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Nextseq 500 high output 75 cycle kit

Manufactured by Illumina
Sourced in United States

The NextSeq 500 High Output 75 cycle kit is a sequencing reagent kit designed for use with the Illumina NextSeq 500 system. The kit provides the necessary reagents and consumables for 75-cycle sequencing runs on the NextSeq 500 platform, which is capable of generating high-throughput sequencing data.

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9 protocols using nextseq 500 high output 75 cycle kit

1

mRNA Sequencing Protocol for Differential Expression Analysis

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For mRNA sequencing (mRNA-seq), 5 ng high quality RNA (RIN ≥ 7) was used. cDNA was synthesized as previously described [52 (link)], converted to the NGS library using a Nextera XT Library Prep kit (Illumina, San Diego, CA, USA), and sequenced with a NextSeq 500 high-output 75 cycle kit (Illumina, San Diego, CA, USA). A quality check and adapter trimming of FASTQ files were performed as described for the sRNA-seq data. Clean reads were aligned to the GRCh38/hg38 human reference genome by HISAT2 [53 (link)]. Count matrices were created using the featureCounts tool according to the genome annotation and were provided to the DESeq2 package. The DE genes (DEGs) with p < 0.05 and |log2FC| ≥ 1 were considered for further analysis.
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2

Transcriptome analysis of TB cohorts

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Assessment of the transcriptome of TST and monocytes from patients in cohort 1 (active and latent TB) was performed by RNA-Seq. cDNA libraries were generated using the KAPA Hyperprep kit (Roche), and sequencing was performed on the Illumina Nextseq using the Nextseq 500 High Output 75 cycle kit (Illumina) according to manufacturers’ instructions, giving 15-20 million 41bp paired end- reads per sample. Mapping and generation of read counts per transcript were done using Kallisto (72 (link)). The R/Bioconductor package tximport was used to import the mapped counts data and summarize the transcript-level data into gene level data (73 (link)).
The TST transcriptome from active TB cohort 2 was derived directly from the data repository E-MTAB-3254 (ArrayExpress), and transcriptional profiling of individuals with cured TB was performed by microarray, as previously described (5 (link)).
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3

Transcriptome analysis of TB cohorts

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Assessment of the transcriptome of TST and monocytes from patients in cohort 1 (active and latent TB) was performed by RNA-Seq. cDNA libraries were generated using the KAPA Hyperprep kit (Roche), and sequencing was performed on the Illumina Nextseq using the Nextseq 500 High Output 75 cycle kit (Illumina) according to manufacturers’ instructions, giving 15-20 million 41bp paired end- reads per sample. Mapping and generation of read counts per transcript were done using Kallisto (72 (link)). The R/Bioconductor package tximport was used to import the mapped counts data and summarize the transcript-level data into gene level data (73 (link)).
The TST transcriptome from active TB cohort 2 was derived directly from the data repository E-MTAB-3254 (ArrayExpress), and transcriptional profiling of individuals with cured TB was performed by microarray, as previously described (5 (link)).
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4

Sequencing-Based Prenatal Aneuploidy Screening

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Following library preparation with KAPA HyperPrep for adapter and index ligation followed by Agencourt AMPureXP purification and amplification, libraries were pooled using an equimolar strategy. Libraries were sequenced using an Illumina NextSeq 500 High Output 75 cycle kit with a 37 bp paired‐end read configuration. On average, each cfDNA sample was sequenced to a depth of ≈20 million paired‐end reads, corresponding to an average genome depth of 0.5X. Reads were aligned to the human reference genome (hg19) with Bowtie (version 1.1.2), and run metrics are calculated with Picard (version 1.141). The placental‐derived fraction for each sample is calculated either by the percent of reads that align to the Y chromosome, or a custom bioinformatic algorithm based on the aggregate length distribution in sequencing reads for samples in which the Y chromosome is not present (ie, female fetuses).16 (link) The 2 methods are not quantitatively compared for every case, but the data are qualitatively reviewed. The fragmentation size‐based method is consistently revalidated as the assay we utilized is validated and utilized clinically as a prenatal screen for fetal aneuploidy.
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5

Fetal Fraction Estimation from cfDNA

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Library preparation is initiated within 24 hour post-extraction of cfDNA. Following library preparation with KAPA HyperPrep for adapter and index ligation followed by Agencourt AMPureXP purification and amplification, libraries were pooled using an equimolar strategy. Libraries were sequenced using an Illumina NextSeq 500 High Output 75 cycle kit with a 37bp paired-end read configuration. On average, each cfDNA sample was sequenced to a depth of approximately 20 million paired-end reads, corresponding to an average genome depth of 0.5X. Reads were aligned to the human reference genome (hg19) with Bowtie (version 1.1.2), and run metrics are calculated with Picard (version 1.141). The placental-derived fraction for each sample is calculated either by the percent of reads that align to the Y chromosome, or a custom bioinformatic algorithm based on the aggregate length distribution in sequencing reads for samples in which the Y chromosome is not present (i.e. female fetuses).27 (link) An indeterminate result was noted if the fetal fraction was <4%. Failures due to technical issues were purposely excluded from the indeterminate group as these were related to collection or processing errors.
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6

Fetal Fraction Analysis from cfDNA

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Following library preparation with KAPA HyperPrep for adapter and index ligation followed by Agencourt AMPureXP purification and amplification, libraries were pooled using an equimolar strategy. Libraries were sequenced using an Illumina NextSeq 500 High Output 75 cycle kit with a 37bp paired-end read configuration. On average, each cfDNA sample was sequenced to a depth of approximately 20 million paired-end reads, corresponding to an average genome depth of 0.5X. Reads were aligned to the human reference genome (hg19) with Bowtie (version 1.1.2), and run metrics were calculated with Picard (version 1.141). The placental-derived fraction for each sample was calculated either by the percent of reads that align to the Y chromosome, or a custom bioinformatic algorithm based on the aggregate length distribution in sequencing reads for samples in which the Y chromosome was not present (i.e. female fetuses).26 (link) An indeterminate result was defined as fetal fraction <4%. Failures due to technical issues, including samples with insufficient quantities of input DNA, were purposely excluded from the indeterminate group as these were related to collection or processing errors.
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7

DNA Library Prep and Sequencing

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Input DNA was tagmented and amplified using Illumina's Nextera XT DNA Library Prep. Libraries were quantified with Thermo's Qubit high-sensitivity DNA kit and run on the Agilent high sensitivity D1000 ScreenTape system for quality control. Sequencing was performed on NextSeq 500 (Illumina) using NextSeq 500 75-cycle High Output kit v2.5.
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8

RNA-Seq Analysis of Mouse Brain Tissue

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Brain tissue was homogenized using a GentleMACS dissociator and mRNA was isolated using the RNeasy mini kit (Qiagen GmbH, Hilden, Germany). RNA concentration (ratio 260/230 and 260/280 nm) was measured using a NanoDrop ND-1000 (Thermo Scientific, Waltham, MA, USA) and RNA integrity evaluated using an RNA screen tape on a Tapestation 2200 (Agilent, Santa Clara, California, USA). A bulk variation of MARSseq [16 (link)] was used to construct RNAseq libraries. Sequencing was performed using an Illumina Nextseq-500 75 cycle high output kit (Illumina, San Diego, California, USA; paired end sequencing). Raw reads were mapped to the Mus musculus genome (mm10) using STAR. Only reads which mapped uniquely to genes were considered for further analysis. Differentially-expressed genes (DEGs) were selected using a 1.5-fold change cutoff between two populations and adjusted p value for multiple gene testing of < 0.05 [17 (link)]. Pathway analysis was performed using Gene Analytics [14 (link)]. Ortholog conversion was done using HUGO Gene Nomenclature Committee.
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9

Bulk RNA-seq Analysis of Brain Tissue

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Brain tissue was homogenized using a GentleMACS dissociator and mRNA isolated using the RNeasy mini kit. RNA concentrations (260/230- and 260/280-nm ratios) were measured using a NanoDrop ND-1000 (Thermo Scientific, Waltham, MA, USA). RNA integrity was evaluated using an RNA screen tape on a Tapestation 2200 (Agilent, Santa Clara, CA, USA). A bulk variation of MARSseq [14 ] was used to construct RNAseq libraries. Sequencing was performed using an Illumina Nextseq-500 75 cycle high output kit (Illumina, San Diego, CA, USA; paired end sequencing). Raw reads were mapped to the Mus musculus genome (mm10) using hisat (version 0.1.6). Only reads with unique mapping were considered for further analysis. Differentially expressed genes (DEGs) were selected using a 2-fold change cutoff between two populations and adjusted p value for multiple gene testing of < 0.05 [15 ]. Principle component analysis (PCA) of all DEGs and heatmaps were generated using Partek Genomics Suite® software, version 7.0 (St. Louis, MO, USA), or RStudio (Integrated Development for R. RStudio, Inc., Boston, USA). The BioVenn tool [16 ] was used to identify common and exclusively expressed genes between groups. Pathway analysis was done using Metascape [17 ] or Gene Analytics [18 ].
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