| 1. |
- Ramilowski, JA, et al.
(författare)
-
Functional annotation of human long noncoding RNAs via molecular phenotyping
- 2020
-
Ingår i: Genome research. - : Cold Spring Harbor Laboratory. - 1549-5469 .- 1088-9051. ; 30:7, s. 1060-1072
-
Tidskriftsartikel (refereegranskat)abstract
- Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
- Grapotte, M, et al.
(författare)
-
Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network
- 2021
-
Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 3297-
-
Tidskriftsartikel (refereegranskat)abstract
- Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.
|
|
| 5. |
|
|
| 6. |
- Tromp, J., et al.
(författare)
-
World Heart Federation Roadmap for Digital Health in Cardiology
- 2022
-
Ingår i: GLOBAL HEALTH. - : UBIQUITY PRESS LTD. - 2211-8160 .- 2308-4553 .- 2211-8179. ; 17:1
-
Tidskriftsartikel (refereegranskat)abstract
- More than 500 million people worldwide live with cardiovascular disease (CVD). Health systems today face fundamental challenges in delivering optimal care due to ageing populations, healthcare workforce constraints, financing, availability and affordability of CVD medicine, and service delivery. Digital health technologies can help address these challenges. They may be a tool to reach Sustainable Development Goal 3.4 and reduce premature mortality from non-communicable diseases (NCDs) by a third by 2030. Yet, a range of fundamental barriers prevents implementation and access to such technologies. Health system governance, health provider, patient and technological factors can prevent or distort their implementation. World Heart Federation (WHF) roadmaps aim to identify essential roadblocks on the pathway to effective prevention, detection, and treatment of CVD. Further, they aim to provide actionable solutions and implementation frameworks for local adaptation. This WHF Roadmap for digital health in cardiology identifies barriers to implementing digital health technologies for CVD and provides recommendations for overcoming them.
|
|
| 7. |
- Yu, Hui, et al.
(författare)
-
Accelerometer sampling requirements for animal behaviour classification and estimation of energy expenditure
- 2023
-
Ingår i: Animal Biotelemetry. - 2050-3385. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Biologgers have contributed greatly to studies of animal movement, behaviours and physiology. Accelerometers, among the various on-board sensors of biologgers, have mainly been used for animal behaviour classification and energy expenditure estimation. However, a general principle for the combined sampling duration and frequency for different taxa is lacking. In this study, we evaluated whether Nyquist–Shannon sampling theorem applies to accelerometer-based classification of animal behaviour and energy expenditure approximation. To evaluate the influence of accelerometer sampling frequency on behaviour classification, we annotated accelerometer data from seven European pied flycatchers (Ficedula hypoleuca) freely moving in aviaries. We also used simulated data to systematically evaluate the combined effect of sampling duration and sampling frequency on the performance of estimating signal frequency and amplitude. Results: We found that a sampling frequency higher than Nyquist frequency at 100 Hz was needed to classify fast, short-burst behavioural movements of pied flycatcher, such as swallowing food with a mean frequency of 28 Hz. In contrast, high frequency movements with longer durations such as flight could be characterized adequately using much lower sampling frequency of 12.5 Hz. To identify rapid transient prey catching manoeuvres within these flight bouts, again a high frequency sampling at 100 Hz was needed. For both the experimental data of the flycatchers and the simulated data, the combination of sampling frequency and sampling duration affected the accuracy of signal frequency and amplitude estimation. For long sampling durations, the sampling frequency equal to the Nyquist frequency was adequate for accurate signal frequency and amplitude estimation. Accuracy declined with decreasing sampling duration, especially for signal amplitude estimation with up to 40% standard deviation of normalized amplitude difference. To accurately estimate signal amplitude at low sampling duration, a sampling frequency of four times the signal frequency was necessary (two times the Nyquist frequency). Conclusions: The appropriate sampling frequency of accelerometers depends on the objective of the specific study and the characteristics of the behaviour. For studies with no constraints on device battery and storage, a sampling frequency of at least two times the Nyquist frequency will achieve relative optimal representative of signal information (i.e., frequency and amplitude). For classification and energy expenditure estimation of short-burst behaviours, 1.4 times the Nyquist frequency of behaviour is required.
|
|
