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Calandrelli, R.

Publications and source records attributed to Calandrelli, R..

2 recordsLinked to original sources

Rainbow-seq: combining cell lineage tracking with single-cell RNA sequencing in preimplantation embryos

Single-cell RNA-seq experiments cannot record cell division history and therefore cannot directly connect intercellular differences at a later developmental stage to their progenitor cells. We developed Rainbow-seq to combine cell division lineage tracing with single-cell RNA-seq. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA-seq experiment to simultaneously read single-cell transcriptomes and decode the lineage marker genes. We traced the lineages deriving from each blastomere in two-cell mouse embryos and observed inequivalent contributions to the embryonic and abembryonic poles in 72% of the blastocysts evaluated. Rainbow-seq on four- and eight-cell embryos with lineage tracing triggered at two-cell stage exhibited remarkable transcriptome-wide differences between the two cell lineages at both stages, including genes involved in negative regulation of transcription and signaling. These data provide critical insights on cell fate choices in cleavage embryos. Rainbow-seq bridged a critical gap between cellular division history and single-cell RNA-seq assays.

developmental biology

GITAR: An open source tool for analysis and visualization of Hi-C data

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present GITAR (Genome Interaction Tools and Resources), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, visualization and topologically associated domains (TADs) analysis. GITAR is composed of two main modules: 1) HiCtool, a Python library to process and visualize Hi-C data, including TADs analysis and 2) Processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline which goes from the raw Hi-C data to the computation, visualization and optimized storage of intra-chromosomal contact matrices and topological domain coordinates. A large collection of standardized processed data allows to compare different datasets in a consistent way and it saves time of work to obtain data for visualization or additional analyses. GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data and it is freely available for the public at http://genomegitar.org as an open source software.

bioinformatics