Phenotype and GWAS Information

Note: Select an agronomic trait and population to view its distribution and accession-level phenotype measurements.

Phenotype Search

Note: Select a trait, study and population to view association results. The six additional cohorts contain 315 reported peak-SNP records from RiceNavi Supplementary Dataset 3, rather than genome-wide summary statistics. Plots can therefore contain only one or a few points. The original Xie (2015) and Chen (2014) results retain their existing coverage and methods.

Agronomic Trait GWAS

Metabolic Trait GWAS

GWAS Results

Chen et al. 2014, Nat Genet — Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. A second replication ends with “_2”, for example “mr1002_2”.

Detailed information about mr1793 is available from the rice metabolite database.

Manhattan Plot

Results are retained when the LR or LMM P-value is ≤ 1e-5 or its rank is within the top 20,000. The plot shows LMM results.

Significant Candidate Loci (Lead Variant)

Variation ID Variation ID V6 Chromosome Position LR P-value LMM P-value
vg0802260819 sf0802259822 8 2260819 3.94E-35 NA
vg1109440009 sf1109434586 11 9440009 1.41E-34 NA
vg0608185060 sf0608184061 6 8185060 1.37E-33 NA
vg0919822474 sf0919821993 9 19822474 1.45E-33 8.66E-06
vg0132861439 sf0132860395 1 32861439 1.98E-33 NA
vg0919811255 sf0919810774 9 19811255 1.23E-32 2.76E-06
vg0920086430 sf0920085949 9 20086430 2.33E-32 NA
vg0202720508 sf0202720506 2 2720508 2.01E-30 7.47E-07
vg0202698817 sf0202698815 2 2698817 NA 1.31E-08
vg0317140190 sf0317139004 3 17140190 NA 1.53E-07
vg0414275568 sf0414266281 4 14275568 NA 1.37E-06
vg0421333379 sf0421161433 4 21333379 NA 2.25E-06
vg0208546299 sf0208546298 2 8546299 NA 2.40E-06
vg1000109717 sf1000108717 10 109717 NA 2.54E-06
vg0314987126 sf0314985773 3 14987126 NA 2.57E-06
vg0315004688 sf0315003335 3 15004688 NA 2.85E-06
vg0207187753 sf0207187753 2 7187753 NA 8.86E-06

Information

This page provides two coordinated modules for trait exploration. Use Phenotype to inspect accession-level measurements and population distributions, or switch to GWAS Results to inspect association signals, Manhattan plots, and lead variants.

Keeping the two workflows on one page makes it possible to move between observed trait variation and its genetic associations without mixing their search controls or result tables.

GWAS results were collected from Xie et al. (2015) and Chen et al. (2014), with additional peak-SNP information obtained from RiceNavi and Wei et al. (2021). Specifically, we collected GWAS peak SNPs linked to functionally characterized rice genes from six populations or panels analyzed by Wei et al. (2021), including Chinese rice accessions (Li et al., 2020), Japanese rice accessions (Yano et al., 2016), the 3K rice panel (Wang et al., 2018), hybrid rice F1 populations (Huang et al., 2015), the QTN library (Wei et al., 2021), and RDP1 (Zhao et al., 2011).


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