Bioinformatics challenges and potentialities in studying extreme environments

1Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Biological systems show impressive adaptations at extreme environments. In extreme environments, directional selection pressure mechanisms acting upon mutational events often produce functional and structural innovations. Examples are the antifreeze proteins in Antarctic fish and their lack of hemoglobin, and the thermostable properties of TAQ polymerase from thermophilic organisms. During the past decade, more than 4000 organisms have been part of genome-sequencing projects. This has enabled the retrieval of information about evolutionary relationships among all living organisms, and has increased the understanding of complex phenomena, such as evolution, adaptation, and ecology. Bioinformatics tools have allowed us to perform genome annotation, crosscomparison, and to understand the metabolic potential of living organisms. In the last few years, research in bioinformatics has started to migrate from the analysis of genomic sequences and structural biology problems to the analysis of genotype-phenotype mapping. We believe that the analysis of multi-omic information, particularly metabolic and transcriptomic data of organisms living in extreme environments, could provide important and general insights into the how natural selection in an ecosystem shapes the molecular constituents. Here we present a review of methods with the aim to bridge the gap between theoretical models, bioinformatics analysis and experimental settings. The amount of data suggests that bioinformatics could be used to investigate whether the adaptation is generated by interesting molecular inventions.We therefore review and discuss the methodology and tools to approach this challenge.

Cite

CITATION STYLE

APA

Angione, C., Liò, P., Pucciarelli, S., Can, B., Conway, M., Lotti, M., … Telatin, A. (2016). Bioinformatics challenges and potentialities in studying extreme environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9874 LNCS, pp. 205–219). Springer Verlag. https://doi.org/10.1007/978-3-319-44332-4_16

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free