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Detailed information for vg1126306082:

Variant ID: vg1126306082 (JBrowse)Variation Type: SNP
Chromosome: chr11Position: 26306082
Reference Allele: AAlternative Allele: G
Primary Allele: GSecondary Allele: A

Inferred Ancestral Allele : G (evidence from allele frequency in Oryza rufipogon: G: 0.79, A: 0.21, others allele: 0.00, population size: 111. )

Flanking Sequence (100 bp) in Reference Genome:


CATAATGGACGGTGCCTACGGCGGTGCACGAATCTCAAAGCAGAGAGCCAACCAGCTAACATGATGCTTGTGTGCTCAATCAATTCTATCCCCAGCTGCT[A/G]
CTGCTCCTCTTCTCATCGCCACGCTACCTCTCAATGGAGGCCTTCCTCGCCGGCTTCCGGGCGCCGCGGCCGCGGGTCCCGGCCGTCTCCGCCGCCGCCC

Reverse complement sequence

GGGCGGCGGCGGAGACGGCCGGGACCCGCGGCCGCGGCGCCCGGAAGCCGGCGAGGAAGGCCTCCATTGAGAGGTAGCGTGGCGATGAGAAGAGGAGCAG[T/C]
AGCAGCTGGGGATAGAATTGATTGAGCACACAAGCATCATGTTAGCTGGTTGGCTCTCTGCTTTGAGATTCGTGCACCGCCGTAGGCACCGTCCATTATG

Allele Frequencies:

Populations Population SizeFrequency of G(primary allele) Frequency of A(secondary allele) Frequency of N Frequency of DEL Frequency of others Allele
All  4726 68.20% 31.50% 0.30% 0.00% NA
All Indica  2759 70.40% 29.10% 0.51% 0.00% NA
All Japonica  1512 72.50% 27.50% 0.00% 0.00% NA
Aus  269 40.10% 59.90% 0.00% 0.00% NA
Indica I  595 71.80% 28.20% 0.00% 0.00% NA
Indica II  465 39.40% 60.40% 0.22% 0.00% NA
Indica III  913 90.10% 9.50% 0.33% 0.00% NA
Indica Intermediate  786 64.80% 34.00% 1.27% 0.00% NA
Temperate Japonica  767 62.50% 37.50% 0.00% 0.00% NA
Tropical Japonica  504 90.50% 9.50% 0.00% 0.00% NA
Japonica Intermediate  241 66.80% 33.20% 0.00% 0.00% NA
VI/Aromatic  96 17.70% 82.30% 0.00% 0.00% NA
Intermediate  90 67.80% 32.20% 0.00% 0.00% NA

Allele Effect:

Var ID Var Locus snpEff Annotation CooVar Annotation Chromatin Accessibility Score PolyPhen-2 Effect PolyPhen-2 Score SIFT Effect SIFT Score
vg1126306082 A -> G LOC_Os11g43600.1 5_prime_UTR_premature_start_codon_gain_variant ; LOW silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N
vg1126306082 A -> G LOC_Os11g43600.1 5_prime_UTR_variant ; 34.0bp to feature; MODIFIER silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N
vg1126306082 A -> G LOC_Os11g43590.1 downstream_gene_variant ; 373.0bp to feature; MODIFIER silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N
vg1126306082 A -> G LOC_Os11g43610.1 downstream_gene_variant ; 4722.0bp to feature; MODIFIER silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N
vg1126306082 A -> G LOC_Os11g43590.2 downstream_gene_variant ; 373.0bp to feature; MODIFIER silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N
vg1126306082 A -> G LOC_Os11g43590.3 downstream_gene_variant ; 373.0bp to feature; MODIFIER silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N
vg1126306082 A -> G LOC_Os11g43590.4 downstream_gene_variant ; 373.0bp to feature; MODIFIER silent_mutation Average:97.493; most accessible tissue: Zhenshan97 panicle, score: 98.421 N N N N

Effects Predicted by Deep Convolutional Neural Networks

For each variant, we constructed two sequences that contain the variation site and the sequence around it, differing only in the variation site. We then used Basenji to predict the chromatin accessibility of each tissue for the two sequences, respectively, and scored the effect of the variant by comparing the changes in chromatin accessibility corresponding to the two genotypes in the 1 kb region around the variation site. The effect score was defined as the logarithmic ratio of the predicted chromatin accessibility of the alternative genotype to the value of the reference genotype.

Var ID Ref Alt Root (RT) Young Leaf (YL) Flag Leaf (FL) Young Panicle (YP) Lemma & Palea (LP) Stamen & Pistil (SP)
vg1126306082 A G -0.04 -0.02 0.0 -0.04 -0.03 -0.04

Putative Genotype-Phenotype Associations:

Var ID LMM P-value LR P-value Trait Subpopulation Is leadSNP Publication
vg1126306082 6.79E-06 4.09E-10 mr1133 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 NA 2.51E-09 mr1191 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 4.62E-07 3.43E-13 mr1644 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 5.37E-06 2.86E-08 mr1667 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 NA 1.77E-08 mr1133_2 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 NA 4.04E-12 mr1191_2 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 NA 1.72E-06 mr1380_2 All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 NA 1.89E-06 mr1380_2 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 7.56E-06 4.12E-08 mr1667_2 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 NA 7.92E-06 mr1875_2 Ind_All Not Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251
vg1126306082 5.61E-07 5.60E-07 mr1972_2 Jap_All YES Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism, Nat Genet, 46(7):714-21, PMID:24908251