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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
10:24

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Published on: August 29, 2014

Comparison of next generation sequencing technologies for transcriptome characterization.

P Kerr Wall1, Jim Leebens-Mack, André S Chanderbali

  • 1Department of Biology, Institute of Molecular Evolutionary Genetics, and The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA. pkerrwall@psu.edu

BMC Genomics
|August 4, 2009
PubMed
Summary
This summary is machine-generated.

A simulation approach optimizes transcriptome sequencing by combining Next-Generation (NG) sequencing methods for cost-effective and complete coverage. This hybrid strategy overcomes challenges of short read lengths and assembly accuracy.

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Area of Science:

  • Transcriptomics
  • Bioinformatics
  • Genomics

Background:

  • Developed a simulation approach to determine optimal transcriptome sequencing strategies.
  • Compared traditional capillary sequencing with Next-Generation (NG) technologies.
  • Utilized Arabidopsis genome mappings and 454-GS20 sequences for model parameterization.

Purpose of the Study:

  • To identify the most complete and cost-effective mixture of sequencing methods for transcriptome sequencing.
  • To compare simulation results of traditional and NG sequencing approaches.
  • To provide a tool for guiding NG transcriptome sequencing projects.

Main Methods:

  • Developed a simulation model parameterized with cDNA sequence reads mapped to the Arabidopsis genome.
  • Generated 454-GS20 sequences and de novo assemblies for California poppy and avocado.
  • Simulated various combinations of NG and traditional EST sequencing strategies.

Main Results:

  • Arabidopsis reads identified over 15,000 genes, including novel splice variants and extended UTRs.
  • Simulations suggest a combination of FLX and Solexa sequencing offers optimal transcriptome coverage at a modest cost.
  • Developed ESTcalc, an online webtool for exploring simulation results and customizing sequencing parameters.

Conclusions:

  • NG sequencing offers significant advances in coverage but presents assembly and accuracy challenges.
  • Hybrid sequencing strategies, improved assemblers, and deeper sequencing can overcome NG limitations.
  • The developed simulator is valuable for planning NG transcriptome sequencing projects across diverse organisms.