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Article ; Online: A fast, reliable and easy method to detect within-species DNA contamination.

Dallavilla, Tiziano / Marceddu, Giuseppe / Casadei, Arianna / De Antoni, Luca / Bertelli, Matteo

2020 Volume 91, Issue 13-S, Page(s) e2020019

Abstract: Background and aim: Next generation sequencing (ngs) is becoming the standard for clinical diagnosis. Different steps of NGS, such as DNA extraction, fragmentation, library preparation and amplification, require handling of samples, making the process ... ...

Abstract	Background and aim: Next generation sequencing (ngs) is becoming the standard for clinical diagnosis. Different steps of NGS, such as DNA extraction, fragmentation, library preparation and amplification, require handling of samples, making the process susceptible to contamination. In diagnostic environments, sample contamination with DNA from the same species can lead to errors in diagnosis. Here we propose a simple method to detect within-sample contamination based on analysis of the heterozygous single nucleotide polymorphisms allele ratio (AR). Methods: A dataset of 38000 heterozygous snps was used to estimate the ar distribution. The parameters of the reference distribution were then used to estimate the contamination probability of a sample. Validation was performed using 12 samples contaminated to different levels. Results: Results show that the method easily detects contamination of 20% or more. The method has a limit of detection of about 10%, threshold below which the number of false positives increases significantly. Conclusions: The method can be applied to any type of ngs analysis and is useful for quality control. Being fast and easy to implement makes it ideal for inclusion in NGS pipelines to improve quality control of data and make results more robust.
MeSH term(s)	DNA Contamination ; High-Throughput Nucleotide Sequencing ; Humans ; Polymorphism, Single Nucleotide ; Quality Control
Language	English
Publishing date	2020-11-09
Publishing country	Italy
Document type	Journal Article
ZDB-ID	2114240-3
ISSN	2531-6745 ; 0392-4203
ISSN (online)	2531-6745
ISSN	0392-4203
DOI	10.23750/abm.v91i13-S.10531
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Article ; Online: PipeMAGI: an integrated and validated workflow for analysis of NGS data for clinical diagnostics.

Marceddu, G / Dallavilla, T / Guerri, G / Manara, E / Chiurazzi, P / Bertelli, M

European review for medical and pharmacological sciences

2019 Volume 23, Issue 15, Page(s) 6753–6765

Abstract: Objective: We describe how to set up a custom workflow for the analysis of next generation sequencing (NGS) data suitable for the diagnosis of genetic disorders and that meets the strictest standards of quality and accuracy. Our method goes from DNA ... ...

Abstract	Objective: We describe how to set up a custom workflow for the analysis of next generation sequencing (NGS) data suitable for the diagnosis of genetic disorders and that meets the strictest standards of quality and accuracy. Our method goes from DNA extraction to data analysis with a computational in-house pipeline. The system was extensively validated using three publicly available Coriell samples, estimating accuracy, sensitivity and specificity. Multiple runs were also made to assess repeatability and reproducibility. Materials and methods: Three different Coriell samples were analyzed in a single run to perform coverage, sensitivity, specificity, accuracy, reproducibility and repeatability analysis. The three samples were analyzed with a custom-made oligonucleotide probe library using Nextera Rapid Capture enrichment technique and subsequently quantified using the Qubit method. Sample quality was verified using a 4200 TapeStation and sequenced on a MiSeq personal sequencer. Analysis of NGS data was then performed with a custom pipeline. Results: The workflow enabled an accurate and precise analysis of NGS data that meets all the requirements of quality and accuracy required by international standards such as ISO15189 and the Association of Molecular Pathology. Conclusions: The proposed analysis/validation workflow has high assay accuracy, precision and robustness and can, therefore, be used for clinical diagnostic applications.
MeSH term(s)	Algorithms ; Computational Biology/methods ; Datasets as Topic ; High-Throughput Nucleotide Sequencing/instrumentation ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Reproducibility of Results ; Sensitivity and Specificity ; Sequence Analysis, DNA/instrumentation ; Sequence Analysis, DNA/methods ; Software ; Workflow
Language	English
Publishing date	2019-08-02
Publishing country	Italy
Document type	Journal Article ; Validation Study
ZDB-ID	605550-3
ISSN	2284-0729 ; 1128-3602 ; 0392-291X
ISSN (online)	2284-0729
ISSN	1128-3602 ; 0392-291X
DOI	10.26355/eurrev_201908_18566
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data.

Marceddu, G / Dallavilla, T / Guerri, G / Zulian, A / Marinelli, C / Bertelli, M

European review for medical and pharmacological sciences

2019 Volume 23, Issue 18, Page(s) 8139–8147

Abstract: Objective: While next generation sequencing (NGS) has become the technology of choice for clinical diagnostics, most genetic laboratories still use Sanger sequencing for orthogonal confirmation of NGS results. Previous studies have shown that when the ... ...

Abstract	Objective: While next generation sequencing (NGS) has become the technology of choice for clinical diagnostics, most genetic laboratories still use Sanger sequencing for orthogonal confirmation of NGS results. Previous studies have shown that when the quality of NGS data is high, most calls are indicated by Sanger sequencing, making confirmation redundant. We aimed at establishing a set of criteria that make it possible to distinguish NGS calls that need orthogonal confirmation from those that do not would significantly decrease the amount of work necessary to reach a diagnosis. Materials and methods: A data set of 7976 NGS calls confirmed as true or false positive by Sanger sequencing was used to train and test different machine learning (ML) approaches. By varying the size and class balance of the training dataset, we measured the performance of the different algorithms to determine the conditions under which ML is a valid approach for confirming NGS calls in a diagnostic environment. Results: Our results indicate that machine learning is a valid approach to find variant calls that need more investigation, but in order to reach the high accuracy required in a clinical environment, the training data set must include enough observations and these observations must be well-balanced between true/false positive NGS calls. Conclusions: Our results show that it is possible to integrate the diagnostic NGS validation workflow with a machine learning approach to reduce the number of Sanger confirmations of high- quality NGS calls, reducing the time and costs of diagnosis.
MeSH term(s)	Algorithms ; High-Throughput Nucleotide Sequencing ; Humans ; Machine Learning ; Reproducibility of Results ; Sequence Analysis, DNA
Language	English
Publishing date	2019-11-06
Publishing country	Italy
Document type	Journal Article
ZDB-ID	605550-3
ISSN	2284-0729 ; 1128-3602 ; 0392-291X
ISSN (online)	2284-0729
ISSN	1128-3602 ; 0392-291X
DOI	10.26355/eurrev_201909_19034
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Article ; Online: Bioinformatic analysis indicates that SARS-CoV-2 is unrelated to known artificial coronaviruses.

Dallavilla, T / Bertelli, M / Morresi, A / Bushati, V / Stuppia, L / Beccari, T / Chiurazzi, P / Marceddu, G

European review for medical and pharmacological sciences

2020 Volume 24, Issue 8, Page(s) 4558–4564

Abstract: Objective: SARS-CoV-2 is responsible for the present coronavirus pandemic and some suggestions were made about its possible artificial origin. We, therefore, compared SARS-CoV-2 with such known viruses that were prepared in the laboratory and other ... ...

Abstract	Objective: SARS-CoV-2 is responsible for the present coronavirus pandemic and some suggestions were made about its possible artificial origin. We, therefore, compared SARS-CoV-2 with such known viruses that were prepared in the laboratory and other relevant natural strains to estimate their genetic relatedness. Materials and methods: BLAST and clustalW were used to identify and align viral sequences of SARS-CoV-2 to other animal coronaviruses (human, bat, mouse, pangolin) and related artificial constructs. Phylogenetics trees were then prepared using iTOL. Results: Our study supports the notion that known artificial coronaviruses, including the chimeric SL-SHC014-MA15 synthesized in 2015, differ too much from SARS-CoV-2 to hypothesize an artificial origin of the latter. On the contrary, our data support the natural origin of the COVID-19 virus, likely derived from bats, possibly transferred to pangolins, before spreading to man. Conclusions: Speculations about the artificial origin of SARS-CoV-2 are most likely unfounded. On the contrary, when carefully handled, engineered organisms provide a unique opportunity to study biological systems in a controlled fashion. Biotechnology is a powerful tool to advance medical research and should not be abandoned because of irrational fears.
MeSH term(s)	Animals ; Betacoronavirus/classification ; COVID-19 ; Chiroptera/virology ; Computational Biology ; Coronavirus Infections ; Humans ; Mice ; Organisms, Genetically Modified ; Pandemics ; Phylogeny ; Pneumonia, Viral ; RNA, Viral/analysis ; SARS-CoV-2 ; Sequence Analysis, RNA ; Whole Genome Sequencing
Chemical Substances	RNA, Viral
Keywords	covid19
Language	English
Publishing date	2020-04-27
Publishing country	Italy
Document type	Journal Article
ZDB-ID	605550-3
ISSN	2284-0729 ; 1128-3602 ; 0392-291X
ISSN (online)	2284-0729
ISSN	1128-3602 ; 0392-291X
DOI	10.26355/eurrev_202004_21041
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Article ; Online: Location and condition based reconstruction of colon cancer microbiome from human RNA sequencing data.

Sambruni, Gaia / Macandog, Angeli D / Wirbel, Jakob / Cagnina, Danilo / Catozzi, Carlotta / Dallavilla, Tiziano / Borgo, Francesca / Fazio, Nicola / Fumagalli-Romario, Uberto / Petz, Wanda L / Manzo, Teresa / Ravenda, Simona P / Zeller, Georg / Nezi, Luigi / Schaefer, Martin H

Genome medicine

2023 Volume 15, Issue 1, Page(s) 32

Abstract: Background: The association between microbes and cancer has been reported repeatedly; however, it is not clear if molecular tumour properties are connected to specific microbial colonisation patterns. This is due mainly to the current technical and ... ...

Abstract	Background: The association between microbes and cancer has been reported repeatedly; however, it is not clear if molecular tumour properties are connected to specific microbial colonisation patterns. This is due mainly to the current technical and analytical strategy limitations to characterise tumour-associated bacteria. Methods: Here, we propose an approach to detect bacterial signals in human RNA sequencing data and associate them with the clinical and molecular properties of the tumours. The method was tested on public datasets from The Cancer Genome Atlas, and its accuracy was assessed on a new cohort of colorectal cancer patients. Results: Our analysis shows that intratumoural microbiome composition is correlated with survival, anatomic location, microsatellite instability, consensus molecular subtype and immune cell infiltration in colon tumours. In particular, we find Faecalibacterium prausnitzii, Coprococcus comes, Bacteroides spp., Fusobacterium spp. and Clostridium spp. to be strongly associated with tumour properties. Conclusions: We implemented an approach to concurrently analyse clinical and molecular properties of the tumour as well as the composition of the associated microbiome. Our results may improve patient stratification and pave the path for mechanistic studies on microbiota-tumour crosstalk.
MeSH term(s)	Humans ; Colorectal Neoplasms/genetics ; Colonic Neoplasms/genetics ; Microbiota ; Bacteria/genetics ; Sequence Analysis, RNA
Language	English
Publishing date	2023-05-02
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-023-01180-9
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Article ; Online: appMAGI: A complete laboratory information management system for clinical diagnostics.

Marceddu, Giuseppe / Dallavilla, Tiziano / Xhuvani, Aleksander / Daja, Muharrem / De Antoni, Luca / Casadei, Arianna / Bertelli, Matteo

Acta bio-medica : Atenei Parmensis

2020 Volume 91, Issue 13-S, Page(s) e2020015

Abstract: Background: The increasing demand for genetic testing for clinical diagnosis and research challenges genetic laboratory capacity to track an increasing number of patient samples through all steps of analysis, from sample collection to report generation. ...

Abstract	Background: The increasing demand for genetic testing for clinical diagnosis and research challenges genetic laboratory capacity to track an increasing number of patient samples through all steps of analysis, from sample collection to report generation. This task is usually performed with the help of a laboratory information management system (LIMS), software that makes it possible to collect, store and retrieve laboratory and sample data. To date there are no open-source options that can manage the entire analytical flow of a genetic laboratory. appMAGI seeks to include all the management aspects of a clinical diagnostic laboratory, making it simpler to process many samples while maintaining the high security and quality standards required in clinical diagnostic practice. Methods: appMAGI is written in python using Django. It is a web application that does not require local installation, making development, updates and maintenance a much easier task. appMAGI runs on the Ubuntu server and uses SQLite as engine database. Results: In this work we describe an innovative LIMS called appMAGI designed to support all aspects of a clinical diagnostic laboratory. appMAGI can track samples throughout the diagnostic workflow and NGS analysis by virtue of a customizable bioinformatics pipeline. It can handle sample non-compliance, manage laboratory stocks, help generate reports and provide insights into sample data by means of special tools. Conclusions: appMAGI is a LIMS endowed with all the features required to manage thousands of samples. Allowing efficient management of patient samples from sample collection to diagnostic report generation.
MeSH term(s)	Computer Systems ; Humans ; Information Management ; Laboratories ; Software ; Workflow
Language	English
Publishing date	2020-11-09
Publishing country	Italy
Document type	Journal Article
ZDB-ID	2114240-3
ISSN	2531-6745 ; 0392-4203
ISSN (online)	2531-6745
ISSN	0392-4203
DOI	10.23750/abm.v91i13-S.10521
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Article ; Online: Monogenic hypertension.

Precone, Vincenza / Krasi, Geraldo / Guerri, Giulia / Stuppia, Liborio / Romeo, Francesco / Perrone, Marco / Marinelli, Carla / Zulian, Alessandra / Dallavilla, Tiziano / Bertelli, Matteo

Acta bio-medica : Atenei Parmensis

2019 Volume 90, Issue 10-S, Page(s) 50–52

Abstract: Hypertension is a significant public health problem. Thirty percent of cases are caused by a single genetic mutation. Hypertension is the predominant and usually the only manifestation in monogenic hypertension Monogenic hypertension may involve ... ...

Abstract	Hypertension is a significant public health problem. Thirty percent of cases are caused by a single genetic mutation. Hypertension is the predominant and usually the only manifestation in monogenic hypertension Monogenic hypertension may involve mineralcorticoid-dependent or -independent increase in Na+ transport. Diagnosis is based on routine physical examination, blood pressure measurement and laboratory analysis of renin, aldosterone, cortisol and potassium. Genetic testing is useful for confirming diagnosis and for differential diagnosis. Monogenic hypertension has autosomal dominant or autosomal recessive inheritance.
MeSH term(s)	Aldosterone/metabolism ; Genetic Testing ; High-Throughput Nucleotide Sequencing ; Humans ; Hydrocortisone/metabolism ; Hypertension/diagnosis ; Hypertension/genetics ; Hypertension/metabolism ; Mutation/genetics ; Potassium/metabolism ; Renin/metabolism
Chemical Substances	Aldosterone (4964P6T9RB) ; Renin (EC 3.4.23.15) ; Potassium (RWP5GA015D) ; Hydrocortisone (WI4X0X7BPJ)
Language	English
Publishing date	2019-09-30
Publishing country	Italy
Document type	Journal Article ; Review
ZDB-ID	2114240-3
ISSN	2531-6745 ; 0392-4203
ISSN (online)	2531-6745
ISSN	0392-4203
DOI	10.23750/abm.v90i10-S.8759
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Article: Bioinformatic analysis indicates that SARS-CoV-2 is unrelated to known artificial coronaviruses

Dallavilla, T / Bertelli, M / Morresi, A / Bushati, V / Stuppia, L / Beccari, T / Chiurazzi, P / Marceddu, G

Eur Rev Med Pharmacol Sci

Abstract: OBJECTIVE: SARS-CoV-2 is responsible for the present coronavirus pandemic and some suggestions were made about its possible artificial origin. We, therefore, compared SARS-CoV-2 with such known viruses that were prepared in the laboratory and other ... ...

Abstract	OBJECTIVE: SARS-CoV-2 is responsible for the present coronavirus pandemic and some suggestions were made about its possible artificial origin. We, therefore, compared SARS-CoV-2 with such known viruses that were prepared in the laboratory and other relevant natural strains to estimate their genetic relatedness. MATERIALS AND METHODS: BLAST and clustalW were used to identify and align viral sequences of SARS-CoV-2 to other animal coronaviruses (human, bat, mouse, pangolin) and related artificial constructs. Phylogenetics trees were then prepared using iTOL. RESULTS: Our study supports the notion that known artificial coronaviruses, including the chimeric SL-SHC014-MA15 synthesized in 2015, differ too much from SARS-CoV-2 to hypothesize an artificial origin of the latter. On the contrary, our data support the natural origin of the COVID-19 virus, likely derived from bats, possibly transferred to pangolins, before spreading to man. CONCLUSIONS: Speculations about the artificial origin of SARS-CoV-2 are most likely unfounded. On the contrary, when carefully handled, engineered organisms provide a unique opportunity to study biological systems in a controlled fashion. Biotechnology is a powerful tool to advance medical research and should not be abandoned because of irrational fears.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #32373995
Database	COVID19

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Article ; Online: Mendelian obesity, molecular pathways and pharmacological therapies: a review.

Paolacci, S / Borrelli, A / Stuppia, L / Campanile, F C / Dallavilla, T / Krajčovič, J / Veselenyiova, D / Beccari, T / Unfer, V / Bertelli, M

European review for medical and pharmacological sciences

2019 Volume 23, Issue 3, Page(s) 1357–1378

Abstract: Objective: In this qualitative review we analyze the major pathways and mechanisms involved in the onset of genetically-determined obesity (Mendelian obesity), identifying possible pharmacological treatments and trials.: Materials and methods: We ... ...

Abstract	Objective: In this qualitative review we analyze the major pathways and mechanisms involved in the onset of genetically-determined obesity (Mendelian obesity), identifying possible pharmacological treatments and trials. Materials and methods: We searched PubMed with the keywords (obesity[Title/Abstract]) AND mutation[Title/Abstract], and OMIM with the keyword "obesity". In both cases, we selected non-syndromic Mendelian obesity. We then searched ClinicalTrials.gov with the following criteria: "recruitment status: active, not recruiting and completed"; "study type: interventional (clinical trial)"; "study results: with results"; type of intervention: "drug or dietary supplement". Results: From the PubMed and OMIM searches we obtained a total of 15 genes associated with monogenic Mendelian obesity. From ClinicalTrials.gov we retrieved 46 completed or active trials of pharmacological treatments. Conclusions: We summarized the molecular bases of Mendelian obesity and searched for any clinical trials completed or underway for the treatment of severe forms of obesity. Most Mendelian obesities are linked to dysfunctions in the leptin/melanocortin signaling pathway, and most of the possible drugs target this pathway in order to improve energy expenditure and reduce food intake.
MeSH term(s)	Anti-Obesity Agents/therapeutic use ; Clinical Trials as Topic ; Genetic Predisposition to Disease ; Humans ; Leptin/genetics ; Leptin/metabolism ; Melanocortins/genetics ; Melanocortins/metabolism ; Mutation ; Obesity, Morbid/drug therapy ; Obesity, Morbid/genetics ; Obesity, Morbid/metabolism ; Signal Transduction
Chemical Substances	Anti-Obesity Agents ; Leptin ; Melanocortins
Language	English
Publishing date	2019-03-13
Publishing country	Italy
Document type	Journal Article ; Review
ZDB-ID	605550-3
ISSN	2284-0729 ; 1128-3602 ; 0392-291X
ISSN (online)	2284-0729
ISSN	1128-3602 ; 0392-291X
DOI	10.26355/eurrev_201902_17031
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Article ; Online: CRB1-Related Cystic Maculopathy in Twins Conceived Through Heterologous Fertilization With Variant-Carrying Oocytes.

Paolacci, Stefano / Iarossi, Giancarlo / Gusson, Elena / Maltese, Paolo Enrico / Dallavilla, Tiziano / Fanelli, Francesca / Zulian, Alessandra / Cerra, Davide / Unfer, Vittorio / Marchini, Giorgio / Bertelli, Matteo

Journal of pediatric ophthalmology and strabismus

2020 Volume 57, Page(s) e19–e24

Abstract: Cystic maculopathy has been associated with genetic disorders such as retinitis pigmentosa, X-linked retinoschisis, cone dystrophy, and foveal retinoschisis. Familial foveal retinoschisis was recently described as a rare disease caused by CRB1 variants. ... ...

Abstract	Cystic maculopathy has been associated with genetic disorders such as retinitis pigmentosa, X-linked retinoschisis, cone dystrophy, and foveal retinoschisis. Familial foveal retinoschisis was recently described as a rare disease caused by CRB1 variants. The authors report the phenotype-genotype pattern of a pair of dizygotic twins with early-onset cystic maculopathy due to CRB1 pathogenic variants. The twins were conceived by heterologous fertilization with variant-carrying oocytes. The probands were monitored for a period of 4 years. Next generation sequencing of a panel of genes responsible for retinal dystrophies was performed. Both children carried three pathogenic variants in CRB1: a novel heterozygous truncating variant p.(Val855*) inherited from the father and two known heterozygous missense variants, p.[(Phe144Val; Thr745Met)], inherited from the oocyte donor. The findings confirm that CRB1 variants can be responsible for foveal retinoschisis with variable clinical expressivity ranging from schitic macular alteration to early-onset forms of cystic maculopathy. The authors highlight the importance of exome analysis of gamete donors to assess the likelihood of recessively inherited disorders by means of a prediction algorithm able to combine parent and donor exome data. [J Pediatr Ophthalmol Strabismus. 2020;57:e19-e24.].
MeSH term(s)	Child, Preschool ; Eye Proteins/genetics ; Female ; Fertilization in Vitro ; Genetic Variation ; Genotype ; Humans ; Male ; Membrane Proteins/genetics ; Mutation, Missense ; Nerve Tissue Proteins/genetics ; Oocytes/pathology ; Phenotype ; Retinoschisis/genetics ; Twins, Dizygotic
Chemical Substances	CRB1 protein, human ; Eye Proteins ; Membrane Proteins ; Nerve Tissue Proteins
Language	English
Publishing date	2020-03-12
Publishing country	United States
Document type	Case Reports ; Journal Article
ZDB-ID	800921-1
ISSN	1938-2405 ; 0191-3913
ISSN (online)	1938-2405
ISSN	0191-3913
DOI	10.3928/01913913-20200204-02
Database	MEDical Literature Analysis and Retrieval System OnLINE

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