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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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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
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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.
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Sanger Sequencing01:57

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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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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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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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Related Experiment Video

Updated: Nov 25, 2025

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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A Distributed Whole Genome Sequencing Benchmark Study.

Richard D Corbett1, Robert Eveleigh2, Joe Whitney3

  • 1Canada's Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Provincial Health Services Authority, Vancouver, BC, Canada.

Frontiers in Genetics
|December 18, 2020
PubMed
Summary
This summary is machine-generated.

Large-scale genome sequencing projects can ensure data quality across multiple centers. Results show consistent accuracy regardless of the sequencing center used, highlighting the importance of standardized analysis pipelines.

Keywords:
benchmarkcomparisongenomeinformaticsvariantwhole genome sequencing

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Area of Science:

  • Genomics
  • Bioinformatics
  • Data Science

Background:

  • Population sequencing initiatives involve multiple distributed centers, necessitating consistent data quality.
  • Ensuring accuracy across different sequencing sites is crucial for large-scale genomic studies.

Purpose of the Study:

  • To assess the impact of sequencing centers and analysis pipelines on whole genome sequencing data quality.
  • To evaluate the reproducibility and concordance of genomic data generated across distributed sites.

Main Methods:

  • Whole genome sequencing of DNA replicates from cell lines across three Canadian centers.
  • Application of site-specific secondary analysis pipelines to generated sequence data.
  • Quality assessment using concordance with benchmark variant truth sets and three-way concordance analysis.

Main Results:

  • Variant concordance between datasets was similar across different sequencing centers and replicates when using the same analysis pipeline.
  • Statistically significant differences in datasets were primarily attributed to the analysis pipeline, not the sequencing center.
  • Standardized and updated analysis pipelines can unify data processing across sites.

Conclusions:

  • Genome sequencing projects can achieve reliable quality and reproducibility across a network of distributed sites.
  • The choice of analysis pipeline significantly impacts data consistency, emphasizing the need for standardization.
  • Collaborative sequencing efforts can be confident in the aggregate data quality generated network-wide.