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      Discovery of the principal specific transcription factors of Apicomplexa and their implication for the evolution of the AP2-integrase DNA binding domains

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          Abstract

          The comparative genomics of apicomplexans, such as the malarial parasite Plasmodium, the cattle parasite Theileria and the emerging human parasite Cryptosporidium, have suggested an unexpected paucity of specific transcription factors (TFs) with DNA binding domains that are closely related to those found in the major families of TFs from other eukaryotes. This apparent lack of specific TFs is paradoxical, given that the apicomplexans show a complex developmental cycle in one or more hosts and a reproducible pattern of differential gene expression in course of this cycle. Using sensitive sequence profile searches, we show that the apicomplexans possess a lineage-specific expansion of a novel family of proteins with a version of the AP2 (Apetala2)-integrase DNA binding domain, which is present in numerous plant TFs. About 20–27 members of this apicomplexan AP2 (ApiAP2) family are encoded in different apicomplexan genomes, with each protein containing one to four copies of the AP2 DNA binding domain. Using gene expression data from Plasmodium falciparum, we show that guilds of ApiAP2 genes are expressed in different stages of intraerythrocytic development. By analogy to the plant AP2 proteins and based on the expression patterns, we predict that the ApiAP2 proteins are likely to function as previously unknown specific TFs in the apicomplexans and regulate the progression of their developmental cycle. In addition to the ApiAP2 family, we also identified two other novel families of AP2 DNA binding domains in bacteria and transposons. Using structure similarity searches, we also identified divergent versions of the AP2-integrase DNA binding domain fold in the DNA binding region of the PI-SceI homing endonuclease and the C-terminal domain of the pleckstrin homology (PH) domain-like modules of eukaryotes. Integrating these findings, we present a reconstruction of the evolutionary scenario of the AP2-integrase DNA binding domain fold, which suggests that it underwent multiple independent combinations with different types of mobile endonucleases or recombinases. It appears that the eukaryotic versions have emerged from versions of the domain associated with mobile elements, followed by independent lineage-specific expansions, which accompanied their recruitment to transcription regulation functions.

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          Most cited references 70

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

           S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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            MUSCLE: a multiple sequence alignment method with reduced time and space complexity

             Robert Edgar (2004)
            Background In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks. Here we present a more complete discussion of the algorithm, describing several previously unpublished techniques that improve biological accuracy and / or computational complexity. We introduce a new option, MUSCLE-fast, designed for high-throughput applications. We also describe a new protocol for evaluating objective functions that align two profiles. Results We compare the speed and accuracy of MUSCLE with CLUSTALW, Progressive POA and the MAFFT script FFTNS1, the fastest previously published program known to the author. Accuracy is measured using four benchmarks: BAliBASE, PREFAB, SABmark and SMART. We test three variants that offer highest accuracy (MUSCLE with default settings), highest speed (MUSCLE-fast), and a carefully chosen compromise between the two (MUSCLE-prog). We find MUSCLE-fast to be the fastest algorithm on all test sets, achieving average alignment accuracy similar to CLUSTALW in times that are typically two to three orders of magnitude less. MUSCLE-fast is able to align 1,000 sequences of average length 282 in 21 seconds on a current desktop computer. Conclusions MUSCLE offers a range of options that provide improved speed and / or alignment accuracy compared with currently available programs. MUSCLE is freely available at .
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              T-Coffee: A novel method for fast and accurate multiple sequence alignment.

              We describe a new method (T-Coffee) for multiple sequence alignment that provides a dramatic improvement in accuracy with a modest sacrifice in speed as compared to the most commonly used alternatives. The method is broadly based on the popular progressive approach to multiple alignment but avoids the most serious pitfalls caused by the greedy nature of this algorithm. With T-Coffee we pre-process a data set of all pair-wise alignments between the sequences. This provides us with a library of alignment information that can be used to guide the progressive alignment. Intermediate alignments are then based not only on the sequences to be aligned next but also on how all of the sequences align with each other. This alignment information can be derived from heterogeneous sources such as a mixture of alignment programs and/or structure superposition. Here, we illustrate the power of the approach by using a combination of local and global pair-wise alignments to generate the library. The resulting alignments are significantly more reliable, as determined by comparison with a set of 141 test cases, than any of the popular alternatives that we tried. The improvement, especially clear with the more difficult test cases, is always visible, regardless of the phylogenetic spread of the sequences in the tests. Copyright 2000 Academic Press.
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                Author and article information

                Affiliations
                simpleNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +1 301 594 2445; Fax: +1 301 435 7794; Email: aravind@ 123456ncbi.nlm.nih.gov
                Journal
                Nucleic Acids Res
                Nucleic Acids Research
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                2005
                2005
                21 July 2005
                : 33
                : 13
                : 3994-4006
                1178005
                10.1093/nar/gki709
                16040597
                © The Author 2005. Published by Oxford University Press. All rights reserved

                The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@ 123456oupjournals.org

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                Genetics

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