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Detailed information for vg0328245483:

Variant ID: vg0328245483 (JBrowse)Variation Type: SNP
Chromosome: chr03Position: 28245483
Reference Allele: CAlternative Allele: T
Primary Allele: CSecondary Allele: T

Inferred Ancestral Allele : T (evidence from allele frequency in Oryza rufipogon: T: 0.55, C: 0.45, others allele: 0.00, population size: 85. )

Flanking Sequence (100 bp) in Reference Genome:


CGTGGGGAGGTTTGGCAGTGCGCGCGCGGCCGAGTCCCTCCGTTCGAAAAAAAAAAAAAAGACAAAACCTGGTTTCCGTATCTAATGTTTGACTGTCCGT[C/T]
TTATTTGAAAAAATTATAAAAAAATTTAAAAAGACAAGTCACGTATAAAATATTAATTATATTTTATCATCTAACAATAATAAAAATACAAATTATAAAA

Reverse complement sequence

TTTTATAATTTGTATTTTTATTATTGTTAGATGATAAAATATAATTAATATTTTATACGTGACTTGTCTTTTTAAATTTTTTTATAATTTTTTCAAATAA[G/A]
ACGGACAGTCAAACATTAGATACGGAAACCAGGTTTTGTCTTTTTTTTTTTTTTCGAACGGAGGGACTCGGCCGCGCGCGCACTGCCAAACCTCCCCACG

Allele Frequencies:

Populations Population SizeFrequency of C(primary allele) Frequency of T(secondary allele) Frequency of N Frequency of DEL Frequency of others Allele
All  4726 34.80% 31.00% 18.81% 15.32% NA
All Indica  2759 1.50% 41.70% 31.17% 25.63% NA
All Japonica  1512 98.40% 0.50% 0.60% 0.46% NA
Aus  269 2.60% 96.70% 0.74% 0.00% NA
Indica I  595 0.30% 54.30% 34.29% 11.09% NA
Indica II  465 2.60% 25.40% 35.27% 36.77% NA
Indica III  913 0.50% 50.30% 20.48% 28.70% NA
Indica Intermediate  786 2.90% 31.80% 38.80% 26.46% NA
Temperate Japonica  767 99.30% 0.30% 0.13% 0.26% NA
Tropical Japonica  504 98.00% 0.40% 0.99% 0.60% NA
Japonica Intermediate  241 96.30% 1.70% 1.24% 0.83% NA
VI/Aromatic  96 72.90% 25.00% 1.04% 1.04% NA
Intermediate  90 44.40% 26.70% 18.89% 10.00% NA

Allele Effect:

Var ID Var Locus snpEff Annotation CooVar Annotation Chromatin Accessibility Score PolyPhen-2 Effect PolyPhen-2 Score SIFT Effect SIFT Score
vg0328245483 C -> T LOC_Os03g49600.1 upstream_gene_variant ; 136.0bp to feature; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> T LOC_Os03g49600.2 upstream_gene_variant ; 136.0bp to feature; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> T LOC_Os03g49600.4 upstream_gene_variant ; 136.0bp to feature; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> T LOC_Os03g49600.5 upstream_gene_variant ; 136.0bp to feature; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> T LOC_Os03g49600.3 upstream_gene_variant ; 136.0bp to feature; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> T LOC_Os03g49610.1 downstream_gene_variant ; 3248.0bp to feature; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> T LOC_Os03g49600-LOC_Os03g49610 intergenic_region ; MODIFIER silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 N N N N
vg0328245483 C -> DEL N N silent_mutation Average:98.453; most accessible tissue: Minghui63 flower, score: 99.241 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)
vg0328245483 C T -0.04 0.02 0.02 -0.02 -0.01 0.0

Putative Genotype-Phenotype Associations:

Var ID LMM P-value LR P-value Trait Subpopulation Is leadSNP Publication
vg0328245483 NA 1.57E-08 mr1005 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
vg0328245483 NA 1.79E-119 mr1750 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
vg0328245483 NA 3.60E-20 mr1838 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
vg0328245483 NA 1.24E-33 mr1944 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
vg0328245483 NA 4.81E-17 mr1162_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
vg0328245483 NA 3.96E-07 mr1205_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
vg0328245483 NA 2.60E-16 mr1342_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
vg0328245483 NA 1.16E-16 mr1712_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
vg0328245483 NA 1.68E-10 mr1761_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
vg0328245483 NA 6.01E-11 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
vg0328245483 NA 9.32E-41 mr1944_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