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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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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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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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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.
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RNA-seq03:21

RNA-seq

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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. 
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Sanger Sequencing01:57

Sanger Sequencing

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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...
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Maxam-Gilbert Sequencing01:05

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Novel Sequence Discovery by Subtractive Genomics
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Novel Sequence Discovery by Subtractive Genomics

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Quality control of next-generation sequencing data without a reference.

Urmi H Trivedi1, Timothée Cézard1, Stephen Bridgett1

  • 1Edinburgh Genomics, Ashworth Laboratories, University of Edinburgh Edinburgh, UK.

Frontiers in Genetics
|May 17, 2014
PubMed
Summary
This summary is machine-generated.

Next-generation sequencing (NGS) enables genomics for any species. A rapid draft genome assembly provides reliable quality control (QC) for NGS data from non-model organisms, eliminating the need for a high-quality reference genome.

Keywords:
Illumina sequencingPCR duplicatesde novo assemblyinsert sizemate pairquality control

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) has revolutionized genomics, enabling data generation for diverse species.
  • Non-model organisms often lack reference genomes, complicating alignment-based quality control (QC) for NGS data.

Purpose of the Study:

  • To demonstrate that a rapid, draft genome assembly can provide reliable QC metrics for NGS data from non-model organisms.
  • To remove the dependency on high-quality reference genomes for NGS data QC.

Main Methods:

  • Generating rapid, non-optimized draft assemblies from raw NGS reads.
  • Utilizing benchmark datasets from control samples across various genome sizes.
  • Applying routine QC tools for assessing NGS data quality.

Main Results:

  • QC inferences from draft assemblies are comparable to those from well-established reference genomes.
  • Draft assemblies enable reliable and informative QC for NGS data in the absence of a reference.

Conclusions:

  • A draft genome assembly is a viable alternative to a high-quality reference for NGS data QC in non-model organisms.
  • This approach enhances the feasibility of genomic studies for species lacking existing reference genomes.