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 mr1922 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
vg0917464960 sf0917463959 9 17464960 1.56E-34 3.10E-06
vg0233645466 sf0233639597 2 33645466 2.39E-34 1.07E-06
vg1227345530 sf1227311930 12 27345530 2.83E-34 5.79E-06
vg0914955409 sf0914954408 9 14955409 5.23E-34 NA
vg0922486189 sf0922485708 9 22486189 1.62E-33 NA
vg0625911134 sf0625910137 6 25911134 1.14E-32 4.46E-06
vg0819251922 sf0819249209 8 19251922 1.93E-31 8.31E-06
vg0919894626 sf0919894145 9 19894626 3.85E-28 1.10E-07
vg1006010925 sf1006027463 10 6010925 NA 1.57E-07
vg0234163711 sf0234157842 2 34163711 NA 3.06E-07
vg1216468379 sf1216465672 12 16468379 NA 1.31E-06
vg1005588645 sf1005605183 10 5588645 NA 1.57E-06
vg1009130986 sf1009059847 10 9130986 NA 1.82E-06
vg0726691050 sf0726690056 7 26691050 NA 2.22E-06
vg0908568026 sf0908567025 9 8568026 NA 3.69E-06
vg1006141936 sf1006158478 10 6141936 NA 4.33E-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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