Thus, evolutionary-based inference systems are playing an increasingly important role in diverse areas, such as elucidation of the tree of life, studies of epidemiology and virulence, drug design, human genetics, cancer or biodiversity. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Įvolutionary theory provides a unifying framework for analysing genomics data and for studying various phenomena in molecular, cell, or developmental biology. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: This work was funded by the Agence Nationale de la Recherche (EvolHHuPro: BLAN07-1-198915) project, the Association Française contre les Myopathies (DDC/KBM: 14390) project and Institute funds from the IGBMC, CNRS, INSERM, and the Université de Strasbourg. Received: NovemAccepted: FebruPublished: March 31, 2011Ĭopyright: © 2011 Thompson et al. Craig Venter Institute, United States of America PLoS ONE 6(3):Įditor: Jonathan Badger, J. We then propose knowledge-enabled, dynamic solutions that will hopefully pave the way to enhanced alignment construction and exploitation in future evolutionary systems biology studies.Ĭitation: Thompson JD, Linard B, Lecompte O, Poch O (2011) A Comprehensive Benchmark Study of Multiple Sequence Alignment Methods: Current Challenges and Future Perspectives. Based on this study, we demonstrate that the existing MSA methods can be exploited in combination to improve alignment accuracy, although novel approaches will still be needed to fully explore the most difficult regions. Third, the badly predicted or fragmentary protein sequences, which make up a large proportion of today's databases, lead to a significant number of alignment errors. Second, motifs in natively disordered regions are often misaligned. First, the locally conserved regions, that reflect functional specificities or that modulate a protein's function in a given cellular context,are less well aligned.
However,we have identified a number of important challenges. We show that alignmentmethods have significantly progressed and can now identify most of the shared sequence features that determine the broad molecular function(s) of a protein family, even for divergent sequences. The benchmark is designed to represent typical problems encountered when aligning the large protein sequence sets that result from today's high throughput biotechnologies. In this paper, we describe a comprehensive evaluation of many of the most popular methods for multiple sequence alignment (MSA), based on a new benchmark test set. By placing the sequence in the framework of the overall family, multiple alignments can be used to identify conserved features and to highlight differences or specificities. Multiple comparison or alignmentof protein sequences has become a fundamental tool in many different domains in modern molecular biology, from evolutionary studies to prediction of 2D/3D structure, molecular function and inter-molecular interactions etc.
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