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Molecular Diagnosis of Autosomal Dominant Polycystic Kidney Disease
Published in Jinghua Hu, Yong Yu, Polycystic Kidney Disease, 2019
Matthew Lanktree, Amirreza Haghighi, Xueweng Song, York Pei
After sequencing, FASTQ files from the sequencer undergo quality control, and are demultiplexed by assigning to the proper sample using the unique oligonucleotide barcode. The trimmed raw sequence is aligned to the human reference genome (hg19, NCBI build GRCh37) and PKD1 targeted region using the Burrows-Wheeler Aligner BWA-MEM alignment algorithm (BWA-0.7.12).26 BWA sequence alignments are converted into an analysis-ready binary alignment (BAM) file using SAMtools, and PCR duplicate reads are marked using Picard tools–1.123. Local realignment and base recalibration are performed using the Genome Analysis Tool Kit (GATK 3.6).27 Using the BAM file as input, single nucleotide variations and small insertion or deletions (InDels) are detected simultaneously using GATK HalotypeCaller 3.6, which produces a variant call format (VCF) file containing all the observed variation. For detecting mosaic or somatic variants, both HalotypeCaller 3.6 and FreeBayes caller v0.9.20-8-gfef284a (https://github.com/ekg/freebayes/) are employed. Freebayes has a tunable allele frequency setting, and we set the alternate allele fraction ≥5% for maximum sensitivity. To exclude false-positive calls, all variants are visually inspected on the Golden Helix Genome Browser (Golden Helix, Bozeman, Montana, USA), which vallows for observation of the variants at the level of the individual read. Poly-T, -C, -A, -G stretches, GC-rich areas and InDel regions may influence the mapping qualities or variant calls, creating false-positive calls. For assessment of mosaic or somatic variants with low alternate allele fraction (≤5%), the recurrent variants observed in multiple unrelated samples are considered sequencing artifacts and are excluded.
Hybrid, ultra-deep metagenomic sequencing enables genomic and functional characterization of low-abundance species in the human gut microbiome
Published in Gut Microbes, 2022
Hao Jin, Lijun You, Feiyan Zhao, Shenghui Li, Teng Ma, Lai-Yu Kwok, Haiyan Xu, Zhihong Sun
BWA MEM (v.0.7.17)56 was used to map reads to the scaffolds; and samtools (v.1.9)57 was used to convert the output file to BAM format. The average depth for each scaffold in each MAG was calculated using MetaBAT2 script jgi_summarize_bam_contig_depths. The depth for each MAG was calculated by the average of each scaffold in the MAG and normalized by scaffold length. The relative abundance of each MAG was computed as the depth of the MAGs normalized by the total reads of the metagenome sample to allow for sample-to-sample comparison. Long reads were aligned to CMAGs using Minimap2 (version: 2.16-r922),46 excluding secondary alignments using samtools. The nanopore coverage was calculated using bedtools genomecov (version: 2.27.1).58 Average per-window depth was computed using mosdepth (version: 0.2.5)59 with a window size of 1000 bp and visualized using the circos package in R.
Targeted long-read sequencing allows for rapid identification of pathogenic disease-causing variants in retinoblastoma
Published in Ophthalmic Genetics, 2022
Kenji Nakamichi, Andrew Stacey, Debarshi Mustafi
FASTQ files were generated using Guppy and aligned to GRCh38 using minimap2 (29). The BAM file was collated, duplicates marked and the reads filtered for a minimum alignment quality score of MAPQ 50 and secondary, supplementary, and optical duplicates were removed using SAMtools (v1.13–5). Variants were called using PEPPER and haplotyping was achieved using Margin. The DeepVariant pipeline was used to generate a phased VCF (24) and haplotagged BAM file. SAMtools was used to isolate reads that mapped to the RB1 target region. The Combined Annotation-Dependent Depletion (CADD) (30,31) score, which integrates diverse genome annotations and scores any possible human SNV or indel event for their deleterious nature, was generated for each phased VCF, to provide a quantitative prediction of deleteriousness, pathogenicity, and molecular functionality of the identified variants.
Identification of novel cis-mutations in the GJA8 gene in a 3-generation Iranian family with autosomal dominant congenital nuclear cataract
Published in Ophthalmic Genetics, 2022
Neda Jabbarpour, Hassan Saei, Mohammad Hossein Jabbarpoor Bonyadi, Mortaza Bonyadi
A four-year-old boy belonging to an Iranian-Azeri Turkish family with autosomal dominant segregating bilateral congenital nuclear cataract was referred for genetic analysis by applying Whole-Exome Sequencing (WES). His mother, grandmother, and six other family members also had bilateral nuclear cataract. Upon written consent, blood samples were taken from all affected and unaffected members of the third-generation family on EDTA tubes. DNA of proband was extracted, quantified, and subjected to WES analysis as described previously (11,12). In brief, the individual’s DNA was extracted from the blood sample. It was subjected to WES using Agilent SureSelect Human All Exon V7 Target Enrichment kit. The enriched library was sequenced on an Illumina NovaSeq 6000 platform. Paired-end 150-bp sequence reads were mapped to the UCSC human reference genome (GRCh37/hg19 and GRCh38/hg38 assembly) by Burrows-Wheeler Aligner (BWA) (11) and CLC genomic workbench software (version 21). Duplicates and low-quality reads were removed (Qbase <20) with the Picard and Trimmomatics V0.39 tools, respectively. Samtools (12) was used for sorting and indexing bam files. The Single nucleotide variants (SNVs) or small insertion or deletions (Indels) were called using Genome Analysis Toolkit (GATK – version 40,205.0) and DeepVariant V 1.1.0 in parallel. The variants were annotated using the Wannovar web tool (13).