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Detailed information for vg0233442145:

Variant ID: vg0233442145 (JBrowse)Variation Type: INDEL
Chromosome: chr02Position: 33442145
Reference Allele: AAlternative Allele: G,AGAG,AG
Primary Allele: ASecondary Allele: G

Inferred Ancestral Allele : A (evidence from allele frequency in Oryza rufipogon: A: 0.76, G: 0.24, others allele: 0.00, population size: 209. )

Flanking Sequence (100 bp) in Reference Genome:


CTGGTAGCAAAGTGAGACAAAGAATAAAGAGAGCAATTCATGATTTCATTCGATCATTCTCCCCTCAAAACCACCAGAGAGAAAGGATCAGGATTCAGGA[A/G,AGAG,AG]
GAGGAGGAGGAAAAAATAAAGTTGATTTGGTTCCCATTTCAAGATTTGCTTGCTCCAACCATTCATGATCCATCCAATCCAATCCAATCCACCCCCCACA

Reverse complement sequence

TGTGGGGGGTGGATTGGATTGGATTGGATGGATCATGAATGGTTGGAGCAAGCAAATCTTGAAATGGGAACCAAATCAACTTTATTTTTTCCTCCTCCTC[T/C,CTCT,CT]
TCCTGAATCCTGATCCTTTCTCTCTGGTGGTTTTGAGGGGAGAATGATCGAATGAAATCATGAATTGCTCTCTTTATTCTTTGTCTCACTTTGCTACCAG

Allele Frequencies:

Populations Population SizeFrequency of A(primary allele) Frequency of G(secondary allele) Frequency of N Frequency of DEL Frequency of others Allele
All  4726 92.50% 6.60% 0.08% 0.00% AGAG: 0.85%; AG: 0.02%
All Indica  2759 96.10% 2.60% 0.07% 0.00% AGAG: 1.27%
All Japonica  1512 99.70% 0.10% 0.00% 0.00% AGAG: 0.13%
Aus  269 16.40% 83.30% 0.37% 0.00% NA
Indica I  595 98.20% 1.30% 0.00% 0.00% AGAG: 0.50%
Indica II  465 98.90% 1.10% 0.00% 0.00% NA
Indica III  913 95.70% 2.40% 0.11% 0.00% AGAG: 1.75%
Indica Intermediate  786 93.30% 4.60% 0.13% 0.00% AGAG: 2.04%
Temperate Japonica  767 99.90% 0.00% 0.00% 0.00% AGAG: 0.13%
Tropical Japonica  504 100.00% 0.00% 0.00% 0.00% NA
Japonica Intermediate  241 98.80% 0.80% 0.00% 0.00% AGAG: 0.41%
VI/Aromatic  96 89.60% 8.30% 0.00% 0.00% AGAG: 2.08%
Intermediate  90 90.00% 6.70% 1.11% 0.00% AG: 1.11%; AGAG: 1.11%

Allele Effect:

Var ID Var Locus snpEff Annotation CooVar Annotation Chromatin Accessibility Score PolyPhen-2 Effect PolyPhen-2 Score SIFT Effect SIFT Score
vg0233442145 A -> AGAG LOC_Os02g54600.1 3_prime_UTR_variant ; 586.0bp to feature; MODIFIER silent_mutation Average:96.285; most accessible tissue: Minghui63 flower, score: 99.263 N N N N
vg0233442145 A -> AGAG LOC_Os02g54590.1 downstream_gene_variant ; 2932.0bp to feature; MODIFIER silent_mutation Average:96.285; most accessible tissue: Minghui63 flower, score: 99.263 N N N N
vg0233442145 A -> G LOC_Os02g54600.1 3_prime_UTR_variant ; 587.0bp to feature; MODIFIER silent_mutation Average:96.285; most accessible tissue: Minghui63 flower, score: 99.263 N N N N
vg0233442145 A -> G LOC_Os02g54590.1 downstream_gene_variant ; 2931.0bp to feature; MODIFIER silent_mutation Average:96.285; most accessible tissue: Minghui63 flower, score: 99.263 N N N N
vg0233442145 A -> AG LOC_Os02g54600.1 3_prime_UTR_variant ; 586.0bp to feature; MODIFIER silent_mutation Average:96.285; most accessible tissue: Minghui63 flower, score: 99.263 N N N N
vg0233442145 A -> AG LOC_Os02g54590.1 downstream_gene_variant ; 2932.0bp to feature; MODIFIER silent_mutation Average:96.285; most accessible tissue: Minghui63 flower, score: 99.263 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)
vg0233442145 A AG 0.07 -0.07 -0.11 -0.04 0.01 0.05
vg0233442145 A AGAG -0.13 -0.1 -0.01 -0.08 -0.08 -0.07
vg0233442145 A G 0.01 -0.03 -0.02 0.03 0.01 0.0

Putative Genotype-Phenotype Associations:

Var ID LMM P-value LR P-value Trait Subpopulation Is leadSNP Publication
vg0233442145 NA 1.62E-20 mr1102 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
vg0233442145 NA 3.88E-15 mr1146 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
vg0233442145 NA 2.10E-43 mr1152 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
vg0233442145 NA 2.51E-29 mr1333 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
vg0233442145 NA 8.55E-35 mr1350 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
vg0233442145 NA 5.02E-11 mr1553 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
vg0233442145 NA 3.77E-06 mr1646 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
vg0233442145 NA 5.50E-32 mr1647 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
vg0233442145 NA 9.31E-36 mr1682 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
vg0233442145 NA 4.77E-27 mr1686 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
vg0233442145 NA 2.40E-58 mr1695 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
vg0233442145 NA 1.00E-06 mr1781 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
vg0233442145 NA 1.46E-23 mr1917 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
vg0233442145 NA 1.14E-16 mr1146_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
vg0233442145 NA 1.21E-32 mr1150_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
vg0233442145 NA 2.89E-19 mr1239_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
vg0233442145 NA 1.48E-22 mr1242_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
vg0233442145 NA 1.66E-10 mr1893_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