Detection of Highly Divergent Tandem Repeats in the Rice Genome

Korotkov, Eugene V.; Kamionskya, A. M.; Korotkova, Maria A.

doi:10.3390/genes12040473

Cited by 6 publications

(14 citation statements)

References 45 publications

(38 reference statements)

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“…Thereafter, X 1 = C − C / D(C) was calculated. "Here, C is the number of PPS intersections with TEs in the rice genome, C is the expected number of PPS intersections with TEs, D(C) is the variance for the expected number of PPS intersections with TEs" [30].…”

Section: The Intersection Of Pps With Known Promoters and Transposonsmentioning

confidence: 99%

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: The Intersection Of Pps With Known Promoters and Transposonsmentioning

confidence: 99%

Mathematical Algorithm for Identification of Eukaryotic Promoter Sequences

et al. 2021

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“…The pepper ( Capsicum annuum ) genome was used as a model to search for TRs with the improved RPWM algorithm. RPWM, which uses position weight matrices (PWMs), 33 was modified to consider the correlation of adjacent nucleotides in TR detection and more accurately determine the statistical significance of the identified TRs. In order to understand the nature of the improvement, let us review the main steps of the RPWM algorithm.…”

Section: Methodsmentioning

confidence: 99%

“…In our previous studies, we have developed the random position weight matrix (RPWM) method, which could effectively detect TRs with the average number of mutations per nucleotide (x) up to 3.2. 31 , 32 , 33 Here, we improved the RPWM method by considering the correlation between adjacent DNA bases, which allowed identification of TRs with 2–200 bp, and refined the estimation of the statistical significance of the found TRs by using the Monte Carlo method. As a result, it was possible to increase the average number of TR-containing regions detected per 10 6 DNA bases by 1.5 times.…”

Section: Introductionmentioning

confidence: 99%

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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“…The MAHDS method was developed early for the multi alignment of promoter sequences and DNA sequences with weak similarity [ 18 , 19 , 20 ]. This method uses mathematical approaches and programs that were previously created to search for tandem repeats in various sequences [ 33 , 45 , 46 , 47 , 48 , 49 ]. In the present work, the site (3 June 2020) was used to construct a multiple alignment by the MAHDS method for various amino acid sequences.…”

Section: Methodsmentioning

confidence: 99%

Application of the MAHDS Method for Multiple Alignment of Highly Diverged Amino Acid Sequences

Korotkov

Kostenko

2022

IJMS

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The aim of this work was to compare the multiple alignment methods MAHDS, T-Coffee, MUSCLE, Clustal Omega, Kalign, MAFFT, and PRANK in their ability to align highly divergent amino acid sequences. To accomplish this, we created test amino acid sequences with an average number of substitutions per amino acid (x) from 0.6 to 5.6, a total of 81 sets. Comparison of the performance of sequence alignments constructed by MAHDS and previously developed algorithms using the CS and Z score criteria and the benchmark alignment database (BAliBASE) indicated that, although the quality of the alignments built with MAHDS was somewhat lower than that of the other algorithms, it was compensated by greater statistical significance. MAHDS could construct statistically significant alignments of artificial sequences with x ≤ 4.8, whereas the other algorithms (T-Coffee, MUSCLE, Clustal Omega, Kalign, MAFFT, and PRANK) could not perform that at x > 2.4. The application of MAHDS to align 21 families of highly diverged proteins (identity < 20%) from Pfam and HOMSTRAD databases showed that it could calculate statistically significant alignments in cases when the other methods failed. Thus, MAHDS could be used to construct statistically significant multiple alignments of highly divergent protein sequences, which accumulated multiple mutations during evolution.

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Detection of Highly Divergent Tandem Repeats in the Rice Genome

Cited by 6 publications

References 45 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

Application of the MAHDS Method for Multiple Alignment of Highly Diverged Amino Acid Sequences

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