Dataset Information

Assembling a COMPASS.

ABSTRACT: Post-translational modifications of histone proteins lie at the heart of the epigenetic landscape in the cell's nucleus and the precise regulation of gene expression. A myriad of studies have showed that several histone-modifying enzymes are controlled by modulatory protein partner subunits and other post-transcriptional modifications deposited in the vicinity of the targeted site. All together, these mechanisms create an intricate network of interactions that regulate enzymatic activities and ultimately control the site-specific deposition of covalent modifications. In this Point-of-View, we discuss our evolving understanding on the assembly and architecture of histone H3 Lys-4 (H3K4) methyltransferase COMPASS complexes and the techniques that progressively allowed us to better define the molecular basis of complex formation and function. We further briefly discuss some of the challenges lying ahead and additional approaches required to understand mechanistic details for the function of such complexes.

SUBMITTER: Couture JF

PROVIDER: S-EPMC3674043 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Assembling a COMPASS.

Couture Jean-Francois JF Skiniotis Georgios G

Epigenetics 20130307 4

Post-translational modifications of histone proteins lie at the heart of the epigenetic landscape in the cell's nucleus and the precise regulation of gene expression. A myriad of studies have showed that several histone-modifying enzymes are controlled by modulatory protein partner subunits and other post-transcriptional modifications deposited in the vicinity of the targeted site. All together, these mechanisms create an intricate network of interactions that regulate enzymatic activities and u ...[more]

PMID: 23470558

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Project description:Background:Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors. Methods:We address this by first leveraging magnetometers' similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth's local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition. Results:The overall recognition accuracy of >?94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was better at estimating posture. Conclusions:Magnetometers were found to accurately identify common behaviours, and were particularly robust to dynamic behaviour recognition. The use of biomechanical considerations to summarise magnetometer data makes the hybrid scheme capable of accommodating data from either or both sensors within the same framework according to each sensor's strengths. This provides future studies with a method to assess the added benefit of using magnetometers for behaviour recognition.

Dataset Information

Assembling a COMPASS.

Publications

Assembling a COMPASS.

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