Advances in sequencing technology

Chan, Eugene

doi:10.1016/j.mrfmmm.2005.01.004

Cited by 138 publications

(97 citation statements)

References 125 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This is reflected in the dramatically lower cost of sequencing. Figure 2 shows the cost per basepair since 1971, when the first DNA molecule was sequenced[55]. Initially, improvements in Sanger sequencing drove this development but with the introduction of the first ‘next-generation’ sequencing machine, the Roche 454 in 2005, the costs have come down by orders of magnitude.…”

Section: Massively Parallel Sequencingmentioning

confidence: 99%

Direct mutation analysis by high-throughput sequencing: From germline to low-abundant, somatic variants

Gundry

Vijg

2012

Mutation Research/Fundamental and Molecular Mechanisms of Mutag

View full text Add to dashboard Cite

DNA mutations are the source of genetic variation within populations. The majority of mutations with observable effects are deleterious. In humans mutations in the germ line can cause genetic disease. In somatic cells multiple rounds of mutations and selection lead to cancer. The study of genetic variation has progressed rapidly since the completion of the draft sequence of the human genome. Recent advances in sequencing technology, most importantly the introduction of massively parallel sequencing (MPS), have resulted in more than a hundred-fold reduction in the time and cost required for sequencing nucleic acids. These improvements have greatly expanded the use of sequencing as a practical tool for mutation analysis. While in the past the high cost of sequencing limited mutation analysis to selectable markers or small forward mutation targets assumed to be representative for the genome overall, current platforms allow whole genome sequencing for less than $5,000. This has already given rise to direct estimates of germline mutation rates in multiple organisms including humans by comparing whole genome sequences between parents and offspring. Here we present a brief history of the field of mutation research, with a focus on classical tools for the measurement of mutation rates. We then review MPS, how it is currently applied and the new insight into human and animal mutation frequencies and spectra that has been obtained from whole genome sequencing. While great progress has been made, we note that the single most important limitation of current MPS approaches for mutation analysis is the inability to address low-abundance mutations that turn somatic tissues into mosaics of cells. Such mutations are at the basis of intra-tumor heterogeneity, with important implications for clinical diagnosis, and could also contribute to somatic diseases other than cancer, including aging. Some possible approaches to gain access to low-abundance mutations are discussed, with a brief overview of new sequencing platforms that are currently waiting in the wings to advance this exploding field even further.

show abstract

Section: Massively Parallel Sequencingmentioning

confidence: 99%

Direct mutation analysis by high-throughput sequencing: From germline to low-abundant, somatic variants

Gundry

Vijg

2012

Mutation Research/Fundamental and Molecular Mechanisms of Mutag

View full text Add to dashboard Cite

show abstract

“…This possibility is near reality as extensive efforts to lower costs of sequencing, i.e. the "$1000 genome" challenge, are currently underway [22][23][24]. In the near term, as attention turns to noncoding regions, there is a need to develop approaches to identify functional regulatory elements and evaluate how sequence variation alters function.…”

Section: Identification Of Candidate Gene Regions and Finding Candidamentioning

confidence: 99%

Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: Current and developing technologies

Chorley

Wang

Campbell

et al. 2008

Mutation Research/Reviews in Mutation Research

156

121

View full text Add to dashboard Cite

The most common form of genetic variation, single nucleotide polymorphisms or SNPs, can affect the way an individual responds to the environment and modify disease risk. Although most of the millions of SNPs have little or no effect on gene regulation and protein activity, there are many circumstances where base changes can have deleterious effects. Non-synonymous SNPs that result in amino acid changes in proteins have been studied because of their obvious impact on protein activity. It is well known that SNPs within regulatory regions of the genome can result in disregulation of gene transcription. However, the impact of SNPs located in putative regulatory regions, or rSNPs, is harder to predict for two primary reasons. First, the mechanistic roles of non-coding genomic sequence remain poorly defined. Second, experimental validation of the functional consequences of rSNPs is often slow and laborious. In this review, we summarize traditional and novel methodologies for candidate rSNPs selection, in particular in silico techniques that aid in candidate rSNP selection. Additionally we will discuss molecular biological techniques that assess the impact of rSNPs on binding of regulatory machinery, as well as functional consequences on transcription. Standard techniques such as EMSA and luciferase reporter constructs are still widely used to assess effects of rSNPs on binding and gene transcription; however, these protocols are often bottlenecks in the discovery process. Therefore, we highlight novel and developing high-throughput protocols that promise to aid in shortening the process of rSNP validation. Given the large amount of genomic information generated from a multitude of re-sequencing and genome-wide SNP array efforts, future focus should be to develop validation techniques that will allow greater understanding of the impact these polymorphisms have on human health and disease.

show abstract

“…Such advancements include the identification of genes through the Human Genome Project, improved and less costly gene sequencing capabilities, improved transgenic animal models, the identification of role of microRNA as regulatory molecules, the use of siRNA techniques in gene expression knock-down models, improved sperm fluorescent in situ hybridization (FISH) techniques, and many other breakthroughs [3,18,21,25,27]. These advancements improve our ability to further identify and evaluate the genetic and epigenetic causes of male infertility, potential clinical therapies, and possible mechanisms of selective regulation of spermatogenesis.…”

Section: Introductionmentioning

confidence: 99%