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 mr1097 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
vg0623248264 sf0623247267 6 23248264 4.70E-17 2.65E-06
vg0135794714 sf0135793671 1 35794714 2.18E-16 2.00E-06
vg0133154189 sf0133153145 1 33154189 4.49E-15 1.95E-06
vg1115409967 sf1114946279 11 15409967 5.19E-15 6.68E-06
vg1203607472 sf1203606471 12 3607472 2.09E-14 NA
vg1115489572 sf1115025885 11 15489572 2.80E-13 3.75E-07
vg0130732040 sf0130730996 1 30732040 1.12E-09 5.60E-17
vg0130500745 sf0130499701 1 30500745 NA 1.04E-07
vg0134539333 sf0134538290 1 34539333 NA 1.81E-07
vg0708063657 sf0708062662 7 8063657 NA 1.33E-06
vg0130922613 sf0130921569 1 30922613 NA 1.79E-06
vg0311538058 sf0311536776 3 11538058 NA 3.58E-06
vg0135645855 sf0135644812 1 35645855 NA 3.77E-06
vg0907140771 sf0907139771 9 7140771 NA 4.59E-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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