Dataset Information

SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing.

ABSTRACT: Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) assesses all classes of SVs and their intersection with transcripts and regulatory sequences, relating predicted effects on gene function with clinical phenotype data. SvAnna places 87% of deleterious SVs in the top ten ranks. The interpretable prioritizations offered by SvAnna will facilitate the widespread adoption of long-read sequencing in diagnostic genomics. SvAnna is available at https://github.com/TheJacksonLaboratory/SvAnn a .

SUBMITTER: Danis D

PROVIDER: S-EPMC9047340 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing.

Danis Daniel D Jacobsen Julius O B JOB Balachandran Parithi P Zhu Qihui Q Yilmaz Feyza F Reese Justin J Haimel Matthias M Lyon Gholson J GJ Helbig Ingo I Mungall Christopher J CJ Beck Christine R CR Lee Charles C Smedley Damian D Robinson Peter N PN

Genome medicine 20220428 1

Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) assesses all classes of SVs and their intersection with transcripts and regulatory sequences, relating predicted effects on gene function with clinical phe ...[more]

PMID: 35484572

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Project description:BackgroundHaploinsufficiency of the transcription factor PAX6 is the main cause of congenital aniridia, a genetic disorder characterized by iris and foveal hypoplasia. 11p13 microdeletions altering PAX6 or its downstream regulatory region (DRR) are present in about 25% of patients; however, only a few complex rearrangements have been described to date. Here, we performed nanopore-based whole-genome sequencing to assess the presence of cryptic structural variants (SVs) on the only two unsolved "PAX6-negative" cases from a cohort of 110 patients with congenital aniridia after unsuccessfully short-read sequencing approaches.ResultsLong-read sequencing (LRS) unveiled balanced chromosomal rearrangements affecting the PAX6 locus at 11p13 in these two patients and allowed nucleotide-level breakpoint analysis. First, we identified a cryptic 4.9 Mb de novo inversion disrupting intron 7 of PAX6, further verified by targeted polymerase chain reaction amplification and sequencing and FISH-based cytogenetic analysis. Furthermore, LRS was decisive in correctly mapping a t(6;11) balanced translocation cytogenetically detected in a second proband with congenital aniridia and considered non-causal 15 years ago. LRS resolved that the breakpoint on chromosome 11 was indeed located at 11p13, disrupting the DNase I hypersensitive site 2 enhancer within the DRR of PAX6, 161 Kb from the causal gene. Patient-derived RNA expression analysis demonstrated PAX6 haploinsufficiency, thus supporting that the 11p13 breakpoint led to a positional effect by cleaving crucial enhancers for PAX6 transactivation. LRS analysis was also critical for mapping the exact breakpoint on chromosome 6 to the highly repetitive centromeric region at 6p11.1.ConclusionsIn both cases, the LRS-based identified SVs have been deemed the hidden pathogenic cause of congenital aniridia. Our study underscores the limitations of traditional short-read sequencing in uncovering pathogenic SVs affecting low-complexity regions of the genome and the value of LRS in providing insight into hidden sources of variation in rare genetic diseases.

Project description:5-methylcytosine (5mC) is the most common chemical modification occurring on the CpG sites across the human genome. Bisulfite conversion combined with short-read whole genome sequencing can capture and quantify the modification at single nucleotide resolution. However, the PCR amplification process could lead to duplicative methylation patterns and introduce 5mC detection bias. Additionally, the limited read length also restricts co-methylation analysis between distant CpG sites. The bisulfite conversion process presents a significant challenge for detecting variant-specific methylation due to the destruction of allele information in the sequencing reads. To address these issues, we sought to characterize the human methylation profiling with the nanopore long-read sequencing, aiming to demonstrate its potential for long-range co-methylation analysis with native modification call and intact allele information retained. In this regard, we first analyzed the nanopore demo data in the adaptive sampling sequencing run targeting all human CpG islands. We applied the linkage disequilibrium (LD) R2 to calculate the co-methylation in nanopore data, and further identified 27,875, 50,481, 26,542 and 51,189 methylation haplotype blocks (MHB) in COLO829, COLO829BL, HCC1395 and HCC1395BL cell lines, respectively. Interestingly, while we found that majority of the co-methylation were in a short range (≤200bp), a small portion (1~3%) showed long distance (≥1,000bp), suggesting potential remote regulatory mechanisms across the genome. To further characterize the epigenetic changes related to transcription factor binding, we profiled the 5mC percentage changes surrounding various motif sites in JASPAR collection and found that CTCF and KLF5 binding sites showed reduced methylation, while FOXE1 and ZNF354A sites showed increased methylation. To further investigate the allele-specific 5mCG in the prostate genome, we designed a target region covering methylation quantitative trait loci (mQTL) and genome-wide association study (GWAS) risk germline variants and generated long reads with adaptive sampling run in the 22Rv1 cell line. To identify the allele-specific methylation in the 22Rv1 cell line, we performed long-read based phasing and compared the 5mCG signals between the two haplotypes. As a result, we identified 6,390 haplotype-specific methylated regions in the 22Rv1 cell line (p-MWU ≤ 1e-5 and delta ≥ 50%). By examining haplotype-specific methylated regions near the phasing variants, we identified examples of allele-specific methylated regions that showed allelespecific accessibility in the ATAC-seq data. By further integrating the ATAC-seq data of 22Rv1, we found that methylation levels were negatively correlated with chromatin accessibility at the genome-wide scale. Our study has revealed native methylome profiling while preserving haplotype information, offering a novel approach to uncovering the regulatory mechanisms of the human prostate genome.

Dataset Information

SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing.

Publications

SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing.

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