Subirana JA, Messeguer X Evolution of Tandem Repeat Satellite Sequences in Two Closely Related Caenorhabditis Species. Diminution of Satellites in Hermaphrodites. (Article) Genes, 8 (12), pp. E351, 2017. (Links | BibTeX | Tags: C.elegans, Minisatellite Repeats) @article{X2017,
title = {Evolution of Tandem Repeat Satellite Sequences in Two Closely Related Caenorhabditis Species. Diminution of Satellites in Hermaphrodites.},
author = {Subirana JA, Messeguer X},
url = {The availability of the genome sequence of the unisexual (male-female) Caenorhabditis nigoni offers an opportunity to compare its non-coding features with the related hermaphroditic species Caenorhabditis briggsae; to understand the evolutionary dynamics of their tandem repeat sequences (satellites), as a result of evolution from the unisexual ancestor. We take advantage of the previously developed SATFIND program to build satellite families defined by a consensus sequence. The relative number of satellites (satellites/Mb) in C. nigoni is 24.6% larger than in C. briggsae. Some satellites in C. nigoni have developed from a proto-repeat present in the ancestor species and are conserved as an isolated sequence in C. briggsae. We also identify unique satellites which occur only once and joint satellite families with a related sequence in both species. Some of these families are only found in C. nigoni, which indicates a recent appearance; they contain conserved adjacent 5\\\' and 3\\\' regions, which may favor transposition. Our results show that the number, length and turnover of satellites are restricted in the hermaphrodite C. briggsae when compared with the unisexual C. nigoni. We hypothesize that this results from differences in unequal recombination during meiotic chromosome pairing, which limits satellite turnover in hermaphrodites.},
year = {2017},
date = {2017-11-28},
journal = {Genes},
volume = {8},
number = {12},
pages = {E351},
keywords = {C.elegans, Minisatellite Repeats}
}
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Albà, M Mar, Laskowski, Roman A, Hancock, John M Detecting cryptically simple protein sequences using the SIMPLE algorithm. (Article) Bioinformatics (Oxford, England), 18 (5), pp. 672–8, 2002, ISSN: 1367-4803. (Abstract | Links | BibTeX | Tags: Algorithms, Amino Acid, Amino Acid Sequence, Amino Acid: genetics, Databases, Genetic, Genetic Variation, Internet, Minisatellite Repeats, Minisatellite Repeats: genetics, Models, Molecular Sequence Data, Protein, Protein: methods, Proteins, Proteins: chemistry, Repetitive Sequences, Saccharomyces cerevisiae, Saccharomyces cerevisiae: genetics, Sensitivity and Specificity, Sequence Analysis, Sequence Homology, Software, Statistical) @article{Alba2002,
title = {Detecting cryptically simple protein sequences using the SIMPLE algorithm.},
author = {Albà, M Mar and Laskowski, Roman A and Hancock, John M},
url = {http://www.ncbi.nlm.nih.gov/pubmed/12050063},
issn = {1367-4803},
year = {2002},
date = {2002-01-01},
journal = {Bioinformatics (Oxford, England)},
volume = {18},
number = {5},
pages = {672--8},
abstract = {Low-complexity or cryptically simple sequences are widespread in protein sequences but their evolution and function are poorly understood. To date methods for the detection of low complexity in proteins have been directed towards the filtering of such regions prior to sequence homology searches but not to the analysis of the regions per se. However, many of these regions are encoded by non-repetitive DNA sequences and may therefore result from selection acting on protein structure and/or function.},
keywords = {Algorithms, Amino Acid, Amino Acid Sequence, Amino Acid: genetics, Databases, Genetic, Genetic Variation, Internet, Minisatellite Repeats, Minisatellite Repeats: genetics, Models, Molecular Sequence Data, Protein, Protein: methods, Proteins, Proteins: chemistry, Repetitive Sequences, Saccharomyces cerevisiae, Saccharomyces cerevisiae: genetics, Sensitivity and Specificity, Sequence Analysis, Sequence Homology, Software, Statistical}
}
Low-complexity or cryptically simple sequences are widespread in protein sequences but their evolution and function are poorly understood. To date methods for the detection of low complexity in proteins have been directed towards the filtering of such regions prior to sequence homology searches but not to the analysis of the regions per se. However, many of these regions are encoded by non-repetitive DNA sequences and may therefore result from selection acting on protein structure and/or function.
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