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Orlov YL, Orlova NG. Bioinformatics tools for the sequence complexity estimates. Biophys Rev 2023; 15:1367-1378. [PMID: 37974990 PMCID: PMC10643780 DOI: 10.1007/s12551-023-01140-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 09/01/2023] [Indexed: 11/19/2023] Open
Abstract
We review current methods and bioinformatics tools for the text complexity estimates (information and entropy measures). The search DNA regions with extreme statistical characteristics such as low complexity regions are important for biophysical models of chromosome function and gene transcription regulation in genome scale. We discuss the complexity profiling for segmentation and delineation of genome sequences, search for genome repeats and transposable elements, and applications to next-generation sequencing reads. We review the complexity methods and new applications fields: analysis of mutation hotspots loci, analysis of short sequencing reads with quality control, and alignment-free genome comparisons. The algorithms implementing various numerical measures of text complexity estimates including combinatorial and linguistic measures have been developed before genome sequencing era. The series of tools to estimate sequence complexity use compression approaches, mainly by modification of Lempel-Ziv compression. Most of the tools are available online providing large-scale service for whole genome analysis. Novel machine learning applications for classification of complete genome sequences also include sequence compression and complexity algorithms. We present comparison of the complexity methods on the different sequence sets, the applications for gene transcription regulatory regions analysis. Furthermore, we discuss approaches and application of sequence complexity for proteins. The complexity measures for amino acid sequences could be calculated by the same entropy and compression-based algorithms. But the functional and evolutionary roles of low complexity regions in protein have specific features differing from DNA. The tools for protein sequence complexity aimed for protein structural constraints. It was shown that low complexity regions in protein sequences are conservative in evolution and have important biological and structural functions. Finally, we summarize recent findings in large scale genome complexity comparison and applications for coronavirus genome analysis.
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Affiliation(s)
- Yuriy L. Orlov
- The Digital Health Institute, I.M. Sechenov First Moscow State Medical University of the Russian Ministry of Health (Sechenov University), Moscow, 119991 Russia
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Agrarian and Technological Institute, Peoples’ Friendship University of Russia, 117198 Moscow, Russia
| | - Nina G. Orlova
- Department of Mathematics, Financial University under the Government of the Russian Federation, Moscow, 125167 Russia
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Alves SIA, Ferreira VBC, Dantas CWD, da Silva ALDC, Ramos RTJ. EasySSR: a user-friendly web application with full command-line features for large-scale batch microsatellite mining and samples comparison. Front Genet 2023; 14:1228552. [PMID: 37693309 PMCID: PMC10483286 DOI: 10.3389/fgene.2023.1228552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 07/28/2023] [Indexed: 09/12/2023] Open
Abstract
Microsatellites, also known as SSRs or STRs, are polymorphic DNA regions with tandem repetitions of a nucleotide motif of size 1-6 base pairs with a broad range of applications in many fields, such as comparative genomics, molecular biology, and forensics. However, the majority of researchers do not have computational training and struggle while running command-line tools or very limited web tools for their SSR research, spending a considerable amount of time learning how to execute the software and conducting the post-processing data tabulation in other tools or manually-time that could be used directly in data analysis. We present EasySSR, a user-friendly web tool with command-line full functionality, designed for practical use in batch identifying and comparing SSRs in sequences, draft, or complete genomes, not requiring previous bioinformatic skills to run. EasySSR requires only a FASTA and an optional GENBANK file of one or more genomes to identify and compare STRs. The tool can automatically analyze and compare SSRs in whole genomes, convert GenBank to PTT files, identify perfect and imperfect SSRs and coding and non-coding regions, compare their frequencies, abundancy, motifs, flanking sequences, and iterations, producing many outputs ready for download such as PTT files, interactive charts, and Excel tables, giving the user the data ready for further analysis in minutes. EasySSR was implemented as a web application, which can be executed from any browser and is available for free at https://computationalbiology.ufpa.br/easyssr/. Tutorials, usage notes, and download links to the source code can be found at https://github.com/engbiopct/EasySSR.
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Affiliation(s)
- Sandy Ingrid Aguiar Alves
- Laboratory of Biological Engineering, Biological Science Institute, Park of Science and Technology, Federal University of Pará, Belém, Brazil
| | - Victor Benedito Costa Ferreira
- Laboratory of Biological Engineering, Biological Science Institute, Park of Science and Technology, Federal University of Pará, Belém, Brazil
| | | | - Artur Luiz da Costa da Silva
- Laboratory of Biological Engineering, Biological Science Institute, Park of Science and Technology, Federal University of Pará, Belém, Brazil
| | - Rommel Thiago Jucá Ramos
- Laboratory of Biological Engineering, Biological Science Institute, Park of Science and Technology, Federal University of Pará, Belém, Brazil
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Korotkov E, Zaytsev K, Fedorov A. Use of 6 Nucleotide Length Words to Study the Complexity of Gene Sequences from Different Organisms. ENTROPY (BASEL, SWITZERLAND) 2022; 24:632. [PMID: 35626518 PMCID: PMC9141341 DOI: 10.3390/e24050632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 04/23/2022] [Accepted: 04/27/2022] [Indexed: 12/02/2022]
Abstract
In this paper, we attempted to find a relation between bacteria living conditions and their genome algorithmic complexity. We developed a probabilistic mathematical method for the evaluation of k-words (6 bases length) occurrence irregularity in bacterial gene coding sequences. For this, the coding sequences from different bacterial genomes were analyzed and as an index of k-words occurrence irregularity, we used W, which has a distribution similar to normal. The research results for bacterial genomes show that they can be divided into two uneven groups. First, the smaller one has W in the interval from 170 to 475, while for the second it is from 475 to 875. Plants, metazoan and virus genomes also have W in the same interval as the first bacterial group. We suggested that second bacterial group coding sequences are much less susceptible to evolutionary changes than the first group ones. It is also discussed to use the W index as a biological stress value.
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Affiliation(s)
- Eugene Korotkov
- Institute of Bioengineering, Federal Research Center of Biotechnology of the Russian Academy of Sciences, 119071 Moscow, Russia
| | - Konstantin Zaytsev
- Bach Institute of Biochemistry, Research Center of Biotechnology of the Russian Academy of Sciences, 119071 Moscow, Russia; (K.Z.); (A.F.)
| | - Alexey Fedorov
- Bach Institute of Biochemistry, Research Center of Biotechnology of the Russian Academy of Sciences, 119071 Moscow, Russia; (K.Z.); (A.F.)
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Korotkov EV, Kamionskya AM, Korotkova MA. Detection of Highly Divergent Tandem Repeats in the Rice Genome. Genes (Basel) 2021; 12:genes12040473. [PMID: 33806152 PMCID: PMC8064497 DOI: 10.3390/genes12040473] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/11/2021] [Accepted: 03/23/2021] [Indexed: 11/25/2022] Open
Abstract
Currently, there is a lack of bioinformatics approaches to identify highly divergent tandem repeats (TRs) in eukaryotic genomes. Here, we developed a new mathematical method to search for TRs, which uses a novel algorithm for constructing multiple alignments based on the generation of random position weight matrices (RPWMs), and applied it to detect TRs of 2 to 50 nucleotides long in the rice genome. The RPWM method could find highly divergent TRs in the presence of insertions or deletions. Comparison of the RPWM algorithm with the other methods of TR identification showed that RPWM could detect TRs in which the average number of base substitutions per nucleotide (x) was between 1.5 and 3.2, whereas T-REKS and TRF methods could not detect divergent TRs with x > 1.5. Applied to the search of TRs in the rice genome, the RPWM method revealed that TRs occupied 5% of the genome and that most of them were 2 and 3 bases long. Using RPWM, we also revealed the correlation of TRs with dispersed repeats and transposons, suggesting that some transposons originated from TRs. Thus, the novel RPWM algorithm is an effective tool to search for highly divergent TRs in the genomes.
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Affiliation(s)
- Eugene V Korotkov
- Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Bld.2, 33 Leninsky Ave., 119071 Moscow, Russia
- MEPhI (Moscow Engineering Physics Institute), National Research Nuclear University, 31 Kashirskoye Shosse, 115409 Moscow, Russia
| | - Anastasiya M Kamionskya
- Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Bld.2, 33 Leninsky Ave., 119071 Moscow, Russia
| | - Maria A Korotkova
- MEPhI (Moscow Engineering Physics Institute), National Research Nuclear University, 31 Kashirskoye Shosse, 115409 Moscow, Russia
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Shamanskiy VA, Timonina VN, Popadin KY, Gunbin KV. ImtRDB: a database and software for mitochondrial imperfect interspersed repeats annotation. BMC Genomics 2019; 20:295. [PMID: 31284879 PMCID: PMC6614062 DOI: 10.1186/s12864-019-5536-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Mitochondria is a powerhouse of all eukaryotic cells that have its own circular DNA (mtDNA) encoding various RNAs and proteins. Somatic perturbations of mtDNA are accumulating with age thus it is of great importance to uncover the main sources of mtDNA instability. Recent analyses demonstrated that somatic mtDNA deletions depend on imperfect repeats of various nature between distant mtDNA segments. However, till now there are no comprehensive databases annotating all types of imperfect repeats in numerous species with sequenced complete mitochondrial genome as well as there are no algorithms capable to call all types of imperfect repeats in circular mtDNA. RESULTS We implemented naïve algorithm of pattern recognition by analogy to standard dot-plot construction procedures allowing us to find both perfect and imperfect repeats of four main types: direct, inverted, mirror and complementary. Our algorithm is adapted to specific characteristics of mtDNA such as circularity and an excess of short repeats - it calls imperfect repeats starting from the length of 10 b.p. We constructed interactive web available database ImtRDB depositing perfect and imperfect repeats positions in mtDNAs of more than 3500 Vertebrate species. Additional tools, such as visualization of repeats within a genome, comparison of repeat densities among different genomes and a possibility to download all results make this database useful for many biologists. Our first analyses of the database demonstrated that mtDNA imperfect repeats (i) are usually short; (ii) associated with unfolded DNA structures; (iii) four types of repeats positively correlate with each other forming two equivalent pairs: direct and mirror versus inverted and complementary, with identical nucleotide content and similar distribution between species; (iv) abundance of repeats is negatively associated with GC content; (v) dinucleotides GC versus CG are overrepresented on light chain of mtDNA covered by repeats. CONCLUSIONS ImtRDB is available at http://bioinfodbs.kantiana.ru/ImtRDB/ . It is accompanied by the software calling all types of interspersed repeats with different level of degeneracy in circular DNA. This database and software can become a very useful tool in various areas of mitochondrial and chloroplast DNA research.
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Affiliation(s)
- Viktor A Shamanskiy
- Center for Mitochondrial Functional Genomics, School of Life Science, Immanuel Kant Baltic Federal University, Kaliningrad, Russia
| | - Valeria N Timonina
- Center for Mitochondrial Functional Genomics, School of Life Science, Immanuel Kant Baltic Federal University, Kaliningrad, Russia
| | - Konstantin Yu Popadin
- Center for Mitochondrial Functional Genomics, School of Life Science, Immanuel Kant Baltic Federal University, Kaliningrad, Russia.,Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Konstantin V Gunbin
- Center for Mitochondrial Functional Genomics, School of Life Science, Immanuel Kant Baltic Federal University, Kaliningrad, Russia. .,Center of Brain Neurobiology and Neurogenetics, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
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Database of Periodic DNA Regions in Major Genomes. BIOMED RESEARCH INTERNATIONAL 2017; 2017:7949287. [PMID: 28182099 PMCID: PMC5274682 DOI: 10.1155/2017/7949287] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Revised: 12/07/2016] [Accepted: 12/21/2016] [Indexed: 12/11/2022]
Abstract
Summary. We analyzed several prokaryotic and eukaryotic genomes looking for the periodicity sequences availability and employing a new mathematical method. The method envisaged using the random position weight matrices and dynamic programming. Insertions and deletions were allowed inside periodicities, thus adding a novelty to the results we obtained. A periodicity length, one of the key periodicity features, varied from 2 to 50 nt. Totally over 60,000 periodicity sequences were found in 15 genomes including some chromosomes of the H. sapiens (partial), C. elegans, D. melanogaster, and A. thaliana genomes.
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Mudunuri SB, Patnana S, Nagarajaram HA. MICdb3.0: a comprehensive resource of microsatellite repeats from prokaryotic genomes. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau005. [PMID: 24536078 PMCID: PMC3926409 DOI: 10.1093/database/bau005] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The MICdb is a comprehensive relational database of perfect microsatellites extracted from completely sequenced and annotated genomes of bacteria and archaea. The current version MICdb3.0 is an updated and revised version of MICdb2.0. As compared with the previous version MICdb2.0, the current release is significantly improved in terms of much larger coverage of genomes, improved presentation of queried results, user-friendly administration module to manage Simple Sequence Repeat (SSR) data such as addition of new genomes, deletion of obsolete data, etc., and also removal of certain features deemed to be redundant. The new web-interface to the database called Microsatellite Analysis Server (MICAS) version 3.0 has been improved by the addition of powerful high-quality visualization tools to view the query results in the form of pie charts and bar graphs. All the query results and graphs can be exported in different formats so that the users can use them for further analysis. MICAS3.0 is also equipped with a unique genome comparison module using which users can do pair-wise comparison of genomes with regard to their microsatellite distribution. The advanced search module can be used to filter the repeats based on certain criteria such as filtering repeats of a particular motif/repeat size, extracting repeats of coding/non-coding regions, sort repeats, etc. The MICdb database has, therefore, been made portable to be administered by a person with the necessary administrative privileges. The MICdb3.0 database and analysis server can be accessed for free from www.cdfd.org.in/micas. Database URL:http://www.cdfd.org.in/micas
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Affiliation(s)
- Suresh B Mudunuri
- Department of Computer Science & Engineering, Grandhi Varalakshmi Venkatarao Institute of Technology, Bhimavaram, Andhra Pradesh 534 207, India, Training & Delivery Department, TalentSprint Educational Services, IIIT Campus, Hyderabad, Andhra Pradesh 500 032, India and Laboratory of Computational Biology, Centre for DNA Fingerprinting & Diagnostics, Hyderabad, Andhra Pradesh 500 001, India
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Chen M, Tan Z, Zeng G. MfSAT: Detect simple sequence repeats in viral genomes. Bioinformation 2011; 6:171-2. [PMID: 21572888 PMCID: PMC3092955 DOI: 10.6026/97320630006171] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2011] [Accepted: 04/25/2011] [Indexed: 01/01/2023] Open
Abstract
Simple sequence repeats (SSRs) are ubiquitous short tandem repeats, which are associated with various regulatory mechanisms and have been found in viral genomes. Herein, we develop MfSAT (Multi-functional SSRs Analytical Tool), a new powerful tool which can fast identify SSRs in multiple short viral genomes and then automatically calculate the numbers and proportions of various SSR types (mono-, di-, tri-, tetra-, penta- and hexanucleotide repeats). Furthermore, it also can detect codon repeats and report the corresponding amino acid.
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Affiliation(s)
- Ming Chen
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China
| | - Zhongyang Tan
- College of Biology, State Key Laboratary for Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082, China
| | - Guangming Zeng
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China
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