Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites
The most popular model for the search of ChIP-seq data for transcription factor binding sites (TFBS) is the positional weight matrix (PWM). However, this model does not take into account dependencies between nucleotide occurrences in different site positions. Currently, two recently proposed models,...
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Siberian Branch of the Russian Academy of Sciences, Federal Research Center Institute of Cytology and Genetics, The Vavilov Society of Geneticists and Breeders
2021-03-01
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| Series: | Вавиловский журнал генетики и селекции |
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| Online Access: | https://vavilov.elpub.ru/jour/article/view/2911 |
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| author | A. V. Tsukanov V. G. Levitsky T. I. Merkulova |
| author_facet | A. V. Tsukanov V. G. Levitsky T. I. Merkulova |
| author_sort | A. V. Tsukanov |
| collection | DOAJ |
| description | The most popular model for the search of ChIP-seq data for transcription factor binding sites (TFBS) is the positional weight matrix (PWM). However, this model does not take into account dependencies between nucleotide occurrences in different site positions. Currently, two recently proposed models, BaMM and InMoDe, can do as much. However, application of these models was usually limited only to comparing their recognition accuracies with that of PWMs, while none of the analyses of the co-prediction and relative positioning of hits of different models in peaks has yet been performed. To close this gap, we propose the pipeline called MultiDeNA. This pipeline includes stages of model training, assessing their recognition accuracy, scanning ChIP-seq peaks and their classif ication based on scan results. We applied our pipeline to 22 ChIP-seq datasets of TF FOXA2 and considered PWM, dinucleotide PWM (diPWM), BaMM and InMoDe models. The combination of these four models allowed a signif icant increase in the fraction of recognized peaks compared to that for the sole PWM model: the increase was 26.3 %. The BaMM model provided the main contribution to the recognition of sites. Although the major fraction of predicted peaks contained TFBS of different models with coincided positions, the medians of the fraction of peaks containing the predictions of sole models were 1.08, 0.49, 4.15 and 1.73 % for PWM, diPWM, BaMM and InMoDe, respectively. Thus, FOXA2 BSs were not fully described by only a sole model, which indicates theirs heterogeneity. We assume that the BaMM model is the most successful in describing the structure of the FOXA2 BS in ChIP-seq datasets under study. |
| format | Article |
| id | doaj-art-aa4bdd50d2e24290a92e4795c73400f0 |
| institution | Kabale University |
| issn | 2500-3259 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | Siberian Branch of the Russian Academy of Sciences, Federal Research Center Institute of Cytology and Genetics, The Vavilov Society of Geneticists and Breeders |
| record_format | Article |
| series | Вавиловский журнал генетики и селекции |
| spelling | doaj-art-aa4bdd50d2e24290a92e4795c73400f02025-02-01T09:58:09ZengSiberian Branch of the Russian Academy of Sciences, Federal Research Center Institute of Cytology and Genetics, The Vavilov Society of Geneticists and BreedersВавиловский журнал генетики и селекции2500-32592021-03-0125171710.18699/VJ21.0021127Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sitesA. V. Tsukanov0V. G. Levitsky1T. I. Merkulova2Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of SciencesInstitute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences; Novosibirsk State UniversityInstitute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences; Novosibirsk State UniversityThe most popular model for the search of ChIP-seq data for transcription factor binding sites (TFBS) is the positional weight matrix (PWM). However, this model does not take into account dependencies between nucleotide occurrences in different site positions. Currently, two recently proposed models, BaMM and InMoDe, can do as much. However, application of these models was usually limited only to comparing their recognition accuracies with that of PWMs, while none of the analyses of the co-prediction and relative positioning of hits of different models in peaks has yet been performed. To close this gap, we propose the pipeline called MultiDeNA. This pipeline includes stages of model training, assessing their recognition accuracy, scanning ChIP-seq peaks and their classif ication based on scan results. We applied our pipeline to 22 ChIP-seq datasets of TF FOXA2 and considered PWM, dinucleotide PWM (diPWM), BaMM and InMoDe models. The combination of these four models allowed a signif icant increase in the fraction of recognized peaks compared to that for the sole PWM model: the increase was 26.3 %. The BaMM model provided the main contribution to the recognition of sites. Although the major fraction of predicted peaks contained TFBS of different models with coincided positions, the medians of the fraction of peaks containing the predictions of sole models were 1.08, 0.49, 4.15 and 1.73 % for PWM, diPWM, BaMM and InMoDe, respectively. Thus, FOXA2 BSs were not fully described by only a sole model, which indicates theirs heterogeneity. We assume that the BaMM model is the most successful in describing the structure of the FOXA2 BS in ChIP-seq datasets under study.https://vavilov.elpub.ru/jour/article/view/2911transcription factor binding sites (tfbs)tfbs <i>de novo</i> searchingchip-seqheterogeneity of tfbs |
| spellingShingle | A. V. Tsukanov V. G. Levitsky T. I. Merkulova Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites Вавиловский журнал генетики и селекции transcription factor binding sites (tfbs) tfbs <i>de novo</i> searching chip-seq heterogeneity of tfbs |
| title | Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites |
| title_full | Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites |
| title_fullStr | Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites |
| title_full_unstemmed | Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites |
| title_short | Application of alternative <i>de novo</i> motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites |
| title_sort | application of alternative i de novo i motif recognition models for analysis of structural heterogeneity of transcription factor binding sites a case study of foxa2 binding sites |
| topic | transcription factor binding sites (tfbs) tfbs <i>de novo</i> searching chip-seq heterogeneity of tfbs |
| url | https://vavilov.elpub.ru/jour/article/view/2911 |
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