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User:Estevezj/sandbox/comparative genomics

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Comparative genomics is the study of the relationship of genome structure and function across different biological species or strains. Comparative genomics is an attempt to take advantage of the information provided by the signatures of selection to understand the function and evolutionary processes that act on genomes. While it is still a young field, it holds great promise to yield insights into many aspects of the evolution of modern species. The sheer amount of information contained in modern genomes (3.2 gigabases in the case of humans) necessitates that the methods of comparative genomics are automated. Gene finding is an important application of comparative genomics, as is discovery of new, non-coding functional elements of the genome.

Human FOXP2 gene and evolutionary conservation is shown in and multiple alignment (at bottom of figure) in this image from the UCSC Genome Browser. Note that conservation tends to cluster around coding regions (exons).

Comparative genomics exploits both similarities and differences in the proteins, RNA, and regulatory regions of different organisms to infer how selection has acted upon these elements. Those elements that are responsible for similarities between different species should be conserved through time (stabilizing selection), while those elements responsible for differences among species should be divergent (positive selection). Finally, those elements that are unimportant to the evolutionary success of the organism will be unconserved (selection is neutral).

One of the important goals of the field is the identification of the mechanisms of eukaryotic genome evolution. It is however often complicated by the multiplicity of events that have taken place throughout the history of individual lineages, leaving only distorted and superimposed traces in the genome of each living organism. For this reason comparative genomics studies of small model organisms (for example yeast) are of great importance to advance our understanding of general mechanisms of evolution.

Having come a long way from its initial use of finding functional proteins, comparative genomics is now concentrating on finding regulatory regions and siRNA molecules. Recently, it has been discovered that distantly related species often share long conserved stretches of DNA that do not appear to code for any protein (see conserved non-coding sequence).[1] One such ultra-conserved region, that was stable from chicken to chimp has undergone a sudden burst of change in the human lineage, and is found to be active in the developing brain of the human embryo.[2]

Computational approaches to genome comparison have recently become a common research topic in computer science. A public collection of case studies and demonstrations is growing, ranging from whole genome comparisons to gene expression analysis.[3] This has increased the introduction of different ideas, including concepts from systems and control, information theory, strings analysis and data mining. It is anticipated that computational approaches will become and remain a standard topic for research and teaching, while multiple courses will begin training students to be fluent in both topics.[4]

See also

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References

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  1. ^ Bejerano G, Pheasant M, Makunin I, Stephen S, Kent WJ, Mattick JS, Haussler D. Ultraconserved elements in the human genome. Science. 2004 May 28;304(5675):1321-5
  2. ^ Pollard KS, Salama SR, Lambert N, Lambot MA, Coppens S, Pedersen JS, Katzman S, King B, Onodera C, Siepel A, Kern AD, Dehay C, Igel H, Ares M Jr, Vanderhaeghen P, Haussler D. An RNA gene expressed during cortical development evolved rapidly in humans. Nature. 2006 Sep 14;443(7108):167-72.
  3. ^ Cristianini N and Hahn M (2006). Introduction to Computational Genomics. Cambridge University Press. ISBN 0-5216-7191-4.
  4. ^ Via, Allegra; De Las Rivas, Javier; Attwood, Teresa K.; Landsman, David; Brazas, Michelle D.; Leunissen, Jack A. M.; Tramontano, Anna; Schneider, Maria Victoria (2011-10-27). "Ten Simple Rules for Developing a Short Bioinformatics Training Course". PLOS Comput Biol. 7 (10): e1002245. doi:10.1371/journal.pcbi.1002245. PMC 3203054. PMID 22046119. Retrieved 2011-12-03.{{cite journal}}: CS1 maint: unflagged free DOI (link)

Further reading

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Category:Evolutionary biology Category:Genomics

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