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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.
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
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. 
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Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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

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...
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.

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Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

Alignment-free sequence comparison based on next-generation sequencing reads.

Kai Song1, Jie Ren, Zhiyuan Zhai

  • 1School of Mathematics, Peking University, Beijing, PR China.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|February 7, 2013
PubMed
Summary
This summary is machine-generated.

Alignment-free genome comparison using novel statistics on next-generation sequencing (NGS) data effectively clusters species. The d(s)(2) statistic accurately reveals phylogenetic relationships without requiring genome assembly.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates vast shotgun read data, posing assembly challenges for organisms lacking reference genomes.
  • Genome comparison is crucial for understanding evolutionary relationships but is often hindered by assembly difficulties.

Purpose of the Study:

  • To evaluate alignment-free sequence comparison statistics for analyzing next-generation sequencing (NGS) shotgun data without assembly.
  • To determine the effectiveness of D(2), D(*)(2), and D(s)(2) statistics in detecting genomic relationships and clustering species.

Main Methods:

  • Theoretical derivation of formulas for sequence relationship detection using a common motif model.
  • Simulations to assess the performance of D(2), D(*)(2), and D(s)(2) statistics under various conditions (tuple length, read length, coverage, sequencing error).
  • Application of variations d(2), d(*)(2), and d(s)(2) to cluster mammalian and tree species using NGS shotgun reads.

Main Results:

  • Theoretical analysis and simulations show D(*)(2) and D(s)(2) outperform D(2) for detecting sequence relationships from NGS data.
  • The performance of D(*)(2) and D(s)(2) is influenced by tuple length, read length, coverage, and sequencing error.
  • Clustering of 5 mammalian and 13 tree species using d(s)(2) aligns with known phylogenetic relationships, even without complete genome sequences.

Conclusions:

  • The alignment-free statistic d(s)(2) is a powerful tool for comparing organisms using NGS shotgun data without the need for assembly.
  • This method facilitates the study of phylogenetic relationships in diverse species, including those with limited genomic resources.