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Detailed information for vg0720205040:

Variant ID: vg0720205040 (JBrowse)Variation Type: SNP
Chromosome: chr07Position: 20205040
Reference Allele: TAlternative Allele: A
Primary Allele: ASecondary Allele: T

Inferred Ancestral Allele : T (evidence from allele frequency in Oryza rufipogon: T: 0.99, others allele: 0.00, population size: 103. )

Flanking Sequence (100 bp) in Reference Genome:


TGCATTTCCAATATCATCAAAACATCTTTCTCATGCTACTCCTAGTCCTTGGCACTCACCTCCTGTAAATCATTCTAATTAACCACTGAACCTTCCTACG[T/A]
CGCCTCGAGCCAATTAATTATAATTCAATTGATTTGATCAATTAAATAACGACAACGTGCATTTATCTTCCCGTTAATTAGTTCGTTCTCCAGGACCAGG

Reverse complement sequence

CCTGGTCCTGGAGAACGAACTAATTAACGGGAAGATAAATGCACGTTGTCGTTATTTAATTGATCAAATCAATTGAATTATAATTAATTGGCTCGAGGCG[A/T]
CGTAGGAAGGTTCAGTGGTTAATTAGAATGATTTACAGGAGGTGAGTGCCAAGGACTAGGAGTAGCATGAGAAAGATGTTTTGATGATATTGGAAATGCA

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 59.20% 37.10% 1.42% 2.37% NA
All Indica  2759 85.00% 9.40% 2.28% 3.30% NA
All Japonica  1512 26.10% 72.60% 0.07% 1.19% NA
Aus  269 1.50% 97.40% 0.74% 0.37% NA
Indica I  595 83.90% 1.80% 7.06% 7.23% NA
Indica II  465 83.40% 15.10% 0.43% 1.08% NA
Indica III  913 88.10% 10.20% 0.22% 1.53% NA
Indica Intermediate  786 83.20% 10.90% 2.16% 3.69% NA
Temperate Japonica  767 3.40% 96.60% 0.00% 0.00% NA
Tropical Japonica  504 63.10% 33.90% 0.00% 2.98% NA
Japonica Intermediate  241 21.20% 77.20% 0.41% 1.24% NA
VI/Aromatic  96 1.00% 99.00% 0.00% 0.00% NA
Intermediate  90 56.70% 40.00% 1.11% 2.22% NA

Allele Effect:

Var ID Var Locus snpEff Annotation CooVar Annotation Chromatin Accessibility Score PolyPhen-2 Effect PolyPhen-2 Score SIFT Effect SIFT Score
vg0720205040 T -> DEL N N silent_mutation Average:65.902; most accessible tissue: Zhenshan97 root, score: 98.554 N N N N
vg0720205040 T -> A LOC_Os07g33770-LOC_Os07g33780 intergenic_region ; MODIFIER silent_mutation Average:65.902; most accessible tissue: Zhenshan97 root, score: 98.554 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)
vg0720205040 T A -0.09 -0.04 -0.03 -0.02 -0.03 -0.03

Putative Genotype-Phenotype Associations:

Var ID LMM P-value LR P-value Trait Subpopulation Is leadSNP Publication
vg0720205040 NA 6.57E-26 mr1422 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
vg0720205040 NA 1.96E-08 mr1422 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
vg0720205040 NA 6.49E-07 mr1443 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
vg0720205040 NA 1.19E-06 mr1443 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
vg0720205040 NA 1.07E-08 mr1539 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
vg0720205040 NA 1.26E-13 mr1540 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
vg0720205040 NA 8.82E-18 mr1583 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
vg0720205040 NA 6.65E-10 mr1720 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
vg0720205040 NA 7.83E-14 mr1732 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
vg0720205040 NA 5.11E-07 mr1925 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
vg0720205040 NA 8.72E-11 mr1228_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
vg0720205040 NA 6.99E-26 mr1422_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
vg0720205040 NA 2.21E-17 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
vg0720205040 NA 1.69E-14 mr1583_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
vg0720205040 NA 2.77E-18 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