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Related Concept Videos

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.
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...
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.

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Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
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Optimization of de novo transcriptome assembly from next-generation sequencing data.

Yann Surget-Groba1, Juan I Montoya-Burgos

  • 1Department of Zoology and Animal Biology, University of Geneva, 1211 Geneva 4, Switzerland.

Genome Research
|August 10, 2010
PubMed
Summary

We developed two novel methods, Multiple-k and Scaffolding using Translation Mapping (STM), to significantly improve transcriptome de novo assembly. These algorithms enhance accuracy and contiguity for non-model organisms and complex transcriptomes.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Transcriptome de novo assembly is crucial for biological research but challenging without a reference genome.
  • Current methods using a single k-mer length are suboptimal for transcriptomes with heterogeneous sequence coverage.

Purpose of the Study:

  • To present two novel algorithmic methods for substantially improving transcriptome de novo assembly.
  • To enhance the contiguity and gene identification in transcriptome assemblies, particularly for non-model organisms.

Main Methods:

  • Multiple-k method: Utilizes various k-mer lengths for de novo transcriptome assembly to handle heterogeneous sequence coverage.
  • Scaffolding using Translation Mapping (STM): Employs mapping against a reference proteome to scaffold contigs, improving assembly accuracy.

Main Results:

  • The Multiple-k method demonstrated good performance in assembling a published transcriptome dataset.
  • The STM method considerably improved simulated data assembly with few errors.
  • Application to Loricaria gr. cataphracta and vertebrate tooth development genes showed increased contiguity, gene identification, and successful assembly where classic methods failed.

Conclusions:

  • The developed Multiple-k and STM methods significantly enhance the quality of transcriptome de novo assembly.
  • These methods are effective for non-model organisms and complex transcriptomes, offering broad applicability in biological research.