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Hiseq 6000

Manufactured by Illumina
Sourced in United States, China

The HiSeq 6000 is a high-throughput sequencing system designed for large-scale genomic projects. It utilizes Illumina's proprietary sequencing-by-synthesis technology to generate high-quality sequencing data. The HiSeq 6000 is capable of producing up to 6 billion reads per run, making it a powerful tool for researchers and organizations working on large-scale genomic analysis projects.

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55 protocols using hiseq 6000

1

RNA-Seq Analysis of Plant Stalk Transcriptomes

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The stalk samples were sent to Wuhan Metware Biotechnology Co., Ltd. (Wuhan, China) for RNA isolation, cDNA library construction, and RNA-Seq. In brief, total RNA was isolated using Trizol reagent (Invitrogen, Carlsbad, CA, United States). Then, the RNA quantity and quality were checked using NanoDrop 1000 (NanoDrop Technologies Inc, Wilmington, DE, United States) and on 1% agarose gels, respectively. The cDNA libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, United States) following the manufacturer’s recommendations and then sequenced on the Illumina HiSeq 6000 using the paired-end technology.
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2

Comprehensive Transcriptome Analysis of RNA-seq

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RNA isolation was carried out following a method described in our previous work [58 (link)], and RNA-seq was carried out using an Illumina HiSeq 6000 system (Illumina, San Diego, CA, USA) at Novogene Biotech (Beijing, China). The sequenced reads (NCBI SRA accession number: PRJNA905488) were filtered by the removal of low-quality reads for subsequent analysis. Transcriptome assembly sequences were annotated in seven databases, including NR, NT, KO, Swiss-Prot, Pfam, KOG, and GO. Differentially expressed genes (DEGs) were identified at a cutoff of |Log2FC)| > 1 (false discovery rate and adjusted p < 0.05). Ten DEGs with different putative functions were selected to confirm the RNA-Seq results by performing qRT-PCR following our previous work [58 (link)]. The employed primers are summarized in Table S6, and the correlation between RNA-seq and qRT-PCR data is presented in Figure S6.
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3

Ancient DNA Sequencing Protocol

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All DNA samples were extracted and processed in a dedicated ancient DNA facility at the University of Kiel following the guidelines on contamination control in ancient DNA [57 (link)–59 (link)], according to a previously published protocol for the non-UGD treated samples [60 (link)]. Shotgun sequencing was performed on the Illumina HiSeq 6000 (2 × 100) platform of the Institute of Clinical Molecular Biology in Kiel.
Adapter sequences were removed and paired-end reads were merged with ClipAndMerge v1.7.7. [61 (link)]. Shotgun sequence data was mapped to the human genome (build hg19) using BWA v0.7.12 [62 (link)] with a reduced mapping stringency parameter ‘-n 0.01’ to account for mismatches in aDNA. Duplicated reads were removed with DeDup v0.12.2 [61 (link)].
To confirm the ancient origin of the sequences, terminal damage of the reads (C to T substitutions) was assessed with DamageProfiler [63 (link)]. After the validation, the first two positions from the 5′ and 3′-ends of the reads were trimmed. Furthermore, X-chromosome and mitochondrial DNA contamination were assessed with ANGSD and Schmutzi, respectively [64 (link),65 (link)].
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4

RNA Isolation and RNA-seq Library Preparation

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The total liver RNA of each group was extracted using TRIzol Reagent according to protocols (Takara, Dalian, China). In each group, nine liver tissues were selected to conduct the high-throughput sequence, wherein three fish in each group were randomly mixed and three biological replicates were finally applied for RNA-seq. After the qualified three micrograms of total RNA from each sample, ployA by magnetic beads with Oligo (dT) can be used to isolate mRNA from total RNA. The mRNA could be randomly fractured by fragmentation buffer, and small fragments of about 300 bp could be separated by magnetic bead screening. RNA fragments were converted to cDNA using random primers, followed by second-strand cDNA synthesis and end repair. End Repair Mix was added to fill the sticky end of the double-stranded cDNA into the flat end, and then base A was added to the 3′ end to connect the Y-shaped joint. Adaptor-tagged cDNA fragments were enriched using the manufacturer’s cocktail and 15-cycle PCR. The target bands were recovered from 2% agarose gel and PCR amplification to obtain the final sequencing libraries. Illumina Hiseq6000 was used for sequencing after the library was qualified by quality inspection. Sequencing reads are paired-end 2 × 150 bp (PE150).
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5

RNA-seq Analysis Pipeline for Differential Gene Expression

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Both RNA-seq and library construction were carried out by Wuhan Metware Biotechnology Co., Ltd (Wuhan, China). The mRNA was purified using a TruSeq RNA Sample Prep Kit (Illumina, USA). Sequencing of the mRNA was conducted using an Illumina HiSeq 6000 sequencer. Using Trimmomatic (v0.39) [88 (link)] and FastQC (v0.11.9) [89 (link)] to filter and trim raw RNA readings, clean reads were produced. HISAT2 was used to draft high-quality reads to the draft reference genome. FeatureCounts (v1.6.3) [90 (link)] was used to quantify gene expression (transcripts per million) (Supplementary Data Table S24). The DESeq2 package [91 (link)] was used to normalize gene expression levels (BaseMean), and an adjusted P-value (Padj) < .05 was used as the threshold to identify DEGs for each comparison group.
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6

Transcriptome Analysis of Plant Samples

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Total RNA was extracted using the RNAprep Pure Plant Kit (Tiangen, China) according to the manufacturer’s instructions. RNA samples that met the quality requirements were used to construct a sequencing library and then sequenced on the Illumina HiSeq 6000 platform. Low-quality reads and reads containing adapters and poly-N were removed using fastp (version 0.19.3; Chen et al., 2018 (link)), and clean reads were de novo assembled using Trinity (version 2.11.0; Grabherr et al., 2011 (link)) to obtain high-quality transcript sequences. Fragments per kilobase of exon per million fragments mapped (FPKM) was used to estimate the gene expression levels. Subsequently, differential expression analysis between two groups was performed using the DESeq2 software (version 1.22.1; Love et al., 2014 (link)). Genes satisfying |Log2 (fold change) |≥1, false discovery rate (FDR), and adjusted p < 0.05 were defined as differentially expressed genes (DEGs). Then, Gene Ontology (GO), KEGG enrichment analysis and transcription factors (TFs) analysis were performed.
All raw sequencing data were submitted to the Genome Sequence Archive (GSA) database under the BioProject accession number CRA007535 at the BIG Sub website (https://ngdc.cncb.ac.cn/gsub/).
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7

Transcriptomic Analysis of Leaf RNA Responses

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Leaf RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), and RNA sequencing was performed in Novogene (Tianjin, China). A total of 18 libraries (2 cultivars × 3 treatments × 3 biological replicates) were sequenced on the Illumina platform (HiSeq 6000), which produced paired-end reads of 150-nucleotide. The adapter sequences and low-quality bases were removed, and the clean data was de novo assembled using the Trinity platform (Trinity) [50 (link)].
The Expectation Maximization (RSEM) was used to map the transcripts to reference unigenes via RNA-seq. The read count numbers were calculated and translated to FPKM (fragments per kilobase of transcript per million mapped reads) gene values [51 (link)]. DESeq was used for analysing differentially expressed genes (DEGs) [52 (link)]. We used FDR ≤ 0.05 and |log2Fold > Change| ≥ 1 as threshold for screening DEGs. All identified DEGs were mapped to gene ontology (GO) and Tokyo Encyclopedia of Genes and Genomes (KEGG) databases. The significantly enriched biochemical pathways were obtained using KOBAS with corrected P-value ≤0.05.
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8

RNA-seq Analysis of Zebrafish Embryos

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RNA-seq analysis was performed by LC-Bio Technology Co., Ltd4 (link). Total RNA was extracted from sorted EGFP+ cells in Tg(fli1a: EGFP) zebrafish embryos by using TRIzol Reagent following the manufacturer’s instructions. cDNA libraries were constructed by SuperScript™ II Reverse Transcriptase (Invitrogen; 18064014), and 150-bp single-end reads were generated on an Illumina HiSeq 6000 platform following the vendor’s recommended protocol. After removing the low-quality bases and undetermined bases by Cutadapt software (version: cutadapt-1.9), we used HISAT2 software (version: hisat2-2.0.4) to map reads to the genome (Ensembl Danio reio v96). The mapped reads of each sample were assembled using StringTie (version: stringtie-1.3.4d.) with default parameters. Then, all transcriptomes from all samples were merged to reconstruct a comprehensive transcriptome by using gffcompare software (version: gffcompare-0.9.8.). After the final transcriptome was generated, StringTie and ballgown were used to estimate the expression levels of all transcripts and perform expression level for mRNAs by calculating FPKM. The differentially expressed mRNAs were selected with fold change >2 or fold change <0.5 and p-value < 0.05 by R package edgeR (http://www.r-project.org/) or DESeq2, and then analysis GO enrichment and KEGG enrichment to the differentially expressed mRNAs.
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9

Transcriptome Analysis via QuantSeq 3' RNA-Seq

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For transcriptome analysis, cells were lysed using TRizol reagent (Thermo Fisher Scientific), and total RNA was isolated from cells after performing the chloroform phase separation, followed by purification with MagMax Total RNA Kit (Thermo Fisher Scientific). According to manufacturer instructions, RNA quality was assessed with a 2100 Bioanalyzer system (Agilent Technologies, Santa Clara, CA, USA). Library preparation was performed with the 3´ QuantSeq kit, and 100 bp single-end reads were generated utilizing the Illumina Hiseq 6000. Library preparation and sequencing were performed at the Iowa State University DNA Facility (Ames, IA, USA).
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10

Sample Preparation for RNA-seq of Fungus

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The sample preparation for RNA sequencing is referenced by the previous paper [27 ,28 (link)]. The mycelia of Guy11 were cultivated into liquid CM for 2 days and transferred into fresh liquid CM, adding 10 μg/mL 9-phenanthrol for 24 h for RNA extraction. Total RNA was extracted from the tissue using TRIzol® Reagent, and genomic DNA was removed using DNase I (Takara, Tokyo, Japan). The RNA samples were sent to Shanghai Majorbio Technology Co., Ltd. for RNA sequencing based on Illumina HiSeq 6000 platform. The raw data have been deposited on NCBI (Project ID: PRJNA797246).
For read mapping, the clean reads were separately aligned to the reference genome (https://www.ncbi.nlm.nih.gov/assembly/GCF_000002495.2 (accessed on 14 October 2011)) with orientation mode using HISAT2 (http://ccb.jhu.edu/software/hisat2/index.shtml (accessed on 24 July 2020)) software. The mapped reads were assembled by StringTie (https://ccb.jhu.edu/software/stringtie/index.shtml?t=example (accessed on 21 April 2020)).
To identify DEGs (differential expression genes) between two different samples, differential expression analysis was performed using DESeq2 with p-adjust < 0.05 and |log2FC| ≥ 1. GO and KEGG were performed by DAVID (https://david.ncifcrf.gov/tools.jsp (accessed on 13 November 2020)).
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