Multiple Alignment of Promoter Sequences from the Arabidopsis thaliana L. Genome

Korotkov, Eugene V.; Suvorova, Yulia M.; Kostenko, Dmitrii O.; Korotkova, Maria A.

doi:10.3390/genes12020135

Cited by 13 publications

(44 citation statements)

References 49 publications

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“…A small value of V Q allows us to accelerate the global alignment and all calculations. First, let us take a look at the general scheme for creating multiple alignments using the MAHDS method, shown in Figure 1 [18]. Thereafter, some of the points shown in Figure 1 will be considered in more detail below in separate paragraphs.…”

Section: Multiple Alignment Of Promoter Sequences From the Rice Genome By The Mahds Methodsmentioning

confidence: 99%

“…The MAHDS method does not use direct calculation of multiple alignment by any comparison of sequences from the set Q. The main idea is to use multiple alignment images in the form of position-weight matrices to calculate multiple alignment (Figure 1, point 2) [18]. Initially, we generated random position-weight matrices (PWM).…”

Section: Multiple Alignment Of Promoter Sequences From the Rice Genome By The Mahds Methodsmentioning

confidence: 99%

“…The genetic algorithm is shown in [23]. The application of the genetic algorithm for multiple alignment of nucleotide sequences is described in detail in [18]. Then the positional weight matrices from the A set are optimized by the genetic algorithm (Figure 1, points 3-5).…”

Section: Multiple Alignment Of Promoter Sequences From the Rice Genome By The Mahds Methodsmentioning

confidence: 99%

“…The minimum size of classes equal to 100 was defined, based on random sequence analysis (Figure 2, point 5). "When this procedure was performed on random sequences, the volume of classes ranged from 0-27 sequences with an average value of 16 sequences" [18]. This means that the probability of creating a class of 100 sequences, due to random factors, is negligible.…”

Section: Creating Classes Of Promoter Sequencesmentioning

confidence: 99%

“…In this work, multiple alignment for promoter sequences from the rice genome was performed and "a mathematical method for calculating multiple alignment for highly different sequences (MAHDS) was developed" [7]. Multiple alignment for nucleotide sequences may be calculated on the site http://victoria.biengi.ac.ru/mahds/auth (accessed on 19 May 2021) [18]. A method for creating promoter classes, based on multiple alignment, was also developed.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical Algorithm for Identification of Eukaryotic Promoter Sequences

et al. 2021

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Identification of promoter sequences in the eukaryotic genome, by computer methods, is an important task of bioinformatics. However, this problem has not been solved since the best algorithms have a false positive probability of 10−3–10−4 per nucleotide. As a result of full genome analysis, there may be more false positives than annotated gene promoters. The probability of a false positive should be reduced to 10−6–10−8 to reduce the number of false positives and increase the reliability of the prediction. The method for multi alignment of the promoter sequences was developed. Then, mathematical methods were developed for calculation of the statistically important classes of the promoter sequences. Five promoter classes, from the rice genome, were created. We developed promoter classes to search for potential promoter sequences in the rice genome with a false positive number less than 10−8 per nucleotide. Five classes of promoter sequences contain 1740, 222, 199, 167 and 130 promoters, respectively. A total of 145,277 potential promoter sequences (PPSs) were identified. Of these, 18,563 are promoters of known genes, 87,233 PPSs intersect with transposable elements, and 37,390 PPSs were found in previously unannotated sequences. The number of false positives for a randomly mixed rice genome is less than 10−8 per nucleotide. The method developed for detecting PPSs was compared with some previously used approaches. The developed mathematical method can be used to search for genes, transposable elements, and transcript start sites in eukaryotic genomes.

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Section: Multiple Alignment Of Promoter Sequences From the Rice Genome By The Mahds Methodsmentioning

confidence: 99%

Section: Multiple Alignment Of Promoter Sequences From the Rice Genome By The Mahds Methodsmentioning

confidence: 99%

Section: Multiple Alignment Of Promoter Sequences From the Rice Genome By The Mahds Methodsmentioning

confidence: 99%

Section: Creating Classes Of Promoter Sequencesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mathematical Algorithm for Identification of Eukaryotic Promoter Sequences

et al. 2021

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Detection of tandem repeats in the Capsicum annuum genome

Rudenko

Korotkov

2023

DNA Research

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In this study, we modified the multiple alignment method based on the generation of random position weight matrices (RPWM) and used it to search for tandem repeats (TRs) in the Capsicum annuum genome. The application of the modified (m)RPWM method, which considers the correlation of adjusting nucleotides, resulted in the identification of 908,072 TR regions with repeat lengths from 2 to 200 bp in the C. annuum genome, where they occupied ~29%. The most common TRs were 2 and 3 bp long followed by those of 21, 4, and 15 bp. We performed clustering analysis of TRs with repeat lengths of 2 and 21 bp and created position-weight matrices (PWMs) for each group; these templates could be used to search for TRs of a given length in any nucleotide sequence. All detected TRs can be accessed through publicly available database (http : //victoria.biengi.ac.ru/capsicum_tr/). Comparison of mRPWM with other TR search methods such as Tandem Repeat Finder, T-REKS, and XSTREAM indicated that mRPWM could detect significantly more TRs at similar false discovery rates, indicating its superior performance. The developed mRPWM method can be successfully applied to the identification of highly divergent TRs, which is important for functional analysis of genomes and evolutionary studies.

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Multiple Alignment of Promoter Sequences from the Human Genome

Kamionskaya

Korotkov

2020

Biiotehnologiâ (Mosk.)

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A new algorithm for multiple alignment of nucleotide sequences of MAHDS has been developed. A statistically significant multiple alignment of promoter sequences from the human genome was first created using this algorithm. Based on the constructed alignments, 25 classes of promoter sequences were created with the volume of each class exceeding 100 sequences. The classes of promoters can be used to search for promoter sequences in eukaryotic genomes. promoter, class, dynamic programming, human genome. The work was partially supported by the Russian Foundation for Basic Research (Grant no. 20-016-00057).

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Multiple Alignment of Promoter Sequences from the Arabidopsis thaliana L. Genome

Cited by 13 publications

References 49 publications

Mathematical Algorithm for Identification of Eukaryotic Promoter Sequences

Mathematical Algorithm for Identification of Eukaryotic Promoter Sequences

Detection of tandem repeats in the Capsicum annuum genome

Multiple Alignment of Promoter Sequences from the Human Genome

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