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12 protocols using miniseq high output reagent kit

1

Illumina TruSight Tumor 15 Profiling

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Library preparation was conducted using the Illumina TruSight Tumor 15 covering 15 genes, which are frequently mutated in solid tumors. Subsequent sequencing of pooled libraries was performed in several runs on the MiniSeq Illumina platform using MiniSeq High Output Reagent Kit (300-cycles). Data analysis was conducted using on-instrument Local Run Manager (LRM) Software with TruSight Tumor 15 analysis module. Passed-filter reads were aligned to human reference genome UCSC hg19 using banded Smith Waterman algorithm. Variants were called using Somatic Variant Caller developed by Illumina. All vcf-datasets were annotated using the Illumina VariantStudio 3.0 Software. Across all samples, several hotspot codons were manually evaluated using the Integrative Genomics Viewer (IGV) for potential low-abundance variants (0.1> VAF <2.0%). Annotated plasma variants had to have allele frequencies above a background threshold of the mean of our control samples (three different non-PDAC cfDNA samples).
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2

Illumina Sequencing of Nextera DNA Libraries

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DNA libraries were prepared with Nextera DNA Flex Library Prep and Nextera DNA CD Indexes (Illumina, San Diego, CA, United States). All libraries were sequenced on an Illumina Miniseq (Illumina, San Diego, CA, United States) using Miniseq High Output Reagent Kit (300-cycles; Illumina, San Diego, CA, United States). The paired-end raw reads were imported into SeqSphere + software (Version 7.1.0, Ridom GmbH, Münster, Germany). Two independently prepared and sequenced samples were combined and quality checked. SeqSpere + uses the SKESA algorithm to assemble the raw reads and several output parameters were analysed to assure high quality sequences. The final assembly statics revealed a contig count of 130, N50 of 63.157, an assembled base count of 2.846.348 bases (2.8 Mbases), and an average genome coverage of 127. The cgMLST percentage of good targets was 98.4 and there was no evidence of contamination.
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3

Whole Genome Sequencing of Evolved E. coli Strains

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gDNA was isolated from the chosen evolved clones and from the ancestor strain. For each sample, 0.2 ng of gDNA was used to prepare DNA libraries using Illumina Nextera XT kit according to the kit’s instructions. Quality of DNA libraries was assessed using BioAnalyzer/Agilent High Sensitivity DNA Kit. Sequencing was performed using a MiniSeq High Output Reagent Kit, 150 or 300-cycles (Illumina, Cat# FC-420–1002, FC-420–1003). An average of 20× coverage per genome was achieved. Reads were passed through quality-based trimming using quality score cutoff of 30 in Trimmomatic (Bolger et al., 2014 (link)). Next, reverse and forward reads were merged into a single fastq file. We used the BreSeq tool (Barrick et al., 2014 (link)) to align the reads to the reference genome (NCBI accession: CP009273) and identify the mutations and genomic rearrangements. We used the gdtools in BreSeq to subtract mutations in the ancestral and control evolved strains from the drug evolved strains. Mutations identified in each evolved population were processed manually into csv spreadsheets and mapped to E. coli genomic coordinates for visualization using the Circa software (OMGenomics).
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4

RNA-seq Analysis of Transcriptome Profiles

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RNA-seq was performed as previously described29 (link). Sequencing libraries were prepared using the QuantSeq 30 mRNA-seq LibraryPrep Kit FWD for Illumina (Lexogen, Inc.). After removal of the RNA template, a second strand was synthesized using random primers. The double-stranded cDNA library was purified using magnetic beads after washing, and the library was amplified by PCR using primers containing adapters and i7 index sequences. Libraries were purified with magnetic beads, quantified using an Affluorometer (Qubit 4, Thermo Fisher Scientific), and pooled to equimolar concentrations. Sequencing was performed on a Mini Seq system (Illumina, San Diego, CA, USA) with 75 cycles using the Mini Seq High Output Reagent Kit. After sequencing, sequence quality was examined using FastQC.
Gene expression difference analysis and pathway analysis were then performed by iDEP. Gene expression difference analysis was performed using DEseq2 [false discovery rate (FDR) cutoff: 0.1, minimum fold change: 2]. Pathway analysis was performed on the GO Biological Process gene set using Generally Applicable Gene Set Enrichment for pathway analysis (GAGE; FDR cutoff:0.10).
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5

Small RNA Library Preparation Protocol

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10 μg of total RNAs with RIN > 8 was used to generate small RNA libraries. The library preparation was performed as essentially described in55 (link), except that a 5’ polyphosphatase (lucigen RP8092H) treatment was performed to be able to clone tri-phosphate small RNAs, and that the PAGE gel extraction after each ligation was substitute with purification by 1.8 volumes of Agencourt RNAClean XP Beads (Beckman Coulter, NC0068576) and 3 volumes of isopropanol. The multiplexed amplified libraries were further purified using PippinPrep DNA size selection with 3% gel cassettes and the following parameters for the selection: BP start (115) and the BP end (165). The purified libraries were quantified using Qubit Fluorometer High Sensitivity dsDNA assay kit (ThermoFisher, Q32851) and sequenced either on NextSeq-500 Illumina platform using the NextSeq 500/550 High Output v2 kit 75 cycles (FC-404-2005) or Illumina MiniSeq platform using MiniSeq High Output Reagent Kit 75-cycles (FC-420-1001).
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6

Small RNA Library Preparation Protocol

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10 μg of total RNAs with RIN > 8 was used to generate small RNA libraries. The library preparation was performed as essentially described in55 (link), except that a 5’ polyphosphatase (lucigen RP8092H) treatment was performed to be able to clone tri-phosphate small RNAs, and that the PAGE gel extraction after each ligation was substitute with purification by 1.8 volumes of Agencourt RNAClean XP Beads (Beckman Coulter, NC0068576) and 3 volumes of isopropanol. The multiplexed amplified libraries were further purified using PippinPrep DNA size selection with 3% gel cassettes and the following parameters for the selection: BP start (115) and the BP end (165). The purified libraries were quantified using Qubit Fluorometer High Sensitivity dsDNA assay kit (ThermoFisher, Q32851) and sequenced either on NextSeq-500 Illumina platform using the NextSeq 500/550 High Output v2 kit 75 cycles (FC-404-2005) or Illumina MiniSeq platform using MiniSeq High Output Reagent Kit 75-cycles (FC-420-1001).
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7

Detecting Favipiravir-resistant Mutations in Candid #1

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RNA was extracted from the supernatant of cells infected with Candid #1 (P2, P4, P6, P8, and P10) using the QIAamp Viral RNA Mini Kit (Qiagen), according to the manufacturer’s instructions. The regions including Favipiravir-resistant mutations in the L and S segment were amplified by RT-PCR as described above. After purification using agarose gel electrophoresis, libraries of PCR products were prepared with the NEBNext Ultra II FS DNA Library Prep Kit (New England Biolabs, Ipswich, MA, USA). Sequence analysis was performed using the MiniSeq instrument (Illumina, San Diego, CA, USA) with the MiniSeq High Output Reagent Kit (Illumina). The obtained reads were trimmed and mapped to the reference JUNV Candid #1 sequence using the CLC Genomics Workbench software (Qiagen). The proportion of mutations at each time point was calculated using the number of mapped reads.
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8

Whole Genome Sequencing with Nextera

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Sequencing Library was prepared using Nextera DNA Library Prep Kit (Illumina) with 100 ng of unbranched purified DNA as template according to manufacturer's protocol. Single-end sequencing of 1 nM library was performed on an Illumina Mini-Seq instrument using MiniSeq High Output Reagent Kit (75 cycles). Sequencing reads were trimmed with TrimGalore! (version 0.4.3.1) (https://github.com/FelixKrueger/TrimGalore) using default parameters to trim Illumina adapter sequences, and then aligned to the hg38 human reference using bowtie2 (version 2.3.4) (16 (link)). Following alignment, reads with mapping quality (MAPQ) less than 30 were filtered with SAMtools (version 1.2) (17 (link)). Finally, genomic coverage of reads was calculated using BEDTools (version 2.25.0) genomecov. Variants were called with FreeBayes and filtered as described above for nanopore sequencing.
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9

Targeted Sequencing for Myeloid Mutations

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Targeted sequencing was performed using AmpliSeq for Illumina Myeloid Panel (Illumina, San Diego, CA, USA) and a custom-designed panel to detect mutations in 68 genes and fusions of 29 driver genes (S1 Table). As a template, 10 ng DNA (for mutations) or cDNA synthesized from 10 ng RNA (for fusions) was used to amplify the target genes. AmpliSeq Library Plus for Illumina (Illumina) was used to generate libraries. The size of the fragment libraries was determined using the 2100 Bioanalyzer. The libraries were analyzed using the MiniSeq High Output Reagent Kit (300 -cycles) with the MiniSeq (Illumina) platform in accordance with the manufacturer’s instructions.
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10

Amplification and Sequencing of sgRNAs

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From each sorted population, as well as ancestor sample, genomic DNA was extract using PureLink genomic DNA mini kit and used as templates for PCR to amplify specifically the sgRNAs in the population. PCR reaction was conducted using 2X KAPA HiFi HotStart ReadyMix, 10 µM of each primer and 20 ng of genomic DNA extracted from the samples in a 50 µl total volume reaction, for 20 cycles, Tm = 58°C. We used shifted primers to increase library complexity. PCR products were purified with SPRI-beads using left-side size selection protocol in which the PCR product and beads were mixed at 1:1.5 ratio. The barcoding PCR and final PCR clean-up was done as described for the genomic tRNA library preparation. Samples were pooled and sequenced using a 75 bp single read output run using MiniSeq high output reagent kit (Ilumina; FC-420–1001).
Reads were trimmed using Cutadapt and then clustered into unique sequences using vsearch (Rognes et al., 2016 (link)). Each unique read was then aligned to the matched sgRNA sequence, allowing up to two mismatches. Finally, we stored all sgRNA types and their frequency in each sample.
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