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.     

Allelic analysis of sheath blight resistance with association mapping in rice

Sheath blight (ShB) caused by the soil-borne pathogen Rhizoctonia solani is one of the most devastating diseases in rice world-wide. Global attention has focused on examining individual mapping populations for quantitative trait loci (QTLs) for ShB resistance, but to date no study has taken advantage of association mapping to examine hundreds of lines for potentially novel QTLs. Our objective was to identify ShB QTLs via association mapping in rice using 217 sub-core entries from the USDA rice core collection, which were phenotyped with a micro-chamber screening method and genotyped with 155 genome-wide markers. Structure analysis divided the mapping panel into five groups, and model comparison revealed that PCA5 with genomic control was the best model for association mapping of ShB. Ten marker loci on seven chromosomes were significantly associated with response to the ShB pathogen. Among multiple alleles in each identified loci, the allele contributing the greatest effect to ShB resistance was named the putative resistant allele. Among 217 entries, entry GSOR 310389 contained the most putative resistant alleles, eight out of ten. The number of putative resistant alleles presented in an entry was highly and significantly correlated with the decrease of ShB rating (r = −0.535) or the increase of ShB resistance. Majority of the resistant entries that contained a large number of the putative resistant alleles belonged to indica, which is consistent with a general observation that most ShB resistant accessions are of indica origin. These findings demonstrate the potential to improve breeding efficiency by using marker-assisted selection to pyramid putative resistant alleles from various loci in a cultivar for enhanced ShB resistance in rice.     

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.     

Genotypic and phenotypic characterization of genetic differentiation and diversity in the USDA rice mini-core collection

A rice mini-core collection consisting of 217 accessions has been developed to represent the USDA core and whole collections that include 1,794 and 18,709 accessions, respectively. To improve the efficiency of mining valuable genes and broadening the genetic diversity in breeding, genetic structure and diversity were analyzed using both genotypic (128 molecular markers) and phenotypic (14 numerical traits) data. This mini-core had 13.5 alleles per locus, which is the most among the reported germplasm collections of rice. Similarly, polymorphic information content (PIC) value was 0.71 in the mini-core which is the highest with one exception. The high genetic diversity in the mini-core suggests there is a good possibility of mining genes of interest and selecting parents which will improve food production and quality. A model-based clustering analysis resulted in lowland rice including three groups, aus (39 accessions), indica (71) and their admixtures (5), upland rice including temperate japonica (32), tropical japonica (40), aromatic (6) and their admixtures (12) and wild rice (12) including glaberrima and four other species of Oryza. Group differentiation was analyzed using both genotypic distance Fst from 128 molecular markers and phenotypic (Mahalanobis) distance D(2) from 14 traits. Both dendrograms built by Fst and D(2) reached similar-differentiative relationship among these genetic groups, and the correlation coefficient showed high value 0.85 between Fst matrix and D(2) matrix. The information of genetic and phenotypic differentiation could be helpful for the association mapping of genes of interest. Analysis of genotypic and phenotypic diversity based on genetic structure would facilitate parent selection for broadening genetic base of modern rice cultivars via breeding effort.     

Association mapping of yield and its components in rice cultivars

To make advances in rice breeding it is important to understand the relatedness and ancestry of introduced rice accessions, and identify SSR markers associated with agronomically important phenotypic traits, for example yield. Ninety-two rice germplasm accessions recently introduced from seven geographic regions of Africa, Asia, and Latin America, and eleven US cultivars, included as checks, were evaluated for yield and kernel characteristics, and genotyped with 123 SSR markers. The SSR markers were highly polymorphic across all accessions. Population structure analysis identified eight main clusters for the accessions which corresponded to the major geographic regions, indicating agreement between genetic and predefined populations. Linkage disequilibrium (LD) patterns and distributions are of fundamental importance for genome-wide mapping association. LD between linked markers decreased with distance and with a substantial drop in LD decay values between 20 and 30 cM, suggesting it should be possible to achieve resolution down to the 25 cM level. For the 103 cultivars, the complex traits yield, kernel width, kernel length, kernel width/length ratio, and 1000-kernel weight, were estimated by analysis of variety trial data. The mixed linear model method was used to disclose marker-trait associations. Many of the associated markers were located in regions where QTL had previously been identified. In conclusion, association mapping in rice is a viable alternative to QTL mapping based on crosses between different lines.     

Cloning of AFLP markers linked to resistance to Peronosclerospora sorghi in maize

Genetic mapping of resistance genes for sorghum downy mildew (SDM) in maize revealed multiple-locus inheritance. A combination of AFLP (amplified fragment length polymorphism) technique with bulked segregant analysis (BSA) was applied to map the genes involved in the resistance to SDM (Peronosclerospora sorghi) in a recombinant inbred population. Three AFLP markers were identified and mapped to chromosomes 1 and 9, in regions previously associated with SDM resistance. One other AFLP marker was found to be associated with disease susceptibility but could not be linked to any chromosome. These four AFLP fragments were isolated, cloned and sequenced. A BLAST search of the GenBank database showed that none of these four sequences was closely related to resistance genes that have been reported previously. Sequence-characterized amplified regions (SCARs) were produced and used to assess the presence of SDM resistance genes and characterize specific genotypes. These markers may be useful in marker-assisted breeding programs.     

Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)

Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.     

Identification of QTLs associated with Fusarium head blight resistance in Zhedar 2 barley

Fusarium head blight (FHB) in barley and wheat, caused by Fusarium graminearum, is a continual problem worldwide. Primarily, FHB reduces yield and quality, and results in the production of the toxin deoxynivalenol (DON), which can affect food safety. Identification of QTLs for FHB severity, DON level and related traits heading-date (HD) and plant-height (HT) with consistent effects across a set of environments, would provide the basis for marker-assisted selection (MAS) and potentially increase the efficiency of selection for resistance. A segregating population of 75 double-haploid lines, developed from the three-way cross Zhedar 2/ND9712//Foster, was used for genome mapping and FHB severity evaluation. A linkage map of 214 RFLP, SSR and AFLP markers was constructed. Phenotypic data were collected in replicated field trials from five environments in two growing seasons. The data were analyzed using MQTL software to detect quantitative trait locus (QTL) × environment (E) interactions. Because of the presence of QTL × E, the MQM procedure in MAPQTL was applied to identify QTLs in single environments. We identified nine QTLs for FHB severity and five for low DON. Many of the disease-related QTLs identified were coincident with FHB QTLs identified in previous studies. Only two of the QTLs identified in this study were consistent across all five environments, and both were Zhedar 2 specific. Five of the FHB QTLs were associated with HD, and two were associated with HT. Regions that appear to be promising candidates for MAS and further genetic analysis include the two FHB QTLs on chromosome 2H and one on 6H, which were also associated with low DON and later heading-date in multiple environments. This study provides a starting point for manipulating Zhedar 2-derived resistance by MAS in barley to develop cultivars that will show effective resistance under disease pressure.Communicated by H.F. Linskens     

Genetic mapping of QTLs associated with greenbug resistance and tolerance in Sorghum bicolor

Ninety three recombinant inbreds of Sorghum bicolor (L. Moench) were derived from a cross between two sorghum lines GBIK and Redlan. This population was used to identify quantitative trait loci (QTLs) for resistance and tolerance to greenbug (Schizaphids graminum Rondani) Biotypes I and K. One hundred and thirteen loci (38 SSRs and 75 RAPDs) were mapped in 12 linkage groups covering 1,530 cM. In general, nine QTLs were detected affecting both resistance and tolerance to greenbug (GB) Biotypes I and K. The phenotypic variance explained by each QTL ranged from 5.6% to 38.4%. Four SSRs and one RAPD marker were associated with the expression of all resistance and tolerance traits. These markers appear to be linked to biotype non-specific resistance and tolerance genes. Four additional markers were associated with biotype-specific resistance or tolerance traits. The detection of more than one locus for each biotype supports the hypothesis that several regions, which represent different genes, control the expression of resistance and tolerance to greenbug in sorghum. The results can be used for marker-assisted selection and the breeding of greenbug-tolerant sorghum cultivars.