Biology subjects

Santuari, L.

Publications and source records attributed to Santuari, L..

6 recordsLinked to original sources

bioRxiv2025

Evaluation of the Ultima Genomics UG 100™ sequencing platform for clinical services

The steep reduction in the cost of genome sequencing started with the introduction of Solexa Sequencing-By-Synthesis technology in 2006 has plateaued recently due to technical limitations in the use of closed flowcells and to the cost of reagents. The Ultima Genomics UG 100 is the first sequencing machine to lower the cost of human genome sequencing to 80$. However, technical limitations in resolving long homopolymer regions undermine the application of this technology to short variant calling in clinical settings. Here, we evaluate the ability of UG 100 to identify short variants in relation to its suitability for clinical accreditation, by comparing it with the Illumina NovaSeq 6000 Systems platform. We focus specifically on the small variant calling performance in long homopolymer regions, both genome-wide and in relation to a set of medically-relevant genes that are challenging to sequence. Our analysis aims at supporting clinicians in determining whether the UG 100 platform is well-suited for their studies, and to guide clinical sequencing centers in evaluating the adoption of this emerging technology.

bioinformatics↗

bioRxiv2024

Integrating knowledge, omics and AI to develop patient-specific virtual avatars

We propose a method for creating personalized regulatory networks, enabling the development of virtual avatars for cancer patients, with patient-derived xenograft (PDX) models as a test case. Starting from a Prior Knowledge Network (PKN) based on the hallmarks of cancer, we constructed gene networks that are contextualized to each sample by integrating sample-specific gene expression data. These networks were optimized using a genetic algorithm to align with individual molecular profiles, focusing on key cancer-related processes. Following network optimization, we employed Graph Convolutional Networks (GCNs) to classify samples based the structures and interactions of their individualized network models and molecular profiles. This personalized approach provides insights into drug responses and helps predict treatment outcomes, offering a path toward more targeted cancer therapies. Author summaryCancer treatment can be more effective when therapies are personalized to each patients unique molecular profile. In this study, we introduce a method to create virtual avatars of cancer patients by personalizing regulatory networks using patient-derived xenograft (PDX) models as a proof of concept. Starting from known cancer hallmarks, we developed individualized gene networks for each sample by leveraging their specific gene expression data. These networks were refined with an optimization process to match the distinct molecular characteristics of each sample. By applying advanced machine learning, specifically Graph Convolutional Networks (GCNs), we classified these personalized models to better understand likely drug responses and predict treatment outcomes. This approach brings us closer to tailoring cancer therapies to individual patients, potentially improving treatment success by targeting key cancer pathways unique to each person.

systems biology↗

bioRxiv2024

sv-channels: filtering genomic deletions using one-dimensional convolutional neural networks

Structural variant (SV) detection in human genomes using short-read sequencing data is hindered by false positives, arising from sequencing and mapping artifacts that mimic genuine SV signals. Despite advances, state-of-the-art SV callers like GRIDSS and Manta exhibit trade-offs between precision and recall, with GRIDSS offering the highest precision and Manta excelling in recall. To address these limitations, we introduce sv-channels, a novel deep learning model designed to improve the precision of SV detection by leveraging read information at call sites. Our method effectively reduces false positives in Mantas deletion callsets, achieving precision that surpasses GRIDSS while maintaining a recall rate comparable to Manta. This represents a significant improvement in SV detection, leveraging Mantas high recall through deep learning and paving the way for more accurate genomic analyses. The sv-channels codebase is openly accessible on GitHub at https://github.com/GooglingTheCancerGenome/sv-channels enabling further research and application in the field.

bioinformatics↗

bioRxiv2024

Seq2scFv: a toolkit for the comprehensive analysis of display libraries from long-read sequencing platforms

Antibodies have emerged as the leading class of biotherapeutics, yet traditional screening methods face significant time and resource challenges in identifying lead candidates. Integrating highthroughput sequencing with computational approaches marks a pivotal advancement in antibody discovery, expanding the antibody space to explore. In this context, a major breakthrough has been the full-length sequencing of single-chain variable fragments (scFvs) used in in vitro display libraries. However, few tools address the task of annotating the paired heavy and light chain variable domains (VH and VL), which is the primary advantage of full-scFv sequencing. To address this methodological gap, we introduce Seq2scFv, a novel open-source toolkit designed for analyzing in vitro display libraries from long-read sequencing platforms. Seq2scFv facilitates the identification and thorough characterization of V(D)J recombination in both VH and VL regions. In addition to providing annotated scFvs, translated sequences and numbered chains, Seq2scFv enables linker inference and characterization, sequence encoding with unique identifiers and quantification of identical sequences across selection rounds, thereby simplifying enrichment identification. With its versatile and standalone functionality, we anticipate that the implementation of Seq2scFv tools in antibody discovery pipelines will efficiently expedite the full characterization of display libraries and potentially facilitate the identification of high-affinity antibody candidates.

immunology↗

bioRxiv2020

The transcription and export complex THO/TREX contributes to transcription termination in plants

Transcription termination has important regulatory functions, impacting mRNA stability, localization and translation potential. Failure to appropriately terminate transcription can also lead to read-through transcription and the synthesis of antisense RNAs which can have profound impact on gene expression. The Transcription-Export (THO/TREX) protein complex plays an important role in coupling transcription with splicing and export of mRNA. However, little is known about the role of the THO/TREX complex in the control of transcription termination. In this work, we show that two proteins of the THO/TREX complex, namely TREX COMPONENT 1 (TEX1 or THO3) and HYPER RECOMBINATION1 (HPR1 or THO1) contribute to the correct transcription termination at several loci in Arabidopsis thaliana. We first demonstrate this by showing defective termination in tex1 and hpr1 mutants at the nopaline synthase (NOS) terminator present in a T-DNA inserted between exon 1 and 3 of the PHO1 locus in the pho1-7 mutant. Read-through transcription beyond the NOS terminator and splicing-out of the T-DNA resulted in the generation of a near full-length PHO1 mRNA (minus exon 2) in the tex1 pho1-7 and hpr1 pho1-7 double mutants, with enhanced production of a truncated PHO1 protein that retained phosphate export activity. Consequently, the strong reduction of shoot growth associated with the severe phosphate deficiency of the pho1-7 mutant was alleviated in the tex1 pho1-7 and hpr1 pho1-7 double mutants. Additionally, we show that RNA termination defects in tex1 and hpr1 mutants leads to 3UTR extensions in several plant genes. These results demonstrate that THO/TREX complex contributes to the regulation of transcription termination. Author summaryProduction of messenger RNAs (mRNAs) involves numerous steps including initiation of transcription, elongation, splicing, termination, as well as export out of the nucleus. All these steps are highly coordinated and failure in any steps has a profound impact on the level and identity of mRNAs produced. The THO/TREX protein complex is associated with nascent RNAs and contributes to several mRNA biogenesis steps, including splicing and export. However, the contribution of the THO/TREX complex to mRNA termination was poorly defined. We have identified a role for two components of the THO/TREX complex, namely the proteins TEX1 and HPR1, in the control of transcription termination in the plant Arabidopsis thaliana. We show that the tex1 and hpr1 mutants have defects in terminating mRNA at the nopaline synthase (NOS) terminator found in T-DNA insertion mutants leading to the transcriptional read-through pass the NOS terminator. We also show that tex1 and hpr1 mutants have defects in mRNA termination at several endogenous genes, leading to the production of 3UTR extensions. Together, these results highlight a role for the THO/TREX complex in mRNA termination.

plant biology↗

bioRxiv2017

Parallel loss of symbiosis genes in relatives of nitrogen-fixing non-legume Parasponia

Rhizobium nitrogen-fixing nodules are a well-known trait of legumes, but nodules also occur in other plant lineages either with rhizobium or the actinomycete Frankia as microsymbiont. The widely accepted hypothesis is that nodulation evolved independently multiple times, with only a few losses. However, insight in the evolutionary trajectory of nodulation is lacking. We conducted comparative studies using Parasponia (Cannabaceae), the only non-legume able to establish nitrogen fixing nodules with rhizobium. This revealed that Parasponia and legumes utilize a large set of orthologous symbiosis genes. Comparing genomes of Parasponia and its non-nodulating relative Trema did not reveal specific gene duplications that could explain a recent gain of nodulation in Parasponia. Rather, Trema and other non-nodulating species in the Order Rosales show evidence of pseudogenization or loss of key symbiosis genes. This demonstrates that these species have lost the potential to nodulate. This finding challenges a long-standing hypothesis on evolution of nitrogen-fixing symbioses, and has profound implications for translational approaches aimed at engineering nitrogen-fixing nodules in crop plants.

plant biology↗