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June 1, 2021  |  

A method for the identification of variants in Alzheimer’s disease candidate genes and transcripts using hybridization capture combined with long-read sequencing

Alzheimer’s disease (AD) is a devastating neurodegenerative disease that is genetically complex. Although great progress has been made in identifying fully penetrant mutations in genes such as APP, PSEN1 and PSEN2 that cause early-onset AD, these still represent a very small percentage of AD cases. Large-scale, genome-wide association studies (GWAS) have identified at least 20 additional genetic risk loci for the more common form of late-onset AD. However, the identified SNPs are typically not the actual causal variants, but are in linkage disequilibrium with the presumed causative variant (Van Cauwenberghe C, et al., The genetic landscape of Alzheimer disease: clinical implications and perspectives. Genet Med 2015;18:421-430).

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June 1, 2021  |  

Screening for causative structural variants in neurological disorders using long-read sequencing

Over the past decades neurological disorders have been extensively studied producing a large number of candidate genomic regions and candidate genes. The SNPs identified in these studies rarely represent the true disease-related functional variants. However, more recently a shift in focus from SNPs to larger structural variants has yielded breakthroughs in our understanding of neurological disorders.Here we have developed candidate gene screening methods that combine enrichment of long DNA fragments with long-read sequencing that is optimized for structural variation discovery. We have also developed a novel, amplification-free enrichment technique using the CRISPR/Cas9 system to target genomic regions.We sequenced gDNA and full-length cDNA extracted from the temporal lobe for two Alzheimer’s patients for 35 GWAS candidate genes. The multi-kilobase long reads allowed for phasing across the genes and detection of a broad range of genomic variants including SNPs to multi-kilobase insertions, deletions and inversions. In the full-length cDNA data we detected differential allelic isoform complexity, novel exons as well as transcript isoforms. By combining the gDNA data with full-length isoform characterization allows to build a more comprehensive view of the underlying biological disease mechanisms in Alzheimer’s disease. Using the novel PCR-free CRISPR-Cas9 enrichment method we screened several genes including the hexanucleotide repeat expansion C9ORF72 that is associated with 40% of familiar ALS cases. This method excludes any PCR bias or errors from an otherwise hard to amplify region as well as preserves the basemodication in a single molecule fashion which allows you to capture mosaicism present in the sample.

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April 21, 2020  |  

Improved assembly and variant detection of a haploid human genome using single-molecule, high-fidelity long reads.

The sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective standalone technology for de novo assembly of human genomes. © 2019 John Wiley & Sons Ltd/University College London.

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April 21, 2020  |  

Chlorella vulgaris genome assembly and annotation reveals the molecular basis for metabolic acclimation to high light conditions.

Chlorella vulgaris is a fast-growing fresh-water microalga cultivated at the industrial scale for applications ranging from food to biofuel production. To advance our understanding of its biology and to establish genetics tools for biotechnological manipulation, we sequenced the nuclear and organelle genomes of Chlorella vulgaris 211/11P by combining next generation sequencing and optical mapping of isolated DNA molecules. This hybrid approach allowed to assemble the nuclear genome in 14 pseudo-molecules with an N50 of 2.8 Mb and 98.9% of scaffolded genome. The integration of RNA-seq data obtained at two different irradiances of growth (high light-HL versus low light -LL) enabled to identify 10,724 nuclear genes, coding for 11,082 transcripts. Moreover 121 and 48 genes were respectively found in the chloroplast and mitochondrial genome. Functional annotation and expression analysis of nuclear, chloroplast and mitochondrial genome sequences revealed peculiar features of Chlorella vulgaris. Evidence of horizontal gene transfers from chloroplast to mitochondrial genome was observed. Furthermore, comparative transcriptomic analyses of LL vs HL provide insights into the molecular basis for metabolic rearrangement in HL vs. LL conditions leading to enhanced de novo fatty acid biosynthesis and triacylglycerol accumulation. The occurrence of a cytosolic fatty acid biosynthetic pathway can be predicted and its upregulation upon HL exposure is observed, consistent with increased lipid amount under HL. These data provide a rich genetic resource for future genome editing studies, and potential targets for biotechnological manipulation of Chlorella vulgaris or other microalgae species to improve biomass and lipid productivity.This article is protected by copyright. All rights reserved.

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April 21, 2020  |  

A robust benchmark for germline structural variant detection

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls =50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

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April 21, 2020  |  

Comparison of mitochondrial DNA variants detection using short- and long-read sequencing.

The recent advent of long-read sequencing technologies is expected to provide reasonable answers to genetic challenges unresolvable by short-read sequencing, primarily the inability to accurately study structural variations, copy number variations, and homologous repeats in complex parts of the genome. However, long-read sequencing comes along with higher rates of random short deletions and insertions, and single nucleotide errors. The relatively higher sequencing accuracy of short-read sequencing has kept it as the first choice of screening for single nucleotide variants and short deletions and insertions. Albeit, short-read sequencing still suffers from systematic errors that tend to occur at specific positions where a high depth of reads is not always capable to correct for these errors. In this study, we compared the genotyping of mitochondrial DNA variants in three samples using PacBio’s Sequel (Pacific Biosciences Inc., Menlo Park, CA, USA) long-read sequencing and illumina’s HiSeqX10 (illumine Inc., San Diego, CA, USA) short-read sequencing data. We concluded that, despite the differences in the type and frequency of errors in the long-reads sequencing, its accuracy is still comparable to that of short-reads for genotyping short nuclear variants; due to the randomness of errors in long reads, a lower coverage, around 37 reads, can be sufficient to correct for these random errors.

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