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Related Concept Videos

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...
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...
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.
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scaleĀ  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
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
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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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Genome sequence data: management, storage, and visualization.

Jacqueline Batley1, David Edwards

  • 1Australian Centre for Plant Functional Genomics, School of Land, Crop and Food Sciences and ARC Centre of Excellence for Integrative Legume Research, University of Queensland, Brisbane, QLD 4072, Australia. j.batley@uq.edu.au

Biotechniques
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Summary
This summary is machine-generated.

Revolutionary DNA sequencing advances lower costs and increase genome data. This shift to short reads challenges bioinformatics, requiring new data management and querying strategies for massive datasets.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Recent advancements in DNA sequencing technology have significantly reduced costs, enabling large-scale genome sequencing.
  • A major shift has occurred from traditional long reads to vast quantities of short reads in sequence data generation.

Purpose of the Study:

  • To address the challenges posed by the increasing volume and format changes in DNA sequencing data.
  • To propose new approaches for managing, storing, and visualizing massive genomic datasets.

Main Methods:

  • Analysis of current trends in DNA sequencing data generation.
  • Evaluation of bioinformatics challenges related to data quantity and format.
  • Exploration of novel data management and querying strategies.

Main Results:

  • The revolution in DNA sequencing has led to an exponential increase in data volume.
  • Short-read data formats present new challenges for storage and analysis.
  • Existing bioinformatics infrastructure requires adaptation to handle future data scales.

Conclusions:

  • The future of genomics relies on adapting bioinformatics tools and strategies to manage and query massive short-read datasets.
  • Effective data management and visualization are crucial for extracting biological insights from next-generation sequencing data.