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Detailed information for vg0309453680:

Variant ID: vg0309453680 (JBrowse)Variation Type: SNP
Chromosome: chr03Position: 9453680
Reference Allele: TAlternative Allele: G,A
Primary Allele: GSecondary Allele: T

Inferred Ancestral Allele: Not determined.

Flanking Sequence (100 bp) in Reference Genome:


ATTTCCCACATTCATATTCACATTCATATTGATGTTAATGAATCTAGACATATATATCTATCTAGATTCATTAACATCAATATAAATGTGTGAAATGCTA[T/G,A]
AATGACTTACATTGTGAAACGGAGGAAGTAATATACATATATAATAAAATTTCCTACTGCACAATATAGAAAAGAGCTAGTAAAAAATGATTGTCTACTA

Reverse complement sequence

TAGTAGACAATCATTTTTTACTAGCTCTTTTCTATATTGTGCAGTAGGAAATTTTATTATATATGTATATTACTTCCTCCGTTTCACAATGTAAGTCATT[A/C,T]
TAGCATTTCACACATTTATATTGATGTTAATGAATCTAGATAGATATATATGTCTAGATTCATTAACATCAATATGAATGTGAATATGAATGTGGGAAAT

Allele Frequencies:

Populations Population SizeFrequency of G(primary allele) Frequency of T(secondary allele) Frequency of N Frequency of DEL Frequency of others Allele
All  4726 79.40% 19.80% 0.70% 0.00% A: 0.11%
All Indica  2759 98.40% 1.10% 0.51% 0.00% A: 0.04%
All Japonica  1512 40.30% 58.70% 0.93% 0.00% A: 0.07%
Aus  269 98.10% 0.40% 0.37% 0.00% A: 1.12%
Indica I  595 98.00% 1.30% 0.67% 0.00% NA
Indica II  465 97.00% 2.40% 0.65% 0.00% NA
Indica III  913 99.80% 0.00% 0.11% 0.00% A: 0.11%
Indica Intermediate  786 97.80% 1.40% 0.76% 0.00% NA
Temperate Japonica  767 2.30% 96.20% 1.43% 0.00% NA
Tropical Japonica  504 93.80% 5.60% 0.40% 0.00% A: 0.20%
Japonica Intermediate  241 49.40% 50.20% 0.41% 0.00% NA
VI/Aromatic  96 96.90% 2.10% 1.04% 0.00% NA
Intermediate  90 81.10% 15.60% 3.33% 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
vg0309453680 T -> A LOC_Os03g17010.1 upstream_gene_variant ; 577.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17010.2 upstream_gene_variant ; 577.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17010.3 upstream_gene_variant ; 577.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17000.2 downstream_gene_variant ; 4977.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17020.1 downstream_gene_variant ; 1900.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17000.4 downstream_gene_variant ; 4977.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17000.3 downstream_gene_variant ; 4977.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17020.2 downstream_gene_variant ; 1150.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> A LOC_Os03g17010-LOC_Os03g17020 intergenic_region ; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17010.1 upstream_gene_variant ; 577.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17010.2 upstream_gene_variant ; 577.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17010.3 upstream_gene_variant ; 577.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17000.2 downstream_gene_variant ; 4977.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17020.1 downstream_gene_variant ; 1900.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17000.4 downstream_gene_variant ; 4977.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17000.3 downstream_gene_variant ; 4977.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17020.2 downstream_gene_variant ; 1150.0bp to feature; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 N N N N
vg0309453680 T -> G LOC_Os03g17010-LOC_Os03g17020 intergenic_region ; MODIFIER silent_mutation Average:81.574; most accessible tissue: Minghui63 young leaf, score: 90.802 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)
vg0309453680 T A -0.02 -0.01 -0.02 -0.02 -0.02 -0.02
vg0309453680 T G -0.01 -0.02 -0.02 -0.01 -0.01 -0.01

Putative Genotype-Phenotype Associations:

Var ID LMM P-value LR P-value Trait Subpopulation Is leadSNP Publication
vg0309453680 NA 9.50E-10 mr1178 Jap_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
vg0309453680 NA 7.36E-08 mr1552 Jap_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
vg0309453680 NA 6.11E-08 mr1304_2 Jap_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
vg0309453680 NA 2.72E-07 mr1347_2 Jap_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
vg0309453680 NA 4.96E-11 mr1368_2 Jap_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
vg0309453680 NA 3.56E-07 mr1446_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
vg0309453680 NA 1.84E-06 mr1449_2 Jap_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
vg0309453680 NA 4.88E-12 mr1454_2 Jap_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
vg0309453680 NA 8.21E-11 mr1530_2 Jap_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
vg0309453680 5.03E-06 1.24E-19 mr1539_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
vg0309453680 NA 1.22E-14 mr1539_2 Jap_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
vg0309453680 NA 2.73E-19 mr1540_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
vg0309453680 NA 5.48E-16 mr1540_2 Jap_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
vg0309453680 NA 4.05E-07 mr1551_2 Jap_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
vg0309453680 NA 3.96E-12 mr1552_2 Jap_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
vg0309453680 NA 1.10E-19 mr1732_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
vg0309453680 NA 1.05E-15 mr1732_2 Jap_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
vg0309453680 NA 6.60E-10 mr1864_2 Jap_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
vg0309453680 NA 1.12E-13 mr1879_2 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
vg0309453680 NA 1.09E-10 mr1879_2 Jap_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
vg0309453680 NA 2.30E-06 mr1910_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