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 mr1045 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
vg0428761895 sf0428576746 4 28761895 2.08E-10 NA
vg0130372159 sf0130371115 1 30372159 2.91E-10 NA
vg0423636908 sf0423451765 4 23636908 3.50E-10 NA
vg0125460828 sf0125459784 1 25460828 4.43E-10 NA
vg0402400401 sf0402395996 4 2400401 6.03E-10 NA
vg0420302986 sf0420131031 4 20302986 2.08E-08 NA
vg0232755756 sf0232749887 2 32755756 1.44E-07 6.84E-08
vg0812016473 sf0812015478 8 12016473 1.26E-06 NA
vg1219590404 sf1219561874 12 19590404 NA 9.13E-07

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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