Check out our Editors-in-Chief’s selection of papers from the March issue of PLOS Computational Biology.
Eleven quick tips for running an interdisciplinary short course for new graduate students
Quantitative reasoning and techniques are increasingly ubiquitous across the life sciences. However, new graduate researchers with a biology background are often not equipped with the skills that are required to apply such techniques correctly and efficiently. In parallel, there are increasing numbers of engineers, mathematicians, and physical scientists interested in studying problems in biology with only basic knowledge of this field. Students from such varied backgrounds can struggle to engage proactively together to tackle problems in biology. There is therefore a need to establish bridges between those disciplines. Timothy E. Saunders and colleagues propose that the beginning of graduate school is the appropriate time to initiate those bridges through an interdisciplinary short course. The authors instigated an intensive 10-day course that brought together new graduate students in the life sciences from across departments within the National University of Singapore. The course was aimed at introducing biological problems as well as some of the quantitative approaches commonly used when tackling those problems. The authors ran the course for three years with over 100 students attending; building on this experience, they share 11 quick tips on how to run such an effective, interdisciplinary short course for new graduate students in the biosciences.
4Cin: A computational pipeline for 3D genome modeling and virtual Hi-C analyses from 4C data
Chromatin conformation capture (3C) methods have revealed the importance of the 3D organization of
the chromatin, which is key to understand many aspects of genome biology. But each of these methods have their own limitations. Here Ibai Irastorza-Azcarate and colleagues present 4Cin, a software that generates 3D models of the chromatin from a small number of 4C-seq experiments — a 3C-based method that provides the frequency of contacts between a given fragment and the genome (one vs all). These 3D models are used to infer all chromosomal contacts within a given genomic region (many vs many). The contact maps facilitate the identification of Topological Associating Domains boundaries. Their software offers a much cheaper, accessible and versatile alternative to other available techniques while providing a comprehensive 3D topological profiling. They applied their software to two different loci to study modifications in genomic structural variants associated to disease phenotypes and to compare the chromatin organization in two different species in a quantitative manner.
ChromoTrace: Computational reconstruction of 3D chromosome configurations for super-resolution microscopy
The 3D structure of DNA in the nucleus is known to be important for many aspects of DNA function, such as how gene expression is regulated. However, current techniques to localise or determine 3D DNA structure are often indirect. The advent of super-resolution microscopy, at a resolution of 20 nm or better, can directly visualize fluorescent probes bound to specific DNA in the nucleus. However it is not trivial to associate how many specific stretches of DNA lie relative to each other, making reliable and precise 3D mapping of large stretches of the genome difficult. Here, Ewan Birney and colleagues propose a method that leverages the fact that they know the sequence of the genome and the resolution of the super-resolution microscope. Their method, ChromoTrace, uses a computer science data structure, suffix trees, that allows one to simultaneously search the entire genome for specific sub-sequences. To show that the method works, they built a simulation scheme for simulating DNA as ensembles of polymer chains in a nucleus and explored the sensitivity of their method to different types of error. ChromoTrace could robustly and accurately reconstruct 3D paths in their simulations.