Non-canonical DNA in human and other ape telomere-to-telomere genomes.

Non-canonical (non-B) DNA structures-e.g., bent DNA, hairpins, G-quadruplexes, Z-DNA, etc.

Mitochondrial DNA mutations in human oocytes undergo frequency-dependent selection but do not increase with age.

Mitochondria, cellular powerhouses, harbor DNA (mtDNA) inherited from the mothers. MtDNA mutations can cause diseases, yet whether they increase with age in human germline cells-oocytes-remains understudied. Here, using highly accurate duplex sequencing of full-length mtDNA, we detected mutations in single oocytes, blood, and saliva in women between 20 and 42 years of age.

funBIalign: a hierachical algorithm for functional motif discovery based on mean squared residue scores.

Unlabelled: Motif discovery is gaining increasing attention in the domain of functional data analysis. Functional motifs are typical "shapes" or "patterns" that recur multiple times in different portions of a single curve and/or in misaligned portions of multiple curves. In this paper, we define functional motifs using an additive model and we propose for their discovery and evaluation.

Evolutionary Dynamics of G-Quadruplexes in Human and Other Great Ape Telomere-to-Telomere Genomes.

G-quadruplexes (G4s) are non-canonical DNA structures that can form at approximately 1% of the human genome. G4s contribute to point mutations and structural variation and thus facilitate genomic instability. They play important roles in regulating replication, transcription, and telomere maintenance, and some of them evolve under purifying selection.

Methylation profiles at birth linked to early childhood obesity.

Childhood obesity represents a significant global health concern and identifying risk factors is crucial for developing intervention programs. Many 'omics' factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months.

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.

Constructing a polygenic risk score for childhood obesity using functional data analysis.

Obesity is a highly heritable condition that affects increasing numbers of adults and, concerningly, of children. However, only a small fraction of its heritability has been attributed to specific genetic variants. These variants are traditionally ascertained from genome-wide association studies (GWAS), which utilize samples with tens or hundreds of thousands of individuals for whom a single summary measurement (e.

Honey bee colony loss linked to parasites, pesticides and extreme weather across the United States.

Honey bee (Apis mellifera) colony loss is a widespread phenomenon with important economic and biological implications, whose drivers are still an open matter of investigation. We contribute to this line of research through a large-scale, multi-variable study combining multiple publicly accessible data sources. Specifically, we analyzed quarterly data covering the contiguous United States for the years 2015-2021, and combined open data on honey bee colony status and stressors, weather data, and land use.

An explainable model of host genetic interactions linked to COVID-19 severity.

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity.

Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems.

Contemporary high-throughput experimental and surveying techniques give rise to ultrahigh-dimensional supervised problems with sparse signals; that is, a limited number of observations (), each with a very large number of covariates ( >> ), only a small share of which is truly associated with the response. In these settings, major concerns on computational burden, algorithmic stability, and statistical accuracy call for substantially reducing the feature space by eliminating redundant covariates before the use of any sophisticated statistical analysis. Along the lines of (Fan and Lv, 2008) and other model- and correlation-based feature screening methods, we propose a model-free procedure called (CIS).

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.

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.

Simultaneous feature selection and outlier detection with optimality guarantees.

Biomedical research is increasingly data rich, with studies comprising ever growing numbers of features. The larger a study, the higher the likelihood that a substantial portion of the features may be redundant and/or contain contamination (outlying values). This poses serious challenges, which are exacerbated in cases where the sample sizes are relatively small.

Metabolomic profiling of stool of two-year old children from the INSIGHT study reveals links between butyrate and child weight outcomes.

Background: Metabolomic analysis is commonly used to understand the biological underpinning of diseases such as obesity. However, our knowledge of gut metabolites related to weight outcomes in young children is currently limited.

Objectives: To (1) explore the relationships between metabolites and child weight outcomes, (2) determine the potential effect of covariates (e.

Selection and thermostability suggest G-quadruplexes are novel functional elements of the human genome.

Approximately 1% of the human genome has the ability to fold into G-quadruplexes (G4s)-noncanonical strand-specific DNA structures forming at G-rich motifs. G4s regulate several key cellular processes (e.g.

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment.

The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the "phase 2" of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens' privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking.

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.

MIP-BOOST: Efficient and Effective Feature Selection for Linear Regression.

Recent advances in mathematical programming have made Mixed Integer Optimization a competitive alternative to popular regularization methods for selecting features in regression problems. The approach exhibits unquestionable foundational appeal and versatility, but also poses important challenges. Here we propose MIP-BOOST, a revision of standard Mixed Integer Programming feature selection that reduces the computational burden of tuning the critical sparsity bound parameter and improves performance in the presence of feature collinearity and of signals that vary in nature and strength.

Knowledge and social relatedness shape research portfolio diversification.

Scientific discovery is shaped by scientists' choices and thus by their career patterns. The increasing knowledge required to work at the frontier of science makes it harder for an individual to embark on unexplored paths. Yet collaborations can reduce learning costs-albeit at the expense of increased coordination costs.

Learning the properties of adaptive regions with functional data analysis.

Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data.

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.

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).