

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 between SSR markers and fibre traits in sea island cotton (<Emphasis Type="BoldItalic">Gossypium barbadense</Emphasis>) germplasm resources

Identification of molecular markers associated with fibre traits can accelerate cotton marker-assisted selection (MAS) programmes. In this study, Gossypium barbadense germplasm accessions with diverse origins (\(n = 123\)) were used to perform association analysis of fibre traits with 120 polymorphic simple sequence repeat (SSR) markers. In total, 120 polymorphic primer pairs amplified 258 loci with a mean of 2.15 loci per primer. Population structure analysis identified three main clusters for the accessions, which indicated agreement of genetic and predefined populations. Marker–trait associations (\(n= 58\)) were detected for 10 fibre traits with 26 SSR markers located on 15 chromosomes. The \(R^{2}\) (phenotypic variation explained) ranged from 3.19 to 15.21%. Two markers (NAU5465 and NAU3013) were found to be stably associated with boll number per plant (BNP) and fibre uniformity (UI), respectively. Four markers (BNL252, NAU3424, NAU3324 and CGR5202) associated with fibre quality traits preferentially clustered on the D8 chromosome, which was thus identified as an important candidate region for study molecular mechanisms underlying fibre quality and for use in breeding cotton cultivars for improving fibre quality. This study generated molecular data with a potential for better understanding of the genetic basis of the fibre traits and provided new markers for MAS in G. barbadense breeding programmes.     

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.     

花生重要农艺及产量性状的全基因组关联分析

通过关联分析法发掘与花生(Arachis hypogaea)产量性状显著关联、同时又在花生基因组上随机分布的SSR位点及优异等位变异,可了解产量相关基因区域的分布特点,有助于利用分子标记辅助选择方法选育高产花生新品种。选用64个SSR标记,采用MLM(Q+K)方法对166份花生资源进行全基因组关联分析。结果表明,通过聚类分析和结构划分,供试群体受其综合性状遗传特点和来源地域的影响可被划分成7个亚群,聚类结果与群体结构基本一致,同时群体特点与材料来源地的生态划分符合同类聚集的规律。通过对6个产量相关性状的3年数值的关联分析,分别发掘出SSR位点有20个、33个和26个,2年以上重复检出的SSR位点有13个(P0.05),各SSR位点的表型变异解释率范围为0.011–0.348 1,平均为0.067 3;共检出590个等位变异,平均每个标记位点12.29个,表型变异解释率值最高的是与单株果数呈显著关联的位点TC1A02(P0.001),含21个等位变异;与产量构成主要因子紧密关联的位点中,百果重的TC1A02-C470(+41.588 5)、TC1A02-C560(+40.926 1)和p PGPseq2E6-B473(+63.953 4),单株果数的TC1A02-C500(+7.374 4),单株饱果数的GM1843-E157(+4.316 6),可用于产量性状的分子辅助育种。     

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 uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton

Key message

A total of 62 SNPs associated with yield-related traits were identified by a GWAS. Based on significant SNPs, two candidate genes pleiotropically increase lint yield.

Abstract

Improved fibre yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. To better decipher the molecular mechanism underlying these traits, we conducted a genome-wide association study to determine candidate loci associated with six yield-related traits in a population of 719 upland cotton germplasm accessions; to accomplish this, we used 10,511 single-nucleotide polymorphisms (SNPs) genotyped by an Illumina CottonSNP63K array. Six traits, including the boll number, boll weight, lint percentage, fruit branch number, seed index and lint index, were assessed in multiple environments; large variation in all phenotypes was detected across accessions. We identified 62 SNP loci that were significantly associated with different traits on chromosomes A07, D03, D05, D09, D10 and D12. A total of 689 candidate genes were screened, and 27 of them contained at least one significant SNP. Furthermore, two genes (Gh_D03G1064 and Gh_D12G2354) that pleiotropically increase lint yield were identified. These identified SNPs and candidate genes provide important insights into the genetic control underlying high yields in G. hirsutum, ultimately facilitating breeding programmes of high-yielding cotton.

     

Favorable QTL Alleles for Yield and Its Components Identified by Association Mapping in Chinese Upland Cotton Cultivars

Linkage disequilibrium based association mapping is a powerful tool for dissecting the genetic basis underlying complex traits. In this study, an association mapping panel consisting of 356 representative Upland cotton cultivars was constructed, evaluated in three environments and genotyped using 381 SSRs to detect molecular markers associated with lint yield and its components. The results showed that abundant phenotypic and moderate genetic diversities existed within this germplasm panel. The population could be divided into two subpopulations, and weak relatedness was detected between pair-wise accessions. LD decayed to the background (r ² = 0.1182, P≤0.01), r ² = 0.1 and r ² = 0.2 level within 12–13 cM, 17–18 cM and 3–4 cM, respectively, providing the potential for association mapping of agronomically important traits in Chinese Upland cotton. A total of 55 marker-trait associations were detected between 26 SSRs and seven lint yield traits, based on a mixed linear model (MLM) and Bonferroni correction (P≤0.05/145, −log₁₀ P≥3.46). Of which 41 could be detected in more than one environment and 17 markers were simultaneously associated with two or more traits. Many associations were consistent with QTLs identified by linkage mapping in previous reports. Phenotypic values of alleles of each loci in 41 stably detected associations were compared, and 23 favorable alleles were identified. Population frequency of each favorable allele in historically released cultivar groups was also evaluated. The QTLs detected in this study will be helpful in further understanding the genetic basis of lint yield and its components, and the favorable alleles may facilitate future high-yield breeding by genomic selection in Upland cotton.     

Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (Gossypium hirsutum L.)

Although upland cotton (Gossypium hirsutism L.) originated in the tropics, this early maturity cotton can be planted as far north as 46°N in China due to the accumulation of numerous phenotypic and physiological adaptations during domestication. However, how the genome of early maturity cotton has been altered by strong human selection remains largely unknown. Herein, we report a cotton genome variation map generated by the resequencing of 436 cotton accessions. Whole‐genome scans for sweep regions identified 357 putative selection sweeps covering 4.94% (112 Mb) of the upland cotton genome, including 5184 genes. These genes were functionally related to flowering time control, hormone catabolism, ageing and defence response adaptations to environmental changes. A genome‐wide association study (GWAS) for seven early maturity traits identified 307 significant loci, 22.48% (69) of which overlapped with putative selection sweeps that occurred during the artificial selection of early maturity cotton. Several previously undescribed candidate genes associated with early maturity were identified by GWAS. This study provides insights into the genetic basis of early maturity in upland cotton as well as breeding resources for cotton improvement.     

陆地棉纤维品质性状关联分析及优异等位基因挖掘

本研究检测了214个陆地棉材料在多环境下的纤维品质指标(上半部平均长度、断裂比强度、马克隆值、伸长率和整齐度),选用在棉花基因组上均匀分布多态性较好的259个SSR标记对供试群体进行基因型检测,利用Tassel软件中的GLM(Q)方法挖掘与纤维品质指标相关的QTLs,依据表型效应值鉴别优异等位变异位点及典型材料。结果显示:同一纤维品质性状在3个地点2~3年内变化趋势相对稳定,纤维上半部平均长度、断裂比强度和整齐度三者之间呈正相关(P<0.01),纤维上半部平均长度/断裂比强度均和马克隆值/伸长率负相关。259个SSR标记共检测到309个等位基因,涉及774个基因型,多态性信息含量(PIC,polymorphic information content)平均为0.2688,基因多样性指数平均为0.2239。按照基因型数据可将该群体划分为2个亚群。通过关联分析获得与纤维品质相关的等位变异位点134个(P<0.01),在3个及以上环境中均可检测到的位点有30个,有3个位点(NAU6177、DPL0886、NAU3607)在7个环境中分别与断裂比强度、马克隆值、伸长率显著关联(P<0.01),最高表型变异解释率分别为11.14%、5.74%和13.99%。31个位点同时与2个及以上纤维品质指标相关,其中,NAU 6177与5个纤维品质指标均显著关联(P<0.01)。与已发表结果比对,17个QTL已被报道与纤维品质性状相关,10个QTL与前人关联指标相同。分析多环境纤维品质关联位点的表型效应,获得72个等位变异位点,5份携带优异等位基因载体材料。本研究在多环境下挖掘与陆地棉纤维品质指标关联的分子标记,同时鉴别携带优异等位变异基因的典型载体材料,为棉花纤维品质分子标记辅助选择及目标基因定位提供有益信息。     

Identification of favorable SNP alleles and candidate genes responsible for inflorescence-related traits via GWAS in chrysanthemum

Key message

81 SNPs were identified for three inflorescence-related traits, in which 15 were highly favorable. Two dCAPS markers were developed for future MAS breeding, and six candidate genes were predicted.

Abstract

Chrysanthemum is a leading ornamental species worldwide and demonstrates a wealth of morphological variation. Knowledge about the genetic basis of its phenotypic variation for key horticultural traits can contribute to its effective management and genetic improvement. In this study, we conducted a genome-wide association study (GWAS) based on two years of phenotype data and a set of 92,617 single nucleotide polymorphisms (SNPs) using a panel of 107 diverse cut chrysanthemums to dissect the genetic control of three inflorescence-related traits. A total of 81 SNPs were significantly associated with the three inflorescence-related traits (capitulum diameter, number of ray florets and flowering time) in at least one environment, with an individual allele explaining 22.72–38.67% of the phenotypic variation. Fifteen highly favorable alleles were identified for the three target traits by computing the phenotypic effect values for the stable associations detected in 2 year-long trials at each locus. Dosage pyramiding effects of the highly favorable SNP alleles and significant linear correlations between highly favorable allele numbers and corresponding phenotypic performance were observed. Two highly favorable SNP alleles correlating to flowering time and capitulum diameter were converted to derived cleaved amplified polymorphic sequence (dCAPS) markers to facilitate future breeding. Finally, six putative candidate genes were identified that contribute to flowering time and capitulum diameter. These results serve as a foundation for analyzing the genetic mechanisms underlying important horticultural traits and provide valuable insights into molecular marker-assisted selection (MAS) in chrysanthemum breeding programs.

     

Genetic analysis of maize germplasm in the Korean Genebank and association with agronomic traits and simple sequence repeat markers

We assessed genetic and phenotypic variation in 105 maize germplasm accessions from RDA-Genebank of Korea and performed association analyses for 11 agronomical traits and 100 simple sequence repeats (SSR). Genetic diversity (GD) analysis revealed a total of 1104 alleles at the 100 SSR loci. The average number of alleles per locus was 11.0. The average GD and polymorphic information content values were 0.73 and 0.70, respectively. The average major allele frequency was 0.41. Population structure analysis indicated that these maize accessions comprised two major groups and one admixed group based on a membership probability threshold of 0.80. The two major groups contained 35 and 46 maize accessions. A mixed linear model of association analysis revealed five marker-trait associations with a significance level of P?≤?0.01 involving five SSR markers. A general linear model showed 72 marker-trait associations involving 42 SSR markers. We confirmed the presence in the general linear model associations of the five significant marker-trait associations (SMTAs) identified in the mixed linear model. For these SMTAs, two loci were associated with stem diameter and one locus each was associated with ear row number, leaf width, and leaf length. These results should prove useful for breeding new inbred lines by selecting parental lines using molecular markers and will help to preserve maize genetic resources in Korea.     

Association mapping for yield and grain quality traits in rice (Oryza sativa L.)

Association analysis was applied to a panel of accessions of Embrapa Rice Core Collection (ERiCC) with 86 SSR and field data from two experiments. A clear subdivision between lowland and upland accessions was apparent, thereby indicating the presence of population structure. Thirty-two accessions with admixed ancestry were identified through structure analysis, these being discarded from association analysis, thus leaving 210 accessions subdivided into two panels. The association of yield and grain-quality traits with SSR was undertaken with a mixed linear model, with markers and subpopulation as fixed factors, and kinship matrix as a random factor. Eight markers from the two appraised panels showed significant association with four different traits, although only one (RM190) maintained the marker-trait association across years and cultivation. The significant association detected between amylose content and RM190 was in agreement with previous QTL analyses in the literature. Herein, the feasibility of undertaking association analysis in conjunction with germplasm characterization was demonstrated, even when considering low marker density. The high linkage disequilibrium expected in rice lines and cultivars facilitates the detection of marker-trait associations for implementing marker assisted selection, and the mining of alleles related to important traits in germplasm.