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Related Concept Videos

Genomics02:02

Genomics

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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...
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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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...
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Next-generation Sequencing03:00

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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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Genome Annotation and Assembly03:36

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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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Related Experiment Video

Updated: Jun 29, 2026

Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources
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Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources

Published on: September 3, 2009

Pre-processing of paleogenomes: mitigating reference bias and postmortem damage in ancient genome data.

Dilek Koptekin1,2,3, Etka Yapar4,5, Kıvılcım Başak Vural4

  • 1Department of Biological Sciences, Middle East Technical University, Ankara, Turkey. dilek.koptekin@metu.edu.tr.

Genome Biology
|January 9, 2025
PubMed
Summary

New methods for paleogenomics reduce errors in ancient DNA analysis. Graph alignment and the bamRefine algorithm minimize reference bias and postmortem damage, improving ancient genome reconstruction.

Keywords:
Ancient DNAGraph-reference genomeMaskingPost-mortem damageReference bias

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Last Updated: Jun 29, 2026

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Optimized Bone Sampling Protocols for the Retrieval of Ancient DNA from Archaeological Remains

Published on: November 30, 2021

Area of Science:

  • Paleogenomics
  • Ancient DNA Analysis
  • Bioinformatics

Background:

  • Low coverage paleogenomes present challenges due to reference bias and postmortem damage.
  • Existing alignment methods to linear reference genomes can introduce inaccuracies.
  • Postmortem damage (PMD) in ancient DNA requires specific mitigation strategies.

Purpose of the Study:

  • To investigate alternative strategies for mitigating reference bias in paleogenomic data.
  • To evaluate methods for overcoming postmortem damage in low coverage ancient genomes.
  • To propose an integrated approach for improved ancient DNA data processing.

Main Methods:

  • Comparison of alignment strategies: linear reference genome vs. graph alignment.
  • Application of read masking techniques, including polymorphic site masking.
  • Evaluation of postmortem damage mitigation: trimming, rescaling, and the novel bamRefine algorithm.

Main Results:

  • Graph alignment and masking known polymorphic sites effectively remove reference bias when applied to raw read files.
  • The bamRefine algorithm, which masks reads at potentially damaged sites, offers a new approach to handling postmortem damage.
  • Combined graph alignment and bamRefine demonstrate a simple strategy to minimize data loss and bias.

Conclusions:

  • Graph alignment coupled with bamRefine is a robust strategy for improving paleogenomic data quality.
  • Minimizing data loss and bias is crucial for accurate ancient genome reconstruction.
  • The study advocates for the community to publish raw FASTQ files to facilitate such analyses.