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

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)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.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 subpopulatio710527FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2011/03110-

Circadian Proteomic Analysis Uncovers Mechanisms of Post-Transcriptional Regulation in Metabolic Pathways.

Transcriptional and translational feedback loops in fungi and animals drive circadian rhythms in transcript levels that provide output from the clock, but post-transcriptional mechanisms also contribute. To determine the extent and underlying source of this regulation, we applied newly developed analytical tools to a long-duration, deeply sampled, circadian proteomics time course comprising half of the proteome. We found a quarter of expressed proteins are clock regulated, but >40% of these do not arise from clock-regulated transcripts, and our analysis predicts that these protein rhythms arise from oscillations in translational rates. Our data highlighted the impact of the clock on metabolic regulation, with central carbon metabolism reflecting both transcriptional and post-transcriptional control and opposing metabolic pathways showing peak activities at different times of day. The transcription factor CSP-1 plays a role in this metabolic regulation, contributing to the rhythmicity and phase of clock-regulated proteins

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Genetic Dissection Of Inflorescence Architecture In Oryza Sativa Using High Density Genomic Data And Novel Phenotyping Strategies

As the carriers of fruits and grains, inflorescences have been an important target of selection throughout domestication and modern breeding in many crop species. In Asian rice (Oryza sativa), one of the world's staple crops, the inflorescence is known as a panicle, due to complex lateral branching patterns. Rice breeders have had trouble measuring panicle phenotypes, limiting their ability to assess the importance of candidate genes from model systems in the context of natural variation and incorporate these findings into field-level crop improvement pipelines. This dissertation describes the development of a novel open-source phenotyping platform, PANorama, which uses skeletonization techniques to extract a range of length, width, and count phenotypes from images of rice panicles. High-resolution phenotyping of panicle traits complemented dense genetic marker data, increasing both the number and effect size of quantitative trait loci (QTL) that were detected for panicle traits within a recombinant inbred line mapping population. Comparisons among traits across a diverse panel of varieties grown in the field revealed that relationships between distinct components of panicle architecture are conserved across O. sativa, despite at least two origins of domestication. However, panicle traits showed distinct distributions within and between the rice subpopulations, suggesting that genetic variation has been partitioned during geographic and ecological radiation of the species. Genome-wide association (GWAS) revealed unique genetic architecture for different types of traits, and identified a large number of trait-specific, small-effect QTL associated with natural variation in panicle development, several of which are near known candidate genes. Finally, while panicle traits occasionally shared associations with traditional agronomic phenotypes and yield components, a large portion of inflorescence associations were located in unique regions of the genome, suggesting that relationships between panicle architecture and agronomic performance in rice are subtle and highly multi-genic. Taken together, these results provide a rich assessment of panicle development in Oryza sativa and establish a methodological framework for breeders interested in optimizing inflorescence architecture in the context of yield

Repeated reciprocal crosses between svt2 and Col-0 wild-type lines

<p>Table 5 raw data gel images (repeats)</p

Summary of PCR-based molecular genotypes

<p>With the exception of svt2 Col R1 M2, where Col and Ler markers and one heterozygous marker were found (svt2 M2 Col-0 rev.1), phenotype matched genotype. That is, a Col-like phenotype correlated with the presence of Col polymorphisms, while a Ler-like phenotype correlated with Ler polymorphisms. C, L, and H refer to Col, Ler, or heterozygous, respectively</p

Root lengths of Col-0 WT, vtc1-1, svt2 (M1) and Ler-0 WT (mm)

<p>Root length in seven-day-old seedlings grown on 1x MS</p

Reciprocal crosses between svt2 and Col-0 wild-type lines

<p>Molecular analysis of the InDel polymorphism markers showed evidence of cryptic but persistent homozygosity, irrespective of the direction of the sexual cross (L1). However, heterozygosity was expected at all loci. n.d., not detected. * indicates that a PCR product failed to generate for these reactions</p