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Detailed information for vg1003113863:

Variant ID: vg1003113863 (JBrowse)Variation Type: SNP
Chromosome: chr10Position: 3113863
Reference Allele: AAlternative Allele: T
Primary Allele: ASecondary Allele: T

Inferred Ancestral Allele : A (evidence from allele frequency in Oryza rufipogon: A: 0.92, T: 0.08, others allele: 0.00, population size: 92. )

Flanking Sequence (100 bp) in Reference Genome:


GAGTCCTGGACAGACCAGCAATGATGAGGTTACAAAATCACGCACCCACCGAAAAAACTGGCACAAGATTAACATATTGGGGAAAAAAATGTAAAGAGGT[A/T]
GACAGGTCCAACTGTATGTCTGCAGATAATTTTCCAATTCCATCGGTTTACCACTACAGACGCCACCGCGAGATACAAAGCTTCAAGACACTGTTTTCAA

Reverse complement sequence

TTGAAAACAGTGTCTTGAAGCTTTGTATCTCGCGGTGGCGTCTGTAGTGGTAAACCGATGGAATTGGAAAATTATCTGCAGACATACAGTTGGACCTGTC[T/A]
ACCTCTTTACATTTTTTTCCCCAATATGTTAATCTTGTGCCAGTTTTTTCGGTGGGTGCGTGATTTTGTAACCTCATCATTGCTGGTCTGTCCAGGACTC

Allele Frequencies:

Populations Population SizeFrequency of A(primary allele) Frequency of T(secondary allele) Frequency of N Frequency of DEL Frequency of others Allele
All  4726 50.60% 30.70% 0.44% 18.24% NA
All Indica  2759 43.00% 26.40% 0.76% 29.90% NA
All Japonica  1512 72.60% 26.40% 0.00% 1.06% NA
Aus  269 7.80% 92.20% 0.00% 0.00% NA
Indica I  595 47.20% 20.80% 0.50% 31.43% NA
Indica II  465 28.00% 43.00% 0.65% 28.39% NA
Indica III  913 55.40% 21.90% 0.66% 22.02% NA
Indica Intermediate  786 34.20% 25.80% 1.15% 38.80% NA
Temperate Japonica  767 61.80% 37.90% 0.00% 0.26% NA
Tropical Japonica  504 88.10% 9.50% 0.00% 2.38% NA
Japonica Intermediate  241 74.30% 24.90% 0.00% 0.83% NA
VI/Aromatic  96 40.60% 49.00% 0.00% 10.42% NA
Intermediate  90 54.40% 33.30% 0.00% 12.22% NA

Allele Effect:

Var ID Var Locus snpEff Annotation CooVar Annotation Chromatin Accessibility Score PolyPhen-2 Effect PolyPhen-2 Score SIFT Effect SIFT Score
vg1003113863 A -> T LOC_Os10g06130.1 3_prime_UTR_variant ; 283.0bp to feature; MODIFIER silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 N N N N
vg1003113863 A -> T LOC_Os10g06130.2 3_prime_UTR_variant ; 283.0bp to feature; MODIFIER silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 N N N N
vg1003113863 A -> T LOC_Os10g06130.3 3_prime_UTR_variant ; 2125.0bp to feature; MODIFIER silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 N N N N
vg1003113863 A -> T LOC_Os10g06130.4 3_prime_UTR_variant ; 2125.0bp to feature; MODIFIER silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 N N N N
vg1003113863 A -> T LOC_Os10g06130.5 3_prime_UTR_variant ; 2125.0bp to feature; MODIFIER silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 N N N N
vg1003113863 A -> T LOC_Os10g06110.1 upstream_gene_variant ; 525.0bp to feature; MODIFIER silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 N N N N
vg1003113863 A -> DEL N N silent_mutation Average:90.024; most accessible tissue: Minghui63 young leaf, score: 93.121 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)
vg1003113863 A T 0.0 -0.01 -0.01 -0.02 -0.02 -0.02

Putative Genotype-Phenotype Associations:

Var ID LMM P-value LR P-value Trait Subpopulation Is leadSNP Publication
vg1003113863 4.16E-06 7.61E-07 mr1538 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
vg1003113863 2.38E-10 4.04E-10 mr1547 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
vg1003113863 3.56E-08 7.83E-10 mr1547 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
vg1003113863 7.63E-15 3.19E-22 mr1709 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
vg1003113863 3.40E-14 7.54E-19 mr1709 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
vg1003113863 NA 3.08E-06 mr1062_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
vg1003113863 NA 9.83E-09 mr1538_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
vg1003113863 3.13E-07 8.30E-10 mr1547_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
vg1003113863 1.97E-08 1.17E-09 mr1547_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
vg1003113863 3.38E-25 1.81E-36 mr1709_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
vg1003113863 4.94E-17 3.28E-19 mr1709_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
vg1003113863 5.59E-10 3.86E-20 mr1709_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