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Novaseq sp

Manufactured by Illumina
Sourced in United States, Belgium, Switzerland

The NovaSeq SP is a powerful next-generation sequencing (NGS) system produced by Illumina. It is designed to deliver high-throughput sequencing capabilities for a wide range of applications, including genomics research, clinical diagnostics, and personalized medicine. The NovaSeq SP system provides users with the ability to generate large volumes of high-quality sequencing data efficiently and cost-effectively.

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42 protocols using novaseq sp

1

Single-cell RNA-seq of APOE genotypes

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For samples from 96-week-old mice, sorted CD45+ cells from each genotype were washed, strained through a 40μm strainer (Flowmi), and resuspended in PBS containing 0.04% BSA at ~1000 cells/μL. Libraries were prepared using 10X Genomics 3’v3 chemistry per manufacturer’s instructions and sequenced on an Illumina NovaSeq SP. Six mice were pooled for the APOE3 library while four mice were pooled for the APOE4 library.
For samples from 10-week-old and 20-week-old mice, cells were also stained with 0.5μg of TotalSeq-C mouse hashing antibody (BioLegend) per genotype before cell sorting. Sorted CD45+ cells from each genotype were then pooled at equal cell numbers, washed, strained through a 40μm strainer (Flowmi), and resuspended in PBS containing 0.04% BSA at ~1500 cells/μL for superloading as previously described97 (link). Libraries were prepared using 10X Genomics 5’v2 chemistry with Feature Barcoding per manufacturer’s instructions and sequenced on an Illumina NovaSeq SP. Three mice were pooled together per genotype for each library.
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2

RNA-seq Analysis of Drosophila Histone Mutants

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In the first round, a total of five samples per genotype were sequenced (Oregon R, Set21, ash122/ash19011, NSDds46, ash122 NSDds46/ash19011 NSD ds46, ΔHisC; 12xH3K36R and ΔHisC; 12xH3K36K) on Illumina HiSeq2500 (Illumina Cambridge Ltd.) by Science for Life Laboratory, Stockholm, and 125-bp paired-end reads were obtained. In the second round, seven samples of ΔH3.3B; ΔH3.3A and an additional six Oregon R samples were sequenced at Science for Life Laboratory, Stockholm using Illumina NovaSeq SP (Illumina Cambridge Ltd.) with a paired-end read length of 150 bp. Reads from both rounds were mapped to the D. melanogaster genome version BDGP6 using STAR v2.5.3 (72 (link)) with default settings. Read counts were obtained with featureCounts v1.5.1 with default settings (73 (link)). Gene abundances were calculated using StringTie v1.3.3 (74 (link)). Replicate 3 of Set21 and replicate 5 of ΔHisC; 12xH3K36K did not pass the quality control in RSeQC (75 (link)) and were therefore excluded in the downstream analysis. DESeq2 v1.18 (76 (link)) was used for differential expression analysis using default parameters and normal log fold change shrinkage.
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3

Drosophila Transcriptome Profiling Pipeline

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In the first round, a total of five samples per genotype were sequenced (Oregon R, Set2 1 , ash1 22 /ash1 9011 , NSD ds46 , ash1 22 NSD ds46 /ash1 9011 NSD ds46 , ΔHisC; 12x H3K36R and ΔHisC; 12x H3K36K ) on Illumina HiSeq2500 (Illumina Cambridge Ltd.) by Science for Life Laboratory, Stockholm and 125 bp paired-end reads were obtained. In the second round, seven samples of ΔH3.3B; ΔH3.3A and an additional six Oregon R samples were sequenced at Science for Life Laboratory, Stockholm using Illumina NovaSeq SP (Illumina Cambridge Ltd.) with a paired-end read length of 150 bp. Reads from both rounds were mapped to the D. melanogaster genome version BDGP6 using STAR v2.5.3 (Dobin et al. 2013 (link)) with default settings. Read counts were obtained with featureCounts v1.5.1 with default settings (Liao et al. 2014 (link)). Gene abundances were calculated using StringTie v1.3.3 (Pertea et al. 2015) (link).
Replicate 3 of Set2 1 and replicate 5 of ΔHisC; 12x H3K36K did not pass the quality control in RSeQC (Wang et al. 2012 (link)) and were therefore excluded in the downstream analysis. DESeq2 v1.18 (Love MI et al. 2014) was used for differential expression analysis using default parameters and normal log fold change shrinkage.
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4

RNA-seq Analysis of Knockdown Transcriptomes

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RNA-sequencing was performed on 3 biological replicates of KD, DBD and DBD+. Total RNA were extracted using RNeasy Extraction Kit and submitted to the Nationwide Children’s Hospital Institute for Genomic Medicine for RNA quality measurement, library preparation, and sequencing. Briefly, cDNA libraries were prepared from total RNA with TruSeq Stranded mRNA Kit (Illumina 20020594) and sequenced on Illumina NovaSeq SP to generate 150-bp paired-end reads. We used in-house RNA-sequencing pipeline to process and analyze the data. Low-quality reads (q < 10) and adapter sequences were trimmed to align to hg19 genome using STAR (Dobin et al., 2013 (link)). After alignment, the reads were counted and differential analysis performed using DESeq2 (Love et al., 2014 (link)).
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5

Transcriptomic Analysis of EpdSCs

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EpdSCs were collected by FACS as described above directly into TRIzol LS (Invitrogen). RNA libraries were generated using SMARTer RNA kit for low-input RNA-seq. Libraries were sequenced on Illumina NovaSeq SP. Raw FASTQ files were trimmed of barcodes using Skewer (v.0.2.2) and transcript abundance quantified using Salmon (v.1.4.0) with a modified GENCODE transcript index (version GRCm38 release M24) to include TRE-Sox9. Gene level counts and transcripts per million (TPM) were calculated using the Tximport (v.1.12.3) package in R (v.3.6.1). For hair placode RNA-seq data, after generating the raw counts, differentially expressed (DEG) gene list was generated with DESeq2 (v.1.16.1).
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6

ATAC-seq Library Preparation for Mouse AMs

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ATAC-seq library preparation was performed on FACS-sorted mouse AMs (200,000 cells per sample) using the ATAC-seq kit from Active motif (#13150) according to the manufacturer’s protocol. The purified DNA was amplified for 10 cycles using indexed primers and size-selected using SPRI bead solution. A quality control (QC) was performed to verify the size distribution of the PCR-enriched library fragments. To this end, aliquots of the DNA libraries were analyzed on a TapeStation, and quantification of the libraries was done using the Qubit. The bar-corded amplicons from ATAC-Library preparation were sequenced in a NovaSeq SP (Illumina) under a 2 × 150 pair-ended format. Reads were quality filtered according to the standard Illumina pipeline, de-multiplexed, and fastq files were generated (GEO accession no. GSE231219).
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7

ATAC-seq and RNA-seq Data Acquisition and Analysis

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Data were collected utilizing the following open-source or commercially available software programs: BD FACSDiva (version 8.0.2), BioRad Image Lab (version 6.0.1, build 34), BioRad CFX Manager (version 3.1). ATAC-seq data was generated by Illumina Novaseq SP. RNA-seq was performed by Azenta Life Sciences (formerly Genewiz). Analyses and/or manuscript preparation were conducted using the Microsoft Office Suite, version 16.43 (including Microsoft Word, Microsoft Excel, and Microsoft Powerpoint), BD FlowJo (version 10.8.1), and open-source software, including tools available on Galaxy (http://usegalaxy.org): Bowtie2 (2.4.4), MACS2, Integrative Genomics Viewer (version 2.9.4), Morpheus (Broad Institute), VolcanoseR (https://huygens.science.uva.nl/VolcaNoseR/)75 (link), and ClustVis (https://bio.tools/clustvis). All statistical analyses were performed using the GraphPad Prism software (version 9.3.1). Data preparation for this manuscript did not require the use of custom code or software. Supplementary Fig. 16 was generated using BioRender (https://biorender.com/).
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8

Transcriptomic Analysis of Hematopoietic Stem Cells

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RNA was isolated from 50,000 to 80,000 sorted HSCs (Lineage-c-Kit+ CD150+ CD48 CD34) from the pools of 1-month infected mice and naive control (n = 10–12 per group) with RNeasy Kit (Qiagen, Cat#74004). RNA-seq library was generated using SMARTer Stranded Total RNA-Seq Kit v2 – Pico Input Mammalian (Takara Bio USA). The sequencing was performed using Illumina NovaSeq SP with a paired-end sequencing length of 10bp. We used STAR (https://github.com/alexdobin/STAR) to align reads against the hg38 genome, and FastQC, RSeQC, MultiQC, and FastQ Screen for the quality control and to check the results for the contamination. Finally, read were counted using featureCounts.
We filtered the count matrix using the filterByExpr() function from the R package edgeR. DESeq2 was used to perform differential expression analysis, and the false discovery rate (FDR) < 0.05 was considered statistically significant. Gene set enrichment analysis was done by sorting gene lists according to their increasing p value and running tmodCERNOtest() function from the tmod R package (Weiner third and Domaszewska).Panel plots with geneset enrichment were plotted with tmodPanelPlot() from tmod, other plots were plotted using ggplot2. Statistically significant results are listed in Tables S2 and S3. Both are related to Figure 5.
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9

ChIP-Seq Protocol for Ovary and OSCs

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ChIP was performed as previously described (Lee et al., 2006 (link)). In brief, 150 μl of ovaries were dissected into ice-cold PBS, crosslinked with 1.8% formaldehyde in PBS for 10 min at room temperature, quenched with Glycine, rinsed in PBS and flash frozen in liquid nitrogen after removing all PBS. Frozen ovaries were disrupted in PBS using a dounce homogenizer, centrifuged at low speed and the pellet was resuspended in lysis buffer. For ChIP from OSCs 5–10 million cells were crosslinked, quenched, and lysed. Sonication (Bioruptor) resulted in DNA fragment sizes of 200–800 bp. Immunoprecipitation with specific antibodies was done overnight at 4 °C in 350–700 μl total volume using 1/3 to 1/4 of chromatin per ChIP (antibodies are listed in Key Resource Table). Then, 40 μl Dynabeads (equal mixture of Protein G and A, Invitrogen) were added and incubated for 1 hr at 4°. After multiple washes, immuno-precipitated protein-DNA complexes were eluted with 1% SDS, treated with RNAse-A, decrosslinked overnight at 65 °C, and proteins were digested with proteinase K before clean-up using ChIP DNA Clean & Concentrator columns (Zymo Research). Barcoded libraries were prepared according to manufacturer’s instructions using the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB), and sequenced on a HiSeqV4, NextSeq550, or NovaSeqSP (Illumina).
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10

CRISPR Screen for Osteoclast Regulators

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RAW264.7 cells expressing Ctsk-T2A-R647 in the endogenous Ctsk locus and stably expressing Cas9-GFP were used to generate Dnmt3a KO cell lines. 150 million Dnmt3a KO cells were infected with the mouse Brie LentiGuide-Puro genome-wide CRISPR library (Doench et al., 2016 (link)) with 2 μg/ml polybrene (Sigma). The Brie library targets 19,674 genes with four guide RNAs (gRNAs) per gene. 24 h after infection, cells harboring the construct were selected for 2 d using 2 μg/ml puromycin (Sigma). After 3–5 d of puromycin withdrawal, cells were replated as single cells at a density of 4,000 cells/cm2 in the presence of sRANKL for 5 d. GFP+ cells with top 5% and bottom 5% in the APC channel were sorted (MA900; Sony). “APC high” represents the top 5% of Ctsk-R647–expressing cells, and “APC low” represents the bottom 5% of Ctsk-R647–expressing cells. DNA was purified from sorted cell pellets, and the guide RNA (gRNA) library was PCR amplified and then sequenced on either Illumina Nextseq 550 or Novaseq SP to obtain read counts for each gRNA. gRNAs were ranked based on fold change in read counts (bottom 5%/top 5%), and rank sum–based statistics were used to calculate statistical significance as previously described (Slabicki et al., 2020 (link)).
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