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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.
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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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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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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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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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An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus
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JUNIPER: Reconstructing Transmission Events from Next-Generation Sequencing Data at Scale.

Ivan Specht1, Gage K Moreno1, Taylor Brock-Fisher1,2

  • 1The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

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Summary
This summary is machine-generated.

We developed JUNIPER, a scalable tool for reconstructing disease transmission networks by analyzing pathogen genetic data. JUNIPER improves understanding of pathogen spread and aids targeted control during outbreaks.

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Area of Science:

  • Epidemiology
  • Computational Biology
  • Genomics

Background:

  • Understanding pathogen transmission dynamics is crucial for effective disease control.
  • Existing tools for transmission reconstruction face scalability and methodological limitations.

Purpose of the Study:

  • To develop a highly-scalable tool, JUNIPER (Joint Underlying Network Inference for Phylogenetic and Epidemiological Reconstructions), for reconstructing pathogen transmission networks.
  • To incorporate intrahost variation and incomplete sampling into outbreak reconstruction models.

Main Methods:

  • Developed a statistical model for within-host variant frequencies using next-generation sequencing data.
  • Integrated within-host variation with population-level evolutionary and transmission models.
  • Enabled simultaneous inference of phylogenies and transmission trees, with algorithmic parallelization for scalability.

Main Results:

  • Validated the within-host variation model on over 160,000 SARS-CoV-2 genomes.
  • Demonstrated JUNIPER's utility on large-scale datasets of bovine H5N1 (1,500+ cases) and human COVID-19 (13,000+ cases).
  • Quantified elevated H5N1 transmission rates in California and identified high-confidence transmission events; showed vaccination efficacy in reducing SARS-CoV-2 transmission.

Conclusions:

  • JUNIPER overcomes computational and methodological limitations of existing tools.
  • Provides a robust framework for large-scale pathogen spread studies.
  • Facilitates targeted control measures by offering critical insights into disease outbreaks.