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.     

Identification of genome regions controlling cotyledon,pod wall/seed coat and pod wall resistance to pea weevil through QTL mapping

Pea weevil, Bruchus pisorum, is one of the limiting factors for field pea (Pisum sativum) cultivation in the world with pesticide application the only available method for its control. Resistance to pea weevil has been found in an accession of Pisum fulvum but transfer of this resistance to cultivated pea (P. sativum) is limited due to a lack of easy-to-use techniques for screening interspecific breeding populations. To address this problem, an interspecific population was created from a cross between cultivated field pea and P. fulvum (resistance source). Quantitative trait locus (QTL) mapping was performed to discover the regions associated with resistance to cotyledon, pod wall/seed coat and pod wall resistance. Three major QTLs, located on linkage groups LG2, LG4 and LG5 were found for cotyledon resistance explaining approximately 80 % of the phenotypic variation. Two major QTLs were found for pod wall/seed coat resistance on LG2 and LG5 explaining approximately 70 % of the phenotypic variation. Co-linearity of QTLs for cotyledon and pod wall/seed coat resistance suggested that the mechanism of resistance for these two traits might act through the same pathways. Only one QTL was found for pod wall resistance on LG7 explaining approximately 9 % of the phenotypic variation. This is the first report on the development of QTL markers to probe Pisum germplasm for pea weevil resistance genes. These flanking markers will be useful in accelerating the process of screening when breeding for pea weevil resistance.     

Promoting Utilization of Saccharum spp. Genetic Resources through Genetic Diversity Analysis and Core Collection Construction

Sugarcane (Saccharum spp.) and other members of Saccharum spp. are attractive biofuel feedstocks. One of the two World Collections of Sugarcane and Related Grasses (WCSRG) is in Miami, FL. This WCSRG has 1002 accessions, presumably with valuable alleles for biomass, other important agronomic traits, and stress resistance. However, the WCSRG has not been fully exploited by breeders due to its lack of characterization and unmanageable population. In order to optimize the use of this genetic resource, we aim to 1) genotypically evaluate all the 1002 accessions to understand its genetic diversity and population structure and 2) form a core collection, which captures most of the genetic diversity in the WCSRG. We screened 36 microsatellite markers on 1002 genotypes and recorded 209 alleles. Genetic diversity of the WCSRG ranged from 0 to 0.5 with an average of 0.304. The population structure analysis and principal coordinate analysis revealed three clusters with all S. spontaneum in one cluster, S. officinarum and S. hybrids in the second cluster and mostly non-Saccharum spp. in the third cluster. A core collection of 300 accessions was identified which captured the maximum genetic diversity of the entire WCSRG which can be further exploited for sugarcane and energy cane breeding. Sugarcane and energy cane breeders can effectively utilize this core collection for cultivar improvement. Further, the core collection can provide resources for forming an association panel to evaluate the traits of agronomic and commercial importance.     

Using minimum DNA marker loci for accurate population classification in rice (Oryza sativa L.)

Because of the rich diversity among rice accessions grown around the world in distinct environments, traditional methods using morphology, cross compatibility and geography for classifying rice accessions according to different sub-populations have given way to use of molecular markers. Having a few robust markers that can quickly assign population structure to germplasm will facilitate making more informed choices about genetic diversity within seedbanks and breeding genepools. WHICHLOCI is a computer program that selects the best combination of loci for population assignment through empirical analysis of molecular marker data. This program has been used in surveys of plant species, for fish population assignment, and in human ancestry analysis. Using WHICHLOCI, we ranked the discriminatory power of 72 DNA markers used to genotype 1,604 accessions of the USDA rice core collection, and developed panels with a minimum number of markers for population assignment with 99% or higher accuracy. A total of 14 markers with high discriminatory power, genetic diversity, allelic frequency, and polymorphic information content were identified. A panel of just four markers, RM551, RM11, RM224 and RM44, was effective in assigning germplasm accessions to any of five sub-populations with 99.4% accuracy. Panels using only three markers were effective for assignment of rice germplasm to specific sub-populations, tropical japonica, temperate japonica, indica, aus, and aromatic. Assignment to tropical japonica, temperate japonica, or indica sub-populations was highly reliable using 3–4 markers, demonstrated by the high correlation with assignment using 72 markers. However, population assignment to aus and aromatic groups was less reliable, possibly due to the smaller representation of this material in the USDA core collection. More reference cultivars may be needed to improve population assignment to these two groups. This study demonstrated that a small number of DNA markers is effective for classification of germplasm into five sub-populations in rice. This will facilitate rapid screening of large rice germplasm banks for population assignment at a modest cost. The resulting information will be valuable to researchers to verify population classification of germplasm prior to initiating genetic studies, maximizing genetic diversity between sub-populations, or minimizing cross incompatibility while maximizing allelic diversity within specific sub-populations.     

Population structure and association mapping of yield contributing agronomic traits in foxtail millet

Key message

Association analyses accounting for population structure and relative kinship identified eight SSR markers ( p < 0.01) showing significant association ( R ²  = 18 %) with nine agronomic traits in foxtail millet.

Abstract

Association mapping is an efficient tool for identifying genes regulating complex traits. Although association mapping using genomic simple sequence repeat (SSR) markers has been successfully demonstrated in many agronomically important crops, very few reports are available on marker-trait association analysis in foxtail millet. In the present study, 184 foxtail millet accessions from diverse geographical locations were genotyped using 50 SSR markers representing the nine chromosomes of foxtail millet. The genetic diversity within these accessions was examined using a genetic distance-based and a general model-based clustering method. The model-based analysis using 50 SSR markers identified an underlying population structure comprising five sub-populations which corresponded well with distance-based groupings. The phenotyping of plants was carried out in the field for three consecutive years for 20 yield contributing agronomic traits. The linkage disequilibrium analysis considering population structure and relative kinship identified eight SSR markers (p < 0.01) on different chromosomes showing significant association (R ² = 18 %) with nine agronomic traits. Four of these markers were associated with multiple traits. The integration of genetic and physical map information of eight SSR markers with their functional annotation revealed strong association of two markers encoding for phospholipid acyltransferase and ubiquitin carboxyl-terminal hydrolase located on the same chromosome (5) with flag leaf width and grain yield, respectively. Our findings on association mapping is the first report on Indian foxtail millet germplasm and this could be effectively applied in foxtail millet breeding to further uncover marker-trait associations with a large number of markers.     

Association mapping of stigma and spikelet characteristics in rice (Oryza sativa L.)

Stigma and spikelet characteristics play an essential role in hybrid seed production. A mini-core of 90 accessions developed from USDA rice core collection was phenotyped in field grown for nine traits of stigma and spikelet and genotyped with 109 DNA markers, 108 SSRs plus an indel. Three major clusters were built upon Rogers’ genetic distance, indicative of indicas, and temperate and tropical japonicas. A mixed linear model combining PC-matrix and K-matrix was adapted for mapping marker-trait associations. Resulting associations were adjusted using false discovery rate technique. We identified 34 marker-trait associations involving 22 SSR markers for eight traits. Four markers were associated with single stigma exsertion (SStgE), six with dual exsertion (DStgE) and five with total exsertion. RM5_Chr1 played major role indicative of high regression with not only DStgE but also SStgE. Four markers were associated with spikelet length, three with width and seven with L/W ratio. Numerous markers were co-associated with multiple traits that were phenotypically correlated, i.e. RM12521_Chr2 associated with all three correlated spikelet traits. The co-association should improve breeding efficiency because single marker could be used to assist breeding for multiple traits. Indica entry 1032 (cultivar 50638) and japonica entry 671 (cultivar Linia 84 Icar) with 80.65 and 75.17% of TStgE, respectively are recommended to breeder for improving stigma exsertion.     

Development and validation of breeder-friendly KASPar markers for <Emphasis Type="Italic">er1</Emphasis>, a powdery mildew resistance gene in pea (<Emphasis Type="Italic">Pisum sativum</Emphasis> L.)

Powdery mildew of pea is caused by Erysiphe pisi DC and is a serious threat to pea (Pisum sativum L.) production throughout much of the world. Development and utilization of genetic resistance to powdery mildew is considered an effective and sustainable strategy to manage this disease. One gene, er1, conferring powdery mildew resistance, was previously cloned and sequenced, and the functional markers for each resistance allele were reported. Allele-specific DNA markers are efficient and powerful tools to facilitate crop improvement and new cultivar development in breeding programs. However, extensive application of these markers is limited by gel-associated obstacles. In this study, eight breeder-friendly kompetitive allele-specific PCR (KASPar) markers were developed to overcome the problems of gel-based markers and increase the efficiency of genotypic screening. In order to identify additional pea germplasm with powdery mildew resistance, these KASPar markers were deployed and used to genotype a pea collection derived from the USDA pea single-plant (PSP) collection. Simultaneously, a phenotypic screening and a genotypic validation using the corresponding gel-based functional markers were conducted on the PSP collection. One pea accession, PI 142775, was identified by both phenotyping and genotyping to carry the allele er1-1 for powdery mildew resistance, indicating that the KASPar assay is an efficient and robust tool for breeding for powdery mildew resistance.     

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.     

A core collection and mini core collection of Oryza sativa L. in China

The extent of and accessibility to genetic variation in a large germplasm collection are of interest to biologists and breeders. Construction of core collections (CC) is a favored approach to efficient exploration and conservation of novel variation in genetic resources. Using 4,310 Chinese accessions of Oryza sativa L. and 36 SSR markers, we investigated the genetic variation in different sized sub-populations, the factors that affect CC size and different sampling strategies in establishing CC. Our results indicated that a mathematical model could reliably simulate the relationship between genetic variation and population size and thus predict the variation in large germplasm collections using randomly sampled populations of 700?C1,500 accessions. We recommend two principles in determining the CC size: (1) compromising between genetic variation and genetic redundancy and (2) retaining the main types of alleles. Based on the most effective scheme selected from 229 sampling schemes, we finally developed a hierarchical CC system, in which different population scales and genetic diversities allow a flexible use of genetic resources. The CC, comprising 1.7% (932) of the accessions in the basic collection, retained more than 85% of both the SSR and phenotypic variations. A mini core collection, comprising 0.3% (189) of the accessions in the basic collection, retained 70.65% of the SSR variation and 76.97% of the phenotypic variation, thus providing a rational framework for intensive surveys of natural variation in complex traits in rice genetic resources and hence utilization of variation in rice breeding.     

Genetic Dissection of Drought and Heat Tolerance in Chickpea through Genome-Wide and Candidate Gene-Based Association Mapping Approaches

To understand the genetic basis of tolerance to drought and heat stresses in chickpea, a comprehensive association mapping approach has been undertaken. Phenotypic data were generated on the reference set (300 accessions, including 211 mini-core collection accessions) for drought tolerance related root traits, heat tolerance, yield and yield component traits from 1–7 seasons and 1–3 locations in India (Patancheru, Kanpur, Bangalore) and three locations in Africa (Nairobi, Egerton in Kenya and Debre Zeit in Ethiopia). Diversity Array Technology (DArT) markers equally distributed across chickpea genome were used to determine population structure and three sub-populations were identified using admixture model in STRUCTURE. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations (r²; when r²<0.20) was found to decay rapidly with the genetic distance of 5 cM. For establishing marker-trait associations (MTAs), both genome-wide and candidate gene-sequencing based association mapping approaches were conducted using 1,872 markers (1,072 DArTs, 651 single nucleotide polymorphisms [SNPs], 113 gene-based SNPs and 36 simple sequence repeats [SSRs]) and phenotyping data mentioned above employing mixed linear model (MLM) analysis with optimum compression with P3D method and kinship matrix. As a result, 312 significant MTAs were identified and a maximum number of MTAs (70) was identified for 100-seed weight. A total of 18 SNPs from 5 genes (ERECTA, 11 SNPs; ASR, 4 SNPs; DREB, 1 SNP; CAP2 promoter, 1 SNP and AMDH, 1SNP) were significantly associated with different traits. This study provides significant MTAs for drought and heat tolerance in chickpea that can be used, after validation, in molecular breeding for developing superior varieties with enhanced drought and heat tolerance.     

Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection

Sugarcane is an economically important crop for both food and biofuel industries. Marker-assisted breeding in sugarcane is becoming a reality with the recent development and deployment of markers linked with disease resistance genes. Large linkage disequilibrium in sugarcane makes genome-wide association studies (GWAS) a better alternative to biparental mapping to identify markers associated with agronomic traits. GWAS was conducted on a Louisiana core collection to identify marker-trait associations (MTA) for 11 cane yield and sucrose traits using single nucleotide polymorphism (SNP) and insertion-deletion (Indel) markers. Significant (P < .05) MTAs were identified for all traits where the top ranked markers explained up to 15% of the total phenotypic variation. High correlations (0.732 to 0.999) were observed between sucrose traits and 56 markers were found consistent across multiple traits. These markers following validation in more diverse populations could be used in marker-assisted selection of clones in sugarcane breeding program in Louisiana and elsewhere.     

Evaluation of Genetic Diversity and Development of a Core Collection of Wild Rice (Oryza rufipogon Griff.) Populations in China

Common wild rice (Oryza rufipogon Griff.), the progenitor of Asian cultivated rice (O. sativa L.), is endangered due to habitat loss. The objectives of this research were to evaluate the genetic diversity of wild rice species in isolated populations and to develop a core collection of representative genotypes for ex situ conservation. We collected 885 wild rice accessions from eight geographically distinct regions and transplanted these accessions in a protected conservation garden over a period of almost two decades. We evaluated these accessions for 13 morphological or phenological traits and genotyped them for 36 DNA markers evenly distributed on the 12 chromosomes. The coefficient of variation of quantitative traits was 0.56 and ranged from 0.37 to 1.06. SSR markers detected 206 different alleles with an average of 6 alleles per locus. The mean polymorphism information content (PIC) was 0.64 in all populations, indicating that the marker loci have a high level of polymorphism and genetic diversity in all populations. Phylogenetic analyses based on morphological and molecular data revealed remarkable differences in the genetic diversity of common wild rice populations. The results showed that the Zengcheng, Gaozhou, and Suixi populations possess higher levels of genetic diversity, whereas the Huilai and Boluo populations have lower levels of genetic diversity than do the other populations. Based on their genetic distance, 130 accessions were selected as a core collection that retained over 90% of the alleles at the 36 marker loci. This genetically diverse core collection will be a useful resource for genomic studies of rice and for initiatives aimed at developing rice with improved agronomic traits.     

Genetic diversity and association mapping in a collection of selected Chinese soybean accessions based on SSR marker analysis

For broadening the narrow genetic base of modern soybean cultivars, 159 accessions were selected from the Chinese soybean collection which contained at least one of seven important agronomic traits: resistance to soybean cyst nematode (SCN) or soybean mosaic virus (SMV), tolerance to salt, cold, or drought, high seed oil content or high protein content. Genetic diversity evaluation using 55 microsatellite loci distributed across the genome indicated that a large amount of genetic diversity (0.806) and allelic variation (781) were conserved in this selected set, which captured 65.6% of the alleles present in Chinese soybean collection (1,863 accessions). On average, 9.4 rare alleles (frequency <5%) per locus were present, which were highly informative. Using model-based Bayesian clustering in STRUCTURE we distinguished four main clusters and a set of accessions with admixed ancestry. The four clusters reflected different geographic regions of origin of the accessions. Since the clusters were also clearly different with respect to the seven agronomic traits, the inferred population structure was introduced when association analysis was conducted. A total of 21 SSR markers on 16 chromosomes were identified as significantly (P < 0.01) associated with high oil content (6), high protein content (1), drought tolerance (5), SCN resistance (6) and SMV resistance (3). Twelve of these markers were located in or near previously identified quantitative trait loci (QTL). The results for both genetic relationship and trait-related markers will be useful for effective conservation and utilization of soybean germplasm.     

Association mapping of seed quality traits using the Canadian flax (Linum usitatissimum L.) core collection

Key message

The identification of stable QTL for seed quality traits by association mapping of a diverse panel of linseed accessions establishes the foundation for assisted breeding and future fine mapping in linseed.

Abstract

Linseed oil is valued for its food and non-food applications. Modifying its oil content and fatty acid (FA) profiles to meet market needs in a timely manner requires clear understanding of their quantitative trait loci (QTL) architectures, which have received little attention to date. Association mapping is an efficient approach to identify QTL in germplasm collections. In this study, we explored the quantitative nature of seed quality traits including oil content (OIL), palmitic acid, stearic acid, oleic acid, linoleic acid (LIO) linolenic acid (LIN) and iodine value in a flax core collection of 390 accessions assayed with 460 microsatellite markers. The core collection was grown in a modified augmented design at two locations over 3 years and phenotypic data for all seven traits were obtained from all six environments. Significant phenotypic diversity and moderate to high heritability for each trait (0.73–0.99) were observed. Most of the candidate QTL were stable as revealed by multivariate analyses. Nine candidate QTL were identified, varying from one for OIL to three for LIO and LIN. Candidate QTL for LIO and LIN co-localized with QTL previously identified in bi-parental populations and some mapped nearby genes known to be involved in the FA biosynthesis pathway. Fifty-eight percent of the QTL alleles were absent (private) in the Canadian cultivars suggesting that the core collection possesses QTL alleles potentially useful to improve seed quality traits. The candidate QTL identified herein will establish the foundation for future marker-assisted breeding in linseed.     

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.     

A mini core subset for capturing diversity and promoting utilization of chickpea genetic resources in crop improvement

A core collection is a chosen subset of large germplasm collection that generally contains about 10% of the total accessions and represents the genetic variability of entire germplasm collection. The purpose of a core collection is to improve the use of genetic resources in crop improvement programs. In many crops the number of accessions contained in the genebank are several thousands, and a core subset consisting of 10% of total accessions would be an unwieldy proposition. In this article we have suggested a two-stage strategy to select a chickpea mini core subset consisting of only about 1% of the entire collection held in trust at ICRISAT’s genebank (16,991 accessions). This mini core subset still represents the diversity of the entire core collection. The first stage involves developing a representative core subset (about 10%) from the entire collection using all the available information on origin, geographical distribution, and characterization and evaluation data of accessions. The second stage involves evaluation of the core subset for various morphological, agronomic, and quality traits, and selecting a further subset of about 10% accessions from the core subset. At both stages standard clustering procedure was used to separate groups of similar accessions. A mini core subset consisting 211 accessions from 1,956 core subset accessions, using data on 22 morphological and agronomic traits, was selected. Newman- Keuls’ test for means, Levene’s test for variances, the chi-square test and Wilcoxon’s rank-sum non-parametric test for frequency distribution analysis for different traits indicated that the variation available in the core collection has been preserved in the mini core subset. The most important phenotypic correlations which may be under the control of coadapted gene complexes, were also preserved in the mini core. This mini core subset, due to its drastically reduced size, will prove to be a point of entry to proper exploitation of chickpea genetic resources. Received: 20 August 2000 / Accepted: 25 September 2000     

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.