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Genome analyzer system

Manufactured by Illumina
Sourced in China, United States

The Genome Analyzer system is a laboratory instrument designed for high-throughput DNA sequencing. It utilizes sequencing-by-synthesis technology to generate sequence data from DNA samples. The system is capable of producing large volumes of sequencing data in a rapid and efficient manner.

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9 protocols using genome analyzer system

1

Transcriptome Assembly of Horseshoe Crab Embryos

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The cDNA library was prepared using the TruSeqTM RNA Sample Preparation Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions. Poly(A)-containing mRNA was purified by Oligo(dT) magnetic beads from 10 μg total RNA sample and fragmented using divalent cations. The cleaved RNA fragments were used for the first strand cDNA synthesis using reverse transcriptase and random primers, followed by second strand cDNA synthesis using DNA polymerase I and RNase H. After second strain cDNA synthesis, fragments were treated with end repair, A-base tailing and adapter ligation consecutively. The sample was further treated by gel size fractionation and PCR amplification to create final cDNA library. The cDNA library was sequenced on the Illumina Cluster Station and Illumina Genome Analyzer system according to the manufacturer’s instructions. The Trinity method was used for de novo assembly of Illumina reads of T. tridentatus embryos [27 (link)]. Briefly, the trinity using de Bruijn graph algorithm was run on the paired-end sequences with the fixed default k-mer size of 25, minimum contig length of 200 and paired fragment length of 500.
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2

Hybrid Genome Assembly of Flavobacterial Endosymbiont

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The Illumina Genome Analyzer System generated 61,593,058 paired-end reads of 100 nt with an insert size of 455 nt. The 454 run generated 78,087 single-end reads with an average length of 190 nt.
Velvet (Zerbino and Birney 2008 (link)) was used to make a hybrid assembly with the Illumina and 454 reads generating 118 contigs with an N50 of 231,364. All contigs were compared with the nt database of NCBI using the BlastN algorithm and only two contigs had high-scoring alignments with sequences from Flavobacteria.
A second assembly was run using Phrap (Gordon et al. 1998 (link)) taking the velvet contigs as input, generating a single circular contig of 309,299 bp which corresponded to the chromosome sequence of the flavobacterial endosymbiont. Average coverage per nucleotide was 1571.4×. Protein-coding genes were predicted using Glimmer3, GeneMark.hmm, and Blast; tRNAs and a tmRNA were identified with tRNAscan-SE; and rRNAs were identified using the web version of WU-BLAST against the Rfam 11.0 sequence library.
Gene function annotation of the predicted protein-coding genes was based on results of BlastP searches against the RefSeq database and of hidden Markov model searches of the Pfam and TIGRFAM databases. The GenePRIMP pipeline (Pati et al. 2010 (link)) was used to search for gene call anomalies and the resulting report was used to perform manual curation of the genome.
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3

Comparative Transcriptome Analysis of Candida albicans Mutants

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Total RNA samples were extracted from the wild type CAI4, the gdt1/gdt1, the pmr1/pmr1, and the gdt1/gdt1 pmr1/pmr1 mutants grown to log phase in SD-URA at 30 °C. RNA integrity was evaluated using an Agilent 2100 Bioanalyzer (Agilent Technologies, USA). RNA-seq libraries were constructed using Illumina’s TruSeq RNA Sample Preparation Kit (Illumina Inc., USA). RNA sequencing, data analysis and sequence assembly were performed by Beijing BioMarker Technologies (Beijing, China). Preparation of the paired-end libraries and sequencing were performed following standard Illumina methods and protocols. The mRNA-seq library was sequenced on the Illumina Hiseq 2500 and Illumina Genome Analyzer system.
To obtain high-quality clean read data for de novo assembly, raw reads from mRNA sequencing were filtered by discarding the reads with adaptor contamination, masking low-quality reads with ambiguous ‘N’ bases and removing reads in which more than 10% bases had a Q-value < 20. Clean reads were assembled into full-length transcriptome from RNA-Seq data with the reference genome (http://www.candidagenome.org/).
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4

High-Throughput DNA Sequencing Workflow

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High-throughput sequencing was performed by using the Illumina Genome Analyzer System or HiSeq 2500. Demultiplex and base calling were performed with the CASAVA 1.8.2 software (Illumina).
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5

Small RNA Profiling in C. elegans

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Thirty-six nucleotide reads were generated from the small RNA libraries using the Illumina Genome Analyzer system. The captured small RNA sequences, after removal of linker and adaptor sequences, were aligned using BLAT against a reference list of known C. elegans mature microRNA sequences downloaded from miRBase (http://www.mirbase.org). The number of captured small RNA sequences that perfectly matched C. elegans annotated microRNAs and lin4_m/let7_m microRNAs was obtained for each library.
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6

Illumina RNA-seq Library Preparation

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The sequencing library of each RNA transcriptome sample was prepared with the TruSeq RNA Sample Preparation kit based on the protocol provided by the manufacturer (Illumina, San Diego, CA). The RNA samples from each group in equal amounts to generate one mixed sample per group. These mixed RNA samples were subsequently used to construct a complementary DNA (cDNA) library and perform Illumina deep sequencing. Briefly, a fragmentation buffer was mixed with magnetic beads and Oligo (dT) was used to isolate the messenger RNA (mRNA), and then the mRNA was fragmented into shorter fragments. The first strand of cDNA was then synthesized with random hexamer-primer using the mRNA fragments as templates. Double-stranded cDNAs were purified with the QiaQuick PCR extraction kit (Qiagen, Germany) and eluted with EB buffer for end repair and poly (A) addition. Finally, sequencing adapters were ligated to ends of the fragments, and the fragments were purified by agarose gel electrophoresis and enriched by PCR amplification to create a cDNA library. The sequencing was conducted in the UNL Genomic Research Core facility by an Illumina Solexa, and the Genome Analyzer System.
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7

Metagenomic DNA Extraction and Sequencing from Brine Samples

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Total genomic DNA was extracted from brine samples using the E.Z.N.A.® Stool DNA Kit (D4015-02, Omega, Inc., United States) according to the manufacturer’s instructions. The metagenomic DNA libraries were generated with 2-μg genome DNA by applying the TruSeq™ DNA Sample Prep Kit (Illumina, San Diego, CA, United States). The average insert size is 350 bp. The quality of all libraries was assessed using an Agilent Bioanalyzer in combination with a DNA LabChip 1000 kit. Sequencing was conducted at LC-BIO TECHNOLOGIES CO., LTD. (Hangzhou, China) with an Illumina Genome Analyzer system pursuant to the manufacturer’s protocol. The sequencing data were submitted to NCBI Sequence Read Archive (SRA1) with accession number PRJNA780248.
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8

Illumina DGE Library Preparation

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The main reagents and supplies were Illumina Gene Expression Sample Prep Kits and Solexa Sequencing Chips (flowcells), and the main instruments were an Illumina Cluster Station and Illumina Genome Analyzer System. All protocols for preparation of DGE libraries were according to the manufacturer's instructions and Gao et al.12 (link).
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9

Comprehensive Gastric Cancer Mutation Analysis

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We used data from TCGA STAD somatic mutation (curated by the Broad Institute, Cambridge, MA) database (version 2016-04-25), of the UCSC XENA group. According to the data description of UCSC XENA, sequencing data were generated on an Illumina (San Diego, CA, USA) Genome Analyzer system. Calls were generated at the Broad Institute Genome Sequencing Center, using the MuTect method [6] . This specific mutation dataset holds information on mutations for 289 gastric cancer (GC) patients. Gene expression data was obtained using the TCGA STAD gene expression dataset, as determined by RNA-Seq of the UCSC Cancer Genomic Browser (CGB) group. Patients' gene expression data was matched to that of the mutation data. According to the data manipulation of UCSC CGB, gene expression levels were equal to log2 transformation of RPKM values, with level 3 data downloaded from the TCGA data coordinating center. Clinical information was downloaded from the same web page as the gene expression dataset. Secondary structure data for the TP53 protein was obtained from DSSP for TP53 model 3Q01, deposited in the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB-PDB) [7] .
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