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

RING finger E3 ubiquitin ligase gene TaAIRP2-1B controls spike length in wheat

E3 ubiquitin ligase genes play important roles in the regulation of plant development. They have been well studied in plants, but have not been sufficiently investigated in wheat. Here, we identified a highly expressed RING finger E3 ubiquitin ligase gene TaAIRP2-1B (ABA-insensitive RING protein 2) in wheat spike. Sequence polymorphism and association analysis showed that TaAIRP2-1B is significantly associated with spike length under various conditions. The genotype with haplotype Hap-1B-1 of TaAIRP2-1B has a longer spike than that of Hap-1B-2, and was positively selected in the process of wheat breeding in China. Moreover, the TaAIRP2-1B-overexpressing rice lines have longer panicles compared with wild-type plants. The expression levels of TaAIRP2-1B in Hap-1B-1 accessions were higher than in Hap-1B-2 accessions. Further study revealed that the expression of TaAIRP2-1B was negatively regulated by TaERF3 (ethylene-responsive factor 3) via binding to the Hap-1B-2 promoter, but not via binding of Hap-1B-1. Additionally, several candidate genes interacting with TaAIRP2-1B were obtained by screening the cDNA library of wheat in yeast cells. It was found that TaAIRP2-1B interacted with TaHIPP3 (heavy metal-associated isoprenylated protein 3) and promoted TaHIPP3 degradation. Our study demonstrates that TaAIRP2-1B controls spike length, and the haplotype Hap-1B-1 of TaAIRP2-1B is a favorable natural variation for spike length enhancement in wheat. This work also provides genetic resources and functional markers for wheat molecular breeding.

Molecular and genetic dissection of the USDA rice mini-core collection using high-density SNP markers

Molecular tools and knowledge of crop germplasm are vital for their effective utilization. In this study, we developed 40,866 high-quality and well distributed SNPs for a rice mini-core collection (RMC) developed by the United States Department of Agriculture (USDA). The high-quality SNPs clustered the USDA-RMC into five subpopulations (Ind, indica; Aus, aus; Afr, African rice; TeJ, temperate japonica; TrJ, tropical japonica) and one admixture (Adm). This classification was further confirmed by phylogenetic and principal component analyses. The rice ARO (aromatic) subpopulation of previous studies was re-assigned with Adm and the WD (wild-type) subpopulation was re-defined to the Afr subpopulation because most of its accessions are African cultivated rice. The Aus and Ind subpopulations had a substantially wider genetic variation than the TrJ and TeJ subpopulations. The genetic diversities were much larger between the Ind or Aus subpopulation and the TrJ or TeJ subpopulation than between the Afr subpopulation and the Ind, Aus, TrJ or TeJ subpopulation. Comparative agronomic trait analysis between the subpopulations also supported the genetic structure and variation of the RMC, and suggested the existence of extensive variation in the genes controlling agronomic traits among them. Furthermore, analysis of ancestral membership of the RMC accessions revealed that reproductive barrier or wide incompatibility existed between the Indica and Japonica groups, while gene flow occurred between them. These results provide high-quality SNPs and knowledge of genetic structure and diversity of the USDA-RMC necessary for enhanced rice research and breeding.

Genome-wide association studies of ionomic and agronomic traits in USDA mini core collection of rice and comparative analyses of different mapping methods

BACKGROUND

Rice is an important human staple food vulnerable to heavy metal contamination leading to serious concerns. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge and markers.

RESULTS

To identify candidate QTLs and develop molecular markers for rice yield and heavy metal content, a total of 191 accessions from the USDA Rice mini-core collection with over 3.2 million SNPs were employed to investigate the QTLs. Sixteen ionomic and thirteen agronomic traits were analyzed utilizing two univariate (GLM and MLM) and two multivariate (MLMM and FarmCPU) GWAS methods. 106, 47, and 97 QTLs were identified for ionomics flooded, ionomics unflooded, and agronomic traits, respectively, with the criterium of p-value < 1.53 × 10^- 8, which was determined by the Bonferroni correction for p-value of 0.05. While 49 (~ 20%) of the 250 QTLs were coinciding with previously reported QTLs/genes, about 201 (~ 80%) were new. In addition, several new candidate genes involved in ionomic and agronomic traits control were identified by analyzing the DNA sequence, gene expression, and the homologs of the QTL regions. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs, suggesting that using multiple GWAS methods can complement each other in QTL identification, especially by combining univariate and multivariate methods.

CONCLUSIONS

While 49 previously reported QTLs/genes were rediscovered, over 200 new QTLs for ionomic and agronomic traits were found in the rice genome. Moreover, multiple new candidate genes for agronomic and ionomic traits were identified. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing the foundation for marker development in breeding and further investigation on reducing heavy-metal contamination and improving crop yields. Finally, the comparative analysis of the GWAS methods showed that each method has unique features and different methods can complement each other.

Genome-Wide Correlation of 36 Agronomic Traits in the 287 Pepper (Capsicum) Accessions Obtained from the SLAF-seq-Based GWAS

There are many agronomic traits of pepper (Capsicum L.) with abundant phenotypes that can benefit pepper growth. Using specific-locus amplified fragment sequencing (SLAF-seq), a genome-wide association study (GWAS) of 36 agronomic traits was carried out for 287 representative pepper accessions. To ensure the accuracy and reliability of the GWAS results, we analyzed the genetic diversity, distribution of labels (SLAF tags and single nucleotide polymorphisms (SNPs)) and population differentiation and determined the optimal statistical model. In our study, 1487 SNPs were highly significantly associated with 26 agronomic traits, and 2126 candidate genes were detected in the 100-kb region up- and down-stream near these SNPs. Furthermore, 13 major association peaks were identified for 11 key agronomic traits. Then we examined the correlations among the 36 agronomic traits and analyzed SNP distribution and found 37 SNP polymerization regions (total size: 264.69 Mbp) that could be selected areas in pepper breeding. We found that the stronger the correlation between the two traits, the greater the possibility of them being in more than one polymerization region, suggesting that they may be linked or that one pleiotropic gene controls them. These results provide a theoretical foundation for future multi-trait pyramid breeding of pepper. Finally, we found that the GWAS signals were highly consistent with those from the nuclear restorer-of-fertility (Rf) gene for cytoplasmic male sterility (CMS), verifying their reliability. We further identified Capana06g002967 and Capana06g002969 as Rf candidate genes by functional annotation and expression analysis, which provided a reference for the study of cytoplasmic male sterility in Capsicum.

Identification of Superior Alleles for Seedling Stage Salt Tolerance in the USDA Rice Mini-Core Collection

Salt stress is a major constraint to rice acreage and production worldwide. The purpose of this study was to evaluate the natural genetic variation available in the United States Department of Agriculture (USDA) rice mini-core collection (URMC) for early vigor traits under salt stress and identify quantitative trait loci (QTLs) for seedling-stage salt tolerance via a genome-wide association study (GWAS). Using a hydroponic system, the seedlings of 162 accessions were subjected to electrical conductivity (EC) 6.0 dS m⁻¹ salt stress at the three-to-four leaf stage. After completion of the study, 59.4% of the accessions were identified as sensitive, 23.9% were identified as moderately tolerant, and 16.7% were identified as highly tolerant. Pokkali was the most tolerant variety, while Nerica-6 was the most sensitive. Adapting standard International Rice Research Institute (IRRI) protocols, eight variables associated with salt tolerance were determined. The GWAS of the URMC, using over three million single-nucleotide polymorphisms (SNPs), identified nine genomic regions associated with salt tolerance that were mapped to five different chromosomes. Of these, none were in the known Saltol QTL region, suggesting different probable genes and mechanisms responsible for salt tolerance in the URMC. The study uncovered genetic loci that explained a large portion of the variation in salt tolerance at the seedling stage. Fourteen highly salt-tolerant accessions, six novel loci, and 16 candidate genes in their vicinity were identified that may be useful in breeding for salt stress tolerance. Identified QTLs can be targeted for fine mapping, candidate gene verification, and marker-assisted breeding in future studies.

Phenotypic and molecular dissection of grain quality using the USDA rice mini-core collection

Grain quality is a major breeding objective and paramount to food production. This study was aimed to phenotypically and molecularly dissect the rice grain quality, especially amylose content (AC), grain protein content (GPC) and alkali spreading value (ASV), using the USDA rice mini-core collection representing the world-wide rice germplasm lines. Grain chemical analysis combined with genome-wide association study (GWAS) was used for the study. A wide genetic variation was observed for these grain quality traits in the mini-core collection. Germplasm lines unique in AC, GPC and ASV and desirable for grain quality improvement were identified. The genetic diversity of the collection was re-analyzed using new SNPs, thus providing a more precise genotypic information about the collection. Furthermore, ten loci significantly associated with these grain quality traits were identified through GWAS using 22947 high-quality SNPs. These results, therefore, provide knowledge, resources and molecular tools for efficient rice grain quality improvement.

Dissecting the Genetic Architecture of Melon Chilling Tolerance at the Seedling Stage by Association Mapping and Identification of the Elite Alleles

Low temperature is an important abiotic stress that negatively affects morphological growth and fruit development in melon (Cucumis melo L.). Chilling stress at the seedling stage causes seedling injury and poor stand establishment, prolonging vegetative growth and delaying fruit harvest. In this study, association mapping was performed for chilling tolerance at the seedling stage on an expanded melon core collection containing 212 diverse accessions by 272 SSRs and 27 CAPSs. Chilling tolerance of the melon seedlings was evaluated by calculating the chilling injury index (CII) in 2016 and 2017. Genetic diversity analysis of the whole accession panel presented two main groups, which corresponded to the two subspecies of C. melo, melo, and agrestis. Both the subspecies were sensitive to chilling but with agrestis being more tolerant. Genome-wide association study (GWAS) was conducted, respectively, on the whole panel and the two subspecies, totally detecting 51 loci that contributed to 74 marker-trait associations. Of these associations, 35 were detected in the whole panel, 21 in melo, and 18 in agrestis. About half of the associations identified in the two subspecies were also observed in the whole panel, and seven associations were shared by both the subspecies. CMCT505_Chr.1 was repeatedly detected in different populations with high phenotypic contribution and could be a key locus controlling chilling tolerance in C. melo. Nine loci were selected for evaluation of the phenotypic effects related to their alleles, which identified 11 elite alleles contributing to seedling chilling tolerance. Four such alleles existed in both the subspecies and six in either of the two subspecies. Analysis of 20 parental combinations for their allelic status and phenotypic values showed that the elite alleles collectively contributed to enhancement of the chilling tolerance. Tagging the loci responsible for chilling tolerance may simultaneously favor dissecting the complex adaptability traits and elevate the efficiency to improve chilling tolerance using marker-assisted selection in melon.

Association Analysis of Arsenic-Induced Straighthead in Rice (Oryza sativa L.) Based on the Selected Population with a Modified Model

A rice physiological disorder makes mature panicle keep erect with empty grains termed as "straighthead." Straighthead causes yield losses and is a serious threat to rice production worldwide. Here, a new study of association mapping was conducted to identify QTL involved in straighthead. A subset of 380 accessions was selected from the USDA rice core collection and genotyped with 72 genome-wide SSR markers. An optimal model implemented with principle components (PCs) was used in this association mapping. As a result, five markers were identified to be significantly associated with straighthead. Three of them, RM263, RM169, and RM224, were consistent with a previous study. Three markers, RM475, RM263, and RM19, had a resistant allele associated with a decrease in straighthead rating (straighthead rating ≤ 4.8). In contrast, the two other marker loci RM169 and RM224 had a few susceptible alleles associated with an increase in straighthead rating (straighthead rating ≥ 8.7). Interestingly, RM475 is close to QTL "qSH-2" and "AsS" with straighthead resistance, which was reported in two studies on linkage mapping of straighthead. This finding adds to previous work and is useful for further genetic study of straighthead.

In-depth genome characterization of a Brazilian common bean core collection using DArTseq high-density SNP genotyping

BACKGROUND

Common bean is a legume of social and nutritional importance as a food crop, cultivated worldwide especially in developing countries, accounting for an important source of income for small farmers. The availability of the complete sequences of the two common bean genomes has dramatically accelerated and has enabled new experimental strategies to be applied for genetic research. DArTseq has been widely used as a method of SNP genotyping allowing comprehensive genome coverage with genetic applications in common bean breeding programs.

RESULTS

Using this technology, 6286 SNPs (1 SNP/86.5 Kbp) were genotyped in genic (43.3%) and non-genic regions (56.7%). Genetic subdivision associated to the common bean gene pools (K = 2) and related to grain types (K = 3 and K = 5) were reported. A total of 83% and 91% of all SNPs were polymorphic within the Andean and Mesoamerican gene pools, respectively, and 26% were able to differentiate the gene pools. Genetic diversity analysis revealed an average H E of 0.442 for the whole collection, 0.102 for Andean and 0.168 for Mesoamerican gene pools (F ST  = 0.747 between gene pools), 0.440 for the group of cultivars and lines, and 0.448 for the group of landrace accessions (F ST  = 0.002 between cultivar/line and landrace groups). The SNP effects were predicted with predominance of impact on non-coding regions (77.8%). SNPs under selection were identified within gene pools comparing landrace and cultivar/line germplasm groups (Andean: 18; Mesoamerican: 69) and between the gene pools (59 SNPs), predominantly on chromosomes 1 and 9. The LD extension estimate corrected for population structure and relatedness (r2SV) was ~ 88 kbp, while for the Andean gene pool was ~ 395 kbp, and for the Mesoamerican was ~ 130 kbp.

CONCLUSIONS

For common bean, DArTseq provides an efficient and cost-effective strategy of generating SNPs for large-scale genome-wide studies. The DArTseq resulted in an operational panel of 560 polymorphic SNPs in linkage equilibrium, providing high genome coverage. This SNP set could be used in genotyping platforms with many applications, such as population genetics, phylogeny relation between common bean varieties and support to molecular breeding approaches.

Association Analysis of Markers Derived from Starch Biosynthesis Related Genes with Starch Physicochemical Properties in the USDA Rice Mini-Core Collection

Rice eating and cooking quality is largely determined by starch physicochemical properties. The diverse accessions in the USDA rice mini-core collection (URMC) facilitate extensive association analysis of starch physicochemical properties with molecular markers specific to starch biosynthesis related genes. To identify significant trait-marker associations that can be utilized in rice breeding programs for improved starch quality, we conducted two association analyses between 26 molecular markers derived from starch biosynthesis related genes and 18 parameters measured of starch physicochemical properties in two sets of the mini-core accessions successfully grown in two environments in China. Many significant trait-marker associations (P < 0.001) were detected in both association analyses. Five markers of Waxy gene, including the (CT)n repeats, the G/T SNP of intron 1, the 23 bp sequence duplication (InDel) of exon 2, the A/C SNP of exon 6, and the C/T SNP of exon 10, were found to be primarily associated with starch traits related to apparent amylose content (AAC), and two markers targeting the 4,329-4,330 bp GC/TT SNPs and 4,198 bp G/A SNP of SSIIa gene were mainly associated with traits related to gelatinization temperature (GT). Two new haplotypes were found in the mini-core collection based on the combinations of the 23 bp InDel and three SNPs (G/T of intron 1, A/C of exon 6, and C/T of exon 10) of Waxy gene. Furthermore, our analyses indicated that the (CT)n polymorphisms of Waxy gene had a non-negligible effect on AAC related traits, as evidenced by significant variation in AAC related traits among rice accessions with the same Waxy SNPs but different (CT) n repeats. As the five Waxy markers and the two SSIIa markers showed consistent major effects on starch quality traits across studies, these markers should have priority for utilization in marker-assisted breeding.

Assessment of Five Chilling Tolerance Traits and GWAS Mapping in Rice Using the USDA Mini-Core Collection

Rice (Oryza sativa L.) is often exposed to cool temperatures during spring planting in temperate climates. A better understanding of genetic pathways regulating chilling tolerance will enable breeders to develop varieties with improved tolerance during germination and young seedling stages. To dissect chilling tolerance, five assays were developed; one assay for the germination stage, one assay for the germination and seedling stage, and three for the seedling stage. Based on these assays, five chilling tolerance indices were calculated and assessed using 202 O. sativa accessions from the Rice Mini-Core (RMC) collection. Significant differences between RMC accessions made the five indices suitable for genome-wide association study (GWAS) based quantitative trait loci (QTL) mapping. For young seedling stage indices, japonica and indica subspecies clustered into chilling tolerant and chilling sensitive accessions, respectively, while both subspecies had similar low temperature germinability distributions. Indica subspecies were shown to have chilling acclimation potential. GWAS mapping uncovered 48 QTL at 39 chromosome regions distributed across all 12 rice chromosomes. Interestingly, there was no overlap between the germination and seedling stage QTL. Also, 18 QTL and 32 QTL were in regions discovered in previously reported bi-parental and GWAS based QTL mapping studies, respectively. Two novel low temperature seedling survivability (LTSS)-QTL, qLTSS3-4 and qLTSS4-1, were not in a previously reported QTL region. QTL with strong effect alleles identified in this study will be useful for marker assisted breeding efforts to improve chilling tolerance in rice cultivars and enhance gene discovery for chilling tolerance.

The Power of Inbreeding: NGS-Based GWAS of Rice Reveals Convergent Evolution during Rice Domestication

Low-coverage whole-genome sequencing is an effective strategy for genome-wide association studies in humans, due to the availability of large reference panels for genotype imputation. However, it is unclear whether this strategy can be utilized in other species without reference panels. Using simulations, we show that this approach is even more relevant in inbred species such as rice (Oryza sativa L.), which are effectively haploid, allowing easy haplotype construction and imputation-based genotype calling, even without the availability of large reference panels. We sequenced 203 rice varieties with well-characterized phenotypes from the United States Department of Agriculture Rice Mini-Core Collection at an average depth of 1.5× and used the data for mapping three traits. For the first two traits, amylose content and seed length, our approach leads to direct identification of the previously identified causal SNPs in the major-effect loci. For the third trait, pericarp color, an important trait underwent selection during domestication, we identified a new major-effect locus. Although known loci can explain color variation in the varieties of two main subspecies of Asian domesticated rice, japonica and indica, the new locus identified is unique to another domesticated rice subgroup, aus, and together with existing loci, can fully explain the major variation in pericarp color in aus. Our discovery of a unique genetic basis of white pericarp in aus provides an example of convergent evolution during rice domestication and suggests that aus may have a domestication history independent of japonica and indica.

Proteomic insights into floral biology

The flower is the most important biological structure for ensuring angiosperms reproductive success. Not only does the flower contain critical reproductive organs, but the wide variation in morphology, color, and scent has evolved to entice specialized pollinators, and arguably mankind in many cases, to ensure the successful propagation of its species. Recent proteomic approaches have identified protein candidates related to these flower traits, which has shed light on a number of previously unknown mechanisms underlying these traits. This review article provides a comprehensive overview of the latest advances in proteomic research in floral biology according to the order of flower structure, from corolla to male and female reproductive organs. It summarizes mainstream proteomic methods for plant research and recent improvements on two dimensional gel electrophoresis and gel-free workflows for both peptide level and protein level analysis. The recent advances in sequencing technologies provide a new paradigm for the ever-increasing genome and transcriptome information on many organisms. It is now possible to integrate genomic and transcriptomic data with proteomic results for large-scale protein characterization, so that a global understanding of the complex molecular networks in flower biology can be readily achieved. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock.

Association Analysis in Rice: From Application to Utilization

Association analysis based on linkage disequilibrium (LD) is an efficient way to dissect complex traits and to identify gene functions in rice. Although association analysis is an effective way to construct fine maps for quantitative traits, there are a few issues which need to be addressed. In this review, we will first summarize type, structure, and LD level of populations used for association analysis of rice, and then discuss the genotyping methods and statistical approaches used for association analysis in rice. Moreover, we will review current shortcomings and benefits of association analysis as well as specific types of future research to overcome these shortcomings. Furthermore, we will analyze the reasons for the underutilization of the results within association analysis in rice breeding.

Genome-wide Association Mapping of Quantitative Trait Loci (QTLs) for Contents of Eight Elements in Brown Rice (Oryza sativa L.)

An association mapping of quantitative trait loci (QTLs) regulating the concentrations of eight elements in brown rice (Oryza sativa L.) was performed using USDA mini-core subset cultivated in two different environments. In addition, correlation between the grain elemental concentrations was also studied. A total of 60 marker loci associated with 8 grain elemental concentrations were identified, and these loci were clustered into 37 genomic regions. Twenty new QTLs were found to be associated with important elements such as Zn, Fe, and P, along with others. Fe concentration was associated with the greatest number of markers in two environments. In addition, several important elemental/metal transporter genes were identified in a few mapped regions. Positive correlation was observed within all grain elemental concentrations. In summary, the results provide insight into the genetic basis of rice grain element accumulation and may help in the identification of genes associated with the accumulation of Zn, Fe, and other essential elements in rice.

Quantitative trait locus analysis and fine mapping of the qPL6 locus for panicle length in rice

Two QTLs were identified to control panicle length in rice backcross lines, and one QTL qPL6 was finely mapped with potential in high yield breeding. Panicle length (PL) is the key determinant of panicle architecture in rice, and strongly affects yield components, such as grain number per panicle. However, this trait has not been well studied genetically nor its contribution to yield improvement. In this study, we performed quantitative trait locus (QTL) analysis for PL in four backcross populations derived from the cross of Nipponbare (japonica) and WS3 (indica), a new plant type (NPT) variety. Two QTLs were identified on chromosome 6 and 8, designated as qPL6 and qPL8, respectively. Near-isogenic lines (NILs) were developed to evaluate their contribution to important agronomic traits. We found that qPL6 and qPL8 had additive effects on PL trait. For the qPL6 locus, the WS3 allele also increased panicle primary and secondary branches and grain number per panicle. Moreover, this allele conferred wide and strong culms, a character of lodging resistance. By analyzing key recombinants in two steps, the qPL6 locus was finely mapped to a 25-kb interval, and 3 candidate genes were identified. According to the single nucleotide polymorphisms (SNPs) within candidate genes, 5 dCaps markers were designed and used to get haplotypes of 96 modern Chinese varieties, which proved that qPL6 locus is differentiated between indica and temperate japonica varieties. Taken together, the superior qPL6 allele can be applied in rice breeding programs for large sink size, particularly for japonica varieties that originally lack the allele.

Development of Cymbidium ensifolium genic-SSR markers and their utility in genetic diversity and population structure analysis in cymbidiums

Background

Cymbidium is a genus of 68 species in the orchid family, with extremely high ornamental value. Marker-assisted selection has proven to be an effective strategy in accelerating plant breeding for many plant species. Analysis of cymbidiums genetic background by molecular markers can be of great value in assisting parental selection and breeding strategy design, however, in plants such as cymbidiums limited genomic resources exist. In order to obtain efficient markers, we deep sequenced the C. ensifolium transcriptome to identify simple sequence repeats derived from gene regions (genic-SSR).

Result

The 7,936 genic-SSR markers were identified. A total of 80 genic-SSRs were selected, and primers were designed according to their flanking sequences. Of the 80 genic-SSR primer sets, 62 were amplified in C. ensifolium successfully, and 55 showed polymorphism when cross-tested among 9 Cymbidium species comprising 59 accessions. Unigenes containing the 62 genic-SSRs were searched against Non-redundant (Nr), Gene Ontology database (GO), eukaryotic orthologous groups (KOGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The search resulted in 53 matching Nr sequences, of which 39 had GO terms, 18 were assigned to KOGs, and 15 were annotated with KEGG. Genetic diversity and population structure were analyzed based on 55 polymorphic genic-SSR data among 59 accessions. The genetic distance averaged 0.3911, ranging from 0.016 to 0.618. The polymorphic index content (PIC) of 55 polymorphic markers averaged 0.407, ranging from 0.033 to 0.863. A model-based clustering analysis revealed that five genetic groups existed in the collection. Accessions from the same species were typically grouped together; however, C. goeringii accessions did not always form a separate cluster, suggesting that C. goeringii accessions were polyphyletic.

Conclusion

The genic-SSR identified in this study constitute a set of markers that can be applied across multiple Cymbidium species and used for the evaluation of genetic relationships as well as qualitative and quantitative trait mapping studies. Genic-SSR’s coupled with the functional annotations provided by the unigenes will aid in mapping candidate genes of specific function.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0124-5) contains supplementary material, which is available to authorized users.

Association mapping for important agronomic traits in core collection of rice (Oryza sativa L.) with SSR markers

Mining elite genes within rice landraces is of importance for the improvement of cultivated rice. An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3). Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations. However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified. The research provided important information for further mining these elite genes within rice landraces and using them for rice breeding.

Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding

The transcript pool of a plant part, under any given condition, is a collection of mRNAs that will pave the way for a biochemical reaction of the plant to stimuli. Over the past decades, transcriptome study has advanced from Northern blotting to RNA sequencing (RNA-seq), through other techniques, of which real-time quantitative polymerase chain reaction (PCR) and microarray are the most significant ones. The questions being addressed by such studies have also matured from a solitary process to expression atlas and marker-assisted genetic enhancement. Not only genes and their networks involved in various developmental processes of plant parts have been elucidated, but also stress tolerant genes have been highlighted. The transcriptome of a plant with altered expression of a target gene has given information about the downstream genes. Marker information has been used for breeding improved varieties. Fortunately, the data generated by transcriptome analysis has been made freely available for ample utilization and comparison. The review discusses this wide variety of transcriptome data being generated in plants, which includes developmental stages, abiotic and biotic stress, effect of altered gene expression, as well as comparative transcriptomics, with a special emphasis on microarray and RNA-seq. Such data can be used to determine the regulatory gene networks, which can subsequently be utilized for generating improved plant varieties.

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 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.

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.

Application of resistance gene analog markers to analyses of genetic structure and diversity in rice

Plant disease resistance gene analog (RGA) markers were designed according to the conserved sequence of known RGAs and used to map resistance genes. We used genome-wide RGA markers for genetic analyses of structure and diversity in a global rice germplasm collection. Of the 472 RGA markers, 138 were polymorphic and these were applied to 178 entries selected from the USDA rice core collection. Results from the RGA markers were similar between two methods, UPGMA and STRUCTURE. Additionally, the results from RGA markers in our study were agreeable with those previously reported from SSR markers, including cluster of ancestral classification, genetic diversity estimates, genetic relatedness, and cluster of geographic origins. These results suggest that RGA markers are applicable for analyses of genetic structure and diversity in rice. However, unlike SSR markers, the RGA markers failed to differentiate temperate japonica, tropical japonica, and aromatic subgroups. The restricted way for developing RGA markers from the cDNA sequence might limit the polymorphism of RGA markers in the genome, thus limiting the discriminatory power in comparison with SSR markers. Genetic differentiation obtained using RGA markers may be useful for defining genetic diversity of a suite of random R genes in plants, as many studies show a differentiation of resistance to a wide array of pathogens. They could also help to characterize the genetic structure and geographic distribution in crops, including rice, wheat, barley, and banana.

Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.)

Seed-size traits, which are controlled by multiple genes in soybean, play an important role in determining seed yield, quality and appearance. However, the molecular mechanisms controlling the size of soybean seeds remain unclear, and little research has been done to investigate these mechanisms. In this study, we performed a genetic analysis to determine the genetic architecture of soybean seed size and shape via linkage and association analyses. We used 184 recombinant inbred lines (RILs) and 219 cultivated soybean accessions to evaluate seed length, seed width and seed height as seed-size traits, and their ratios of these values as seed-shape traits. Our results showed that all six traits had high heritability ranging from 92.46 to 98.47 %. Linkage analysis in the RILs identified 12 quantitative traits loci (QTLs), with five of these QTLs being associated with seed size, five with seed shape and two with the two first principal components of our principal component analysis (PCA). Association analysis in the 219 accessions detected 41 single nucleotide polymorphism (SNP)-trait associations, with 20 of these SNPs being associated with seed-size traits, seven with seed-shape traits and 14 with the two first principal components of our PCA. This analysis reveals that seed-size and seed-shape may be controlled by different genetic factors. Our results provide a greater understanding of phenotypic structure and genetic architecture of soybean seed, and the QTLs detected in this study form a basis for future fine mapping, quantitative trait gene cloning and molecular breeding in soybean.

Sequence variations in OsAGPase significantly associated with amylose content and viscosity properties in rice (Oryza sativa L.)

Sequence-based variations in starch synthesis-related genes (SSRGs) exert a basic influence on the determination of eating quality in rice (Oryza sativa L.). This study aimed to investigate the relationship between the sequence variations from parts of 10 SSRGs and the amylose content (AC) plus rapid viscosity analysis (RVA) profiles in a heuristic rice core set by association mapping (AM). In total, 86 sequence variations were found in 10 sequenced amplicons, including 79 single-nucleotide polymorphisms (SNPs), six insertion-deletions (InDels) and one polymorphic simple sequence repeat (SSR). Among them, 61 variations were exon-based, of which 41 should lead to amino acid changes. Four subpopulations were revealed by population structure analysis based on 170 genome-wide SSR genotypes. The final AM showed a sum of four significant associations between three phenotypic indices and three sequence variations. An ADP-glucose pyrophosphorylase small unit 1 (OsAGPS1) SNP (A-G) was significantly associated with increased AC (P<0·001, R(2)=15·6%), while a 12-bp deletion of AGPase large unit 4 (OsAGPL4) was significantly related to the decreased breakdown viscosity (BDV) (P<0·001, R(2)=16·6%) in both general linear model (GLM) and mixed linear model (MLM). This study provides a new perspective of allele mining for breeding strategies based on marker-assisted selection.

Genetic diversity assessment of sesame core collection in China by phenotype and molecular markers and extraction of a mini-core collection

BACKGROUND

Sesame (Sesamum indicum L.) is one of the four major oil crops in China. A sesame core collection (CC) was established in China in 2000, but no complete study on its genetic diversity has been carried out at either the phenotypic or molecular level. To provide technical guidance, a theoretical basis for further collection, effective protection, reasonable application, and a complete analysis of sesame genetic resources, a genetic diversity assessment of the sesame CC in China was conducted using phenotypic and molecular data and by extracting a sesame mini-core collection (MC).

RESULTS

Results from a genetic diversity assessment of sesame CC in China were significantly inconsistent at the phenotypic and molecular levels. A Mantel test revealed the insignificant correlation between phenotype and molecular marker information (r = 0.0043, t = 0.1320, P = 0.5525). The Shannon-Weaver diversity index (I) and Nei genetic diversity index (h) were higher (I = 0.9537, h = 0.5490) when calculated using phenotypic data from the CC than when using molecular data (I = 0.3467, h = 0.2218). A mini-core collection (MC) containing 184 accessions was extracted based on both phenotypic and molecular data, with a low mean difference percentage (MD, 1.64%), low variance difference percentage (VD, 22.58%), large variable rate of coefficient of variance (VR, 114.86%), and large coincidence rate of range (CR, 95.76%). For molecular data, the diversity indices and the polymorphism information content (PIC) for the MC were significantly higher than for the CC. Compared to an alternative random sampling strategy, the advantages of capturing genetic diversity and validation by extracting a MC using an advanced maximization strategy were proven.

CONCLUSIONS

This study provides a comprehensive characterization of the phenotypic and molecular genetic diversities of the sesame CC in China. A MC was extracted using both phenotypic and molecular data. Low MD% and VD%, and large VR% and CR% suggested that the MC provides a good representation of the genetic diversity of the original CC. The MC was more genetically diverse with higher diversity indices and a higher PIC value than the CC. A MC may aid in reasonably and efficiently selecting materials for sesame breeding and for genotypic biological studies, and may also be used as a population for association mapping in sesame.

Genome-wide association study of resistant starch (RS) phenotypes in a barley variety collection

Barley is primarily grown for feed and malt, but in some regions of the world it is also considered to be a staple food. Some barley types such as high-amylose barley have also gained importance as health-promoting foods. Starch that is not readily digested in the upper mammalian gastrointestinal system, or resistant starch (RS), is considered to be valuable because it prevents some diet-related diseases such as colon cancer. RS was quantified in a diverse collection of 209 spring barley varieties released in Europe during the past 100 years. The RS content varied from <1% to >15% in the collection, with 13 varieties having high RS content (>11%) and 15 varieties below 1%. Combined with genome-wide association scanning (GWAS), SNP markers and candidate genes controlling the RS content in grains were identified. This identified 40 SNP markers with a LOD score above 2, located on chromosomes 2H, 3H, 5H, and 6H, respectively. Among these SNPs, 10 genes with a known role in starch biosynthesis were associated on the basis of synteny conservation to the rice genome. The β-glucan content was quantified in 61 varieties selected to represent extreme as well as medium RS values. The β-glucan amount in the 15 varieties with RS <1% ranged from 1.7 to 3.2%, ranged from 1.76 to 2.54% in the 13 varieties with RS >11%, and ranged from 1.95 to 2.82% for those with 1%< RS < 11%. No statistically significant correlation between RS content and β-glucan content was found. This association analysis of commercial varieties revealed a large variation in RS content and identified a number of SNP markers that can be explored for selection and further dissection of the pathway and control of RS phenotype.

Association mapping of plant resistance to insects

Association mapping is rapidly becoming an important method to explore the genetic architecture of complex traits in plants and offers unique opportunities for studying resistance to insect herbivores. Recent studies indicate that there is a trade-off between resistance against generalist and specialist insects. Most studies, however, use a targeted approach that will easily miss important components of insect resistance. Genome-wide association mapping provides a comprehensive approach to explore the whole array of plant defense mechanisms in the context of the generalist-specialist paradigm. As association mapping involves the screening of large numbers of plant lines, specific and accurate high-throughput phenotyping (HTP) methods are needed. Here, we discuss the prospects of association mapping for insect resistance and HTP requirements.

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.

Genetic variation and association mapping of silica concentration in rice hulls using a germplasm collection

An association analysis on the genetic variability for silica concentration in rice hulls was performed using a "Mini-Core" set of 174 accessions representative of the germplasm diversity found in the USDA world collection of rice. Hull silica concentration was determined in replicated trials conducted in two southern states in the USA and was analyzed for its association with 164 genome-wide DNA markers. Among the accessions, the average silica concentration ranged from 120 to 251 mg g(-1). Ample variation was seen within each of the five sub-populations of rice, as well as the 14 geographic regions that the accessions originated from. There was also an effect due to location and accession × location (G × E) interaction demonstrating the importance of assessing silica concentration across multiple environments. Twelve markers on ten chromosomes were significantly associated with hull silica concentration. Six markers (RM5644, RM5371, RM1335, RM283, RM263, and RM178) corroborated quantitative trait locus for silica concentration identified in other mapping studies. Our results provide germplasm and genetic markers that will assist breeding efforts to develop cultivars that have either high or low hull silica concentration. High silica hulls are good raw material for silica based industrial compounds, while low silica hulls are more biodegradable.

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.