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Prediction of chromatin looping using deep hybrid learning(DHL)

Quantitative Biology 2023年第2期11卷 155-162页

作者： Mateusz Chilinski Anup Kumar Halder dariusz plewczynski Faculty of Mathematics and Information Sciences Warsaw University of Technology00-662 WarsawPoland Laboratory of Functional and Structural Genomics Centre of New Technologies University of Warsaw 02-097 WarsawPoland

Background:With the development of rapid and cheap sequencing techniques,the cost of whole-genome sequencing(WGS)has dropped ***,the complexity of the human genome is not limited to the pure sequenceand additional experiments are required to learn the human genome's influence on complex *** of the most exciting aspects for scientists nowadays is the spatial organisation of the genome,which can be discovered using spatial experiments(e.g.,Hi-C,ChIA-PET).The information about the spatial contacts helps in the analysis and brings new insights into our understanding of the disease ***:We have used an ensemble of deep learning with classical machine learning *** deep learning network we used was DNABERT,which utilises the BERT language model(based on transformers)for the genomic *** classical machine learning models included support vector machines(SVMs),random forests(RFs),and K-nearest neighbor(KNN).The whole approach was wrapped together as deep hybrid learning(DHL).Results:We found that the DNABERT can be used to predict the ChIA-PET experiments with high ***,the DHL approach has increased the metrics on CTCF and RNAPII ***:DHL approach should be taken into consideration for the models utilising the power of deep *** straightforward in the concept,it can improve the results significantly.

关键词： deep learning 3D genomics transformers spatial organisation of nucleus ChIA-PET DNA-Seq

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Dormancy heterogeneity among Arabidopsis thaliana seeds is linked to individual seed size

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Plant Communications 2024年第2期5卷 215-227页

作者： Michal Krzyszton Sebastian P.Sacharowski Veena Halale Manjunath Katarzyna Muter Grzegorz Bokota Ce Wang dariusz plewczynski Tereza Dobisova Szymon Swiezewski Laboratory of Seeds Molecular Biology Institute of Biochemistry and BiophysicsPAS02-106 WarsawPoland Laboratory of Functional and Structural Genomics Centre of New TechnologiesUniversity of WarsawWarsawPoland Laboratory of Bioinformatics and Computational Genomics Faculty of Mathematics and Information ScienceWarsaw University of TechnologyWarsawPoland Labdeers Ltd. 680-01 BoskoviceCzech Republic

Production of morphologically and physiologically variable seeds is an important strategy that helps plants to survive in unpredictable natural ***,the model plant Arabidopsis thaliana and most agronomically essential crops produce visually homogenous *** automated phenotype analysis,we observed that small seeds in Arabidopsis tend to have higher primary and secondary dormancy levels than large *** analysis revealed distinct gene expression profiles between large and small *** seeds have higher expression of translation-related genes implicated in germination *** contrast,small seeds have elevated expression of many positive regulators of dormancy,including a key regulator of this process,the DOG1 *** in DOG1 expression are associated with differential production of its alternative cleavage and polyadenylation isoforms;in small seeds,the proximal poly(A)site is selected,resulting in a short mRNA ***,single-seed RNA sequencing analysis demonstrated that large seeds resemble DOG1 knockout mutant ***,on the single-seed level,expression of genes affected by seed size is correlated with expression of genes that position seeds on the path toward *** results demonstrate an unexpected link between seed size and dormancy phenotypes in a species that produces highly homogenous seed pools,suggesting that the correlation between seed morphology and physiology is more widespread than initially assumed.

关键词： seed size dormancy DOG1 Arabidopsis

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