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.
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. The different spatio-temporal resolutions of these data are addressed through an up-scaling approach that generates additional statistical features which capture more complex distributional characteristics and significantly improve modeling performance. Treating this expanded feature set with state-of-the-art feature selection methods, we obtained findings that, nation-wide, are in line with the current knowledge on the aggravating roles of Varroa destructor and pesticides in colony loss. Moreover, we found that extreme temperature and precipitation events, even when controlling for other factors, significantly impact colony loss. Overall, our results reveal the complexity of biotic and abiotic factors affecting managed honey bee colonies across the United States.
Abstract
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. In this article, we use data on the publication histories of a very large sample of physicists to measure the effects of knowledge and social relatedness on their diversification strategies. Using bipartite networks, we compute a measure of topic similarity and a measure of social proximity. We find that scientists’ strategies are not random, and that they are significantly affected by both. Knowledge relatedness across topics explains
$$\approx 10\%$$
≈
10
%
of logistic regression deviances and social relatedness as much as
$$\approx 30\%$$
≈
30
%
, suggesting that science is an eminently social enterprise: when scientists move out of their core specialization, they do so through collaborations. Interestingly, we also find a significant negative interaction between knowledge and social relatedness, suggesting that the farther scientists move from their specialization, the more they rely on collaborations. Our results provide a starting point for broader quantitative analyses of scientific diversification strategies, which could also be extended to the domain of technological innovation—offering insights from a comparative and policy perspective.
Abstract
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.
Graphical Abstract
Graphical Abstract
Guiblet et al. show that loci capable of forming non-canonical (non-B) DNA structures are a major driver of variation in nucleotide substitution levels across the genome. Image credit: Wilfried Guiblet.
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. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The manifestation of mitochondrial DNA (mtDNA) diseases depends on the frequency of heteroplasmy (the presence of several alleles in an individual), yet its transmission across generations cannot be ...readily predicted owing to a lack of data on the size of the mtDNA bottleneck during oogenesis. For deleterious heteroplasmies, a severe bottleneck may abruptly transform a benign (low) frequency in a mother into a disease-causing (high) frequency in her child. Here we present a high-resolution study of heteroplasmy transmission conducted on blood and buccal mtDNA of 39 healthy mother–child pairs of European ancestry (a total of 156 samples, each sequenced at ∼20,000× per site). On average, each individual carried one heteroplasmy, and one in eight individuals carried a disease-associated heteroplasmy, with minor allele frequency ≥1%. We observed frequent drastic heteroplasmy frequency shifts between generations and estimated the effective size of the germ-line mtDNA bottleneck at only ∼30–35 (interquartile range from 9 to 141). Accounting for heteroplasmies, we estimated the mtDNA germ-line mutation rate at 1.3 × 10 ⁻⁸ (interquartile range from 4.2 × 10 ⁻⁹ to 4.1 × 10 ⁻⁸) mutations per site per year, an order of magnitude higher than for nuclear DNA. Notably, we found a positive association between the number of heteroplasmies in a child and maternal age at fertilization, likely attributable to oocyte aging. This study also took advantage of droplet digital PCR (ddPCR) to validate heteroplasmies and confirm a de novo mutation. Our results can be used to predict the transmission of disease-causing mtDNA variants and illuminate evolutionary dynamics of the mitochondrial genome.
Significance The frequency of intraindividual mitochondrial DNA (mtDNA) polymorphisms—heteroplasmies—can change dramatically from mother to child owing to the mitochondrial bottleneck at oogenesis. For deleterious heteroplasmies such a change may transform alleles that are benign at low frequency in a mother into disease-causing alleles when at a high frequency in her child. Our study estimates the mtDNA germ-line bottleneck to be small (30–35) and documents a positive association between the number of child heteroplasmies and maternal age at fertilization, enabling prediction of transmission of disease-causing variants and informing mtDNA evolution.
Chromosomal common fragile sites (CFSs) are unstable genomic regions that break under replication stress and are involved in structural variation. They frequently are sites of chromosomal ...rearrangements in cancer and of viral integration. However, CFSs are undercharacterized at the molecular level and thus difficult to predict computationally. Newly available genome-wide profiling studies provide us with an unprecedented opportunity to associate CFSs with features of their local genomic contexts. Here, we contrasted the genomic landscape of cytogenetically defined aphidicolin-induced CFSs (aCFSs) to that of nonfragile sites, using multiple logistic regression. We also analyzed aCFS breakage frequencies as a function of their genomic landscape, using standard multiple regression. We show that local genomic features are effective predictors both of regions harboring aCFSs (explaining ∼77% of the deviance in logistic regression models) and of aCFS breakage frequencies (explaining ∼45% of the variance in standard regression models). In our optimal models (having highest explanatory power), aCFSs are predominantly located in G-negative chromosomal bands and away from centromeres, are enriched in Alu repeats, and have high DNA flexibility. In alternative models, CpG island density, transcription start site density, H3K4me1 coverage, and mononucleotide microsatellite coverage are significant predictors. Also, aCFSs have high fragility when colocated with evolutionarily conserved chromosomal breakpoints. Our models are predictive of the fragility of aCFSs mapped at a higher resolution. Importantly, the genomic features we identified here as significant predictors of fragility allow us to draw valuable inferences on the molecular mechanisms underlying aCFSs.
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.
Mutation rates of microsatellites vary greatly among loci. The causes of this heterogeneity remain largely enigmatic yet are crucial for understanding numerous human neurological diseases and genetic ...instability in cancer. In this first genome-wide study, the relative contributions of intrinsic features and regional genomic factors to the variation in mutability among orthologous human-chimpanzee microsatellites are investigated with resampling and regression techniques. As a result, we uncover the intricacies of microsatellite mutagenesis as follows. First, intrinsic features (repeat number, length, and motif size), which all influence the probability and rate of slippage, are the strongest predictors of mutability. Second, mutability increases nonuniformly with length, suggesting that processes additional to slippage, such as faulty repair, contribute to mutations. Third, mutability varies among microsatellites with different motif composition likely due to dissimilarities in secondary DNA structure formed by their slippage intermediates. Fourth, mutability of mononucleotide microsatellites is impacted by their location on sex chromosomes vs. autosomes and inside vs. outside of Alu repeats, the former confirming the importance of replication and the latter suggesting a role for gene conversion. Fifth, transcription status and location in a particular isochore do not influence microsatellite mutability. Sixth, compared with intrinsic features, regional genomic factors have only minor effects. Finally, our regression models explain approximately 90% of variation in microsatellite mutability and can generate useful predictions for the studies of human diseases, forensics, and conservation genetics.
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