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Clc main workbench v7

Manufactured by Qiagen
Sourced in Denmark, United Kingdom

CLC Main Workbench v7 is a bioinformatics software suite developed by Qiagen. It provides tools for analyzing and visualizing biological sequence data, including DNA, RNA, and protein sequences. The software supports a range of functionalities, such as sequence alignment, phylogenetic analysis, and genome assembly, among others.

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13 protocols using clc main workbench v7

1

Sequence Assembly and SNP Identification

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Sequence assembly was performed in CLC Main Workbench v7.9.1 (Qiagen, UK), and SNPs were identified and called based on the respective 3D7 reference sequences. Nucleotide positions which displayed a peak within a peak in the sequence chromatograms were noted as “mixed.” Consensus sequences were extracted from the sequence assemblies using CLC Genomics Workbench v9.5.3 and used to construct multiple-sequence alignments in Clustal Omega v1.2.1 (60 (link)). SNP frequencies were calculated per gene per time point, and singletons were confirmed by an additional round of PCR and sequencing.
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2

Sequencing and Analysis of Pfcrt Gene

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The MID tagged Pfcrt (PF3D7_0709000) primers failed to generate nested PCR amplicons; therefore, Pfcrt was amplified and sequenced using previously described primers and PCR conditions (31 (link), 32 (link)) on an ABI3730xl system (Applied Biosystems). The Pfcrt sequence assembly was performed in CLC Main Workbench v7.9.1 (Qiagen, UK), and SNPs were identified and called based on the 3D7 reference sequences. Nucleotide positions that displayed a peak within a peak in the sequence chromatograms were noted as “mixed.” Consensus sequences were extracted from the sequence assemblies using CLC Genomics Workbench v9.5.3 and used to construct multiple-sequence alignments in Clustal Omega v1.2.1 (67 (link), 68 (link)) to identify SNPs.
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3

16S rRNA Gene Sequencing Protocol

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The 16S rRNA gene was amplified using primers SSU-bact-27F (5′-AGAGTTTGATCMTGGCTGAG-3′) and SSU-bact-519R (5′-GWATTACCGCGGCKGCTG-3′) [55 (link)]. The resulting PCR products were sequenced on the Genetic Analyzer 3500 (Applied Biosystems™, Foster City, CA, USA). Obtained sequences were extracted using Sequencing Analysis v5.4 software (Applied Biosystems), assembled using CLC Main Workbench v7.0.2 (CLC-bio, Aarhus, Denmark), and blasted against the NCBI 16S rRNA database.
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4

Bacterial Identification by 16S rRNA Sequencing

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Two of the isolates (R4 and R5) were untypable by PFGE using both primary and secondary restriction enzymes, XbaI and BlnI/AvrII, respectively. Their identity was further confirmed by 16S rRNA sequencing.
The 16S rRNA gene was amplified using primers SSU-bact-27F (5 -AGAGTTTGATCMTGGCTGAG-3 ) and SSU-bact-519R (5 -GWATTACCGCGGCKGCTG-3 ) [28]. Amplification was performed in a total volume of 20 μl containing 2-mM deoxynucleoside triphosphates, 10X Taq buffer, 25 mM MgCl 2, 20 μM of each primer and 5 U/μl of HotStart AmpliTaq Gold DNA polymerase. The thermal cycling conditions were the following: 95 for 12 min, followed by 30 cycles of 94 • C for 30 s, 53 • C for 30 s and 72 • C for 1 min, and a final extension of 72 • C for 10 min. The resulting PCR products were sequenced on the Genetic Analyzer 3500 (Applied Biosystems TM , CA, USA). Obtained sequences were extracted using Sequencing Analysis v5.4 software (Applied Biosystems), assembled using CLC Main Workbench v7.0.2 (CLC-bio, Aarhus, Denmark) and blasted against the NCBI 16S rRNA database.
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5

Centipede Venom Protein GC Analysis

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We used CLC Main WorkBench v7 (Qiagen, Aarhus, Denmark) to calculate GC frequencies of all nucleotide sequences encoding centipede venom proteins and peptides published by Jenner et al.23 (link). Descriptive statistics were calculated with GraphPad Prism v8.4.1 (GraphPad Software, La Jolla California USA, www.graphpad.com), and are available as Supplementary Data 3.
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6

Bushmeat Species Identification by DNA Barcoding

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The sequences were examined using CLC Main Work Bench v.7 (www.qiagenbioinformatics.com) to detect base calling conflicts. The forward and reverse sequences were aligned to generate consensus sequences, then compared to available sequences in the NCBI database by using BLAST tools. A cutoff point of 95% of sequence similarity [26 (link)–28 ] was used to identify species for each bushmeat sample, however, the top hit (in most cases > 98% similarity) was recorded as the species of origin.
All statistical analyses were performed in R v3.4.4 [29 ]. The kappa2 function of the IRR package was used to determine concordance between seller-reported and laboratory-confirmed results[30 ]. A Chi-squared test was performed to test whether the match/mismatch percentages were similar between different reported species using the prop.test function in R. The prop.test function was also used to perform pairwise analysis of the individual species (seller-reported versus laboratory-confirmed) [16 (link)]. One-sample t-test power analysis was performed to calculate the sample size with the following assumptions: power = 0.95, Significance = 0.05, an Effect size of 0.25.
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7

Phylogenetic Analysis of Representative Burkholderia Genomes

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Representative genomes from individual Burkholderia, Paraburkholderia, Caballeronia and Robbsia species were downloaded from the NCBI RefSeq database (accessed Feb. 2017). In addition, genomes from strains LMG 28154T, TSV85 and TSV86 were added to the database. Nucleotide and amino acid sequences of annotated CDS were extracted and searched against a database of 40 nearly universal, single copy gene markers using the FetchMG program with the –v flag to retain only the best hits (Sunagawa et al., 2013 (link)). Twenty-three COGs present in all genomes were extracted, aligned with Clustal Omega and the resulting alignments were concatenated using the AlignIO utility of Biopython (Cock et al., 2009 (link)). The concatenated alignment was trimmed with TrimAl (Capella-Gutierrez et al., 2009 (link)) to remove columns with >10% gaps and poorly aligned sections of the alignment were removed manually in CLC Main Workbench v.7.7 (Qiagen, Aarhus, Denmark). A concatenated nucleotide alignment of 15092 bp was used to build a phylogenetic tree with FastTree, using the GTR CAT model (Price et al., 2010 (link)). The tree was edited in iTOL (Letunic and Bork, 2016 (link)).
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8

Viral dsRNA Extraction and Sequencing Protocol

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CnFGV1 genomic dsRNA was extracted using the Double-RNA Viral dsRNA Extraction Mini Kit (iNtRON Biotechnologies, Seongnam-Si, Korea) and electrophoresed on a 1.5% (w/v) agarose gel. Potentially present fungal DNA and ribosomal RNA were eliminated treating the extracts with both enzymes dsDNase and S1 Nuclease (Thermo Fisher Scientific, Waltham, MA, USA). A subset of three dsRNA extracts (M10535, M10544, and M10545) was subjected to RNA-seq using the TruSeq RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced on an Illumina MiSeq v2 (Microsynth AG, Balgach, Switzerland). De novo assembly of reads was carried out using Trinity v2.6.5 [39 (link)]. The obtained contigs were aligned using CLC Main Workbench v7 (CLC bio, Qiagen Digital Insights, Hilden, Germany) and subjected to searches using the ORFfinder resource of NCBI (https://www.ncbi.nlm.nih.gov; accessed on 22 July 2021) and the BLASTp suite of the UniProt portal (v 2.9.0+; https://www.uniprot.org; accessed on 22 July 2021).
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9

Amplification and Sequencing of Putative Regulatory Regions

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Amplification of genomic DNA fragments was performed with standard PCR and specific primers (Table 4) in samples of 3 bulls from each group. Putative regulatory regions of the gene (700 bp 5' of the transcription start and 1,000 bp 3' of the stop codon containing the 3'‐untranslated region) were included in screening for single nucleotide polymorphisms (SNPs). After purification of the amplicons with the High Pure PCR Product Purification Kit (Roche Diagnostics, Mannheim, Germany), the PCR products were subjected to cycle sequencing and analyzed on an ABI PRISM 310 Genetic Analyzer (Applied Biosystems, Darmstadt, Germany). The PCR primers were also used for DNA sequencing. Sequences were compared using CLC Main Workbench (v. 7.7, CLCbio, Aarhus, Denmark).
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10

Phylogenetic Analysis of Genetic Sequences

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Sequencing was carried out in an ABI PRISM 310 Genetic Analyzer (Applied Biosystems, CA, United States) and the resultant chromatograms analysed and aligned using CLC Main Workbench v7.7 (CLCBio, Aarhus, Denmark) and by MEGA software v.6.06 [20 (link)]. MEGABLAST, BLASTn and BLASTp algorithms were used for nucleotide and putative protein similarity searches through GenBank (http://blast.ncbi.nlm.nih.gov/Blast.cgi) [21 (link)]. Nucleotide and amino acid sequence alignments were generated in CLUSTAL W, implemented in the BioEdit software [22 (link)]. Phylogenetic and molecular evolutionary analyses were performed with the maximum likelihood method using Tamura-Nei and Jones-Taylor-Thornton algorithms for nucleotide and amino acid sequences, respectively. These were determined as optimal algorithms using Find best DNA/protein- substitution model tools implemented in MEGA v.6.06.
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