Silvestro G. Conticello
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View article: MODOMICS: a database of RNA modifications and related information. 2025 update and 20th anniversary
MODOMICS: a database of RNA modifications and related information. 2025 update and 20th anniversary Open
MODOMICS is the reference database of RNA modifications and related information, integrating chemical, biochemical, structural, and functional data. In this 2025 update, marking the 20th anniversary of MODOMICS, the database has been signi…
View article: Unlocking the regulatory code of RNA: launching the Human RNome Project
Unlocking the regulatory code of RNA: launching the Human RNome Project Open
The human RNome, the complete set of RNA molecules in human cells, arises through complex processing and includes diverse molecular species. While research traditionally focuses on four canonical nucleotide residues, the RNome, encompassin…
View article: Human-like<i>APOBEC3</i>gene expression and anti-viral responses following replacement of mouse<i>Apobec3</i>with the 7-gene human<i>APOBEC3</i>locus
Human-like<i>APOBEC3</i>gene expression and anti-viral responses following replacement of mouse<i>Apobec3</i>with the 7-gene human<i>APOBEC3</i>locus Open
The seven human APOBEC3 (hA3) genes encode polynucleotide cytidine deaminases that play vital roles in restricting replication of viruses and retrotransposons. However, off-target A3 deamination of the cellular genome is a major source of …
View article: Unraveling C-to-U RNA editing events from direct RNA sequencing
Unraveling C-to-U RNA editing events from direct RNA sequencing Open
In mammals, RNA editing events involve the conversion of adenosine (A) in inosine (I) by ADAR enzymes or the hydrolytic deamination of cytosine (C) in uracil (U) by the APOBEC family of enzymes, mostly APOBEC1. RNA editing has a plethora o…
View article: COVID-19 annual update: a narrative review
COVID-19 annual update: a narrative review Open
Three and a half years after the pandemic outbreak, now that WHO has formally declared that the emergency is over, COVID-19 is still a significant global issue. Here, we focus on recent developments in genetic and genomic research on COVID…
View article: DNA Deamination Is Required for Human APOBEC3A-Driven Hepatocellular Carcinoma In Vivo
DNA Deamination Is Required for Human APOBEC3A-Driven Hepatocellular Carcinoma In Vivo Open
Although the APOBEC3 family of single-stranded DNA cytosine deaminases is well-known for its antiviral factors, these enzymes are rapidly gaining attention as prominent sources of mutation in cancer. APOBEC3′s signature single-base substit…
View article: DNA Deamination Is Required for Human APOBEC3A-Driven Hepatocellular Carcinoma In Vivo
DNA Deamination Is Required for Human APOBEC3A-Driven Hepatocellular Carcinoma In Vivo Open
Although the APOBEC3 family of single-stranded DNA cytosine deaminases are well-known as antiviral factors, these enzymes are rapidly gaining attention as prominent sources of mutation in cancer. APOBEC3 signature single base substitutions…
View article: Identification and characterization of novel ETV4 splice variants in prostate cancer
Identification and characterization of novel ETV4 splice variants in prostate cancer Open
ETV4, one of ETS proteins overexpressed in prostate cancer, promotes migration, invasion, and proliferation in prostate cells. This study identifies a series of previously unknown ETV4 alternatively spliced transcripts in human prostate ce…
View article: Unraveling C-to-U RNA editing events from direct RNA sequencing
Unraveling C-to-U RNA editing events from direct RNA sequencing Open
In mammals, RNA editing events involve the conversion of adenosine (A) in inosine (I) by ADAR enzymes or the hydrolytic deamination of cytosine (C) in uracil (U) by the APOBEC family of enzymes, mostly APOBEC1. RNA editing has a plethora o…
View article: Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Datasets accompanying the paper https://doi.org/10.1101/2021.10.18.464684
View article: Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Datasets accompanying the paper https://doi.org/10.1101/2021.10.18.464684
View article: Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Datasets accompanying the paper https://doi.org/10.1101/2021.10.18.464684
View article: Additional file 3 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Additional file 3 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Additional file 3. Table S2. External WGBS sample information.
View article: Additional file 4 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Additional file 4 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Additional file 4. Table S3. Tumor vs. normal differences for 4-mer end motifs.
View article: Additional file 5 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Additional file 5 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Additional file 5. ichorCNA plots for all cfNano and matched Illumina WGS samples.
View article: Additional file 2 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Additional file 2 of Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
Additional file 2. Table S1. cfNano sample information and statistics.
View article: MODOMICS: a database of RNA modification pathways. 2021 update
MODOMICS: a database of RNA modification pathways. 2021 update Open
The MODOMICS database has been, since 2006, a manually curated and centralized resource, storing and distributing comprehensive information about modified ribonucleosides. Originally, it only contained data on the chemical structures of mo…
View article: Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing Open
The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for clinical sequencing. We recently demonstrated ONT sha…
View article: raw-modifcation-calls-fixed-format.zip
raw-modifcation-calls-fixed-format.zip Open
Methylation calling of nanopore sWGS data. 5mC was called using DeepSignal Version: 0.1.8, with model.CpG.R9.4_1D.human_hx1.bn17.sn360.v0.1.7+/bn_17.sn_360.epoch_9.ckpt, which was downloaded from the DeepSignal Google Drive (https://drive.…
View article: Additional file 2 of Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients
Additional file 2 of Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients Open
Additional file 2: Supplementary tables. Spreadsheet file including analyzed data and statistics. Table S1. Case series and run statistics. Table S2. Performance of NanoGLADIATOR pipeline in “nocontrol” and “paired” mode. Table S3. Correla…
View article: bedsFromBAMsForGEO.zip
bedsFromBAMsForGEO.zip Open
Filtering of alignments for ichorCNA and fragmentomic analysis. Samtools (Version 1.9) was used to filter BAM alignments, unmapped reads, secondary and supplementary reads, reads with Minimap2 mapping quality less than 20 as in https://doi…
View article: grouped-beta-value_bedgraph.zip
grouped-beta-value_bedgraph.zip Open
From the modified DeepSignal modification_call output described above (in “raw-modifcation-calls-fixed-format.zip”), we then extracted the methylation calls for each (strand-specific) CpG from column 9 (called_label field), and calculated …
View article: nkx2.1.incluster13_distalPeaks_PAL.bed.highestScoreMotifs
nkx2.1.incluster13_distalPeaks_PAL.bed.highestScoreMotifs Open
NKX2-1 transcription factor binding site (TFBS) analysis. First, we used HOMER to identify predicted NKX2-1 binding sites (using the HOMER built in matrix “nkx2.1.motif”) across the GRCh38 genome, and removed any site within the ENCODE bla…
View article: SegmentationResultsMartignano2021.zip
SegmentationResultsMartignano2021.zip Open
Segmentation results from our previous CNV analysis (https://doi.org/10.1186/s12943-021-01327-5) were converted from GRCh37 to GRCh38 using NCBI remap API and divided into non-overlapping 10Mb bins. All genomic coordinates are in GRCh38.