title: Cecal microbiota of mus musculus: AOM treated A/J min/+ mice fed different fibers: Sample       302
design: "DNA was extracted from cecal contents by mechanical lysis (FastPrep; Matrix E (Medinor)) and QiaAmp DNA Stool kit using a modified protocol.  PCR was performed in triplicates and paired end sequencing (2×150bp) were performed using the protocol presented in (Caporaso, Kuczynski et al. 2010). Briefly, the V4 region of the 16S rRNA gene was amplified with region-specific primers that included the Illumina flowcell adapter sequences. The reverse amplification primer also contained a twelve base barcode sequence that supports pooling of different samples. Samples were purified with AMpure (Agencourt Bioscience Corporation) and quantified using the Quant-iT Picogreen ds DNA with picogreen before pooling. The sample pool was purified again with Ampure, quantified using the Quant-iT Picogreen ds DNA, diluted to 4nM, and the MiSeq protocol “Preparing DNA Libraries for Sequencing on The MiSeq” provided by Illumina was then followed. In addition to the experimental samples, the MiSeq run also contained a control library made from phiX Control v3 which, in this run, accounted for 10% of reads.   The library quantification and sequencing were performed at Nofima. The sample pool was quantified using picogreen, diluted to 2nM, and the MiSeq Protocol provided by Illumina was then followed.  The MiSeq Control Software (MCS) version used was RTA 1.17.28.  The forward and reverse reads were joined in QIIME version 1.7.0. Next, the barcodes corresponding to the reads that failed to assemble were removed. The sequences were then demultiplexed in QIIME allowing zero barcode errors and a quality score of 30 (Q30) using the QIIME toolkit (Caporaso, Kuczynski et al. 2010). 16S rDNA (V4)- trimmed, paired reads were concatonated: The Miseq         generated one Read1.fastq, one Read2.fastq and one index.fastq file including all my samples         (we used custom-barcoded primers as published by Caporaso et al., 2010) The R1.fastq +         R2.fastq was joined in Qiime and the barcodes in the Index.fastq file not matching the new         out.join.fastq file was removed generating an out.barcode.fastq file. The samples were         demultiplexed in qiime using the “split_libraries_fastq.py” command allowing no errors in         the barcodes and using a quality score of 30 (Q30). It is form this step I got my *.fna and         *.qual files (by adding the “store_demultiplexed_fastq” command). "