Francesco Ferrari


Istituto di Genetica Molecolare “Luigi Luca Cavalli-Sforza” – CNR
Via Abbiategrasso, 207
27100 Pavia

E-mail: francesco.ferrari@igm.cnr.it



Curriculum Vitae – Download

Complete List of Publications – Download

Research Activity

My group is especially interested in studying the role of chromatin 3D organization in regulating genome functionality. Our expertise is particularly focused on the use of 3D chromatin architecture data obtained by Hi-C, derived from chromosome conformation capture (3C), and other genome-wide techniques based on high-throughput sequencing. We also use other functional genomics data, mainly derived from transcriptomics and epigenomics techniques.

We leverage our expertise in these omics data to gain mechanistic insights into transcription regulation at different levels.

On a large scale, we investigate mechanisms for the coordinated regulation of large chromatin domains in physiological and disease conditions. These involve, for example, the organization of the genome in distinct structural domains, such as Topological Associated Domains (TADs), or Lamina Associated Domains (LADs).

On a finer scale, instead, we study distal regulatory elements (enhancers) and their epigenetic or genetic alterations in genetics diseases and cancer. In this context, we leverage chromatin 3D organization data to refine the association of distal regulatory elements and their target genes, to characterize the functional role of enhancers in epigenetics and gene expression regulation, within the broader gene regulatory network.

 

Research Projects

  • Altered enhancer-genes regulatory network in cancer.

We are working on the characterization of non-coding mutations in cancer altering the complex regulatory network of genes and their non-coding regulatory elements (promoters and enhancers).

  • Heterochromatin alterations in aging and diseases.

Together with a collaborator we are working on a novel experimental technique for characterizing chromatin accessibility in different normal and pathological conditions. We are applying it to study heterochromatin structure changes in aging and diseases.

  • Chromatin architecture data analysis methods.

We are working on novel computational biology methods for the analysis of functional genomics data, in particular for epigenetics marks (ChIP-seq data) and 3D chromatin architecture (Hi-C data).

  • Single cells resolution definition of transcriptional circuits.

Together with collaborators we are leveraging single cells genomics data to identify transcriptional and epigenetics regulatory modules activated in different processes with heterogeneous or rare cell sub-populations. For example, this includes characterizing tumor infiltrating immune cells or, in other projects, the identification of biomarkers of diseases in sub-populations of circulating cells.


Recent Publications

2021

Salviato E; Djordjilovic V; Hariprakash JM; Tagliaferri I; Pal K; Ferrari F

Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory interactions Journal Article

In: Nucleic acids research, 49 (17), 2021.

Abstract | Links | BibTeX

Van Beek JJP; Puccio S; Roberto A; De Paoli F; Graziano G; Salviato E; Alvisi G; Zanon V; Scarpa A; Zaghi E; Calvi M; Di Vito C; Mineri R; Sarina B; De Philippis C; Santoro A; Mariotti J; Bramanti S; Ferrari F; Castagna L; Mavilio D; Lugli E

Single-cell profiling reveals the dynamics of cytomegalovirusspecific T-cells in haploidentical hematopoietic stem cell transplantation Journal Article

In: Haematologica, 106 (10), pp. 2768-2773, 2021.

Links | BibTeX

Morello G; Cancila V; La Rosa M; Germano G; Lecis D; Amodio V; Zanardi F; Iannelli F; Greco D; La Paglia L; Fiannaca A; Urso AM; Graziano G; Ferrari F; Pupa SM; Sangaletti S; Chiodoni C; Pruneri G; Bardelli A; Colombo MP; Tripodo C

T Cells Expressing Receptor Recombination/Revision Machinery Are Detected in the Tumor Microenvironment and Expanded in Genomically Over-unstable Models Journal Article

In: Cancer immunology research, 2021.

Abstract | Links | BibTeX

Pal K; Ferrari F

Visualizing and Annotating Hi-C Data Journal Article

In: Methods in molecular biology, 2301 , pp. 97-132, 2021.

Abstract | Links | BibTeX

2020

Bianchi A; Mozzetta C; Pegoli G; Lucini F; Valsoni S; Rosti V; Petrini C; Cortesi A; Gregoretti F; Antonelli L; Oliva G; De Bardi M; Rizzi R; Bodega B; Pasini D; Ferrari F; Bearzi C; Lanzuolo C

Dysfunctional polycomb transcriptional repression contributes to lamin A/C-dependent muscular dystrophy. Journal Article

In: Journal of clinical investigation, 130 (5), pp. 2408-2421, 2020.

Abstract | Links | BibTeX

Pal K; Tagliaferri I; Livi CM; Ferrari F

HiCBricks: building blocks for efficient handling of large Hi-C datasets. Journal Article

In: Bioinformatics, 36 (6), pp. 1917-1919, 2020.

Abstract | Links | BibTeX

Sebestyen E; Marullo F; Lucini F; Petrini C; Bianchi A; Valsoni S; Olivieri I; Antonelli L; Gregoretti F; Oliva G; Ferrari F; Lanzuolo C

SAMMY-seq reveals early alteration of heterochromatin and deregulation of bivalent genes in Hutchinson-Gilford Progeria Syndrome. Journal Article

In: Nature communications, 11 (1), pp. 6274, 2020.

Abstract | Links | BibTeX

0000

Hariprakash JM; Ferrari F

Computational Biology Solutions to Identify Enhancers-target Gene Pairs Journal Article

In: Computational and structural biotechnology journal, 17 , pp. 821-831, 0000.

Abstract | Links | BibTeX

Pal K; Forcato M; Jost D; Sexton T; Vaillant C; Salviato E; Mazza EMC; Lugli E; Cavalli G; Ferrari F

Global chromatin conformation differences in the Drosophila dosage compensated chromosome X. Journal Article

In: Nature Communications, 25 (10), pp. 5355, 0000.

Abstract | Links | BibTeX

Pal K; Forcato M; Ferrari F

Hi-C analysis: from data generation to integration Journal Article

In: Biophysical reviews, 11 (1), pp. 67-78, 0000.

Abstract | Links | BibTeX

Pal K; Tagliaferri I; Livi CM; Ferrari F

HiCBricks: building blocks for efficient handling of large Hi-C datasets. Journal Article Forthcoming

In: Bioinformatics, Forthcoming.

Abstract | Links | BibTeX

Puccio S; Grillo G; Licciulli F; Severgnini M; Liuni S; Bicciato S; De Bellis G; Ferrari F; Peano C

WoPPER: Web server for Position Related data analysis of gene Expression in Prokaryotes. Journal Article

In: Nucleic Acids Research, 45 (W1), pp. W109-W115, 0000.

Abstract | Links | BibTeX