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 mr1671 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
vg0304273109 sf0304272111 3 4273109 5.93E-93 1.02E-06
vg0627387528 sf0627386531 6 27387528 5.77E-92 NA
vg0122087924 sf0122086879 1 22087924 9.95E-91 NA
vg0334653299 sf0334646169 3 34653299 5.53E-90 NA
vg0707116055 sf0707115060 7 7116055 5.44E-89 NA
vg0334633999 sf0334626869 3 34633999 1.08E-85 3.82E-15
vg0304319579 sf0304318581 3 4319579 1.88E-78 7.81E-10
vg0334580739 sf0334573609 3 34580739 NA 3.04E-14
vg0304338025 sf0304337027 3 4338025 NA 8.09E-09
vg0726383683 sf0726382689 7 26383683 NA 1.28E-07
vg0503843762 sf0503843739 5 3843762 NA 1.39E-06
vg0324949511 sf0324947591 3 24949511 NA 1.62E-06
vg1000738859 sf1000737835 10 738859 NA 2.47E-06
vg0811071019 sf0811070024 8 11071019 NA 3.50E-06
vg0805155218 sf0805154221 8 5155218 NA 4.94E-06
vg1120296880 sf1119830804 11 20296880 NA 8.99E-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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