Dataset Information

Hybrid-denovo: a de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags.

ABSTRACT: Background:Illumina paired-end sequencing has been increasingly popular for 16S rRNA gene-based microbiota profiling. It provides higher phylogenetic resolution than single-end reads due to a longer read length. However, the reverse read (R2) often has significant low base quality, and a large proportion of R2s will be discarded after quality control, resulting in a mixture of paired-end and single-end reads. A typical 16S analysis pipeline usually processes either paired-end or single-end reads but not a mixture. Thus, the quantification accuracy and statistical power will be reduced due to the loss of a large amount of reads. As a result, rare taxa may not be detectable with the paired-end approach, or low taxonomic resolution will result in a single-end approach. Results:To have both the higher phylogenetic resolution provided by paired-end reads and the higher sequence coverage by single-end reads, we propose a novel OTU-picking pipeline, hybrid-denovo, that can process a hybrid of single-end and paired-end reads. Using high-quality paired-end reads as a gold standard, we show that hybrid-denovo achieved the highest correlation with the gold standard and performed better than the approaches based on paired-end or single-end reads in terms of quantifying the microbial diversity and taxonomic abundances. By applying our method to a rheumatoid arthritis (RA) data set, we demonstrated that hybrid-denovo captured more microbial diversity and identified more RA-associated taxa than a paired-end or single-end approach. Conclusions:Hybrid-denovo utilizes both paired-end and single-end 16S sequencing reads and is recommended for 16S rRNA gene targeted paired-end sequencing data.

SUBMITTER: Chen X

PROVIDER: S-EPMC5841375 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hybrid-denovo: a de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags.

Chen Xianfeng X Johnson Stephen S Jeraldo Patricio P Wang Junwen J Chia Nicholas N Kocher Jean-Pierre A JA Chen Jun J

GigaScience 20180301 3

<h4>Background</h4>Illumina paired-end sequencing has been increasingly popular for 16S rRNA gene-based microbiota profiling. It provides higher phylogenetic resolution than single-end reads due to a longer read length. However, the reverse read (R2) often has significant low base quality, and a large proportion of R2s will be discarded after quality control, resulting in a mixture of paired-end and single-end reads. A typical 16S analysis pipeline usually processes either paired-end or single-e ...[more]

PMID: 29267858

Similar Datasets

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Yijun Ruan mailto:ruanyj@gis.a-star.edu.sg). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track was produced as part of the ENCODE Project. It shows the locations of protein factor mediated chromatin interactions determined by Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) data (Fullwood et al., 2010) extracted from five different human cancer cell lines (K562 (chronic myeloid leukemia), HCT116 (colorectal cancer), HeLa-S3 (cervical cancer), MCF-7 (breast cancer), and NB4 (promyelocytic)). A chromatin interaction is defined as the association of two regions of the genome that are far apart in terms of genomic distance, but are spatially proximate to each other in the 3-dimensional cellular nucleus. Additionally, ChIA-PET experiments generate transcription factor binding sites. A binding site is defined as a region of the genome that is highly enriched by specific Chromatin ImmunoPrecipitation (ChIP) against a transcription factor, which indicates that the transcription factor binds specifically to this region. The protein factors displayed in the track include estrogen receptor alpha (ERa), RNA polymerase II (RNAPII), and CCCTC binding factor (CTCF). For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) is a global de novo high-throughput method for characterizing the 3-dimensional structure of chromatin in the nucleus. In the ChIA-PET protocol, samples were cross-linked and fragmented, then subjected to chromatin immunoprecipitation. The DNA fragments that were brought together by the chromatin interactions were then proximity-ligated. During this proximity-ligation step, the half-linkers (created by the fragmentation) containing flanking MmeI sites (type IIS restriction enzymes) were first ligated to the DNA fragments and then ligated to each other to form full linkers. Full linkers bridge either two ends of a self-circularized fragment, or two ends of two different chromatin fragments. The material was then reverse cross-linked, purified and digested with MmeI. MmeI cuts 20 base pairs away from its recognition site. Tag-linker-tag (paired-end tag, PET) constructs were sequenced by ultra-high-throughput methods (Illumina or SOLiD paired-end sequencing). ChIA-PET reads were processed with the ChIA-PET Tool (Li et al., 2010) by the following steps: linker filtering, short reads mapping, PET classification, binding site identification, and interaction cluster identification. The high-confidence binding sites and chromatin interaction clusters were reported. Chromatin interactions identified by ChIA-PET have been validated by 3C, ChIP-3C, 4C and DNA-FISH (Fullwood et al., 2009).

Project description:BackgroundBiofuels extracted from the seeds of Camelina sativa have recently been used successfully as environmentally friendly jet-fuel to reduce greenhouse gas emissions. Camelina sativa is genetically very close to Arabidopsis thaliana, and both are members of the Brassicaceae. Although public databases are currently available for some members of the Brassicaceae, such as A. thaliana, A. lyrata, Brassica napus, B. juncea and B. rapa, there are no public Expressed Sequence Tags (EST) or genomic data for Camelina sativa. In this study, a high-throughput, large-scale RNA sequencing (RNA-seq) of the Camelina sativa transcriptome was carried out to generate a database that will be useful for further functional analyses.ResultsApproximately 27 million clean "reads" filtered from raw reads by removal of adaptors, ambiguous reads and low-quality reads (2.42 gigabase pairs) were generated by Illumina paired-end RNA-seq technology. All of these clean reads were assembled de novo into 83,493 unigenes and 103,196 transcripts using SOAPdenovo and Trinity, respectively. The average length of the transcripts generated by Trinity was 697 bp (N50 = 976), which was longer than the average length of unigenes (319 bp, N50 = 346 bp). Nonetheless, the assembly generated by SOAPdenovo produced similar number of non-redundant hits (22,435) with that of Trinity (22,433) in BLASTN searches of the Arabidopsis thaliana CDS sequence database (TAIR). Four public databases, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Swiss-prot, NCBI non-redundant protein (NR), and the Cluster of Orthologous Groups (COG), were used for unigene annotation; 67,791 of 83,493 unigenes (81.2%) were finally annotated with gene descriptions or conserved protein domains that were mapped to 25,329 non-redundant protein sequences. We mapped 27,042 of 83,493 unigenes (32.4%) to 119 KEGG metabolic pathways.ConclusionsThis is the first report of a transcriptome database for Camelina sativa, an environmentally important member of the Brassicaceae. We showed that C. savita is closely related to Arabidopsis spp. and more distantly related to Brassica spp. Although the majority of annotated genes had high sequence identity to those of A. thaliana, a substantial proportion of disease-resistance genes (NBS-encoding LRR genes) were instead more closely similar to the genes of other Brassicaceae; these genes included BrCN, BrCNL, BrNL, BrTN, BrTNL in B. rapa. As plant genomes are under long-term selection pressure from environmental stressors, conservation of these disease-resistance genes in C. sativa and B. rapa genomes implies that they are exposed to the threats from closely-related pathogens in their natural habitats.

Dataset Information

Hybrid-denovo: a de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags.

Publications

Hybrid-denovo: a de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets