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 mr1510 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
vg0809843322 sf0809842326 8 9843322 6.39E-11 NA
vg0218633626 sf0218627757 2 18633626 1.10E-10 NA
vg0504695747 sf0504695724 5 4695747 1.77E-10 NA
vg0501354532 sf0501354516 5 1354532 2.22E-10 NA
vg0500069986 sf0500069986 5 69986 2.35E-10 NA
vg0806499371 sf0806498376 8 6499371 8.07E-10 2.31E-06
vg0401135977 sf0401131527 4 1135977 2.85E-08 NA
vg0814484428 sf0814481714 8 14484428 1.17E-07 NA
vg0715290134 sf0715289141 7 15290134 4.41E-07 4.84E-06
vg0804314979 sf0804313982 8 4314979 5.60E-07 NA
vg0715326471 sf0715325478 7 15326471 9.13E-07 NA
vg0719155095 sf0719154102 7 19155095 NA 1.39E-06
vg0709538360 sf0709537366 7 9538360 NA 2.52E-06
vg1020835773 sf1020764252 10 20835773 NA 3.14E-06
vg0134535445 sf0134534402 1 34535445 NA 9.28E-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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