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 mr1698 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
vg0234351254 sf0234345385 2 34351254 1.77E-28 1.17E-06
vg1121988122 sf1121521993 11 21988122 4.51E-27 7.73E-08
vg0717369423 sf0717368430 7 17369423 5.15E-27 4.39E-07
vg0717364385 sf0717363392 7 17364385 7.31E-27 3.72E-07
vg0717415215 sf0717414222 7 17415215 1.93E-26 2.76E-06
vg1015191238 sf1015120006 10 15191238 2.85E-26 1.44E-06
vg0307075857 sf0307074855 3 7075857 8.41E-26 5.24E-06
vg0904244136 sf0904243136 9 4244136 3.38E-25 3.17E-06
vg0121627643 sf0121626598 1 21627643 3.57E-25 5.14E-07
vg0128531441 sf0128530396 1 28531441 4.68E-25 4.91E-06
vg0404270383 sf0404265990 4 4270383 NA 1.33E-09
vg0404048007 sf0404043614 4 4048007 NA 5.84E-07
vg0400996445 sf0400991997 4 996445 NA 6.35E-07
vg0404504944 sf0404500548 4 4504944 NA 1.20E-06
vg0426445210 sf0426260083 4 26445210 NA 3.33E-06
vg1212822297 sf1212819636 12 12822297 NA 3.56E-06
vg1117422908 sf1116956762 11 17422908 NA 7.82E-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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