Forces shaping the fastest evolving regions in the human genome
2006

Forces Shaping the Fastest Evolving Regions in the Human Genome

Sample size: 24 publication Evidence: high

Author Information

Author(s): Pollard Katherine S, Salama Sofie R, King Bryan, Kern Andrew D, Dreszer Tim, Katzman Sol, Siepel Adam, Pedersen Jakob S, Bejerano Gill, Baertsch Robert, Rosenbloom Kate R, Kent Jim, Haussler David

Primary Institution: Department of Biomolecular Engineering, University of California Santa Cruz

Hypothesis

The main differences between chimps and humans will be found in non-coding regulatory DNA.

Conclusion

The study identified 202 genomic elements that are highly conserved in vertebrates but show evidence of significantly accelerated substitution rates in humans, suggesting multiple evolutionary forces at play.

Supporting Evidence

  • The study found 202 genomic elements that are highly conserved in vertebrates but show accelerated substitution rates in humans.
  • Resequencing confirmed that the five most accelerated elements are dramatically changed in humans but not in other primates.
  • The accelerated elements show a strong bias for AT to GC nucleotide changes.
  • Many of the HARs are located near genes associated with transcription factors.
  • Evidence suggests that multiple evolutionary forces, including biased gene conversion, may be shaping these regions.
  • Some HARs may have been under positive selection.
  • The study supports the hypothesis that non-coding regulatory DNA plays a significant role in human evolution.
  • Findings indicate that the evolutionary changes in these regions occurred rapidly over the last 5 million years.

Takeaway

Scientists looked at parts of our DNA that change quickly over time to understand what makes humans different from chimps. They found many changes in areas that don't make proteins but help control how genes work.

Methodology

The study used comparative genomics to identify human accelerated regions (HARs) and applied likelihood ratio tests to assess substitution rates.

Potential Biases

Potential biases in the SNP data could influence the results regarding selection and polymorphism.

Limitations

The study's conclusions may be affected by ascertainment biases in the SNP data used for analysis.

Participant Demographics

The study involved a 24-member subset of the National Human Genome Research Institute Polymorphism Discovery Resource Panel.

Statistical Information

P-Value

p<0.05

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1371/journal.pgen.0020168

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