Nurses' intention to leave, nurse workload and in-hospital patient mortality in Italy: A descriptive and regression study.

Higher nurse-to-patient ratios are associated with poor patient care and adverse nurse outcomes, including emotional exhaustion and intention to leave. We examined the effect of nurses' intention to leave and nurse-patient workload on in-hospital patient mortality in Italy. A multicentered descriptive and regression study using clinical data of patients aged 50 years or older with a hospital stay of at least two days admitted to surgical wards linked with nurse variables including workload and education levels, work environment, job satisfaction, intention to leave, nurses' perception of quality and safety of care, and emotional exhaustion. The final dataset included 15 hospitals, 1046 nurses, and 37,494 patients. A 10 % increase in intention to leave and an increase of one unit in nurse-patient workload increased likelihood of inpatient hospital mortality by 14 % (odds ratio 1.14; 1.02-1.27 95 % CI) and 3.4 % (odds ratio 1.03; 1.00-1.06 95 % CI), respectively. No other studies have reported a significant association between intention to leave and patient mortality. To improve patient outcomes, the healthcare system in Italy needs to implement policies on safe human resources policy stewardship, leadership, and governance to ensure nurse wellbeing, higher levels of safety, and quality nursing care.

Accurate sequencing of DNA motifs able to form alternative (non-B) structures.

Approximately 13% of the human genome at certain motifs have the potential to form noncanonical (non-B) DNA structures (e.g., G-quadruplexes, cruciforms, and Z-DNA), which regulate many cellular processes but also affect the activity of polymerases and helicases. Because sequencing technologies use these enzymes, they might possess increased errors at non-B structures. To evaluate this, we analyzed error rates, read depth, and base quality of Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT) sequencing at non-B motifs. All technologies showed altered sequencing success for most non-B motif types, although this could be owing to several factors, including structure formation, biased GC content, and the presence of homopolymers. Single-nucleotide mismatch errors had low biases in HiFi and ONT for all non-B motif types but were increased for G-quadruplexes and Z-DNA in all three technologies. Deletion errors were increased for all non-B types but Z-DNA in Illumina and HiFi, as well as only for G-quadruplexes in ONT. Insertion errors for non-B motifs were highly, moderately, and slightly elevated in Illumina, HiFi, and ONT, respectively. Additionally, we developed a probabilistic approach to determine the number of false positives at non-B motifs depending on sample size and variant frequency, and applied it to publicly available data sets (1000 Genomes, Simons Genome Diversity Project, and gnomAD). We conclude that elevated sequencing errors at non-B DNA motifs should be considered in low-read-depth studies (single-cell, ancient DNA, and pooled-sample population sequencing) and in scoring rare variants. Combining technologies should maximize sequencing accuracy in future studies of non-B DNA.

Rescuing biologically relevant consensus regions across replicated samples.

BACKGROUND: Protein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites. RESULTS: We rescue weak binding sites using MSPC, which efficiently exploits replicates to lower the threshold required to identify a site while keeping a low false-positive rate, and we compare it to IDR, a widely used post-processing method for identifying highly reproducible peaks across replicates. We observe several master transcription regulators (e.g., SP1 and GATA3) and HDAC2-GATA1 regulatory networks on rescued regions in K562 cell line. CONCLUSIONS: We argue the biological relevance of weak binding sites and the information they add when rescued by MSPC. An implementation of the proposed extended MSPC methodology and the scripts to reproduce the performed analysis are freely available at https://genometric.github.io/MSPC/ ; MSPC is distributed as a command-line application and an R package available from Bioconductor ( https://doi.org/doi:10.18129/B9.bioc.rmspc ).

Advanced age increases frequencies of de novo mitochondrial mutations in macaque oocytes and somatic tissues.

Mutations in mitochondrial DNA (mtDNA) contribute to multiple diseases. However, how new mtDNA mutations arise and accumulate with age remains understudied because of the high error rates of current sequencing technologies. Duplex sequencing reduces error rates by several orders of magnitude via independently tagging and analyzing each of the two template DNA strands. Here, using duplex sequencing, we obtained high-quality mtDNA sequences for somatic tissues (liver and skeletal muscle) and single oocytes of 30 unrelated rhesus macaques, from 1 to 23 y of age. Sequencing single oocytes minimized effects of natural selection on germline mutations. In total, we identified 17,637 tissue-specific de novo mutations. Their frequency increased ∼3.5-fold in liver and ∼2.8-fold in muscle over the ∼20 y assessed. Mutation frequency in oocytes increased ∼2.5-fold until the age of 9 y, but did not increase after that, suggesting that oocytes of older animals maintain the quality of their mtDNA. We found the light-strand origin of replication (OriL) to be a hotspot for mutation accumulation with aging in liver. Indeed, the 33-nucleotide-long OriL harbored 12 variant hotspots, 10 of which likely disrupt its hairpin structure and affect replication efficiency. Moreover, in somatic tissues, protein-coding variants were subject to positive selection (potentially mitigating toxic effects of mitochondrial activity), the strength of which increased with the number of macaques harboring variants. Our work illuminates the origins and accumulation of somatic and germline mtDNA mutations with aging in primates and has implications for delayed reproduction in modern human societies.

Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy.

We investigate patterns of COVID-19 mortality across 20 Italian regions and their association with mobility, positivity, and socio-demographic, infrastructural and environmental covariates. Notwithstanding limitations in accuracy and resolution of the data available from public sources, we pinpoint significant trends exploiting information in curves and shapes with Functional Data Analysis techniques. These depict two starkly different epidemics; an "exponential" one unfolding in Lombardia and the worst hit areas of the north, and a milder, "flat(tened)" one in the rest of the country-including Veneto, where cases appeared concurrently with Lombardia but aggressive testing was implemented early on. We find that mobility and positivity can predict COVID-19 mortality, also when controlling for relevant covariates. Among the latter, primary care appears to mitigate mortality, and contacts in hospitals, schools and workplaces to aggravate it. The techniques we describe could capture additional and potentially sharper signals if applied to richer data.

Non-B DNA: a major contributor to small- and large-scale variation in nucleotide substitution frequencies across the genome.

Approximately 13% of the human genome can fold into non-canonical (non-B) DNA structures (e.g. G-quadruplexes, Z-DNA, etc.), which have been implicated in vital cellular processes. Non-B DNA also hinders replication, increasing errors and facilitating mutagenesis, yet its contribution to genome-wide variation in mutation rates remains unexplored. Here, we conducted a comprehensive analysis of nucleotide substitution frequencies at non-B DNA loci within noncoding, non-repetitive genome regions, their ±2 kb flanking regions, and 1-Megabase windows, using human-orangutan divergence and human single-nucleotide polymorphisms. Functional data analysis at single-base resolution demonstrated that substitution frequencies are usually elevated at non-B DNA, with patterns specific to each non-B DNA type. Mirror, direct and inverted repeats have higher substitution frequencies in spacers than in repeat arms, whereas G-quadruplexes, particularly stable ones, have higher substitution frequencies in loops than in stems. Several non-B DNA types also affect substitution frequencies in their flanking regions. Finally, non-B DNA explains more variation than any other predictor in multiple regression models for diversity or divergence at 1-Megabase scale. Thus, non-B DNA substantially contributes to variation in substitution frequencies at small and large scales. Our results highlight the role of non-B DNA in germline mutagenesis with implications to evolution and genetic diseases.

Human L1 Transposition Dynamics Unraveled with Functional Data Analysis.

Long INterspersed Elements-1 (L1s) constitute >17% of the human genome and still actively transpose in it. Characterizing L1 transposition across the genome is critical for understanding genome evolution and somatic mutations. However, to date, L1 insertion and fixation patterns have not been studied comprehensively. To fill this gap, we investigated three genome-wide data sets of L1s that integrated at different evolutionary times: 17,037 de novo L1s (from an L1 insertion cell-line experiment conducted in-house), and 1,212 polymorphic and 1,205 human-specific L1s (from public databases). We characterized 49 genomic features-proxying chromatin accessibility, transcriptional activity, replication, recombination, etc.-in the ±50 kb flanks of these elements. These features were contrasted between the three L1 data sets and L1-free regions using state-of-the-art Functional Data Analysis statistical methods, which treat high-resolution data as mathematical functions. Our results indicate that de novo, polymorphic, and human-specific L1s are surrounded by different genomic features acting at specific locations and scales. This led to an integrative model of L1 transposition, according to which L1s preferentially integrate into open-chromatin regions enriched in non-B DNA motifs, whereas they are fixed in regions largely free of purifying selection-depleted of genes and noncoding most conserved elements. Intriguingly, our results suggest that L1 insertions modify local genomic landscape by extending CpG methylation and increasing mononucleotide microsatellite density. Altogether, our findings substantially facilitate understanding of L1 integration and fixation preferences, pave the way for uncovering their role in aging and cancer, and inform their use as mutagenesis tools in genetic studies.

Age-related accumulation of de novo mitochondrial mutations in mammalian oocytes and somatic tissues.

Mutations create genetic variation for other evolutionary forces to operate on and cause numerous genetic diseases. Nevertheless, how de novo mutations arise remains poorly understood. Progress in the area is hindered by the fact that error rates of conventional sequencing technologies (1 in 100 or 1,000 base pairs) are several orders of magnitude higher than de novo mutation rates (1 in 10,000,000 or 100,000,000 base pairs per generation). Moreover, previous analyses of germline de novo mutations examined pedigrees (and not germ cells) and thus were likely affected by selection. Here, we applied highly accurate duplex sequencing to detect low-frequency, de novo mutations in mitochondrial DNA (mtDNA) directly from oocytes and from somatic tissues (brain and muscle) of 36 mice from two independent pedigrees. We found mtDNA mutation frequencies 2- to 3-fold higher in 10-month-old than in 1-month-old mice, demonstrating mutation accumulation during the period of only 9 mo. Mutation frequencies and patterns differed between germline and somatic tissues and among mtDNA regions, suggestive of distinct mutagenesis mechanisms. Additionally, we discovered a more pronounced genetic drift of mitochondrial genetic variants in the germline of older versus younger mice, arguing for mtDNA turnover during oocyte meiotic arrest. Our study deciphered for the first time the intricacies of germline de novo mutagenesis using duplex sequencing directly in oocytes, which provided unprecedented resolution and minimized selection effects present in pedigree studies. Moreover, our work provides important information about the origins and accumulation of mutations with aging/maturation and has implications for delayed reproduction in modern human societies. Furthermore, the duplex sequencing method we optimized for single cells opens avenues for investigating low-frequency mutations in other studies.

A High-Resolution View of Adaptive Event Dynamics in a Plasmid.

Coadaptation between bacterial hosts and plasmids frequently results in adaptive changes restricted exclusively to host genome leaving plasmids unchanged. To better understand this remarkable stability, we transformed naïve Escherichia coli cells with a plasmid carrying an antibiotic-resistance gene and forced them to adapt in a turbidostat environment. We then drew population samples at regular intervals and subjected them to duplex sequencing-a technique specifically designed for identification of low-frequency mutations. Variants at ten sites implicated in plasmid copy number control emerged almost immediately, tracked consistently across the experiment's time points, and faded below detectable frequencies toward the end. This variation crash coincided with the emergence of mutations on the host chromosome. Mathematical modeling of trajectories for adaptive changes affecting plasmid copy number showed that such mutations cannot readily fix or even reach appreciable frequencies. We conclude that there is a strong selection against alterations of copy number even if it can provide a degree of growth advantage. This incentive is likely rooted in the complex interplay between mutated and wild-type plasmids constrained within a single cell and underscores the importance of understanding of intracellular plasmid variability.

Functional data analysis for computational biology.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Long-read sequencing technology indicates genome-wide effects of non-B DNA on polymerization speed and error rate.

DNA conformation may deviate from the classical B-form in ∼13% of the human genome. Non-B DNA regulates many cellular processes; however, its effects on DNA polymerization speed and accuracy have not been investigated genome-wide. Such an inquiry is critical for understanding neurological diseases and cancer genome instability. Here, we present the first simultaneous examination of DNA polymerization kinetics and errors in the human genome sequenced with Single-Molecule Real-Time (SMRT) technology. We show that polymerization speed differs between non-B and B-DNA: It decelerates at G-quadruplexes and fluctuates periodically at disease-causing tandem repeats. Analyzing polymerization kinetics profiles, we predict and validate experimentally non-B DNA formation for a novel motif. We demonstrate that several non-B motifs affect sequencing errors (e.g., G-quadruplexes increase error rates), and that sequencing errors are positively associated with polymerase slowdown. Finally, we show that highly divergent G4 motifs have pronounced polymerization slowdown and high sequencing error rates, suggesting similar mechanisms for sequencing errors and germline mutations.

IWTomics: testing high-resolution sequence-based 'Omics' data at multiple locations and scales.

Summary: With increased generation of high-resolution sequence-based 'Omics' data, detecting statistically significant effects at different genomic locations and scales has become key to addressing several scientific questions. IWTomics is an R/Bioconductor package (integrated in Galaxy) that, exploiting sophisticated Functional Data Analysis techniques (i.e. statistical techniques that deal with the analysis of curves), allows users to pre-process, visualize and test these data at multiple locations and scales. The package provides a friendly, flexible and complete workflow that can be employed in many genomic and epigenomic applications. Availability and implementation: IWTomics is freely available at the Bioconductor website (http://bioconductor.org/packages/IWTomics) and on the main Galaxy instance (https://usegalaxy.org/). Supplementary information: Supplementary data are available at Bioinformatics online.

Integration and Fixation Preferences of Human and Mouse Endogenous Retroviruses Uncovered with Functional Data Analysis.

Endogenous retroviruses (ERVs), the remnants of retroviral infections in the germ line, occupy ~8% and ~10% of the human and mouse genomes, respectively, and affect their structure, evolution, and function. Yet we still have a limited understanding of how the genomic landscape influences integration and fixation of ERVs. Here we conducted a genome-wide study of the most recently active ERVs in the human and mouse genome. We investigated 826 fixed and 1,065 in vitro HERV-Ks in human, and 1,624 fixed and 242 polymorphic ETns, as well as 3,964 fixed and 1,986 polymorphic IAPs, in mouse. We quantitated >40 human and mouse genomic features (e.g., non-B DNA structure, recombination rates, and histone modifications) in ±32 kb of these ERVs' integration sites and in control regions, and analyzed them using Functional Data Analysis (FDA) methodology. In one of the first applications of FDA in genomics, we identified genomic scales and locations at which these features display their influence, and how they work in concert, to provide signals essential for integration and fixation of ERVs. The investigation of ERVs of different evolutionary ages (young in vitro and polymorphic ERVs, older fixed ERVs) allowed us to disentangle integration vs. fixation preferences. As a result of these analyses, we built a comprehensive model explaining the uneven distribution of ERVs along the genome. We found that ERVs integrate in late-replicating AT-rich regions with abundant microsatellites, mirror repeats, and repressive histone marks. Regions favoring fixation are depleted of genes and evolutionarily conserved elements, and have low recombination rates, reflecting the effects of purifying selection and ectopic recombination removing ERVs from the genome. In addition to providing these biological insights, our study demonstrates the power of exploiting multiple scales and localization with FDA. These powerful techniques are expected to be applicable to many other genomic investigations.

Peak shape clustering reveals biological insights.

BACKGROUND: ChIP-seq experiments are widely used to detect and study DNA-protein interactions, such as transcription factor binding and chromatin modifications. However, downstream analysis of ChIP-seq data is currently restricted to the evaluation of signal intensity and the detection of enriched regions (peaks) in the genome. Other features of peak shape are almost always neglected, despite the remarkable differences shown by ChIP-seq for different proteins, as well as by distinct regions in a single experiment. RESULTS: We hypothesize that statistically significant differences in peak shape might have a functional role and a biological meaning. Thus, we design five indices able to summarize peak shapes and we employ multivariate clustering techniques to divide peaks into groups according to both their complexity and the intensity of their coverage function. In addition, our novel analysis pipeline employs a range of statistical and bioinformatics techniques to relate the obtained peak shapes to several independent genomic datasets, including other genome-wide protein-DNA maps and gene expression experiments. To clarify the meaning of peak shape, we apply our methodology to the study of the erythroid transcription factor GATA-1 in K562 cell line and in megakaryocytes. CONCLUSIONS: Our study demonstrates that ChIP-seq profiles include information regarding the binding of other proteins beside the one used for precipitation. In particular, peak shape provides new insights into cooperative transcriptional regulation and is correlated to gene expression.