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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.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Genomics02:02

Genomics

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...
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-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Updated: May 14, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Next-generation sequencing in understanding complex neurological disease.

Adam E Handel1, Giulio Disanto, Sreeram V Ramagopalan

  • 1Department of Physiology, Anatomy and Genetics, University of Oxford, UK.

Expert Review of Neurotherapeutics
|February 2, 2013
PubMed
Summary

Next-generation sequencing advances understanding of complex neurological diseases. This review covers methodologies, applications, and challenges in studying conditions like multiple sclerosis.

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Area of Science:

  • Genomics
  • Neuroscience
  • Medical Genetics

Background:

  • Next-generation sequencing (NGS) has generated extensive human genome and transcriptome data.
  • Significant progress in Mendelian neurological disorders contrasts with slower advances in complex neurological diseases.
  • Complex neurological diseases include multiple sclerosis, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.

Purpose of the Study:

  • To review current NGS methodologies for studying complex neurological diseases.
  • To present studies demonstrating NGS's utility in uncovering the genetic basis of these disorders, with a focus on multiple sclerosis.
  • To discuss potential future clinical and research applications of NGS in neurology.

Main Methods:

  • Review of current next-generation sequencing techniques.
  • Analysis of selected studies applying NGS to complex neurological diseases.
  • Identification of common pitfalls in NGS experimental design and execution.

Main Results:

  • NGS methodologies are increasingly applied to complex neurological disease research.
  • Specific studies illustrate the potential of NGS to elucidate genetic etiologies.
  • Challenges and limitations in current NGS approaches for complex diseases are identified.

Conclusions:

  • NGS offers powerful tools for investigating the genetic underpinnings of complex neurological disorders.
  • Future applications of NGS platforms hold promise for both clinical diagnosis and research advancements.
  • Addressing experimental pitfalls is crucial for maximizing the impact of NGS in neurology.