Biology subjects

Denti, L.

Publications and source records attributed to Denti, L..

At least 19 recordsLinked to original sources

bioRxiv2026

The Genome In A Bottle HG002 assembly-based variant benchmark set enables comprehensive benchmarking of small and structural variants.

High-accuracy, high-resolution benchmark data are fundamental to improving the accuracy and generalizability of sequencing technologies and associated algorithms. Most existing benchmarks for DNA sequencing rely on mapping to a single linear reference, omitting inaccessible and highly repetitive complex genomic regions. Here, we present the Genome in a Bottle (GIAB) Consortium's HG002 v5.0q benchmark set, a more comprehensive variant benchmark derived from a fully phased, highly curated, and accurate diploid assembly of HG002. Our approach leverages recent advances in long-read sequencing and assembly to provide confident small- and structural-variant calls across previously inaccessible regions, including segmental duplications, homopolymers, tandem repeats, and complex immune loci. The v5.0 benchmark significantly expands the callable genome relative to v4.2.1, adding x200 Mbp of sequence and increasing variant detection by 18 % for small variants and 3-fold for structural variants compared to previous benchmarks. The benchmark regions include more variants in repetitive regions, including 1.2 x segmental duplications, 1.8 x tandem repeats, and 2.0 x homopolymers, compared to v4.2.1. Separate and combined small- and structural-variant benchmarks are available for three versions of the human reference genome (GRCh37, GRCh38, and CHM13). We validate the reliability of this benchmark set by comparing multiple sequencing technologies and variant calling pipelines and curating differences. The v5.0q benchmark provides a critical resource for the development and validation of next-generation sequencing technologies and analysis methods.

genomics↗

bioRxiv2026

A Csf1r lineage gives rise to dermal lymphatic endothelial cells

Lymphatic vessels are formed during embryonic and postnatal development to facilitate interstitial fluid clearance and immune regulation after birth. Their organ-specific heterogeneity in organisation and function is preceded by heterogenous origins of lymphatic endothelial cells (LECs), the main building blocks of lymphatic vessels. In the dermis, a subset of LECs was reported to arise from blood capillaries, which themselves differentiate, in part, from paraxial mesoderm. However, it is not known whether additional cell lineages contribute to the dermal LEC population. Here, we have combined transcriptomic analyses with genetic lineage tracing and wholemount immunostaining to show that 60% of LECs in the embryonic day (E) 13.5 and E15.5 dermis are derived from a cell lineage that expresses Csf1r, a marker of myeloid cells and their progeny. Csf1r lineage LECs persist in adult dermal lymphatic vasculature and are indispensable for normal lymphatic development, because Prox1 deletion within the Csf1r lineage causes dermal oedema and blood-filled lymphatic vessels. As Csf1r lineage dermal LECs do not themselves express Csf1r and also do not arise from Csf1r-expressing differentiated myeloid cells, our findings imply the existence of a Csf1r-expressing non-LEC precursor population for the majority of dermal LECs and will prompt further work to identify this cell population.

developmental biology↗

bioRxiv2025

Anyone can be the best: Impact of diverse methodologies on the evaluation of structural variant callers

Structural variants (SVs) are medium and large-scale genomic alterations that shape phenotypic diversity and disease risk. Numerous methods have been proposed for discovering SVs, however their benchmarking has been inconsistent across studies, often resulting in contradictory findings. One of the main sources of conflicting evaluation re-sults is the lack of consistency in the SV callsets used as ground truth, ranging from curated callsets released by consortia to more recent approaches that construct callsets from high-quality telomere-to-telomere de novo haplotype assemblies. The discrepancies between benchmarks are further compounded by the choice of the reference genome (GRCh37, GRCh38, and T2T-CHM13), where using T2T-CHM13reveals a different deletion/insertion profile, indicating reduced reference bias. We evaluated the performance of several state-of-the-art SV discovery methods from long-read whole-genome sequencing data and observed substantial variation in their performance and rankings, depending on the choice of ground truth, reference genome, and genomic regions used for evaluation. Counter-intuitively, the more complete reference genome T2T-CHM13does not inherently solve the problem of SV benchmarking; instead it reveals the limitations of each detection method in complex genomic regions. The substantial variation in detection accuracy across different genomic regions calls for additional caution in downstream analyses and in drawing conclusions based on predicted SVs. These findings underscore the complexity of evaluating SV detection methods and highlight the need for careful consideration and, ideally, field-standard best practices when reporting performance metrics.

bioinformatics↗

bioRxiv2025

PanSpace: Fast and Scalable Indexing for Massive Bacterial Databases

MotivationSpecies identification is a critical task in agriculture, food processing, and health-care. The rapid growth of genomic databases -- driven in part by the increasing investigation of bacterial genomes in clinical microbiology -- has outpaced the capabilities of conventional tools such as BLAST for basic search and query tasks. A key bottleneck in microbiome studies lies in building indexes that allow rapid species identification and classification from assemblies while scaling efficiently to massive resources such as the AllTheBacteria database, thus enabling large-scale analyses to be performed even on a common laptop. ResultsWe introduce PanSpace, the first convolutional neural network-based approach that leverages dense vector (embedding) indexing --- scalable to billions of embeddings --- for indexing and querying massive bacterial genome databases. PanSpace is specifically designed to classify bacterial draft assemblies. Compared to the most recent and competitive tool for this task, PanSpace requires only ~2 GB of disk space to index the AllTheBacteria database, an 8x reduction relative to existing methods. Moreover, it delivers ultra-fast query performance, processing more than 1,000 assemblies in less than two and a half minutes, while preserving the utmost accuracy of state-of-the-art approaches. AvailabilityPanSpace is available at https://github.com/pg-space/panspace.

genomics↗

bioRxiv2025

Pangenome graph augmentation from unassembled long reads

Pangenomes are becoming increasingly popular data structures for genomics analyses due to their ability to compactly represent the genetic diversity within populations. Constructing a pangenome graph, however, is still a time-consuming and expensive process. A promising approach for pangenome construction consists of progressively augmenting a pangenome graph with additional high-quality assemblies. Currently, there is no method for augmenting a pangenome graph with unassembled reads from newly sequenced samples without first aligning the reads to a reference genome and performing variant calling and genotyping on the new individuals. In this work, we present the first assembly-free and mapping-free approach for augmenting an existing pangenome graph using unassembled long reads from an individual not already present in the pangenome. Our approach consists of finding sample specific sequences in reads using efficient indexes, clustering reads corresponding to the same novel variant(s), and then building a consensus sequence to be added to the pangenome graph for each variant separately. Using simulated reads based on Human Pangenome Reference Consortium (HPRC) assemblies, we demonstrate the effectiveness of the proposed approach for progressively augmenting the pangenome with long reads, without the need for de novo assembly or predicting genetic variants of the new sample. The software is freely available at https://github.com/ldenti/palss.

bioinformatics↗

bioRxiv2024

Differential Analysis of Alternative Splicing Events in gene regions using Residual Neural Networks

Several computational methods for the differential analysis of alternative splicing (AS) events among RNA-seq samples typically rely on estimating isoform-level gene expression. However, these approaches are often error-prone due to the interplay of individual AS events, which results in different isoforms with locally similar sequences. Moreover, methods based on isoform-level quantification usually need annotated transcripts. In this work, we leverage the ability of deep learning networks to learn features from images, to propose deepSpecas, a novel method for event-based AS differential analysis between two RNA-seq samples. Our method does not rely on isoform abundance estimation, neither on a specific annotation. deepSpecas employs an image embedding scheme to represent the alignments of the two samples on the same region and utilizes a residual neural network to predict the AS events possibly expressed within that region. To our knowledge deepSpecas is the first deep learning approach for performing an event-based AS analysis of RNA-seq samples. To validate deepSpecas, we also address the lack of high quality AS benchmark datasets. For this purpose, we manually curated a set of regions exhibiting AS events. These regions were used for training our model and for comparing our method with state-of-the-art event-based AS analysis tools. Our results highlight that deepSpecas achieves higher precision at the expense of a small reduction in sensitivity. The tool and the manually curated regions are available at https://github.com/sciccolella/deepSpecas.

bioinformatics↗

bioRxiv2024

PangeBlocks: customized construction of pangenome graphs via maximal blocks

BackgroundThe construction of a pangenome graph is a fundamental task in pangenomics. A natural theoretical question is how to formalize the computational problem of building an optimal pangenome graph, making explicit the underlying optimization criterion and the set of feasible solutions. Current approaches build a pangenome graph with some heuristics, without assuming some explicit optimization criteria. Thus it is unclear how a specific optimization criterion affects the graph topology and downstream analysis, like read mapping and variant calling. MethodsIn this paper, by leveraging the notion of maximal block in a Multiple Sequence Alignment (MSA), we reframe the pangenome graph construction problem as an exact cover problem on blocks called Minimum Weighted Block Cover (MWBC). Then we propose an Integer Linear Programming (ILP) formulation for the MWBC problem that allows us to study the most natural objective functions for building a graph. ResultsWe provide an implementation of the ILP approach for solving the MWBC and we evaluate it on SARS-CoV-2 complete genomes, showing how different objective functions lead to pangenome graphs that have different properties, hinting that the specific downstream task can drive the graph construction phase. ConclusionWe show that a customized construction of a pangenome graph based on selecting objective functions has a direct impact on the resulting graphs. In particular, our formalization of the MWBC problem, based on finding an optimal subset of blocks covering an MSA, paves the way to novel practical approaches to graph representations of an MSA where the user can guide the construction.

bioinformatics↗

bioRxiv2024

Diverse somatic Transformer and sex chromosome karyotype pathways regulate gene expression in Drosophila gonad development

The somatic sex determination gene transformer (tra) is required for the highly sexually dimorphic development of most somatic cells, including those of the gonads. In addition, somatic tra is required for the germline development even though it is not required for sex determination within germ cells. Germ cell autonomous gene expression is also necessary for their sex determination. To understand the interplay between these signals, we compared the phenotype and gene expression of larval wild-type gonads and the sex-transformed tra gonads. XX larval ovaries transformed into testes were dramatically smaller than wild-type, with significant reductions in germ cell number, likely due to altered geometry of the stem cell niche. Additionally, there was a defect in progression into spermatocyte stages. XY larval testes transformed into ovaries had excessive germ cells, possibly due to the earlier onset of cell division. We suggest that germ cells are neither fully female nor male following somatic sex transformation, with certain pathways characteristic of each sex expressed in tra mutants. We found multiple patterns of somatic and germline gene expression control exclusively due to tra, exclusively due to sex chromosome karyotype, but usually due to a combination of these factors showing tra and sex chromosome karyotype pathways regulate gene expression during Drosophila gonad development.

developmental biology↗

bioRxiv2024

A Pax3 lineage gives rise to transient haematopoietic progenitors

During embryonic development, muscle tissues, skin, and a subset of vascular endothelial cells arise from Pax3-expressing embryonic progenitors defined as paraxial mesoderm. By contrast, haemogenic potential is well established for extra-embryonic mesoderm and intra-embryonic lateral plate mesoderm which do not express Pax3. To date, it is not known whether the haematopoietic system also contains Pax3 lineage cells. Here, we show that the mouse foetal liver and foetal circulation contain a transient population of Pax3 lineage cells with hallmarks of haematopoietic progenitors and the potential to generate both myeloid and erythroid cells. We propose that Pax3 lineage haematopoietic cells should be investigated to better understand normal haematopoietic development from different mesodermal derivatives. Further, genetic alterations of Pax3 lineage haematopoietic cells should be investigated for their potential to cause haematopoietic malignancies.

developmental biology↗

bioRxiv2024

NRP1-expressing myeloid cells promote arteriogenesis in the ischemic limb

Peripheral arterial disease can cause limb threatening blood flow restriction, requiring amputation in up to a third of patients despite contemporary treatments. Stimulating new blood vessel growth in ischemic limbs using growth factors such as VEGF-A or supplying mixed cell populations via autologous transplantation has been investigated as a therapy for surgically intractable cases, but to date has proven ineffective in randomised controlled clinical studies. To identify more potent pro-arteriogenic cell populations, we have investigated VEGF-A responsive myeloid cell populations in a mouse model of severe hindlimb ischemia. We found that NRP1 ablation from monocytes and macrophages impaired arteriogenesis in the adductor muscle and flow recovery in the injured limb. Vice versa, the exogenous delivery of NRP1-expressing (but not NRP1-negative) macrophages enhanced arteriogenesis in the adductor and flow recovery in the ischemic limb in a VEGF signalling-dependent manner. Further, patient-derived NRP1-expressing monocytes promoted vascular morphogenesis ex vivo. As the levels of circulating NRP1-expressing monocytes were raised in patients with limb ischemia, the therapeutic delivery of autologous NRP1-expressing monocytes could be explored as a treatment for critical limb ischemia.

pathology↗

bioRxiv2023

Targeting NRP1 with EG00229 induces neurovascular permeability

NRP1 is a therapeutic target for inhibiting vascular endothelial growth factor (VEGF)-induced blood vessel dysfunction. The small molecule EG00229 was designed to inhibit VEGF binding to NRP1 and reduce pathological blood vessel growth. However, it is unknown whether EG00229 could also be used to reduce VEGF164-induced vascular leakage, which often exacerbates ischemic diseases due to VEGF upregulation. Here, we show that prior treatment with EG00229 prevents VEGF164-induced vascular permeability signalling, but, unexpectedly, also find that EG00229 increased rather than inhibited vascular leakage. Thus, EG00229 increased vascular leakage either when added alone or concurrently with VEGF164, both in perfused retinal explants and across primary brain EC monolayers. This EG00229-induced vascular leakage was not an off-target effect, because it relied on endothelial NRP1 expression and NRP1s VEGF164 binding pocket, yet was independent of VEGFR1 and VEGFR2. Moreover, EG00229 activated molecular events typical of VEGF164-induced paracellular permeability, including p38 MAP kinase (p38) and SRC family kinase (SFK) phosphorylation as well as CDH5 rearrangement in endothelial junctions. Investigating EG00229-induced signalling therefore helps elucidate NRP1-dependent mechanisms of paracellular permeability induction and might help identifying new approaches to modulate the neurovascular barrier.

physiology↗

bioRxiv2023

Differential quantification of alternative splicing events on spliced pangenome graphs

Pangenomes are becoming a powerful framework to perform many bioinformatics analyses taking into account the genetic variability of a population, thus reducing the bias introduced by a single reference genome. With the wider diffusion of pangenomes, integrating genetic variability with transcriptome diversity is becoming a natural extension that demands specific methods for its exploration. In this work, we extend the notion of spliced pangenomes to that of annotated spliced pangenomes; this allows us to introduce a formal definition of Alternative Splicing (AS) events on a graph structure. To investigate the usage of graph pangenomes for the quantification of AS events across conditions, we developed pantas, the first pangenomic method for the detection and differential analysis of AS events from short RNA-Seq reads. A comparison with state-of-the-art linear reference-based approaches proves that pantas achieves competitive accuracy, making spliced pangenomes effective for conducting AS events quantification and opening future directions for the analysis of population-based transcriptomes. pantas is open-source and freely available at github.com/algolab/pantas. Author summaryThe ever increasing availability of complete genomes is advancing our comprehension of many biological mechanisms and is enhancing the knowledge we can extract from sequencing data. Pange3PM ESTnome graphs are a convenient way to represent multiple genomes and the genetic variability within a population. Integrating genetic variability with transcriptome diversity can improve our understanding of alternative splicing, a regulation mechanism which allows a single gene to code for multiple proteins. However, many unanswered questions are limiting our comprehension of the relationship between genetic and trancriptomic variations. With this work, we start to fill this gap by introducing pantas, the first approach based on pangenome graphs for the detection and differential quantification of alternative splicing events. A comparison with state-of-the-art approaches based on linear genome prove that pangenome graphs can be effectively used to perform such an analysis. By integrating genetic and transcriptome variability in a single structure, pantas can pave the way to next generation bioinformatic approaches for the accurate analysis of the relations between genetic variations and alternative splicing aberrations.

bioinformatics↗

bioRxiv2023

ESGq: Alternative Splicing events quantification across conditions based on Event Splicing Graphs

Alternative Splicing (AS) is a regulation mechanism that contributes to protein diversity and is also associated to many diseases and tumors. Alternative splicing events quantification from RNA-Seq reads is a crucial step in understanding this complex biological mechanism. However, tools for AS events detection and quantification show inconsistent results. This reduces their reliability in fully capturing and explaining alternative splicing. We introduce ESGq, a novel approach for the quantification of AS events across conditions based on read alignment against Event Splicing Graphs. By comparing ESGq to two state-of-the-art tools on real RNA-Seq data, we validate its performance and evaluate the statistical correlation of the results. ESGq is freely available at https://github.com/AlgoLab/ESGq.

bioinformatics↗

bioRxiv2022

Tamoxifen exacerbates morbidity and mortality in mice receiving medetomidine anaesthesia

Tamoxifen-induced CreER-LoxP recombination is often used to induce spatiotemporally controlled gene deletion in genetically modified mice. Prior work has shown that tamoxifen and tamoxifen-induced CreER activation can have off-target effects that should be controlled. However, it has not yet been reported whether tamoxifen administration, independently of CreER expression, interacts adversely with commonly used anaesthetic drugs such as medetomidine or its enantiomer dexmedetomidine in mice. Here we report a high incidence of urinary plug formation and morbidity in male mice on a mixed C57Bl6/J and 129/SvEv background when tamoxifen treatment was followed by ketamine-medetomidine anaesthesia. Medetomidine is therefore contra-indicated for male mice after tamoxifen treatment. As dexmedetomidine causes morbidity and mortality in male mice at higher rates than medetomidine even without tamoxifen treatment, our findings suggest that dexmedetomidine is not a suitable alternative for anaesthesia of male mice after tamoxifen treatment. We conclude that the choice of anaesthetic drug needs to be carefully evaluated in studies using male mice that have undergone tamoxifen treatment for inducing CreER-LoxP recombination.

genetics↗

bioRxiv2022

RecGraph: adding recombinations to sequence-to-graph alignments

The transition towards graph pangenomes is posing several new challenging questions, most notably how to extend the classical notion of read alignment from a sequence-to-sequence to a sequence-to-graph setting. Especially on variation graphs, where paths corresponding to individual genomes are labeled, notions of alignments that are strongly inspired by the classical ones are usually able to capture only variations that can be expressed by mismatches or gaps, such as SNPs or short insertions and deletions. On the other hand the recent investigation of pangenomes at bacterial scale (Colquhoun et al, 2021) shows that most tools are tailored for human pangenomes and are not suited to bacteria which exhibit, among other characteristics, a larger variability. Such variability leads to the need for incorporating a greater flexibility when computing an alignment. In this paper, we extend the usual notion of sequence-to-graph alignment by including recombinations among the variations that explicitly represented and evaluated in an alignment. From a computational modeling point of view, a recombination corresponds to identifying a new path of the variation graph which is a mosaic of two different paths, possibly joined by a new arc. We provide a dynamic programming algorithm for computing an optimal alignment that allows recombinations with an affine penalty. We have implemented our approach with the tool RecGraph and we have analyzed its accuracy over some over some bacterial pangenome graphs.

bioinformatics↗

bioRxiv2022

Improved structural variant discovery in hard-to-call regions using sample-specific string detection from accurate long reads

Structural variants (SVs) account for a large amount of sequence variability across genomes and play an important role in human genomics and precision medicine. Despite intense efforts over the years, the discovery of SVs in individuals remains challenging due to the diploid and highly repetitive structure of the human genome, and by the presence of SVs that vastly exceed sequencing read lengths. However, the recent introduction of low-error long-read sequencing technologies such as PacBio HiFi may finally enable to overcome these barriers. Here we present SVDSS, a novel hybrid method for discovery of SVs from long-read sequencing technologies (e.g., PacBio HiFi) that combines and effectively leverages mapping-free, mapping-based and assembly-based methodologies for overall superior SV discovery performance. Our experiments on several human samples show that SVDSS outperforms state-of-the-art mapping-based methods for discovery of insertion and deletion SVs in PacBio HiFi reads and achieves significant improvements in calling SVs in repetitive regions of the genome. SVDSS is open source and publicly available at: https://github.com/Parsoa/SVDSS

bioinformatics↗

bioRxiv2021

Comparative genome analysis using sample-specific string detection in accurate long reads

MotivationComparative genome analysis of two or more whole-genome sequenced (WGS) samples is at the core of most applications in genomics. These include discovery of genomic differences segregating in population, case-control analysis in common diseases, and rare disorders. With the current progress of accurate long-read sequencing technologies (e.g., circular consensus sequencing from PacBio sequencers) we can dive into studying repeat regions of genome (e.g., segmental duplications) and hard-to-detect variants (e.g., complex structural variants). ResultsWe propose a novel framework for addressing the comparative genome analysis by discovery of strings that are specific to one genome ("samples-specific" strings). We have developed an accurate and efficient novel method for discovery of samples-specific strings between two groups of WGS samples. The proposed approach will give us the ability to perform comparative genome analysis without the need to map the reads and is not hindered by shortcomings of the reference genome. We show that the proposed approach is capable of accurately finding samples-specific strings representing nearly all variation (> 98%) reported across pairs or trios of WGS samples using accurate long reads (e.g., PacBio HiFi data). AvailabilityThe proposed tool is publicly available at https://github.com/Parsoa/PingPong.

bioinformatics↗

bioRxiv2021

KIT is required for fetal liver erythropoiesis but dispensable for angiogenesis

Blood vessels are fundamental to sustain organ growth and tissue metabolism. In the mouse embryo, endothelial cell (EC) progenitors almost concomitantly give rise to the first blood vessels in the yolk sac and the large vessels of the embryo proper. Thereafter, the vascular network expands by angiogenesis to vascularize developing organs such as the brain. Although the first blood cells form in the yolk sac before blood vessels have assembled, consecutive waves of hematopoietic progenitors subsequently bud from hemogenic endothelium located within the wall of yolk sac and large intraembryonic vessels in a process termed endothelial to hematopoietic transition (endoHT). The receptor tyrosine kinase KIT is required for late embryonic erythropoiesis, but KIT is also expressed earlier in the hemogenic endothelium, in hematopoietic progenitors that arise via endoHT from hemogenic endothelium and non-hemogenic ECs, such as in the brain. However, it remains unclear whether KIT has essential roles in early hematopoiesis or even blood vessel growth. Here, we have combined transcriptomic analysis to delineate Kit expression with the analysis of knockout mice to show that KIT is expressed during but dispensable for yolk sac endoHT or brain angiogenesis but required for transient definitive erythropoiesis in the fetal liver.

developmental biology↗