Francesco Strozzi

Dr. Francesco Strozzi

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
11 July 2013 in Nature Protocols
Verified
Journal Article
Closed access
PDF file
BHBrian W. Haas
Brian W. Haas
Alexie PapanicolaouAlexie Papanicolaou
Alexie Papanicolaou
MYMoran Yassour
Moran Yassour
MGManfred Grabherr
Manfred Grabherr
PBPhilip D Blood
Philip D Blood
ARAviv Regev
Aviv Regev

20 July 2020 in Nature Biotechnology
Verified
Journal Article
Open access
PDF file
AAAlexandre Almeida
Alexandre Almeida
SNStephen Nayfach
Stephen Nayfach
MBMiguel Boland
Miguel Boland
FSFrancesco Strozzi
Francesco Strozzi
MBMartin Beracochea
Martin Beracochea
RFRobert D. Finn
Robert D. Finn
Comprehensive, high-quality reference genomes are required for functional characterization and taxonomic assignment of the human gut microbiota. We present the Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes. These genomes encode >170 million protein sequences, which we collated in the Unified Human Gastrointestinal Protein (UHGP) catalog. The UHGP more than doubles the number of gut proteins in comparison to those present in the Integrated Gene Catalog. More than 70% of the UHGG species lack cultured representatives, and 40% of the UHGP lack functional annotations. Intraspecies genomic variation analyses revealed a large reservoir of accessory genes and single-nucleotide variants, many of which are specific to individual human populations. The UHGG and UHGP collections will enable studies linking genotypes to phenotypes in the human gut microbiome.

5 July 2019 in Science Advances
Verified
Journal Article
Open access
PDF file
RWR. John Wallace
R. John Wallace
GSGoor Sasson
Goor Sasson
PGPhil Garnsworthy
Phil Garnsworthy
ITIlma Tapio
Ilma Tapio
EGEmma Gregson
Emma Gregson
IMItzhak Mizrahi
Itzhak Mizrahi
Cow genes dictate environmentally friendly microbiomes: a step towards reducing greenhouse gas emissions.

19 January 2017 in Journal of Animal Science and Biotechnology
Verified
Journal Article
Open access
PDF file
ITIlma Tapio
Ilma Tapio
TSTimothy J. Snelling
Timothy J. Snelling
FSFrancesco Strozzi
Francesco Strozzi
RWR. John Wallace
R. John Wallace
Methane emissions from ruminant livestock contribute significantly to the large environmental footprint of agriculture. The rumen is the principal source of methane, and certain features of the microbiome are associated with low/high methane phenotypes. Despite their primary role in methanogenesis, the abundance of archaea has only a weak correlation with methane emissions from individual animals. The composition of the archaeal community appears to have a stronger effect, with animals harbouring the Methanobrevibacter gottschalkii clade tending to be associated with greater methane emissions. Ciliate protozoa produce abundant H2, the main substrate for methanogenesis in the rumen, and their removal (defaunation) results in an average 11% lower methane emissions in vivo, but the results are not consistent. Different protozoal genera seem to result in greater methane emissions, though community types (A, AB, B and O) did not differ. Within the bacteria, three different ‘ruminotypes’ have been identified, two of which predispose animals to have lower methane emissions. The two low-methane ruminotypes are generally characterized by less abundant H2-producing bacteria. A lower abundance of Proteobacteria and differences in certain Bacteroidetes and anaerobic fungi seem to be associated with high methane emissions. Rumen anaerobic fungi produce abundant H2 and formate, and their abundance generally corresponds to the level of methane emissions. Thus, microbiome analysis is consistent with known pathways for H2 production and methanogenesis, but not yet in a predictive manner. The production and utilisation of formate by the ruminal microbiota is poorly understood and may be a source of variability between animals.

21 January 2017 in BMC Plant Biology
Verified
Journal Article
Open access
PDF file
VMValentina Maschietto
Valentina Maschietto
CCCinzia Colombi
Cinzia Colombi
RPRaul Pirona
Raul Pirona
GPGiorgio Pea
Giorgio Pea
FSFrancesco Strozzi
Francesco Strozzi
ALAlessandra Lanubile
Alessandra Lanubile
Fusarium verticillioides is a common maize pathogen causing ear rot (FER) and contamination of the grains with the fumonisin B1 (FB1) mycotoxin. Resistance to FER and FB1 contamination are quantitative traits, affected by environmental conditions, and completely resistant maize genotypes to the pathogen are so far unknown. In order to uncover genomic regions associated to reduced FER and FB1 contamination and identify molecular markers for assisted selection, an F2:3 population of 188 progenies was developed crossing CO441 (resistant) and CO354 (susceptible) genotypes. FER severity and FB1 contamination content were evaluated over 2 years and sowing dates (early and late) in ears artificially inoculated with F. verticillioides by the use of either side-needle or toothpick inoculation techniques. Weather conditions significantly changed in the two phenotyping seasons and FER and FB1 content distribution significantly differed in the F3 progenies according to the year and the sowing time. Significant positive correlations (P < 0.01) were detected between FER and FB1 contamination, ranging from 0.72 to 0.81. A low positive correlation was determined between FB1 contamination and silking time (DTS). A genetic map was generated for the cross, based on 41 microsatellite markers and 342 single nucleotide polymorphisms (SNPs) derived from Genotyping-by-Sequencing (GBS). QTL analyses revealed 15 QTLs for FER, 17 QTLs for FB1 contamination and nine QTLs for DTS. Eight QTLs located on linkage group (LG) 1, 2, 3, 6, 7 and 9 were in common between FER and FB1, making possible the selection of genotypes with both low disease severity and low fumonisin contamination. Moreover, five QTLs on LGs 1, 2, 4, 5 and 9 located close to previously reported QTLs for resistance to other mycotoxigenic fungi. Finally, 24 candidate genes for resistance to F. verticillioides are proposed combining previous transcriptomic data with QTL mapping. This study identified a set of QTLs and candidate genes that could accelerate breeding for resistance of maize lines showing reduced disease severity and low mycotoxin contamination determined by F. verticillioides.

10 April 2015 in BMC Genomics
Verified
Journal Article
Open access
PDF file
ENEzequiel L Nicolazzi
Ezequiel L Nicolazzi
ACAndrea Caprera
Andrea Caprera
NNNelson Nazzicari
Nelson Nazzicari
PCPaolo Alessandro Cozzi
Paolo Alessandro Cozzi
FSFrancesco Strozzi
Francesco Strozzi
ASAlessandra Stella
Alessandra Stella
In recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information. Here we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion. This platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.