Search

Most cancers re-activate telomerase to maintain telomere length and thus acquire immortality. Activating telomerase promoter mutations are found in many cancers, including melanoma. However, it is unclear when and if telomerase is strictly required during tumorigenesis. We combined the telomerase mutant (tert -/- ) with two established zebrafish melanoma models. We show that tert -/- melanomas initially develop with similar incidence and invasiveness to tert +/+ tumors. However, they eventually decline in growth and regress. Late tert -/- tumors exhibit reduced cell proliferation, increased apoptosis, and melanocyte differentiation. Notably, these tumors show enhanced immune cell infiltration and can resume growth when transplanted into immunocompromised hosts. We propose that telomerase is required for melanoma in zebrafish, albeit at later stages of progression, to sustain tumor growth while avoiding immune rejection and regression. Thus, the absence of telomerase restricts melanoma through tumor-autonomous mechanisms (cell-cycle arrest, apoptosis, and melanocyte differentiation) and a non-tumor-autonomous mechanism (immune rejection)., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder, a pipeline for constructing pangenome graphs without bias or exclusion. The PanGenome Graph Builder uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events and infer phylogenetic relationships., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Shared genetic polymorphisms between populations and species can be ascribed to ancestral variation or to more recent gene flow. Here, we mapped shared polymorphisms in Saccharomyces cerevisiae and its sister species Saccharomyces paradoxus, which diverged 4-6 million years ago. We used a dense map of single-nucleotide diagnostic markers (mean distance 15.6 base pairs) in 1,673 sequenced S. cerevisiae isolates to catalogue 3,852 sequence blocks (≥5 consecutive markers) introgressed from S. paradoxus, with most being recent and clade-specific. The highly diverged wild Chinese S. cerevisiae lineages were depleted of introgressed blocks but retained an excess of individual ancestral polymorphisms derived from incomplete lineage sorting, perhaps due to less dramatic population bottlenecks. In the non-Chinese S. cerevisiae lineages, we inferred major hybridization events and detected cases of overlapping introgressed blocks across distinct clades due to either shared histories or convergent evolution. We experimentally engineered, in otherwise isogenic backgrounds, the introgressed PAD1-FDC1 gene pair that independently arose in two S. cerevisiae clades and revealed that it increases resistance against diverse antifungal drugs. Overall, our study retraces the histories of divergence and secondary contacts across S. cerevisiae and S. paradoxus populations and unveils a functional outcome., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Molecular phylogenetics studies the evolutionary relationships among the individuals of a population through their biological sequences. It may provide insights about the origin and the evolution of viral diseases, or highlight complex evolutionary trajectories. A key task is inferring phylogenetic trees from any type of sequencing data, including raw short reads. Yet, several tools require pre-processed input data e.g. from complex computational pipelines based on de novo assembly or from mappings against a reference genome. As sequencing technologies keep becoming cheaper, this puts increasing pressure on designing methods that perform analysis directly on their outputs. From this viewpoint, there is a growing interest in alignment-, assembly-, and reference-free methods that could work on several data including raw reads data., Results: We present phyBWT2, a newly improved version of phyBWT (Guerrini et al. in 22nd International Workshop on Algorithms in Bioinformatics (WABI) 242:23-12319, 2022). Both of them directly reconstruct phylogenetic trees bypassing both the alignment against a reference genome and de novo assembly. They exploit the combinatorial properties of the extended Burrows-Wheeler Transform (eBWT) and the corresponding eBWT positional clustering framework to detect relevant blocks of the longest shared substrings of varying length (unlike the k-mer-based approaches that need to fix the length k a priori). As a result, they provide novel alignment-, assembly-, and reference-free methods that build partition trees without relying on the pairwise comparison of sequences, thus avoiding to use a distance matrix to infer phylogeny. In addition, phyBWT2 outperforms phyBWT in terms of running time, as the former reconstructs phylogenetic trees step-by-step by considering multiple partitions, instead of just one partition at a time, as previously done by the latter., Conclusions: Based on the results of the experiments on sequencing data, we conclude that our method can produce trees of quality comparable to the benchmark phylogeny by handling datasets of different types (short reads, contigs, or entire genomes). Overall, the experiments confirm the effectiveness of phyBWT2 that improves the performance of its previous version phyBWT, while preserving the accuracy of the results., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Pangenomes provide access to an accurate representation of the genetic diversity of species, both in terms of sequence polymorphisms and structural variants (SVs). Here we generated the Saccharomyces cerevisiae Reference Assembly Panel (ScRAP) comprising reference-quality genomes for 142 strains representing the species' phylogenetic and ecological diversity. The ScRAP includes phased haplotype assemblies for several heterozygous diploid and polyploid isolates. We identified circa (ca.) 4,800 nonredundant SVs that provide a broad view of the genomic diversity, including the dynamics of telomere length and transposable elements. We uncovered frequent cases of complex aneuploidies where large chromosomes underwent large deletions and translocations. We found that SVs can impact gene expression near the breakpoints and substantially contribute to gene repertoire evolution. We also discovered that horizontally acquired regions insert at chromosome ends and can generate new telomeres. Overall, the ScRAP demonstrates the benefit of a pangenome in understanding genome evolution at population scale., (© 2023. The Author(s).)

Hybrids between diverged lineages contain novel genetic combinations but an impaired meiosis often makes them evolutionary dead ends. Here, we explore to what extent an aborted meiosis followed by a return-to-growth (RTG) promotes recombination across a panel of 20 Saccharomyces cerevisiae and S. paradoxus diploid hybrids with different genomic structures and levels of sterility. Genome analyses of 275 clones reveal that RTG promotes recombination and generates extensive regions of loss-of-heterozygosity in sterile hybrids with either a defective meiosis or a heavily rearranged karyotype, whereas RTG recombination is reduced by high sequence divergence between parental subgenomes. The RTG recombination preferentially arises in regions with low local heterozygosity and near meiotic recombination hotspots. The loss-of-heterozygosity has a profound impact on sexual and asexual fitness, and enables genetic mapping of phenotypic differences in sterile lineages where linkage analysis would fail. We propose that RTG gives sterile yeast hybrids access to a natural route for genome recombination and adaptation., (© 2021. The Author(s).)

Mutations, recombinations, and genome duplications may promote genetic diversity and trigger evolutionary processes. However, quantifying these events in diploid hybrid genomes is challenging. Here, we present an integrated experimental and computational workflow to accurately track the mutational landscape of yeast diploid hybrids (MuLoYDH) in terms of single-nucleotide variants, small insertions/deletions, copy-number variants, aneuploidies, and loss-of-heterozygosity. Pairs of haploid Saccharomyces parents were combined to generate ancestor hybrids with phased genomes and varying levels of heterozygosity. These diploids were evolved under different laboratory protocols, in particular mutation accumulation experiments. Variant simulations enabled the efficient integration of competitive and standard mapping of short reads, depending on local levels of heterozygosity. Experimental validations proved the high accuracy and resolution of our computational approach. Finally, applying MuLoYDH to four different diploids revealed striking genetic background effects. Homozygous Saccharomyces cerevisiae showed a ∼4-fold higher mutation rate compared with its closely related species S. paradoxus. Intraspecies hybrids unveiled that a substantial fraction of the genome (∼250 bp per generation) was shaped by loss-of-heterozygosity, a process strongly inhibited in interspecies hybrids by high levels of sequence divergence between homologous chromosomes. In contrast, interspecies hybrids exhibited higher single-nucleotide mutation rates compared with intraspecies hybrids. MuLoYDH provided an unprecedented quantitative insight into the evolutionary processes that mold diploid yeast genomes and can be generalized to other genetic systems., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

The Oxford Nanopore Technologies MinION is a new device, based on nanopore sequencing that is able to generate reads of tens of kilobases in length with faster sequencing time with respect to other platforms. To evaluate the capability of nanopore data to be exploited for resequencing analyses we used the largest MinION data set to date and we compared with Illumina and Pacific Biosciences technologies. By using five different mapping approaches we estimated that the global sequencing error rate of MinION reads, mainly caused by inserted and deleted bases, is around 11%. The study of error distribution showed that substituted, inserted and deleted bases are not randomly distributed along the reads, but mainly occur in specific nucleotide patterns, generating a significant number of genomic loci that can be misclassified as false-positive variants. With 40× sequencing coverage, MinION data can produce at best around one false substitution and insertion every 10-50 kb, and one false deletion every 1000 bp, making use of this technology still challenging for small-sized variant discovery. We also analyzed depth of coverage distribution and we demonstrated that nanopore sequencing is a uniform process that generates sequences randomly and independently without classical sources of bias such as GC-content and mappability. Owing to these properties, the MinION data can be readily used to detect genomic regions involved in copy number variants with high accuracy, outperforming other state-of-the-art sequencing methods in terms of both sensitivity and specificity., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Chiari malformation type I (CMI) is a congenital abnormality of the cranio-cerebral junction with an estimated incidence of 1 in 1280. CMI is characterized by underdevelopment of the occipital bone and posterior fossa (PF) and consequent cerebellar tonsil herniation. The presence for a genetic basis to CMI is supported by many lines of evidence. The cellular and molecular mechanisms leading to CM1 are poorly understood. The occipital bone formation is dependent on complex interactions between genes and molecules with pathologies resulting from disruption of this delicate process. Whole-exome sequencing of affected and not affected individuals from two Italian families with non-isolated CMI was undertaken. Single-nucleotide and short insertion-deletion variants were prioritized using KGGSeq knowledge-based platform. We identified three heterozygous missense variants: DKK1 c.121G>A (p.(A41T)) in the first family, and the LRP4 c.2552C>G (p.(T851R)) and BMP1 c.941G>A (p.(R314H)) in the second family. The variants were located at highly conserved residues, segregated with the disease, but they were not observed in 100 unaffected in-house controls. DKK1 encodes for a potent soluble WNT inhibitor that binds to LRP5 and LRP6, and is itself regulated by bone morphogenetic proteins (BMPs). DKK1 is required for embryonic head development and patterning. LRP4 is a novel osteoblast expressed receptor for DKK1 and a WNT and BMP 4 pathways integrator. Screening of DKK1 in a cohort of 65 CMI sporadic patients identified another missense variant, the c.359G>T (p.(R120L)), in two unrelated patients. These findings implicated the WNT signaling in the correct development of the cranial mesenchyme originating the PF.

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the performance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 outperforms other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprecedented resolution. EXCAVATOR2 is freely available at http://sourceforge.net/projects/excavator2tool/., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Bilateral perisylvian polymicrogyria (BPP), the most common form of regional polymicrogyria, causes the congenital bilateral perisylvian syndrome, featuring oromotor dysfunction, cognitive impairment, and epilepsy. The causes of BPP are heterogeneous, but only a few genetic causes have been reported. The aim of this study was to identify additional genetic causes of BPP and characterise their frequency in this population., Methods: Children (aged ≤18 years) with polymicrogyria were enrolled into our research programme from July, 1980, to October, 2015, at two centres (Florence, Italy, and Seattle, WA, USA). We obtained samples (blood and saliva) throughout this period at both centres and did whole-exome sequencing on DNA from eight trios (two parents and one affected child) with BPP in 2014. After the identification of mosaic PIK3R2 mutations in two of these eight children, we performed targeted screening of PIK3R2 by two methods in a cohort of 118 children with BPP. First, we performed targeted sequencing of the entire PIK3R2 gene by single molecule molecular inversion probes (smMIPs) on 38 patients with BPP with normal to large head size. Second, we did amplicon sequencing of the recurrent PIK3R2 mutation (Gly373Arg) in 80 children with various types of polymicrogyria including BPP. One additional patient had clinical whole-exome sequencing done independently, and was included in this study because of the phenotypic similarity to our cohort., Findings: We identified a mosaic mutation (Gly373Arg) in a regulatory subunit of the PI3K-AKT-mTOR pathway, PIK3R2, in two children with BPP. Of the 38 patients with BPP and normal to large head size who underwent targeted next-generation sequencing by smMIPs, we identified constitutional and mosaic PIK3R2 mutations in 17 additional children. In parallel, one patient had the recurrent PIK3R2 mutation identified by clinical whole-exome sequencing. Seven of these 20 patients had BPP alone, and 13 had BPP in association with features of the megalencephaly-polymicrogyria-polydactyly-hydrocephalus (MPPH) syndrome. 19 patients had the same mutation (Gly373Arg), and one had a nearby missense mutation (Lys376Glu). Mutations were constitutional in 12 patients and mosaic in eight patients. In patients with mosaic mutations, we noted substantial variation in alternate (mutant) allele levels, ranging from ten (3%) of 377 reads to 39 (37%) of 106 reads, equivalent to 5-73% of cells analysed. Levels of mosaicism varied from undetectable to 37 (17%) of 216 reads in blood-derived DNA compared with 2030 (29%) of 6889 reads to 275 (43%) of 634 reads in saliva-derived DNA., Interpretation: Constitutional and mosaic mutations in the PIK3R2 gene are associated with developmental brain disorders ranging from BPP with a normal head size to the MPPH syndrome. The phenotypic variability and low-level mosaicism, which challenge conventional molecular methods, have important implications for genetic testing and counselling., Funding: US National Institutes of Health., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools - and their underlying algorithms - designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication - with particular emphasis on human genetics and copy number variants - for researchers involved in the investigation of these genomic events.

Background: By examining the genotype calls generated by the 1000 Genomes Project we discovered that the human reference genome GRCh37 contains almost 20,000 loci in which the reference allele has never been observed in healthy individuals and around 70,000 loci in which it has been observed only in the heterozygous state., Results: We show that a large fraction of this rare reference allele (RRA) loci belongs to coding, functional and regulatory elements of the genome and could be linked to rare Mendelian disorders as well as cancer. We also demonstrate that classical germline and somatic variant calling tools are not capable to recognize the rare allele when present in these loci. To overcome such limitations, we developed a novel tool, named RAREVATOR, that is able to identify and call the rare allele in these genomic positions. By using a small cancer dataset we compared our tool with two state-of-the-art callers and we found that RAREVATOR identified more than 1,500 germline and 22 somatic RRA variants missed by the two methods and which belong to significantly mutated pathways., Conclusions: These results show that, to date, the investigation of around 100,000 loci of the human genome has been missed by re-sequencing experiments based on the GRCh37 assembly and that our tool can fill the gap left by other methods. Moreover, the investigation of the latest version of the human reference genome, GRCh38, showed that although the GRC corrected almost all insertions and a small part of SNVs and deletions, a large number of functionally relevant RRAs still remain unchanged. For this reason, also future resequencing experiments, based on GRCh38, will benefit from RAREVATOR analysis results. RAREVATOR is freely available at http://sourceforge.net/projects/rarevator .

Motivation: Runs of homozygosity (ROH) are sizable chromosomal stretches of homozygous genotypes, ranging in length from tens of kilobases to megabases. ROHs can be relevant for population and medical genetics, playing a role in predisposition to both rare and common disorders. ROHs are commonly detected by single nucleotide polymorphism (SNP) microarrays, but attempts have been made to use whole-exome sequencing (WES) data. Currently available methods developed for the analysis of uniformly spaced SNP-array maps do not fit easily to the analysis of the sparse and non-uniform distribution of the WES target design., Results: To meet the need of an approach specifically tailored to WES data, we developed [Formula: see text], an original algorithm based on heterogeneous hidden Markov model that incorporates inter-marker distances to detect ROH from WES data. We evaluated the performance of [Formula: see text] to correctly identify ROHs on synthetic chromosomes and examined its accuracy in detecting ROHs of different length (short, medium and long) from real 1000 genomes project data. [Formula: see text] turned out to be more accurate than GERMLINE and PLINK, two state-of-the-art algorithms, especially in the detection of short and medium ROHs., Availability and Implementation: [Formula: see text] is a collection of bash, R and Fortran scripts and codes and is freely available at https://sourceforge.net/projects/h3m2/., Contact: albertomagi@gmail.com, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Glioblastoma (GBM) is a very aggressive and lethal brain tumor with poor prognosis. Despite new treatment strategies, patients' median survival is still less than 1 year in most cases. Few studies have focused exclusively on this disease in children and most of our understanding of the disease process and its clinical outcome has come from studies on malignant gliomas in childhood, combining children with the diagnosis of GBM with other pediatric patients harboring high grade malignant tumors other than GBM. In this study we investigated, using array-CGH platforms, children (median age of 9 years) affected by GBM (WHO-grade IV). We identified recurrent Copy Number Alterations demonstrating that different chromosome regions are involved, in various combinations. These observations suggest a condition of strong genomic instability. Since cancer is an acquired disease and inherited factors play a significant role, we compared for the first time the constitutional Copy Number Variations with the Copy Number Alterations found in tumor biopsy. We speculate that genes included in the recurrent 9p21.3 and 16p13.3 deletions and 1q32.1-q44 duplication play a crucial role for tumorigenesis and/or progression. In particular we suggest that the A2BP1 gene (16p13.3) is one possible culprit of the disease. Given the rarity of the disease, the poor quality and quantity of bioptic material and the scarcity of data in the literature, our findings may better elucidate the genomic background of these tumors. The recognition of candidate genes underlying this disease could then improve treatment strategies for this devastating tumor.

We developed a novel software tool, EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.

In this article, we investigate the role of connectivity in promoting coherent activity in excitatory neural networks. In particular, we would like to understand if the onset of collective oscillations can be related to a minimal average connectivity and how this critical connectivity depends on the number of neurons in the networks. For these purposes, we consider an excitatory random network of leaky integrate-and-fire pulse coupled neurons. The neurons are connected as in a directed Erdös-Renyi graph with average connectivity scaling as a power law with the number of neurons in the network. The scaling is controlled by a parameter γ, which allows to pass from massively connected to sparse networks and therefore to modify the topology of the system. At a macroscopic level, we observe two distinct dynamical phases: an asynchronous state corresponding to a desynchronized dynamics of the neurons and a regime of partial synchronization (PS) associated with a coherent periodic activity of the network. At low connectivity, the system is in an asynchronous state, while PS emerges above a certain critical average connectivity (c). For sufficiently large networks, (c) saturates to a constant value suggesting that a minimal average connectivity is sufficient to observe coherent activity in systems of any size irrespectively of the kind of considered network: sparse or massively connected. However, this value depends on the nature of the synapses: reliable or unreliable. For unreliable synapses, the critical value required to observe the onset of macroscopic behaviors is noticeably smaller than for reliable synaptic transmission. Due to the disorder present in the system, for finite number of neurons we have inhomogeneities in the neuronal behaviors, inducing a weak form of chaos, which vanishes in the thermodynamic limit. In such a limit, the disordered systems exhibit regular (non chaotic) dynamics and their properties correspond to that of a homogeneous fully connected network for any γ-value. Apart for the peculiar exception of sparse networks, which remain intrinsically inhomogeneous at any system size.

Motivation: The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data., Results: Here we face the many aspects that cover the detection of CNVs by using read count approach. We first study the characteristics and systematic biases of read count distributions, focusing on the normalization methods designed for removing these biases. Subsequently, we compare the algorithms designed to detect the boundaries of CNVs and we investigate the ability of read count data to predict the exact number of DNA copy. Finally, we review the tools publicly available for analysing read count data. To better understand the state of the art of read count approaches, we compare the performance of the three most widely used sequencing technologies (Illumina Genome Analyzer, Roche 454 and Life Technologies SOLiD) in all the analyses that we perform.

Predicting the biological function of all the genes of an organism is one of the fundamental goals of computational system biology. In the last decade, high-throughput experimental methods for studying the functional interactions between gene products (GPs) have been combined with computational approaches based on Bayesian networks for data integration. The result of these computational approaches is an interaction network with weighted links representing connectivity likelihood between two functionally related GPs. The weighted network generated by these computational approaches can be used to predict annotations for functionally uncharacterized GPs. Here we introduce Weighted Network Predictor (WNP), a novel algorithm for function prediction of biologically uncharacterized GPs. Tests conducted on simulated data show that WNP outperforms other 5 state-of-the-art methods in terms of both specificity and sensitivity and that it is able to better exploit and propagate the functional and topological information of the network. We apply our method to Saccharomyces cerevisiae yeast and Arabidopsis thaliana networks and we predict Gene Ontology function for about 500 and 10000 uncharacterized GPs respectively.

Diblock semifluorinated n-alkanes can form aggregates and gels in fluorinated solvents. We have investigated the thermal behavior of binary mixtures comprising F(CF(2))(8)(CH(2))(16)H and fluorinated solvents. The solvents were perfluorohexane, perfluoroheptane, perfluorooctane, perfluorooctyl bromide, perfluorodecalin, and perfluorotributylamine. The phase diagrams were used to calculate the activity coefficients of the two components and the main excess thermodynamic functions. The solubility and self-assembly behavior of F(8)H(16) in the fluorinated solvents are related to the different solute-solvent dispersion interactions that depend on the polarizabilities and ionization potentials of the interacting species, and on the structural properties of the solvent.

In systems characterized by a rough potential-energy landscape, local energetic minima and saddles define a network of metastable states whose topology strongly influences the dynamics. Changes in temperature, causing the merging and splitting of metastable states, have nontrivial effects on such networks and must be taken into account. We do this by means of a recently proposed renormalization procedure. This method is applied to analyze the topology of the network of metastable states for different polypeptidic sequences in a minimalistic polymer model. A smaller spectral dimension emerges as a hallmark of stability of the global energy minimum and highlights a nonobvious link between dynamic and thermodynamic properties.