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 mr1154 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
vg0619603076 sf0619602079 6 19603076 5.71E-57 NA
vg0626042276 sf0626041279 6 26042276 5.78E-57 NA
vg0917214543 sf0917213542 9 17214543 8.28E-57 NA
vg0211534075 sf0211534071 2 11534075 1.62E-56 NA
vg0215681856 sf0215675986 2 15681856 5.49E-56 NA
vg0130732040 sf0130730996 1 30732040 NA 3.98E-12
vg0130670983 sf0130669939 1 30670983 NA 4.35E-12
vg0130644853 sf0130643809 1 30644853 NA 4.80E-09
vg1115413712 sf1114950024 11 15413712 NA 2.92E-07
vg0303180062 sf0303179058 3 3180062 NA 6.01E-07
vg0303169957 sf0303168953 3 3169957 NA 8.30E-07
vg0135794714 sf0135793671 1 35794714 NA 9.18E-07
vg0139977615 sf0139976572 1 39977615 NA 1.18E-06
vg0129917132 sf0129916087 1 29917132 NA 2.57E-06
vg0134539333 sf0134538290 1 34539333 NA 3.29E-06
vg0138627461 sf0138626418 1 38627461 NA 4.08E-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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