RNA quality was assessed on a Fragment Analyzer (Advanced Analytical Technologies, Inc.); all RNAs had an RQN of 7.9–10. From 100 ng total RNA, mRNA was isolated with the NEBNext Poly(A) mRNA Magnetic Isolation Module. RNA-seq libraries were prepared from the mRNA using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (New England Biolabs). Cluster generation was performed with the resulting libraries using the Illumina TruSeq SR Cluster Kit v4 reagents and sequenced on the Illumina HiSeq 2500 using TruSeq SBS Kit v4 reagents (Illumina). Sequencing data were demultiplexed using the bcl2fastq Conversion Software (version 2.20, Illumina).
Bcl2fastq conversion software
Manufactured by Illumina
Sourced in United States
Bcl2fastq Conversion Software is a bioinformatics tool used to convert raw sequencing data from the Illumina platform into the standard FASTQ format. It allows users to demultiplex sequencing data and generate FASTQ files from BCL files produced by Illumina sequencing instruments.
Automatically generated - may contain errors
Lab products found in correlation
Tapestation 4200, by Agilent Technologies (7 mentions)
Nanodrop nd 1000 spectrophotometer, by Thermo Fisher Scientific (6 mentions)
Novaseq 6000, by Illumina (5 mentions)
Hiseq 2500, by Illumina (4 mentions)
Hiseq 4000, by Illumina (4 mentions)
Truseq stranded mrna sample prep kit, by Illumina (4 mentions)
Hiseq 400, by Illumina (4 mentions)
Stranded mrna prep, by Illumina (3 mentions)
Real time analysis software, by Illumina (3 mentions)
Qubit 3.0 fluorometer, by Thermo Fisher Scientific (3 mentions)
Nebnext ultra 2 directional rna library prep kit for, by Illumina (2 mentions)
Xt library kit, by Illumina (2 mentions)
Truseq rna sample preparation v2 guide, by Illumina (2 mentions)
Truseq stranded mrna library prep assay, by Illumina (2 mentions)
S1 reagent kit v1, by Illumina (2 mentions)
Nextseq 500, by Illumina (2 mentions)
Fastq files, by Illumina (2 mentions)
Truseq stranded mrna library preparation kit, by Illumina (2 mentions)
Purelink rna isolation kit, by Thermo Fisher Scientific (2 mentions)
Rneasy tissue kit, by Qiagen (2 mentions)
84 protocols using bcl2fastq conversion software
1
RNA-seq Library Preparation and Sequencing
2
BCL to FASTQ Conversion Protocol
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BCL files were converted to FASTQ files using bcl2fastq Conversion Software version v2.20.0.422 (Illumina).
3
Microbiome Profiling by Shotgun Sequencing
4
Metagenomics and Metatranscriptomics Data Processing
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Raw sequence data were demultiplexed into sample-specific fastq files using bcl2fastq conversion software from Illumina. Adapter residues were trimmed from both the 5′- and the 3′-end of the reads using Adapter Removal tool v.2.1.3. The sequences were trimmed for quality using MEEPTOOLS64 (link), retaining reads with a minimum read length of 70 b and MEEP quality score <1. Human reads were identified and removed from each sample by aligning the reads to the hg19 build of the human genome, using the BWA aligner. Taxonomic classification and relative abundance of bacteria in the metagenomes and metatranscriptomes, using harmonized bioinformatics pipelines with the other iHMP projects for upload to the HMP DACC, were obtained using Metaphlan2 (ref. 65 (link)), with default parameters. The human-filtered MGS and MTS nodes were created at HMP DACC, WGSRawSeqSet and MicrobTranscriptomicsRawSeqSet, respectively, which link to the controlled-access data at the database of Genotypes and Phenotypes (study no. 20280). Metaphlan2 output community profiles of metagenomes and metatranscriptomes have been uploaded to HMP DACC, wgs_community node and microb_metatranscriptome node, as tab-delimited text files.
5
RNA Isolation and Sequencing of Cell Cultures
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Total RNA was extracted from two million cells with TRIzolate reagent in biological duplicates (originating from two different growths of cells from the same tier of the biobank). For details, see Supplementary Methods. RNA concentration and sample purity were determined using a NanoDrop 1000 instrument (Thermo Fisher Scientific, Waltham, MA, USA). For the analysis of fragment distribution and calculation of RIN values (calculated being at least 9.4; mean: 9.8), RNA samples were loaded to Agilent RNA 6000 Nano microchips (Agilent, Santa Clara, CA, USA). Sequencing libraries were prepared following Illumina’s TruSeq RNA Sample Preparation v2 Guide with poly(A) selection using 1 μg total RNA as the starting material. Indexed libraries were pooled and subjected to single-end sequencing on a NextSeq500 sequencer (Illumina, San Diego, CA, USA) with 50-bp read length. Library preparation, cluster generation, sequencing and base calling were performed at the Genomic Medicine and Bioinformatic Core Facility at the University of Debrecen, Hungary. Demultiplexing was performed using the bcl2fastq Conversion Software (Illumina).
6
Viral Metatranscriptomics of Grapevines
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Total nucleic acid (TNA) extracts were prepared from 22 grapevine accessions as previously described [24 (link)]. TNA was isolated from petioles of selected grapevines. Aliquots of TNA from source samples were subjected to ribosomal RNA (rRNA) depletion and complementary DNA (cDNA) library construction employing a TruSeq Stranded Total RNA with Ribo-Zero Plant kit (Illumina, San Diego, CA, USA). Later, cDNA libraries were sequenced using the Illumina NextSeq 500 platform located at the UC-Davis Genome Center. Sequencing reads were demultiplexed and adapter trimmed via bcl2fastq Conversion Software (Illumina). Trimmed reads were de novo assembled into contigs using SPAdes [25 (link)]. Generated contigs were compared against the complete non-redundant GenBank virus database using BLASTn for nts and BLASTx for aa, providing the annotation used for viral agent identification. Contigs above 500 nts, and with identity over the 80% at the nt or aa level were taken as threshold in order to call the virus species.
7
Drosophila Transcriptome Analysis via 10X Genomics
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Per-read per-sample FASTQ files were generated using the Illumina bcl2fastq Conversion software (v2.17) to convert BCL base call files outputted by the sequencing instrument into the FASTQ format.
The 10× Genomics analysis software, Cell Ranger (v1.3.1 for replicate 1 and v2.0.0 for replicate 2), specifically the “cellranger count” pipeline, was used to process the FASTQ files in order to align reads to the Drosophila melanogaster reference genome (dm6) (Dos Santos et al. 2015 (link)) and generate gene-barcode expression matrices. The output of multiple samples from the “cellranger count” pipeline were aggregated using the “cellranger aggr” pipeline of Cell Ranger, normalizing the combined output to the same sequencing depth and recomputing the gene-barcode matrices and expression analysis accordingly for the aggregated data.
The 10× Genomics analysis software, Cell Ranger (v1.3.1 for replicate 1 and v2.0.0 for replicate 2), specifically the “cellranger count” pipeline, was used to process the FASTQ files in order to align reads to the Drosophila melanogaster reference genome (dm6) (Dos Santos et al. 2015 (link)) and generate gene-barcode expression matrices. The output of multiple samples from the “cellranger count” pipeline were aggregated using the “cellranger aggr” pipeline of Cell Ranger, normalizing the combined output to the same sequencing depth and recomputing the gene-barcode matrices and expression analysis accordingly for the aggregated data.
8
Dual-species RNA-seq data processing
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Base calls were converted to fastq format and demultiplexed using Illumina's bcl2fastq conversion software (v.2.16.0.10) tolerating one mismatch per library barcode. Reads were filtered for a valid unique molecular identifier (UMI) and sample barcode, tolerating one mismatch per barcode. Trimming was performed using Trimmomatic (version 0.33) (Bolger et al., 2014 (link)). Trimmed reads were mapped to a combined human (GRCh38.p12) and rat (Rnor_6.0) reference genome using STAR (Dobin et al., 2013 (link)) (version 2.5.1b), with default settings (--runThreadN 1, --outReadsUnmapped None, --outFilterType Normal, --outFilterScoreMin 0, --outFilterMultimapNmax 10, --outFilterMismatchNmax 10, --alignIntronMin 21, --alignIntronMax 0, --alignMatesGapMax 0, --alignSJoverhangMin 5, --alignSJDBoverhangMin 3, --sjdbOverhang 100). Uniquely mapped reads (mapping quality of 255) were extracted and read duplicates were removed using the UMI-tools software package (Smith et al., 2017 (link)). Raw reads from BAM files were further processed to generate count matrices with HTSeq (Anders et al., 2015 (link)) (version 0.9.1) using a combined Gencode GRCh38.p12 (release 29, Ensembl 94) and rat (Rnor_6.0) reference transcriptome, to separate counts from human neurons and rat astrocytes.
9
Swine Genome Sequencing Workflow
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Prior to further processing, raw data were quality checked for overrepresented and duplicate sequences with FastQC (www.bioinformatics.babraham.ac.uk/projects/fastqc ). Duplicates were removed by picardtool and samtools (Broad Institute).
All programs used in further processing raw reads were embedded in Python scripts to connect the different steps and programs.
First, raw sequences were converted from a base call file (.bcl) to .fastq files and mixed probes were demultiplexed through the program bcl2fastq Conversion Software from Illumina (bcl2fastq_conversion_software_184.html?langsel=/de/">https://emea.support.illumina.com/downloads/bcl2fastq_conversion_software_184.html?langsel=/de/ ).
Next, sequences in .fastq format were aligned to the swine genome (S. scrofa 11.1, Genebank assembly accession: GCA_000003025.6) with the mem algorithm implemented in the Burrows Wheeler Alignment software (Li and Durbin 2009 (link)) and stored as .bam files. Quality control for the aligned sequences was performed by identifying read groups and tagging duplicated reads. Statistics were created with the utility flagstats from SAMtools (Li et al. 2009 (link)).
All programs used in further processing raw reads were embedded in Python scripts to connect the different steps and programs.
First, raw sequences were converted from a base call file (.bcl) to .fastq files and mixed probes were demultiplexed through the program bcl2fastq Conversion Software from Illumina (
Next, sequences in .fastq format were aligned to the swine genome (S. scrofa 11.1, Genebank assembly accession: GCA_000003025.6) with the mem algorithm implemented in the Burrows Wheeler Alignment software (Li and Durbin 2009 (link)) and stored as .bam files. Quality control for the aligned sequences was performed by identifying read groups and tagging duplicated reads. Statistics were created with the utility flagstats from SAMtools (Li et al. 2009 (link)).
10
Sequencing and Alignment of Drosophila Transcriptome
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Per-read per-sample FASTQ files were generated using the Illumina bcl2fastq conversion software (v2.20) to convert per-cycle BCL base-call files outputted by the sequencing instrument into the FASTQ format. The alignment program STAR (v2.4.5a) (Dobin et al. 2013 (link)) was used for mapping reads to the D. melanogaster reference genome dm6 (Dos Santos et al. 2015 (link)) and the application FastQ Screen (v0.5.2) (Wingett and Andrews 2018 (link)) was used to check for contaminants. The software featureCounts (Subread package v1.4.6-p3) (Liao et al. 2013 (link), 2014 (link)) was used to generate the matrix of read counts for annotated genomic features.
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