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Genome-wide association and high-resolution phenotyping link Oryza sativa panicle traits to numerous trait-specific QTL clusters.

ABSTRACT: Rice panicle architecture is a key target of selection when breeding for yield and grain quality. However, panicle phenotypes are difficult to measure and susceptible to confounding during genetic mapping due to correlation with flowering and subpopulation structure. Here we quantify 49 panicle phenotypes in 242 tropical rice accessions with the imaging platform PANorama. Using flowering as a covariate, we conduct a genome-wide association study (GWAS), detect numerous subpopulation-specific associations, and dissect multi-trait peaks using panicle phenotype covariates. Ten candidate genes in pathways known to regulate plant architecture fall under GWAS peaks, half of which overlap with quantitative trait loci identified in an experimental population. This is the first study to assess inflorescence phenotypes of field-grown material using a high-resolution phenotyping platform. Herein, we establish a panicle morphocline for domesticated rice, propose a genetic model underlying complex panicle traits, and demonstrate subtle links between panicle size and yield performance.

SUBMITTER: Crowell S

PROVIDER: S-EPMC4742901 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Genome-wide association and high-resolution phenotyping link Oryza sativa panicle traits to numerous trait-specific QTL clusters.

Crowell Samuel S Korniliev Pavel P Falcão Alexandre A Ismail Abdelbagi A Gregorio Glenn G Mezey Jason J McCouch Susan S

Nature communications 20160204

Rice panicle architecture is a key target of selection when breeding for yield and grain quality. However, panicle phenotypes are difficult to measure and susceptible to confounding during genetic mapping due to correlation with flowering and subpopulation structure. Here we quantify 49 panicle phenotypes in 242 tropical rice accessions with the imaging platform PANorama. Using flowering as a covariate, we conduct a genome-wide association study (GWAS), detect numerous subpopulation-specific ass ...[more]

PMID: 26841834

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Project description:BACKGROUND:Developing chilling tolerant accessions of domesticated Asian rice is a potential source of significant crop improvement. The uniquely chilling sensitive nature of the tropically originating Oryza sativa make it the most important cereal crop that can gain significantly from improved tolerance to low temperatures. However, mechanisms underlying this complex trait are not fully understood. Oryza sativa has two subspecies with different levels of chilling tolerance, JAPONICA and INDICA, providing an ideal tool to investigate mechanistic differences in the chilling stress tolerance responses within this important crop species. RESULTS:The Rice Diversity Panel 1 (RDP1) was used to investigate a core set of Oryza sativa accessions. The tools available for this panel allowed for a comprehensive analysis of two chilling tolerance traits at multiple temperatures across a 354-cultivar subset of the RDP1. Chilling tolerance trait values were distributed as mostly subpopulation specific clusters of Tolerant, Intermediate, and Sensitive accessions. Genome-wide association study (GWAS) mapping approaches using all 354 accessions yielded a total of 245 quantitative trait loci (QTL), containing 178 unique QTL covering 25% of the rice genome, while 40 QTL were identified by multiple traits. QTL mappings using subsets of rice accession clusters yielded another 255 QTL, for a total of 500 QTL. The genes within these multiple trait QTL were analyzed for Gene Ontology (GO) term and potential pathway enrichments. Terms related to "carbohydrate biosynthesis", "carbohydrate transmembrane transport", "small molecule protein modification", and "plasma membrane" were enriched from this list. Filtering was done to identify more likely candidate pathways involved in conferring chilling tolerance, resulting in enrichment of terms related to "Golgi apparatus", "stress response", "transmembrane transport", and "signal transduction". CONCLUSIONS:Taken together, these GO term clusters revealed a likely involvement of Golgi-mediated subcellular and extracellular vesicle and intracellular carbohydrate transport as a general cold stress tolerance response mechanism to achieve cell and metabolic homeostasis under chilling stress.

Project description:BackgroundIn crops, inflorescence complexity and the shape and size of the seed are among the most important characters that influence yield. For example, rice panicles vary considerably in the number and order of branches, elongation of the axis, and the shape and size of the seed. Manual low-throughput phenotyping methods are time consuming, and the results are unreliable. However, high-throughput image analysis of the qualitative and quantitative traits of rice panicles is essential for understanding the diversity of the panicle as well as for breeding programs.ResultsThis paper presents P-TRAP software (Panicle TRAit Phenotyping), a free open source application for high-throughput measurements of panicle architecture and seed-related traits. The software is written in Java and can be used with different platforms (the user-friendly Graphical User Interface (GUI) uses Netbeans Platform 7.3). The application offers three main tools: a tool for the analysis of panicle structure, a spikelet/grain counting tool, and a tool for the analysis of seed shape. The three tools can be used independently or simultaneously for analysis of the same image. Results are then reported in the Extensible Markup Language (XML) and Comma Separated Values (CSV) file formats. Images of rice panicles were used to evaluate the efficiency and robustness of the software. Compared to data obtained by manual processing, P-TRAP produced reliable results in a much shorter time. In addition, manual processing is not repeatable because dry panicles are vulnerable to damage. The software is very useful, practical and collects much more data than human operators.ConclusionsP-TRAP is a new open source software that automatically recognizes the structure of a panicle and the seeds on the panicle in numeric images. The software processes and quantifies several traits related to panicle structure, detects and counts the grains, and measures their shape parameters. In short, P-TRAP offers both efficient results and a user-friendly environment for experiments. The experimental results showed very good accuracy compared to field operator, expert verification and well-known academic methods.

Project description:Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.

Dataset Information

Genome-wide association and high-resolution phenotyping link Oryza sativa panicle traits to numerous trait-specific QTL clusters.

Publications

Genome-wide association and high-resolution phenotyping link Oryza sativa panicle traits to numerous trait-specific QTL clusters.

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