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
Lucini F; Petrini C; Salviato E; Pal K; Rosti V; Gorini F; Santarelli P; Quadri R; Lembo G; Graziano G; Di Patrizio Soldateschi E; Tagliaferri I; Pinatel E; Sebestyén E; Rotta L; Gentile F; Vaira V; Lanzuolo C; Ferrari F Biochemical properties of chromatin domains define genome compartmentalization Journal Article In: Nucleic acids research, vol. 52, iss. 12, no. e54, 2024. Hariprakash JM; Salviato E; La Mastra F; Sebestyén E; Tagliaferri I; Silva RS; Lucini F; Farina L; Cinquanta M; Rancati I; Riboni M; Minardi SP; Roz L; Gorini F; Lanzuolo C; Casola S; Ferrari F Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer Journal Article In: Cancer research, vol. 84, iss. 1, pp. 133-153, 2024. Frittoli E; Palamidessi A; Iannelli F; Zanardi F; Villa S; Barzaghi L; Abdo H; Cancila V; Beznoussenko GV; Della Chiara G; Pagani M; Malinverno C; Bhattacharya D; Pisati F; Yu W; Galimberti V; Bonizzi G; Martini E; Mironov AA; Gioia U; Ascione F; Li Q; Havas K; Magni S; Lavagnino Z; Pennacchio FA; Maiuri P; Caponi S; Mattarelli M; Martino S; d'Adda di Fagagna F; Rossi C; Lucioni M; Tancredi R; Pedrazzoli P; Vecchione A; Petrini C; Ferrari F; Lanzuolo C; Bertalot G; Nader G; Foiani M; Piel M; Cerbino R; Giavazzi F; Tripodo C; Scita G Tissue fluidification promotes a cGAS-STING cytosolic DNA response in invasive breast cancer Journal Article In: Nature materials, vol. 22, iss. 5, pp. 644-655, 2023. Kerschbamer E; Arnoldi M; Tripathi T; Pellegrini M; Maturi S; Erdin S; Salviato E; Di Leva F; Sebestyén E; Dassi E; Zarantonello G; Benelli M; Campos E; Basson MA; Gusella JF; Gustincich S; Piazza S; Demichelis F; Talkowski ME; Ferrari F; Biagioli M CHD8 suppression impacts on histone H3 lysine 36 trimethylation and alters RNA alternative splicing Journal Article In: Nucleic acids research, vol. 50, iss. 22, pp. 12809-12828, 2022. Bicciato S; Ferrari F Hi-C Data Analysis Methods and Protocols Book SpringerLink, 2022, ISBN: 978-1-0716-1390-0. 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, vol. 49, no. 17, 2021. Arnone CM; Polito VA; Mastronuzzi A; Carai A; Diomedi FC; Antonucci L; Petrilli LL; Vinci M; Ferrari F; Salviato E; Scarsella M; De Stefanis C; Weber G; Quintarelli C; De Angelis B; Brenner MK; Gottschalk S; Hoyos V; Locatelli F; Caruana I; Del Bufalo F Oncolytic adenovirus and gene therapy with EphA2-BiTE for the treatment of pediatric high-grade gliomas Journal Article In: Journal for immunotherapy of cancer, vol. 9, iss. 5, 2021. 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, vol. 106, no. 10, pp. 2768-2773, 2021. 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 In: Cancer immunology research, 2021. Pal K; Ferrari F Visualizing and Annotating Hi-C Data Journal Article In: Methods in molecular biology, vol. 2301, pp. 97-132, 2021. 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, vol. 130, no. 5, pp. 2408-2421, 2020. Pal K; Tagliaferri I; Livi CM; Ferrari F HiCBricks: building blocks for efficient handling of large Hi-C datasets. Journal Article In: Bioinformatics, vol. 36, no. 6, pp. 1917-1919, 2020. 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, vol. 11, no. 1, pp. 6274, 2020. Hariprakash JM; Ferrari F Computational Biology Solutions to Identify Enhancers-target Gene Pairs Journal Article In: Computational and structural biotechnology journal, vol. 17, pp. 821-831, 2019. 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, vol. 25, no. 10, pp. 5355, 2019. Pal K; Forcato M; Ferrari F Hi-C analysis: from data generation to integration Journal Article In: Biophysical reviews, vol. 11, no. 1, pp. 67-78, 2019. 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. 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, vol. 45, no. W1, pp. W109-W115, 2017.
2024
@article{%a1.%Y_166,
title = {Biochemical properties of chromatin domains define genome compartmentalization},
author = {Lucini F and Petrini C and Salviato E and Pal K and Rosti V and Gorini F and Santarelli P and Quadri R and Lembo G and Graziano G and Di Patrizio Soldateschi E and Tagliaferri I and Pinatel E and Sebestyén E and Rotta L and Gentile F and Vaira V and Lanzuolo C and Ferrari F},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae454/7684597?login=true},
doi = {10.1093/nar/gkae454},
year = {2024},
date = {2024-08-06},
journal = {Nucleic acids research},
volume = {52},
number = {e54},
issue = {12},
abstract = {Chromatin three-dimensional (3D) organization inside the cell nucleus determines the separation of euchromatin and heterochromatin domains. Their segregation results in the definition of active and inactive chromatin compartments, whereby the local concentration of associated proteins, RNA and DNA results in the formation of distinct subnuclear structures. Thus, chromatin domains spatially confined in a specific 3D nuclear compartment are expected to share similar epigenetic features and biochemical properties, in terms of accessibility and solubility. Based on this rationale, we developed the 4f-SAMMY-seq to map euchromatin and heterochromatin based on their accessibility and solubility, starting from as little as 10 000 cells. Adopting a tailored bioinformatic data analysis approach we reconstruct also their 3D segregation in active and inactive chromatin compartments and sub-compartments, thus recapitulating the characteristic properties of distinct chromatin states. A key novelty of the new method is the capability to map both the linear segmentation of open and closed chromatin domains, as well as their compartmentalization in one single experiment.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1.%Y_138,
title = {Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer},
author = {Hariprakash JM and Salviato E and La Mastra F and Sebestyén E and Tagliaferri I and Silva RS and Lucini F and Farina L and Cinquanta M and Rancati I and Riboni M and Minardi SP and Roz L and Gorini F and Lanzuolo C and Casola S and Ferrari F},
url = {https://aacrjournals.org/cancerres/article/84/1/133/731819/Leveraging-Tissue-Specific-Enhancer-Target-Gene},
doi = {10.1158/0008-5472.CAN-23-1129},
year = {2024},
date = {2024-02-12},
urldate = {2024-02-12},
journal = {Cancer research},
volume = {84},
issue = {1},
pages = {133-153},
abstract = {Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification. Significance: Mapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2023
@article{%a1.%Yb_114,
title = {Tissue fluidification promotes a cGAS-STING cytosolic DNA response in invasive breast cancer},
author = {Frittoli E and Palamidessi A and Iannelli F and Zanardi F and Villa S and Barzaghi L and Abdo H and Cancila V and Beznoussenko GV and Della Chiara G and Pagani M and Malinverno C and Bhattacharya D and Pisati F and Yu W and Galimberti V and Bonizzi G and Martini E and Mironov AA and Gioia U and Ascione F and Li Q and Havas K and Magni S and Lavagnino Z and Pennacchio FA and Maiuri P and Caponi S and Mattarelli M and Martino S and {d'Adda di Fagagna F} and Rossi C and Lucioni M and Tancredi R and Pedrazzoli P and Vecchione A and Petrini C and Ferrari F and Lanzuolo C and Bertalot G and Nader G and Foiani M and Piel M and Cerbino R and Giavazzi F and Tripodo C and Scita G },
url = {https://www.nature.com/articles/s41563-022-01431-x},
doi = {10.1038/s41563-022-01431-x},
year = {2023},
date = {2023-08-08},
journal = {Nature materials},
volume = {22},
issue = {5},
pages = {644-655},
abstract = {The process in which locally confined epithelial malignancies progressively evolve into invasive cancers is often promoted by unjamming, a phase transition from a solid-like to a liquid-like state, which occurs in various tissues. Whether this tissue-level mechanical transition impacts phenotypes during carcinoma progression remains unclear. Here we report that the large fluctuations in cell density that accompany unjamming result in repeated mechanical deformations of cells and nuclei. This triggers a cellular mechano-protective mechanism involving an increase in nuclear size and rigidity, heterochromatin redistribution and remodelling of the perinuclear actin architecture into actin rings. The chronic strains and stresses associated with unjamming together with the reduction of Lamin B1 levels eventually result in DNA damage and nuclear envelope ruptures, with the release of cytosolic DNA that activates a cGAS-STING (cyclic GMP-AMP synthase-signalling adaptor stimulator of interferon genes)-dependent cytosolic DNA response gene program. This mechanically driven transcriptional rewiring ultimately alters the cell state, with the emergence of malignant traits, including epithelial-to-mesenchymal plasticity phenotypes and chemoresistance in invasive breast carcinoma.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2022
@article{%a1.%Yb_54,
title = {CHD8 suppression impacts on histone H3 lysine 36 trimethylation and alters RNA alternative splicing},
author = {Kerschbamer E and Arnoldi M and Tripathi T and Pellegrini M and Maturi S and Erdin S and Salviato E and Di Leva F and Sebestyén E and Dassi E and Zarantonello G and Benelli M and Campos E and Basson MA and Gusella JF and Gustincich S and Piazza S and Demichelis F and Talkowski ME and Ferrari F and Biagioli M},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkac1134/6947080?login=false},
doi = {10.1093/nar/gkac1134},
year = {2022},
date = {2022-03-24},
journal = {Nucleic acids research},
volume = {50},
issue = {22},
pages = {12809-12828},
abstract = {Disruptive mutations in the chromodomain helicase DNA-binding protein 8 gene (CHD8) have been recurrently associated with autism spectrum disorders (ASDs). Here we investigated how chromatin reacts to CHD8 suppression by analyzing a panel of histone modifications in induced pluripotent stem cell-derived neural progenitors. CHD8 suppression led to significant reduction (47.82%) in histone H3K36me3 peaks at gene bodies, particularly impacting on transcriptional elongation chromatin states. H3K36me3 reduction specifically affects highly expressed, CHD8-bound genes and correlates with altered alternative splicing patterns of 462 genes implicated in 'regulation of RNA splicing' and 'mRNA catabolic process'. Mass spectrometry analysis uncovered a novel interaction between CHD8 and the splicing regulator heterogeneous nuclear ribonucleoprotein L (hnRNPL), providing the first mechanistic insights to explain the CHD8 suppression-derived splicing phenotype, partly implicating SETD2, a H3K36me3 methyltransferase. In summary, our results point toward broad molecular consequences of CHD8 suppression, entailing altered histone deposition/maintenance and RNA processing regulation as important regulatory processes in ASD.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@book{%a1.%Ybn,
title = {Hi-C Data Analysis Methods and Protocols},
author = { Bicciato S and Ferrari F},
url = {https://link.springer.com/book/10.1007/978-1-0716-1390-0},
doi = {10.1007/978-1-0716-1390-0},
isbn = {978-1-0716-1390-0},
year = {2022},
date = {2022-05-30},
volume = {2301},
publisher = {SpringerLink},
series = {Methods in Molecular Biology },
keywords = {},
pubstate = {published},
tppubtype = {book}
}
2021
@article{%a1:%Ybv,
title = {Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory interactions},
author = {Salviato E and Djordjilovic V and Hariprakash JM and Tagliaferri I and Pal K and Ferrari F},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab547/6312759},
doi = {10.1093/nar/gkab547},
year = {2021},
date = {2021-10-18},
urldate = {2021-08-25},
journal = {Nucleic acids research},
volume = {49},
number = {17},
abstract = {A growing amount of evidence in literature suggests that germline sequence variants and somatic mutations in non-coding distal regulatory elements may be crucial for defining disease risk and prognostic stratification of patients, in genetic disorders as well as in cancer. Their functional interpretation is challenging because genome-wide enhancer-target gene (ETG) pairing is an open problem in genomics. The solutions proposed so far do not account for the hierarchy of structural domains which define chromatin three-dimensional (3D) architecture. Here we introduce a change of perspective based on the definition of multi-scale structural chromatin domains, integrated in a statistical framework to define ETG pairs. In this work (i) we develop a computational and statistical framework to reconstruct a comprehensive map of ETG pairs leveraging functional genomics data; (ii) we demonstrate that the incorporation of chromatin 3D architecture information improves ETG pairing accuracy and (iii) we use multiple experimental datasets to extensively benchmark our method against previous solutions for the genome-wide reconstruction of ETG pairs. This solution will facilitate the annotation and interpretation of sequence variants in distal non-coding regulatory elements. We expect this to be especially helpful in clinically oriented applications of whole genome sequencing in cancer and undiagnosed genetic diseases research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Yb_71,
title = {Oncolytic adenovirus and gene therapy with EphA2-BiTE for the treatment of pediatric high-grade gliomas},
author = {Arnone CM and Polito VA and Mastronuzzi A and Carai A and Diomedi FC and Antonucci L and Petrilli LL and Vinci M and Ferrari F and Salviato E and Scarsella M and De Stefanis C and Weber G and Quintarelli C and De Angelis B and Brenner MK and Gottschalk S and Hoyos V and Locatelli F and Caruana I and Del Bufalo F},
url = {https://jitc.bmj.com/content/9/5/e001930.long},
doi = {10.1136/jitc-2020-001930},
year = {2021},
date = {2021-11-19},
urldate = {2021-11-19},
journal = {Journal for immunotherapy of cancer},
volume = {9},
issue = {5},
abstract = {Background: Pediatric high-grade gliomas (pHGGs) are among the most common and incurable malignant neoplasms of childhood. Despite aggressive, multimodal treatment, the outcome of children with high-grade gliomas has not significantly improved over the past decades, prompting the development of innovative approaches. Methods: To develop an effective treatment, we aimed at improving the suboptimal antitumor efficacy of oncolytic adenoviruses (OAs) by testing the combination with a gene-therapy approach using a bispecific T-cell engager (BiTE) directed towards the erythropoietin-producing human hepatocellular carcinoma A2 receptor (EphA2), conveyed by a replication-incompetent adenoviral vector (EphA2 adenovirus (EAd)). The combinatorial approach was tested in vitro, in vivo and thoroughly characterized at a molecular level. Results: After confirming the relevance of EphA2 as target in pHGGs, documenting a significant correlation with worse clinical outcome of the patients, we showed that the proposed strategy provides significant EphA2-BiTE amplification and enhanced tumor cell apoptosis, on coculture with T cells. Moreover, T-cell activation through an agonistic anti-CD28 antibody further increased the activation/proliferation profiles and functional response against infected tumor cells, inducing eradication of highly resistant, primary pHGG cells. The gene-expression analysis of tumor cells and T cells, after coculture, revealed the importance of both EphA2-BiTE and costimulation in the proposed system. These in vitro observations translated into significant tumor control in vivo, in both subcutaneous and a more challenging orthotopic model. Conclusions: The combination of OA and EphA2-BiTE gene therapy strongly enhances the antitumor activity of OA, inducing the eradication of highly resistant tumor cells, thus supporting the clinical translation of the approach.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Ybv,
title = {Single-cell profiling reveals the dynamics of cytomegalovirusspecific T-cells in haploidentical hematopoietic stem cell transplantation},
author = {Van Beek JJP and Puccio S and Roberto A and De Paoli F and Graziano G and Salviato E and Alvisi G and Zanon V and Scarpa A and Zaghi E and Calvi M and Di Vito C and Mineri R and Sarina B and De Philippis C and Santoro A and Mariotti J and Bramanti S and Ferrari F and Castagna L and Mavilio D and Lugli E},
url = {https://haematologica.org/article/view/haematol.2020.276352},
doi = {10.3324/haematol.2020.276352},
year = {2021},
date = {2021-09-06},
urldate = {2021-08-25},
journal = {Haematologica},
volume = {106},
number = {10},
pages = {2768-2773},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Ybv,
title = {T Cells Expressing Receptor Recombination/Revision Machinery Are Detected in the Tumor Microenvironment and Expanded in Genomically Over-unstable Models},
author = {Morello G and Cancila V and La Rosa M and Germano G and Lecis D and Amodio V and Zanardi F and Iannelli F and Greco D and La Paglia L and Fiannaca A and Urso AM and Graziano G and Ferrari F and Pupa SM and Sangaletti S and Chiodoni C and Pruneri G and Bardelli A and Colombo MP and Tripodo C},
url = {https://cancerimmunolres.aacrjournals.org/content/early/2021/06/08/2326-6066.CIR-20-0645.long},
doi = {10.1158/2326-6066.CIR-20-0645},
year = {2021},
date = {2021-08-25},
journal = {Cancer immunology research},
abstract = {Tumors undergo dynamic immunoediting as part of a process that balances immunologic sensing of emerging neoantigens and evasion from immune responses. Tumor-infiltrating lymphocytes (TIL) comprise heterogeneous subsets of peripheral T cells characterized by diverse functional differentiation states and dependence on T-cell receptor (TCR) specificity gained through recombination events during their development. We hypothesized that within the tumor microenvironment (TME), an antigenic milieu and immunologic interface, tumor-infiltrating peripheral T cells could reexpress key elements of the TCR recombination machinery, namely, Rag1 and Rag2 recombinases and Tdt polymerase, as a potential mechanism involved in the revision of TCR specificity. Using two syngeneic invasive breast cancer transplantable models, 4T1 and TS/A, we observed that Rag1, Rag2, and Dntt in situ mRNA expression characterized rare tumor-infiltrating T cells. In situ expression of the transcripts was increased in coisogenic Mlh1-deficient tumors, characterized by genomic overinstability, and was also modulated by PD-1 immune-checkpoint blockade. Through immunolocalization and mRNA hybridization analyses, we detected the presence of rare TDT+RAG1/2+ cells populating primary tumors and draining lymph nodes in human invasive breast cancer. Analysis of harmonized single-cell RNA-sequencing data sets of human cancers identified a very small fraction of tumor-associated T cells, characterized by the expression of recombination/revision machinery transcripts, which on pseudotemporal ordering corresponded to differentiated effector T cells. We offer thought-provoking evidence of a TIL microniche marked by rare transcripts involved in TCR shaping.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Ybv,
title = {Visualizing and Annotating Hi-C Data},
author = {Pal K and Ferrari F},
url = {https://link.springer.com/protocol/10.1007%2F978-1-0716-1390-0_5},
doi = {10.1007/978-1-0716-1390-0_5},
year = {2021},
date = {2021-08-25},
journal = {Methods in molecular biology},
volume = {2301},
pages = {97-132},
abstract = {Epigenomics studies require the combined analysis and integration of multiple types of data and annotations to extract biologically relevant information. In this context, sophisticated data visualization techniques are fundamental to identify meaningful patterns in the data in relation to the genomic coordinates. Data visualization for Hi-C contact matrices is even more complex as each data point represents the interaction between two distant genomic loci and their three-dimensional positioning must be considered. In this chapter we illustrate how to obtain sophisticated plots showing Hi-C data along with annotations for other genomic features and epigenomics data. For the example code used in this chapter we rely on a Bioconductor package able to handle even high-resolution Hi-C datasets. The provided examples are explained in details and highly customizable, thus facilitating their extension and adoption by end users for other studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
@article{%a1:%Y_426,
title = {Dysfunctional polycomb transcriptional repression contributes to lamin A/C-dependent muscular dystrophy.},
author = {Bianchi A and Mozzetta C and Pegoli G and Lucini F and Valsoni S and Rosti V and Petrini C and Cortesi A and Gregoretti F and Antonelli L and Oliva G and {De Bardi M} and Rizzi R and Bodega B and Pasini D and Ferrari F and Bearzi C and Lanzuolo C},
url = {https://www.jci.org/articles/view/128161},
doi = {10.1172/JCI128161},
year = {2020},
date = {2020-01-01},
journal = {Journal of clinical investigation},
volume = {130},
number = {5},
pages = {2408-2421},
abstract = {Lamin A is a component of the inner nuclear membrane that, together with epigenetic factors, organizes the genome in higher order structures required for transcriptional control. Mutations in the lamin A/C gene cause several diseases belonging to the class of laminopathies, including muscular dystrophies. Nevertheless, molecular mechanisms involved in the pathogenesis of lamin A-dependent dystrophies are still largely unknown. The polycomb group (PcG) of proteins are epigenetic repressors and lamin A interactors, primarily involved in the maintenance of cell identity. Using a murine model of Emery-Dreifuss muscular dystrophy (EDMD), we show here that lamin A loss deregulated PcG positioning in muscle satellite stem cells, leading to derepression of non-muscle-specific genes and p16INK4a, a senescence driver encoded in the Cdkn2a locus. This aberrant transcriptional program caused impairment in self-renewal, loss of cell identity, and premature exhaustion of the quiescent satellite cell pool. Genetic ablation of the Cdkn2a locus restored muscle stem cell properties in lamin A/C-null dystrophic mice. Our findings establish a direct link between lamin A and PcG epigenetic silencing and indicate that lamin A-dependent muscular dystrophy can be ascribed to intrinsic epigenetic dysfunctions of muscle stem cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Y_462,
title = {HiCBricks: building blocks for efficient handling of large Hi-C datasets.},
author = {Pal K and Tagliaferri I and Livi CM and Ferrari F},
url = {https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz808/5614425},
doi = {10.1093/bioinformatics/btz808},
year = {2020},
date = {2020-01-01},
journal = {Bioinformatics},
volume = {36},
number = {6},
pages = {1917-1919},
abstract = {Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high quality data visualization.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Y_477,
title = {SAMMY-seq reveals early alteration of heterochromatin and deregulation of bivalent genes in Hutchinson-Gilford Progeria Syndrome. },
author = {Sebestyen E and Marullo F and Lucini F and Petrini C and Bianchi A and Valsoni S and Olivieri I and Antonelli L and Gregoretti F and Oliva G and Ferrari F and Lanzuolo C},
url = {https://www.nature.com/articles/s41467-020-20048-9},
doi = {10.1038/s41467-020-20048-9},
year = {2020},
date = {2020-01-01},
journal = {Nature communications},
volume = {11},
number = {1},
pages = {6274},
abstract = {Hutchinson-Gilford progeria syndrome is a genetic disease caused by an aberrant form of Lamin A resulting in chromatin structure disruption, in particular by interfering with lamina associated domains. Early molecular alterations involved in chromatin remodeling have not been identified thus far. Here, we present SAMMY-seq, a high-throughput sequencing-based method for genome-wide characterization of heterochromatin dynamics. Using SAMMY-seq, we detect early stage alterations of heterochromatin structure in progeria primary fibroblasts. These structural changes do not disrupt the distribution of H3K9me3 in early passage cells, thus suggesting that chromatin rearrangements precede H3K9me3 alterations described at later passages. On the other hand, we observe an interplay between changes in chromatin accessibility and Polycomb regulation, with site-specific H3K27me3 variations and transcriptional dysregulation of bivalent genes. We conclude that the correct assembly of lamina associated domains is functionally connected to the Polycomb repression and rapidly lost in early molecular events of progeria pathogenesis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2019
@article{%a1:%Y%_42,
title = {Computational Biology Solutions to Identify Enhancers-target Gene Pairs},
author = {Hariprakash JM and Ferrari F},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611831/},
doi = {10.1016/j.csbj.2019.06.012},
year = {2019},
date = {2019-01-17},
journal = {Computational and structural biotechnology journal},
volume = {17},
pages = {821-831},
abstract = {Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Y_61,
title = {Global chromatin conformation differences in the Drosophila dosage compensated chromosome X.},
author = {Pal K and Forcato M and Jost D and Sexton T and Vaillant C and Salviato E and Mazza EMC and Lugli E and Cavalli G and Ferrari F},
url = {https://www.nature.com/articles/s41467-019-13350-8},
doi = {Nature Communications},
year = {2019},
date = {2019-02-27},
journal = {Nature Communications},
volume = {25},
number = {10},
pages = {5355},
abstract = {In Drosophila melanogaster the single male chromosome X undergoes an average twofold transcriptional upregulation for balancing the transcriptional output between sexes. Previous literature hypothesised that a global change in chromosome structure may accompany this process. However, recent studies based on Hi-C failed to detect these differences. Here we show that global conformational differences are specifically present in the male chromosome X and detectable using Hi-C data on sex-sorted embryos, as well as male and female cell lines, by leveraging custom data analysis solutions. We find the male chromosome X has more mid-/long-range interactions. We also identify differences at structural domain boundaries containing BEAF-32 in conjunction with CP190 or Chromator. Weakening of these domain boundaries in male chromosome X co-localizes with the binding of the dosage compensation complex and its co-factor CLAMP, reported to enhance chromatin accessibility. Together, our data strongly indicate that chromosome X dosage compensation affects global chromosome structure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Y_62,
title = {Hi-C analysis: from data generation to integration},
author = {Pal K and Forcato M and Ferrari F},
url = {https://link.springer.com/article/10.1007%2Fs12551-018-0489-1},
doi = {10.1007/s12551-018-0489-1},
year = {2019},
date = {2019-02-21},
journal = {Biophysical reviews},
volume = {11},
number = {1},
pages = {67-78},
abstract = {In the epigenetics field, large-scale functional genomics datasets of ever-increasing size and complexity have been produced using experimental techniques based on high-throughput sequencing. In particular, the study of the 3D organization of chromatin has raised increasing interest, thanks to the development of advanced experimental techniques. In this context, Hi-C has been widely adopted as a high-throughput method to measure pairwise contacts between virtually any pair of genomic loci, thus yielding unprecedented challenges for analyzing and handling the resulting complex datasets. In this review, we focus on the increasing complexity of available Hi-C datasets, which parallels the adoption of novel protocol variants. We also review the complexity of the multiple data analysis steps required to preprocess Hi-C sequencing reads and extract biologically meaningful information. Finally, we discuss solutions for handling and visualizing such large genomics datasets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{%a1:%Y_63,
title = {HiCBricks: building blocks for efficient handling of large Hi-C datasets.},
author = {Pal K and Tagliaferri I and Livi CM and Ferrari F},
url = {https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz808/5614425},
doi = {10.1093/bioinformatics/btz808},
year = {2019},
date = {2019-11-28},
journal = {Bioinformatics},
abstract = {Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high quality data visualization.},
keywords = {},
pubstate = {forthcoming},
tppubtype = {article}
}
2017
@article{%a1:%Y_183,
title = {WoPPER: Web server for Position Related data analysis of gene Expression in Prokaryotes.},
author = {Puccio S and Grillo G and Licciulli F and Severgnini M and Liuni S and Bicciato S and De Bellis G and Ferrari F and Peano C},
url = {https://academic.oup.com/nar/article/45/W1/W109/3782601},
doi = {10.1093/nar/gkx329},
year = {2017},
date = {2017-07-13},
journal = {Nucleic Acids Research},
volume = {45},
number = {W1},
pages = {W109-W115},
abstract = {The structural and conformational organization of chromosomes is crucial for gene expression regulation in eukaryotes and prokaryotes as well. Up to date, gene expression data generated using either microarray or RNA-sequencing are available for many bacterial genomes. However, differential gene expression is usually investigated with methods considering each gene independently, thus not taking into account the physical localization of genes along a bacterial chromosome. Here, we present WoPPER, a web tool integrating gene expression and genomic annotations to identify differentially expressed chromosomal regions in bacteria. RNA-sequencing or microarray-based gene expression data are provided as input, along with gene annotations. The user can select genomic annotations from an internal database including 2780 bacterial strains, or provide custom genomic annotations. The analysis produces as output the lists of positionally related genes showing a coordinated trend of differential expression. Graphical representations, including a circular plot of the analyzed chromosome, allow intuitive browsing of the results. The analysis procedure is based on our previously published R-package PREDA. The release of this tool is timely and relevant for the scientific community, as WoPPER will fill an existing gap in prokaryotic gene expression data analysis and visualization tools. WoPPER is open to all users and can be reached at the following URL: https://WoPPER.ba.itb.cnr.it.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}