Sendai virus persistence questions the transient naive reprogramming method for iPSC generation.

Since the revolutionary discovery of induced pluripotent stem cells (iPSCs) by Shinya Yamanaka, the comparison between iPSCs and embryonic stem cells (ESCs) has revealed significant differences in their epigenetic states and developmental potential. A recent compelling study published in Nature by Buckberry et al.1 demonstrated that a transient-naive-treatment (TNT) could facilitate epigenetic reprogramming and improve the developmental potential of human iPSCs (hiPSCs). However, the study characterized bulk hiPSCs instead of isolating clonal lines and overlooked the persistent expression of Sendai virus carrying exogenous Yamanaka factors. Our analyses revealed that Sendai genes were expressed in most control PSC samples, including hESCs, which were not intentionally infected. The highest levels of Sendai expression were detected in samples continuously treated with naive media, where it led to overexpression of exogenous MYC, SOX2, and KLF4, altering both the expression levels and ratios of reprogramming factors. Our findings call for further research to verify the effectiveness of the TNT method in the context of delivery methods that ensure prompt elimination of exogenous factors, leading to the generation of bona fide transgene-independent iPSCs.

A community-based approach to image analysis of cells, tissues and tumors.

Emerging multiplexed imaging platforms provide an unprecedented view of an increasing number of molecular markers at subcellular resolution and the dynamic evolution of tumor cellular composition. As such, they are capable of elucidating cell-to-cell interactions within the tumor microenvironment that impact clinical outcome and therapeutic response. However, the rapid development of these platforms has far outpaced the computational methods for processing and analyzing the data they generate. While being technologically disparate, all imaging assays share many computational requirements for post-collection data processing. As such, our Image Analysis Working Group (IAWG), composed of researchers in the Cancer Systems Biology Consortium (CSBC) and the Physical Sciences - Oncology Network (PS-ON), convened a workshop on "Computational Challenges Shared by Diverse Imaging Platforms" to characterize these common issues and a follow-up hackathon to implement solutions for a selected subset of them. Here, we delineate these areas that reflect major axes of research within the field, including image registration, segmentation of cells and subcellular structures, and identification of cell types from their morphology. We further describe the logistical organization of these events, believing our lessons learned can aid others in uniting the imaging community around self-identified topics of mutual interest, in designing and implementing operational procedures to address those topics and in mitigating issues inherent in image analysis (e.g., sharing exemplar images of large datasets and disseminating baseline solutions to hackathon challenges through open-source code repositories).

FAN-C: a feature-rich framework for the analysis and visualisation of chromosome conformation capture data.

Chromosome conformation capture data, particularly from high-throughput approaches such as Hi-C, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data ( https://github.com/vaquerizaslab/fanc ). Due to its compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.

The Birth of the 3D Genome during Early Embryonic Development.

The 3D structure of chromatin in the nucleus is important for the regulation of gene expression and the correct deployment of developmental programs. The differentiation of germ cells and early embryonic development (when the zygotic genome is activated and transcription is taking place for the first time) are accompanied by dramatic changes in gene expression and the epigenetic landscape. Recent studies used Hi-C to investigate the 3D chromatin organization during these developmental transitions, uncovering remarkable remodeling of the 3D genome. Here, we highlight the changes described so far and discuss some of the implications that these findings have for our understanding of the mechanisms and functionality of 3D chromatin architecture.

Generation of Genome-wide Chromatin Conformation Capture Libraries from Tightly Staged Early Drosophila Embryos.

Investigating the three-dimensional architecture of chromatin offers invaluable insight into the mechanisms of gene regulation. Here, we describe a protocol for performing the chromatin conformation capture technique in situ Hi-C on staged Drosophila melanogaster embryo populations. The result is a sequencing library that allows the mapping of all chromatin interactions that occur in the nucleus in a single experiment. Embryo sorting is done manually using a fluorescent stereo microscope and a transgenic fly line containing a nuclear marker. Using this technique, embryo populations from each nuclear division cycle, and with defined cell cycle status, can be obtained with very high purity. The protocol may also be adapted to sort older embryos beyond gastrulation. Sorted embryos are used as inputs for in situ Hi-C. All experiments, including sequencing library preparation, can be completed in five days. The protocol has low input requirements and works reliably using 20 blastoderm stage embryos as input material. The end result is a sequencing library for next generation sequencing. After sequencing, the data can be processed into genome-wide chromatin interaction maps that can be analyzed using a wide range of available tools to gain information about topologically associating domain (TAD) structure, chromatin loops, and chromatin compartments during Drosophila development.

Xrp1 genetically interacts with the ALS-associated FUS orthologue caz and mediates its toxicity.

Cabeza (caz) is the single Drosophila melanogaster orthologue of the human FET proteins FUS, TAF15, and EWSR1, which have been implicated in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. In this study, we identified Xrp1, a nuclear chromatin-binding protein, as a key modifier of caz mutant phenotypes. Xrp1 expression was strongly up-regulated in caz mutants, and Xrp1 heterozygosity rescued their motor defects and life span. Interestingly, selective neuronal Xrp1 knockdown was sufficient to rescue, and neuronal Xrp1 overexpression phenocopied caz mutant phenotypes. The caz/Xrp1 genetic interaction depended on the functionality of the AT-hook DNA-binding domain in Xrp1, and the majority of Xrp1-interacting proteins are involved in gene expression regulation. Consistently, caz mutants displayed gene expression dysregulation, which was mitigated by Xrp1 heterozygosity. Finally, Xrp1 knockdown substantially rescued the motor deficits and life span of flies expressing ALS mutant FUS in motor neurons, implicating gene expression dysregulation in ALS-FUS pathogenesis.

Chromatin Architecture Emerges during Zygotic Genome Activation Independent of Transcription.

Chromatin architecture is fundamental in regulating gene expression. To investigate when spatial genome organization is first established during development, we examined chromatin conformation during Drosophila embryogenesis and observed the emergence of chromatin architecture within a tight time window that coincides with the onset of transcription activation in the zygote. Prior to zygotic genome activation, the genome is mostly unstructured. Early expressed genes serve as nucleation sites for topologically associating domain (TAD) boundaries. Activation of gene expression coincides with the establishment of TADs throughout the genome and co-localization of housekeeping gene clusters, which remain stable in subsequent stages of development. However, the appearance of TAD boundaries is independent of transcription and requires the transcription factor Zelda for locus-specific TAD boundary insulation. These results offer insight into when spatial organization of the genome emerges and identify a key factor that helps trigger this architecture.

TADtool: visual parameter identification for TAD-calling algorithms.

Eukaryotic genomes are hierarchically organized into topologically associating domains (TADs). The computational identification of these domains and their associated properties critically depends on the choice of suitable parameters of TAD-calling algorithms. To reduce the element of trial-and-error in parameter selection, we have developed TADtool: an interactive plot to find robust TAD-calling parameters with immediate visual feedback. TADtool allows the direct export of TADs called with a chosen set of parameters for two of the most common TAD calling algorithms: directionality and insulation index. It can be used as an intuitive, standalone application or as a Python package for maximum flexibility. AVAILABILITY AND IMPLEMENTATION: TADtool is available as a Python package from GitHub (https://github.com/vaquerizaslab/tadtool) or can be installed directly via PyPI, the Python package index (tadtool). CONTACT: kai.kruse@mpi-muenster.mpg.de, jmv@mpi-muenster.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online.