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Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples

Overview of attention for article published in BMC Bioinformatics, December 2015
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Title
Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples
Published in
BMC Bioinformatics, December 2015
DOI 10.1186/1471-2105-16-s18-s13
Pubmed ID
Authors

Yi-Lin Chen, Chuan-Chun Lee, Ya-Lan Lin, Kai-Min Yin, Chung-Liang Ho, Tsunglin Liu

Abstract

Next-generation sequencing (NGS) technology has transformed metagenomics because the high-throughput data allow an in-depth exploration of a complex microbial community. However, accurate species identification with NGS data is challenging because NGS sequences are relatively short. Assembling 16S rDNA segments into longer sequences has been proposed for improving species identification. Current approaches, however, either suffer from amplification bias due to one single primer or insufficient 16S rDNA reads in whole genome sequencing data. Multiple primers were used to amplify different 16S rDNA segments for 454 sequencing, followed by 454 read classification and assembly. This permitted targeted sequencing while reducing primer bias. For test samples containing four known bacteria, accurate and near full-length 16S rDNAs of three known bacteria were obtained. For real soil and sediment samples containing dioxins in various concentrations, 16S rDNA sequences were lengthened by 50% for about half of the non-rare microbes, and 16S rDNAs of several microbes reached more than 1000 bp. In addition, reduced primer bias using multiple primers was illustrated. A new experimental and computational pipeline for obtaining long 16S rDNA sequences was proposed. The capability of the pipeline was validated on test samples and illustrated on real samples. For dioxin-containing samples, the pipeline revealed several microbes suitable for future studies of dioxin chemistry.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 179 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 1%
Estonia 1 <1%
Unknown 176 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 34 19%
Student > Ph. D. Student 25 14%
Student > Master 19 11%
Researcher 16 9%
Unspecified 11 6%
Other 26 15%
Unknown 48 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 45 25%
Agricultural and Biological Sciences 26 15%
Immunology and Microbiology 17 9%
Environmental Science 13 7%
Unspecified 11 6%
Other 14 8%
Unknown 53 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 December 2015.
All research outputs
#14,392,043
of 23,498,099 outputs
Outputs from BMC Bioinformatics
#4,556
of 7,400 outputs
Outputs of similar age
#201,236
of 392,308 outputs
Outputs of similar age from BMC Bioinformatics
#97
of 154 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 392,308 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 154 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.