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35 protocols using clc genomics workbench v6

1

Mitochondrial Genome Assembly and Transcriptome Analysis

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All raw DNA and RNA-seq reads went through quality filtering and adapter trimming in CLC Genomics Workbench v. 6.5 (CLC Inc, Aarhus, Denmark). For PE reads, regions with Phred quality less than 20 were trimmed, no more than one N was allowed in the remaining sequence, than TruSeq adapter trimming and a minimum length threshold of 50 nt were applied. For MP reads, a more complex adapter trimming procedure was implemented to remove internal adapters and pairs with incorrect read orientation. The PE reads were merged in a pairwise fashion using CLC Genomics Workbench v. 6.5 with default settings. The mitochondrial genome of E. gracilis was assembled with the Newbler assembler (GS De Novo Assembler v. 2.9) from MP and PE (merged and not merged) reads. A number of assembly parameters were tested to maximize the length of mitochondrion-encoded genes. Draft RNA-seq assembly was performed with CLC Genomics Workbench v. 6.5 using standard de novo assembly settings.
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2

Transcriptomic Assembly Comparison: CLC Genomics vs Oyster River

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Raw paired-end reads were quality-checked using FastQC (v0.11.9; https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) before transcriptomic assembly. Two assemblies were then made, first via the de novo assembly option in CLC Genomics WorkBench v.6.0.4 (CLCBio, Boston, MA) using raw reads, with scaffolding enabled, a minimum contig length of 200 bp, and automatic word and bubble sizes of 24 and 50, respectively. The second was assembled using the Oyster River Protocol (ORP, v2.2.6; [42 (link)]) and default settings (TPM_FILT = 1, STRAND = RF, MEM = 150, CPU = 24), on an Amazon Web Service EC2 server with 32 vCPUs and 128 GB of RAM. The first step in the ORP pipeline is read error correction via Rcorrector (v1.0.3), followed by Illumina adaptor removal and trimming of reads with Phred quality below 3, using Trimmomatic (v0.38). Trinity (v2.8.4; [43 (link)]), Spades55, Spades75 (v3.13.0; [44 (link)]) and Transabyss (v2.0.1; [45 (link)]) are then used to make four de novo assemblies, which are merged via a modified version of Orthofinder (v2.2.6; [46 (link)]) packaged in OrthoFuser [45 (link)]. The CLC and ORP-merged assemblies were assessed via BUSCO (v4.0.6; [47 ]) with the insecta_odb10 database, and TransRate (v1.0.3; [48 (link)]) read mapping.
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3

Sequence Mapping Comparison: CLC vs GS Workbench

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Sequence data mapping was performed using CLC Genomics Workbench v6.0.4 (CLC Inc, Aarhus, Denmark). CLC Reference Mapper was run with default settings (Insertion cost = 3, Deletion cost = 3, Mismatch cost = 2, Length fraction = 0.5 and similarity fraction = 0.8). CLC default settings were arbitrarily assigned as low stringency settings. Medium stringency settings were arbitrarily defined as Insertion cost = 3, Deletion cost = 3, Mismatch cost = 2, Length fraction = 0.7 and similarity fraction = 0.8. High stringency settings were defined as Insertion cost = 3, Deletion cost = 3, Mismatch cost = 3, Length fraction = 1.0 and similarity fraction = 1.0. GS Reference Mapper software (v2.0.01.14; Roche/454) was used to produce reference-guided assemblies of each of the Roche datasets with respect to the DENV-1 genome (GenBank; DVU88536).
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4

Comparative Genomics of Trichuris Parasites

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Reads (~100 bp) of each genome were assembled using CLC Genomics Workbench v.6.0.4 (CLC Inc, Aarhus, Denmark) de novo except for sample TSDK that was assembled using TSUG and GenBank entry GU070737 (TSCH). The files of the NGS raw data can be provided upon request. For TTHUG, sequences were manually checked, edited, and trimmed using Vector NTI [18 (link)] and BioEdit [19 ] and aligned to TTB1. After assembly, genome annotation was performed using the pipeline MITOS [20 (link)] and BLAST search tools available through NCBI (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Secondary structures for all tRNAs were predicted using tRNAScan-SE [21 (link)] and ARWEN [22 (link)].
The genomes were compared with T. trichiura from a human in China (TTHCH) (GU385218); Trichuris sp. GHL from francois' leaf monkey (T.GHL) from China (KC461179), and T. suis from China (TSCH) (GU070737). Protein-coding genes (PCGs) and ribosomal DNA genes were individually extracted and aligned by ClustalW using default settings. Another data set was generated by concatenating all PCG and rDNA sequences. Genetic distances were estimated for these data sets using MEGA v.6.1 [23 (link)]. Nucleotide diversity (π) was calculated across the genomes of Trichuris from humans and non-human primates and Trichuris from pigs using a sliding window of 100 bp with 25 bp steps implemented in DnaSP v.5 [24 (link)].
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5

Stringent Variant Calling in Genomics

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Raw sequence files (FASTQ) were imported into CLC Genomics Workbench (v.6; Qiagen) and mapped onto the human genome (GRCh37/hg19). Only full‐length, paired, uniquely‐mapping reads with <= 3 mismatches were used for variant calling. Variants with depth of coverage <30, or with genotype quality scores <25, were excluded. In addition, alleles not observed on both strands (with a minimum frequency ≥ 0.1) or with allelic imbalances (heterozygote genotype calls with one allele observed with frequency < 0.25 or homozygote alleles observed with frequency < 0.85) were also excluded. After compilation of the dataset, positions not covered in at least 95% of the cases or controls were then removed.
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6

NGS Panel for Autosomal Dominant Retinitis Pigmentosa

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Starting from 2012, a targeted NGS panel was introduced using a flexible protocol, consisting of singleplex PCR followed by NexteraXT library preparation and sequencing on a MiSeq instrument [8 (link)]. The CLC Genomics Workbench v.6 (Qiagen) was employed for read mapping against the hg19 human reference genome and variant calling. To date, our diagnostic panel consists of ten adRP genes (CRX, PRPF6, PRPF8, PRPF31, PRPH2, RDH12, RHO, RPE65, RP1, SNRNP200).
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7

Bacterial 16S rRNA gene sequencing

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DNA was extracted from bacterial cells using a Qiagen DNAeasy blood and tissue kit. DNA isolated from bacterial clones was PCR amplified using primers (Additional file 1: Table S2) that specifically target the bacterial 16S rRNA gene. Bacterial clones (n = 38) were taxonomically characterized using this procedure. PCR products were sequenced at the DNA analysis facility on Science Hill at Yale University. The 16S rRNA sequence data was compared to catalogued sequences using the Basic Local Alignment Search Tool (BLASTn) and CLC Genomics Workbench v.6 (Venlo, Netherlands).
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8

Genomic DNA Extraction and Sequencing of P. gingivalis

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Total DNA was purified from P. gingivalis using the Promega Wizard genomic DNA purification kit (Promega, Madison, WI). DNA amplification by PCR was performed using the high-fidelity ExTaq polymerase (TaKaRa Bio, Inc., Otsu, Shiga, Japan). Primers were synthesized by Sigma-Aldrich, Inc. (Sigma Life Sciences, The Woodlands, TX) or Integrated DNA Technologies (IDT); Coralville, IA. Primers used in this study are listed in Table 2 in the supplemental material. DNA sequencing was performed by SeqWright DNA Technology Services (Houston, TX). Sequence assembly and DNA and protein analysis were done with CLC Genomics Workbench, v6 (CLC bio, Cambridge, MA). The fimA upstream and downstream DNA sequences from strains 53977 and 49417 were submitted to GenBank under accession numbers KF770042 and KF770043, respectively.
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9

Chloroplast Genome Analysis of Eleusine Species

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Complete E. indica chloroplast genome (KU833246) were downloaded from NCBI. The other Eleusine species’ CDS datasets were aligned to the chloroplast genome using Blastn at the E-value threshold 10−5, word size 20, and minimum match size 90. E. coracana reads were mapped to the aligned Eleusine species’ CDSs separately. SNVs, MNVs, replacements, insertions, and deletions were called from each of the mappings in CLC Genomics Workbench v.6.5.2 (CLC Bio, Aarhus, Denmark).
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10

Comprehensive Genomic Variant Detection

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Variants are mainly classified into five different types: single nucleotide variants (SNVs), multiple nucleotide variants (MNVs), insertions, deletions, and replacements. SNVs are one base replaced by another base, most commonly referred to as a single nucleotide polymorphism (SNP). MNVs are two or more SNVs in succession. Insertions are events where one or more bases are inserted in the experimental data compared to the reference. Deletions are events where one or more bases are deleted from the experimental data compared to the reference. Replacements are more complex events where one or more bases have been replaced by one or more bases, where the identified allele has a length different from the reference.
Read mapping and detection of SNVs, MNVs, replacements, insertions, and deletions were conducted using the tools ‘map reads to reference’ and ‘probabilistic variant detection’ separately in CLC Genomics Workbench v.6.5.2 (CLC Bio, Aarhus, Denmark). The mapping parameters were set to ‘Mismatch cost = 3, Insertion cost = 3, Deletion cost = 3, Length fraction = 0.95, Similarity fraction = 0.95’. The variants calling parameters were set to ‘Minimum coverage = 30, Variant probability = 90’.
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