Biology subjects

Alexander, S.

Publications and source records attributed to Alexander, S..

3 recordsLinked to original sources

bioRxiv2017

Correlative live and super-resolution imaging reveals the dynamic structure of replication domains

Chromosome organization in higher eukaryotes controls gene expression, DNA replication, and DNA repair. Genome mapping has revealed the functional units of chromatin at the sub-megabase scale as self-interacting regions called topologically associating domains (TADs) and showed they correspond to replication domains (RDs). A quantitative structural and dynamic description of RD behavior in the nucleus is however missing, as visualization of dynamic subdiffraction-sized RDs remains challenging. Using fluorescence labeling of RDs combined with correlative live and super-resolution microscopy in situ, we determined biophysical parameters to characterize the internal organization, spacing and mechanical coupling of RDs. We found that RDs are typically 150 nm in size and contain four co-replicating regions spaced 60 nm apart. Spatially neighboring RDs are spaced 300 nm apart and connected by highly flexible linker regions that couple their motion only below 550 nm. Our pipeline allows a robust quantitative characterization of chromosome structure in situ, and provides important biophysical parameters to understand general principles of chromatin organization.

cell biology↗

bioRxiv2017

ChromoTrace: Reconstruction of 3D Chromosome Configurations by Super-Resolution Microscopy

MotivationThe three-dimensional structure of chromatin plays a key role in genome function, including gene expression, DNA replication, chromosome segregation, and DNA repair. Furthermore the location of genomic loci within the nucleus, especially relative to each other and nuclear structures such as the nuclear envelope and nuclear bodies strongly correlates with aspects of function such as gene expression. Therefore, determining the 3D position of the 6 billion DNA base pairs in each of the 23 chromosomes inside the nucleus of a human cell is a central challenge of biology. Recent advances of super-resolution microscopy in principle enable the mapping of specific molecular features with nanometer precision inside cells. Combined with highly specific, sensitive and multiplexed fluorescence labeling of DNA sequences this opens up the possibility of mapping the 3D path of the genome sequence in situ.\n\nResultsHere we develop computational methodologies to reconstruct the sequence configuration of all human chromosomes in the nucleus from a super-resolution image of a set of fluorescent in situ probes hybridized to the genome in a cell. To test our approach we develop a method for the simulation of chromatin packing in an idealized human nucleus. Our reconstruction method, ChromoTrace, uses suffix trees to assign a known linear ordering of in situ probes on the genome to an unknown set of 3D in situ probe positions in the nucleus from super-resolved images using the known genomic probe spacing as a set of physical distance constraints between probes. We find that ChromoTrace can assign the 3D positions of the majority of loci with high accuracy and reasonable sensitivity to specific genome sequences. By simulating spatial resolution, label multiplexing and noise scenarios we assess algorithm performance under realistic experimental constraints. Our study shows that it is feasible to achieve chromosome-wide reconstruction of the 3D DNA path in chromatin based on super-resolution microscopy images.

bioinformatics↗

bioRxiv2016

SIRVs: Spike-In RNA Variants as External Isoform Controls in RNA-Sequencing

Spike-In RNA variants (SIRVs) enable for the first time the validation of RNA sequencing workflows using external isoform transcript controls. 69 transcripts, derived from seven human model genes, cover the eukaryotic transcriptome complexity of start- and end-site variations, alternative splicing, overlapping genes, and antisense transcription in a condensed format. Reference RNA samples were spiked with SIRV mixes, sequenced, and exemplarily four data evaluation pipelines were challenged to account for biases introduced by the RNA-Seq workflow. The deviations of the respective isoform quantifications from the known inputs allow to determine the comparability of sequencing experiments and to extrapolate to which degree alterations in an RNA-Seq workflow affect gene expression measurements. The SIRVs as external isoform controls are an important gauge for inter-experimental comparability and a modular spike-in contribution to clear the way for diagnostic RNA-Seq applications.

molecular biology↗