Display options:

Search results

53 variations found. OsZS_04G0299100 (OsZS_04T0299100.1), ranging from 20,308,180 bp to 20,312,259 bp (including 2 kb upstream and 1 kb downstream of the gene).

Syntenic genes

Gene Structure

Five-point stars indicate variants annotated as snpEff HIGH impact or PolyPhen-2 damaging.

Chromatin accessibility landscape across tissues

Allele-specific chromatin accessibility effects predicted by Basenji are reported as the signed local sequence activity log-ratio (LSAR): log2(PALT + 1) − log2(PREF + 1), using local predictions averaged across the central eight 128-bp output bins (1,024 bp total). Positive and negative values indicate increased and reduced predicted accessibility for the alternative allele, respectively. For ZS97RS3 SNPs, a light-red five-point star (★) indicates an HEV.

Detailed Variation Information

Var ID Chrom Position Primary Allele Secondary Allele Primary Allele Frequency DEL Frequency Var GWAS Results Effect
vz0420308276 chr04 20308276 A C 99.50% 0.56% A -> C,T NA
NA
vz0420308351 chr04 20308351 A G 68.50% 0.00% A -> G NA
NA
vz0420308515 chr04 20308515 T A 63.10% 0.03% T -> A NA
NA
vz0420308680 chr04 20308680 T C 96.90% 0.00% T -> C NA
NA
vz0420308780 chr04 20308780 G A 96.80% 0.00% G -> A NA
NA
vz0420308860 chr04 20308860 T C 97.10% 0.03% T -> C NA
NA
vz0420308927 chr04 20308927 G C 68.30% 0.00% G -> C NA
NA
vz0420309084 chr04 20309084 G C 96.90% 0.03% G -> C NA
NA
vz0420309265 chr04 20309265 G T 97.10% 0.17% G -> T NA
NA
vz0420309272 chr04 20309272 A T 97.10% 0.26% A -> T NA
NA
vz0420309284 chr04 20309284 T A 97.10% 0.10% T -> A NA
NA
vz0420309853 chr04 20309853 G T 99.70% 0.50% G -> T NA
NA
vz0420310234 chr04 20310234 T A 100.00% 0.23% T -> A NA
NA
vz0420310289 chr04 20310289 A T 63.00% 0.10% A -> T NA
NA
vz0420310333 chr04 20310333 G T 97.00% 0.17% G -> T NA
NA
vz0420310352 chr04 20310352 A C 99.70% 0.17% A -> C NA
NA
vz0420310372 chr04 20310372 G C 96.70% 0.26% G -> C NA
NA
vz0420310384 chr04 20310384 T G 64.40% 0.86% T -> G,A NA
NA
vz0420310401 chr04 20310401 G A 99.90% 0.46% G -> A NA
NA
vz0420310406 chr04 20310406 G A 99.40% 0.46% G -> A NA
NA
vz0420310408 chr04 20310408 C T 68.50% 1.03% C -> T NA
NA
vz0420310419 chr04 20310419 G A 72.00% 1.19% G -> A NA
NA
vz0420310436 chr04 20310436 C T 68.60% 1.26% C -> T NA
NA
vz0420310444 chr04 20310444 C G 97.90% 0.46% C -> G NA
NA
vz0420310445 chr04 20310445 C T 96.90% 0.33% C -> T NA
NA
vz0420310458 chr04 20310458 C A 96.80% 0.50% C -> A,T NA
NA
vz0420310465 chr04 20310465 C T 96.50% 0.63% C -> T NA
NA
vz0420310471 chr04 20310471 C T 68.20% 0.56% C -> T,A NA
NA
vz0420310473 chr04 20310473 A G 64.70% 0.66% A -> G NA
NA
vz0420310512 chr04 20310512 T C 62.80% 0.46% T -> C NA
NA
vz0420310528 chr04 20310528 C T 96.20% 0.60% C -> T NA
NA
vz0420310531 chr04 20310531 A G 64.60% 0.63% A -> G NA
NA
vz0420310541 chr04 20310541 C T 99.70% 0.56% C -> T NA
NA
vz0420310551 chr04 20310551 T C 96.80% 0.83% T -> C,A NA
NA
vz0420310595 chr04 20310595 A C 64.20% 0.13% A -> C NA
NA
vz0420310693 chr04 20310693 G T 96.90% 0.07% G -> T NA
NA
vz0420310714 chr04 20310714 G A 99.60% 2.45% G -> A NA
NA
vz0420310846 chr04 20310846 T C 64.20% 0.23% T -> C NA
NA
vz0420311136 chr04 20311136 G T 93.60% 0.00% G -> T NA
NA
vz0420311436 chr04 20311436 A T 64.20% 0.00% A -> T NA
NA
vz0420311438 chr04 20311438 C G 64.40% 0.00% C -> G NA
NA
vz0420311453 chr04 20311453 G T 98.40% 0.00% G -> T NA
NA
vz0420311524 chr04 20311524 G A 64.40% 0.00% G -> A NA
NA
vz0420311600 chr04 20311600 C G 99.40% 0.00% C -> G NA
NA
vz0420311660 chr04 20311660 G C 97.00% 0.03% G -> C NA
NA
vz0420311778 chr04 20311778 A C 97.00% 0.00% A -> C NA
NA
vz0420311872 chr04 20311872 A G 99.10% 0.00% A -> G NA
NA
vz0420311983 chr04 20311983 C T 71.20% 0.03% C -> T NA
NA
vz0420312012 chr04 20312012 A NULL 100.00% 0.00% A -> T NA
NA
vz0420312070 chr04 20312070 T C 99.70% 0.03% T -> C NA
NA
vz0420312155 chr04 20312155 A G 63.10% 0.13% A -> G NA
NA
vz0420312242 chr04 20312242 T A 99.00% 0.46% T -> A NA
NA
vz0420312258 chr04 20312258 T C 63.50% 0.20% T -> C NA
NA

Information

This module provides a gene-centered integrative view of genetic variation and regulatory features in rice. It summarizes local genetic variants, functional and phenotypic annotations, chromatin accessibility, model-predicted regulatory effects of non-coding variants, and population genetic statistics within the genomic neighborhood of a queried gene. Quantitative chromatin accessibility and transcriptome profiles across multiple tissues, developmental stages, and three reference varieties are jointly presented to support functional, regulatory, and evolutionary interpretation.

Gene Expression Profiles: Quantitative gene expression levels across multiple tissues and developmental stages are shown where available. These profiles enable direct comparison between transcriptional output and local regulatory activity, facilitating interpretation of tissue-specific gene regulation.

Chromatin Accessibility Landscape: Tissue-resolved chromatin accessibility profiles are visualized across the queried genomic region using ATAC-seq data. Accessibility signals are quantified from Tn5 insertion events aggregated into fixed genomic windows of 250 bp with a sliding step of 100 bp. Heatmap-style visualization highlights spatial and tissue-specific patterns of chromatin openness, revealing putative cis-regulatory elements and their tissue specificity.

Regulatory Effect Predictions for Non-coding Variants: Allele-specific chromatin accessibility effects are predicted using Basenji (Kelley et al., 2018), a deep learning sequence-to-signal model trained to predict chromatin accessibility from genomic sequence. The signed local sequence activity log-ratio is LSAR = log2(PALT + 1) − log2(PREF + 1), where PALT and PREF are local predictions averaged across the central eight 128-bp output bins (1,024 bp total). Positive values indicate that the alternative allele is predicted to increase chromatin accessibility, whereas negative values indicate reduced accessibility relative to the reference allele. These scores enable systematic prioritization of non-coding variants with potential regulatory impact.

High-impact regulatory variants (HEVs): HEV cutoffs depend on both the reference genome and the variant set used for calibration. A symbol is shown for a tissue-specific score only when its absolute unrounded value reaches the applicable cutoff. Both predicted increases and decreases can therefore be marked.

  • Nipponbare (IRGSP-1.0; vg) SNP and non-SNP variants: A light-red ★ denotes an HEV at 0.052 (exact value 0.051688551903), a cutoff calibrated from the SNP-only q90 and applied to both SNP and non-SNP scores. A red ★ denotes a strong HEV at the combined SNP and non-SNP q90 cutoff of 0.106 (exact value 0.10640232). Strong HEVs are displayed as ★ only.
  • MH63RS3 (vm) SNPs: a light-red ★ denotes an HEV at the SNP-only q90 cutoff of 0.052 (exact value 0.052074253559). No strong-HEV tier is used.
  • ZS97RS3 (vz) SNPs: a light-red ★ denotes an HEV at the SNP-only q90 cutoff of 0.047 (exact value 0.047439455986). No strong-HEV tier is used.

These model-derived HEVs are distinct from snpEff HIGH-impact or PolyPhen-2 damaging annotations. “Strong” describes the predicted effect magnitude relative to the combined calibration cutoff; it is not a confidence score.

Population differentiation and diversity statistics: Population genetic statistics are displayed across the gene neighborhood to provide evolutionary context. Genetic differentiation is quantified using FST, calculated in sliding windows of 10 kb with a step size of 1 kb between predefined rice populations. Nucleotide diversity (π) is computed using the same window and step size to measure local genetic variation within populations. Joint visualization of FST and π highlights genomic regions under potential selection and links regulatory variation with population-level evolutionary processes.

Genetic Variants in the Gene Neighborhood: All genetic variants located within the gene body and flanking regions are listed and visualized along the genomic coordinate system. Variants are annotated with sequence context, functional annotations, and population-level allele statistics, enabling detailed inspection of local genetic diversity and variant distribution.

TOC

Navigation