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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.
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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
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...
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.
Challenges of the Maxam-Gilbert Method
The...

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Related Experiment Video

Updated: May 16, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Population genomics based on low coverage sequencing: how low should we go?

C Alex Buerkle1, Zachariah Gompert

  • 1Department of Botany and Program in Ecology, University of Wyoming, Laramie, WY, USA. buerkle@uwyo.edu

Molecular Ecology
|November 24, 2012
PubMed
Summary

For molecular ecology studies, maximizing the number of individuals sampled, rather than deep sequencing coverage, yields the most population genetic information. Low coverage sequencing is optimal for accurate and precise parameter estimates.

Related Experiment Videos

Last Updated: May 16, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Area of Science:

  • Molecular Ecology
  • Population Genetics
  • Bioinformatics

Background:

  • Modern molecular ecology relies heavily on DNA sequencing data.
  • Resource limitations necessitate strategic allocation of sequencing reads across coverage depth, individual sampling, and genomic coverage.

Purpose of the Study:

  • To analyze the trade-off between sequencing coverage depth and the number of individuals sampled.
  • To determine optimal strategies for maximizing information about population genetic parameters within budget constraints.

Main Methods:

  • Utilized simple Bayesian models for allele frequencies.
  • Analyzed the relationship between coverage depth and individual sampling for information gain.
  • Compared information yield for population vs. individual genetic parameter inference.

Main Results:

  • Increased individual sampling, even at the expense of coverage depth, provides more information about population genetic parameters.
  • Optimal strategy involves maximizing individual sampling, aiming for approximately 1x coverage per individual.
  • Bayesian models support accurate inference from low-coverage data for individual genetic parameters.

Conclusions:

  • Low-coverage sequencing is sufficient and optimal for molecular ecology studies.
  • Prioritizing the sampling of more individuals over deep sequencing enhances the accuracy and precision of population genetic estimates.