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 mr1324 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
vg0920030283 sf0920029802 9 20030283 1.98E-20 6.34E-06
vg0122690936 sf0122689891 1 22690936 9.45E-20 3.23E-07
vg0914717208 sf0914716207 9 14717208 1.70E-19 NA
vg0725046371 sf0725045377 7 25046371 1.87E-19 8.34E-06
vg0504766271 sf0504766248 5 4766271 4.36E-19 NA
vg0504742919 sf0504742896 5 4742919 5.90E-19 4.80E-06
vg1002992765 sf1002991742 10 2992765 1.15E-18 1.33E-06
vg1013444607 sf1013373377 10 13444607 5.37E-17 1.27E-07
vg0332518144 sf0332511017 3 32518144 NA 4.22E-07
vg0822936315 sf0822933602 8 22936315 NA 7.71E-07
vg0522004462 sf0521941904 5 22004462 NA 1.43E-06
vg0520708958 sf0520646399 5 20708958 NA 3.15E-06
vg1214644530 sf1214641870 12 14644530 NA 6.86E-06
vg1218022381 sf1217993817 12 18022381 NA 7.16E-06
vg0520223717 sf0520161190 5 20223717 NA 8.44E-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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