Stochastic Sensitivity Analysis and Kernel Inference via Distributional Data

Cellular processes are noisy due to the stochastic nature of biochemical reactions. As such, it is impossible to predict the exact quantity of a molecule or other attributes at the single-cell level. However, the distribution of a molecule over a population is often deterministic and is governed by the underlying regulatory networks relevant to the cellular functionality of interest. Recent studies have started to exploit this property to infer network states. To facilitate the analysis of distributional data in a general experimental setting, we introduce a computational framework to efficiently characterize the sensitivity of distributional output to changes in external stimuli. Further, we establish a probability-divergence-based kernel regression model to accurately infer signal level based on distribution measurements. Our methodology is applicable to any biological system subject to stochastic dynamics and can be used to elucidate how population-based information processing may contribute to organism-level functionality. It also lays the foundation for engineering synthetic biological systems that exploit population decoding to more robustly perform various biocomputation tasks, such as disease diagnostics and environmental-pollutant sensing.     

Cell Growth and Size Homeostasis in Silico

Cell growth in size is a complex process coordinated by intrinsic and environmental signals. In a research work performed by a different group, size distributions of an exponentially growing population of mammalian cells were used to infer cell-growth rate in size. The results suggested that cell growth was neither linear nor exponential, but subject to size-dependent regulation. To explain the observed growth pattern, we built a mathematical model in which growth rate was regulated by the relative amount of mRNA and ribosomes in a cell. Under the growth model and a stochastic division rule, we simulated the evolution of a population of cells. Both the sampled growth rate and size distribution from this in silico population agreed well with experimental data. To explore the model space, alternative growth models and division rules were studied. This work may serve as a starting point to understand the mechanisms behind cell growth and size regulation using predictive models.     

High molecular diversity in the true service tree (Sorbus domestica) despite rareness: data from Europe with special reference to the Austrian occurrence

Background and Aims Sorbus domestica (Rosaceae) is one of the rarest deciduous tree species in Europe and is characterized by a scattered distribution. To date, no large-scale geographic studies on population genetics have been carried out. Therefore, the aims of this study were to infer levels of molecular diversity across the major part of the European distribution of S. domestica and to determine its population differentiation and structure. In addition, spatial genetic structure was examined together with the patterns of historic and recent gene flow between two adjacent populations.Methods Leaf or cambium samples were collected from 17 populations covering major parts of the European native range from north-west France to south-east Bulgaria. Seven nuclear microsatellites and one chloroplast minisatellite were examined and analysed using a variety of methods.Key Results Allelic richness was unexpectedly high for both markers within populations (mean per locus: 3·868 for nSSR and 1·647 for chloroplast minisatellite). Moreover, there was no evidence of inbreeding (mean F_is = –0·047). The Italian Peninsula was characterized as a geographic region with comparatively high genetic diversity for both genomes. Overall population differentiation was moderate (F_ST = 0·138) and it was clear that populations formed three groups in Europe, namely France, Mediterranean/Balkan and Austria. Historic gene flow between two local Austrian populations was high and asymmetric, while recent gene flow seemed to be disrupted.Conclusions It is concluded that molecular mechanisms such as self-incompatibility and high gene flow distances are responsible for the observed level of allelic richness as well as for population differentiation. However, human influence could have contributed to the present genetic pattern, especially in the Mediterranean region. Comparison of historic and recent gene flow may mirror the progress of habitat fragmentation in eastern Austria.     

Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling

Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational “deconvolution” of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ‘ON’ versus ‘OFF’ cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies.     

Statistical Inference for Nanopore Sequencing with a Biased Random Walk?Model

Nanopore sequencing promises long read-lengths and single-molecule resolution, but the stochastic motion of the DNA molecule inside the pore is, as of this writing, a barrier to high accuracy reads. We develop a method of statistical inference that explicitly accounts for this error, and demonstrate that high accuracy (>99%) sequence inference is feasible even under highly diffusive motion by using a hidden Markov model to jointly analyze multiple stochastic reads. Using this model, we place bounds on achievable inference accuracy under a range of experimental parameters.     

Strong Discrepancies between Local Temperature Mapping and Interpolated Climatic Grids in Tropical Mountainous Agricultural Landscapes

Bridging the gap between the predictions of coarse-scale climate models and the fine-scale climatic reality of species is a key issue of climate change biology research. While it is now well known that most organisms do not experience the climatic conditions recorded at weather stations, there is little information on the discrepancies between microclimates and global interpolated temperatures used in species distribution models, and their consequences for organisms’ performance. To address this issue, we examined the fine-scale spatiotemporal heterogeneity in air, crop canopy and soil temperatures of agricultural landscapes in the Ecuadorian Andes and compared them to predictions of global interpolated climatic grids. Temperature time-series were measured in air, canopy and soil for 108 localities at three altitudes and analysed using Fourier transform. Discrepancies between local temperatures vs. global interpolated grids and their implications for pest performance were then mapped and analysed using GIS statistical toolbox. Our results showed that global interpolated predictions over-estimate by 77.5±10% and under-estimate by 82.1±12% local minimum and maximum air temperatures recorded in the studied grid. Additional modifications of local air temperatures were due to the thermal buffering of plant canopies (from −2.7°K during daytime to 1.3°K during night-time) and soils (from −4.9°K during daytime to 6.7°K during night-time) with a significant effect of crop phenology on the buffer effect. This discrepancies between interpolated and local temperatures strongly affected predictions of the performance of an ectothermic crop pest as interpolated temperatures predicted pest growth rates 2.3–4.3 times lower than those predicted by local temperatures. This study provides quantitative information on the limitation of coarse-scale climate data to capture the reality of the climatic environment experienced by living organisms. In highly heterogeneous region such as tropical mountains, caution should therefore be taken when using global models to infer local-scale biological processes.     

Northward geographic diversification of a kleptoparasitic spider Argyrodes lanyuensis (Araneae,Theridiidae) from the Philippine Archipelago to Orchid Island

Oceanic islands are unique geographic systems that promote local adaptations and allopatric speciation in many of their highly endemic taxa. This is a common case in the Philippine Archipelago, where numerous unrelated taxa on islands have been inferred to have diversified in isolation. However, few cases have been reported in invertebrates especially among parasitic organisms. Here, we tested for biogeographical structure in novel populations of the “generalist" kleptoparasitic spider, Argyrodes lanyuensis Yoshida, Tso & Severinghaus, 1998 in the Philippines. Results showed that, in addition to Orchid/Lanyu Island, this species has a wide geographic distribution in the Philippine Archipelago. The estimated divergence time of this lineage using the mitochondrial cytochrome oxidase 1 (mt‐CO1) suggests that this species diverged ca 3.12 MYA, during the Pliocene. Two reciprocal monophyletic clades were elucidated in A. lanyuensis, but with limited differentiation across Pleistocene Aggregate Island Complex (PAIC) boundaries and modern‐day islands. However, in our analyses of morphological variation, we identified two phenotypically differentiated units in males (Orchid Island, Taiwan + Luzon, Philippine PAIC populations vs. Palawan + West Visayan + Mindanao PAIC populations). We infer that this species diverged in the southern portion of the Philippine Archipelago and only recently colonized Orchid Island. Our study provides new information on the extensive distribution of A. lanyuensis outside Orchid Island, Taiwan, but we documented a very limited geographically associated genetic variation. Our study points to behavioral phenomena such as foraging behavior as essential contributor to the evolutionary process of species diversification, in contrast to the traditionally invoked geographic drivers of divergence.     

High Spatiotemporal-Resolution Magnetic Tweezers: Calibration and Applications for DNA Dynamics

The observation of biological processes at the molecular scale in real time requires high spatial and temporal resolution. Magnetic tweezers are straightforward to implement, free of radiation or photodamage, and provide ample multiplexing capability, but their spatiotemporal resolution has lagged behind that of other single-molecule manipulation techniques, notably optical tweezers and AFM. Here, we present, to our knowledge, a new high-resolution magnetic tweezers apparatus. We systematically characterize the achievable spatiotemporal resolution for both incoherent and coherent light sources, different types and sizes of beads, and different types and lengths of tethered molecules. Using a bright coherent laser source for illumination and tracking at 6 kHz, we resolve 3 Å steps with a 1 s period for surface-melted beads and 5 Å steps with a 0.5 s period for double-stranded-dsDNA-tethered beads, in good agreement with a model of stochastic bead motion in the magnetic tweezers. We demonstrate how this instrument can be used to monitor the opening and closing of a DNA hairpin on millisecond timescales in real time, together with attendant changes in the hairpin dynamics upon the addition of deoxythymidine triphosphate. Our approach opens up the possibility of observing biological events at submillisecond timescales with subnanometer resolution using camera-based detection.     

Interrogating Biology with Force: Single Molecule High-Resolution Measurements with Optical Tweezers

Single molecule force spectroscopy methods, such as optical and magnetic tweezers and atomic force microscopy, have opened up the possibility to study biological processes regulated by force, dynamics of structural conformations of proteins and nucleic acids, and load-dependent kinetics of molecular interactions. Among the various tools available today, optical tweezers have recently seen great progress in terms of spatial resolution, which now allows the measurement of atomic-scale conformational changes, and temporal resolution, which has reached the limit of the microsecond-scale relaxation times of biological molecules bound to a force probe. Here, we review different strategies and experimental configurations recently developed to apply and measure force using optical tweezers. We present the latest progress that has pushed optical tweezers’ spatial and temporal resolution down to today’s values, discussing the experimental variables and constraints that are influencing measurement resolution and how these can be optimized depending on the biological molecule under study.     

Abundance of montane salamanders over an elevational gradient

Climate change is expected to systematically alter the distribution and population dynamics of species around the world. The effects are expected to be particularly strong at high latitudes and elevations, and for ectothermic species with small ranges and limited movement potential, such as salamanders in the southern Appalachian Mountains. In this study, we sought to establish baseline abundance estimates for plethodontid salamanders (family: Plethodontidae) over an elevational gradient in Great Smoky Mountains National Park. In addition to generating these baseline data for multiple species, we describe methods for surveying salamanders that allow for meaningful comparisons over time by separating observation and ecological processes generating the data. We found that Plethodon jordani had a mid‐elevation peak (1,500 m) in abundance and Desmognathus wrighti increased in abundance with elevation up to the highest areas of the park (2025 m), whereas Eurycea wilderae increased in abundance up to 1,600 m and then plateaued with increasing uncertainty. Litter depth, herbaceous ground cover, and proximity to stream were also important predictors of abundance (dependent upon species), whereas daily temperature, precipitation, ground cover, and humidity influenced detection rates. Our data provide some of the first minimally biased information for future studies to assess changes in the abundance and distribution of salamanders in this region. Understanding abundance patterns along with detailed baseline distributions will be critical for comparisons with future surveys to understand the population and community‐level effects of climate change on montane salamanders.     

Genetic Diversity and Population Structure in a Legacy Collection of Spring Barley Landraces Adapted to a Wide Range of Climates

Global environmental change and increasing human population emphasize the urgent need for higher yielding and better adapted crop plants. One strategy to achieve this aim is to exploit the wealth of so called landraces of crop species, representing diverse traditional domesticated populations of locally adapted genotypes. In this study, we investigated a comprehensive set of 1485 spring barley landraces (Lrc1485) adapted to a wide range of climates, which were selected from one of the largest genebanks worldwide. The landraces originated from 5° to 62.5° N and 16° to 71° E. The whole collection was genotyped using 42 SSR markers to assess the genetic diversity and population structure. With an average allelic richness of 5.74 and 372 alleles, Lrc1485 harbours considerably more genetic diversity than the most polymorphic current GWAS panel for barley. Ten major clusters defined most of the population structure based on geographical origin, row type of the ear and caryopsis type – and were assigned to specific climate zones. The legacy core reference set Lrc648 established in this study will provide a long-lasting resource and a very valuable tool for the scientific community. Lrc648 is best suited for multi-environmental field testing to identify candidate genes underlying quantitative traits but also for allele mining approaches.     

High frequency of rare variants with a moderate-to-high predicted biological effect in protocadherin genes of extremely obese

Relatively rare variants with a moderate-to-high biological effect may contribute to the genetic predisposition of common disorders. To investigate this for obesity, we performed exome sequencing for 30 young (mean age: 29.7 years) extremely obese Caucasian subjects (mean body mass index: 51.1 kg/m²; m/f = 11/29). Rare variants with a moderate-to-high predicted biological effect were assembled and subjected to functional clustering analysis. It showed that the 55 clustered protocadherin genes on chromosome 5q31 have a significantly (P = 0.002) higher frequency of rare variants than a set of 325 reference genes. Since the protocadherin genes are expressed in the hypothalamus, we tested another 167 genes related to the function of the hypothalamus, but in those genes, the frequency of rare variants was not different from that of the reference genes. To verify the relation of variation in the protocadherin genes with extreme obesity, we analyzed data from more than 4,000 European Americans present on the Exome Variant Server, representing a sample of the general population. The significant enrichment of rare variants in the protocadherin genes was only observed with the group of extremely obese individuals but not in the “general population”, indicating an association between rare variants in the protocadherin cluster genes and extreme obesity.     

Population Genetic Structure of the Magnificent Frigatebird Fregata magnificens (Aves,Suliformes) Breeding Colonies in the Western Atlantic Ocean

The Magnificent Frigatebird Fregata magnificens has a pantropical distribution, nesting on islands along the Atlantic and Pacific coasts. In the Caribbean, there is little genetic structure among colonies; however, the genetic structure among the colonies off Brazil and its relationship with those in the Caribbean are unknown. In this study, we used mtDNA and microsatellite markers to infer population structure and evolutionary history in a sample of F. magnificens individuals collected in Brazil, Grand Connétable (French Guyana), and Barbuda. Virtually all Brazilian individuals had the same mtDNA haplotype. There was no haplotype sharing between Brazil and the Caribbean, though Grand Connétable shared haplotypes with both regions. A Bayesian clustering analysis using microsatellite data found two genetic clusters: one associated with Barbuda and the other with the Brazilian populations. Grand Connétable was more similar to Barbuda but had ancestry from both clusters, corroborating its “intermediate” position. The Caribbean and Grand Connétable populations showed higher genetic diversity and effective population size compared to the Brazilian population. Overall, our results are in good agreement with an effect of marine winds in isolating the Brazilian meta-population.     

Population Regulation in Magellanic Penguins: What Determines Changes in Colony Size?

Seabirds are often studied at individual colonies, but the confounding effects of emigration and mortality processes in open populations may lead to inappropriate conclusions on the mechanisms underlying population changes. Magellanic penguin (Spheniscus magellanicus) colonies of variable population sizes are distributed along the Argentine coastline. In recent decades, several population and distributional changes have occurred, with some colonies declining and others newly established or increasing. We integrated data of eight colonies scattered along ∼ 600 km in Northern Patagonia (from 41°26´S, 65°01´W to 45°11´S, 66°30´W, Rio Negro and Chubut provinces) and conducted analysis in terms of their growth rates, production of young and of the dependence of those vital rates on colony age, size, and location. We contrasted population trends estimated from abundance data with those derived from population modeling to understand if observed growth rates were attainable under closed population scenarios. Population trends were inversely related to colony size, suggesting a density dependent growth pattern. All colonies located in the north—which were established during the last decades—increased at high rates, with the smallest, recently established colonies growing at the fastest rate. In central-southern Chubut, where colonies are the oldest, the largest breeding aggregations declined, but smaller colonies remained relatively stable. Results provided strong evidence that dispersal played a major role in driving local trends. Breeding success was higher in northern colonies, likely mediated by favorable oceanographic conditions. However, mean foraging distance and body condition of chicks at fledging were influenced by colony size. Recruitment of penguins in the northern area may have been triggered by a combination of density dependence, likely exacerbated by less favorable oceanographic conditions in the southern sector. Our results reaffirm the idea that individual colony trends do not provide confident indicators of population health, highlighting the need to redefine the scale for the study of population changes.     

Detectability and impact of repetitive surveys on threatened West African crocodylians

West African crocodylians are among the most threatened and least studied crocodylian species globally. Assessing population status and establishing a basis for population monitoring is the highest priority action for this region. Monitoring of crocodiles is influenced by many factors that affect detectability, including environmental variables and individual‐ or population‐level wariness. We investigated how these factors affect detectability and counts of the critically endangered Mecistops cataphractus and the newly recognized Crocodylus suchus. We implemented 195 repetitive surveys at 38 sites across Côte d’Ivoire between 2014 and 2019. We used an occupancy‐based approach and a count‐based GLMM analysis to determine the effect of environmental and anthropogenic variables on detection and modeled crocodile wariness over repetitive surveys. Despite their rarity and level of threat, detection probability of both species was relatively high (0.75 for M. cataphractus and 0.81 for C. suchus), but a minimum of two surveys were required to infer absence of either species with 90% confidence. We found that detection of M. cataphractus was significantly negatively influenced by fishing net encounter rate, while high temperature for the previous 48 h of the day of the survey increased C. suchus detection. Precipitation and aquatic vegetation had significant negative and positive influence, respectively, on M. cataphractus counts and showed the opposite effect for C. suchus counts. We also found that fishing encounter rate had a significant negative effect on C. suchus counts. Interestingly, survey repetition did not generally affect wariness for either species, though there was some indication that at least M. cataphractus was more wary by the fourth replicate. These results are informative for designing future survey and monitoring protocols for these threatened crocodylians in West Africa and for other endangered crocodylians globally.     

Cell to Cell Variability of Radiation-Induced Foci: Relation between Observed Damage and Energy Deposition

Most studies that aim to understand the interactions between different types of photon radiation and cellular DNA assume homogeneous cell irradiation, with all cells receiving the same amount of energy. The level of DNA damage is therefore generally determined by averaging it over the entire population of exposed cells. However, evaluating the molecular consequences of a stochastic phenomenon such as energy deposition of ionizing radiation by measuring only an average effect may not be sufficient for understanding some aspects of the cellular response to this radiation. The variance among the cells associated with this average effect may also be important for the behaviour of irradiated tissue. In this study, we accurately estimated the distribution of the number of radiation-induced γH2AX foci (RIF) per cell nucleus in a large population of endothelial cells exposed to 3 macroscopic doses of gamma rays from ⁶⁰Co. The number of RIF varied significantly and reproducibly from cell to cell, with its relative standard deviation ranging from 36% to 18% depending on the macroscopic dose delivered. Interestingly, this relative cell-to-cell variability increased as the dose decreased, contrary to the mean RIF count per cell. This result shows that the dose effect, in terms of the number of DNA lesions indicated by RIF is not as simple as a purely proportional relation in which relative SD is constant with dose. To analyse the origins of this observed variability, we calculated the spread of the specific energy distribution for the different target volumes and subvolumes in which RIF can be generated. Variances, standard deviations and relative standard deviations all changed similarly from dose to dose for biological and calculated microdosimetric values. This similarity is an important argument that supports the hypothesis of the conservation of the association between the number of RIF per nucleus and the specific energy per DNA molecule. This comparison allowed us to calculate a volume of 1.6 μm³ for which the spread of the specific energy distribution could explain the entire variability of RIF counts per cell in an exposed cell population. The definition of this volume may allow to use a microdosimetric quantity to predict heterogeneity in DNA damage. Moreover, this value is consistent with the order of magnitude of the volume occupied by the hydrated sugar-phosphate backbone of the DNA molecule, which is the part of the DNA molecule responsible for strand breaks.     

A new model of forelimb ecomorphology for predicting the ancient habitats of fossil turtles

Various morphological proxies have been used to infer habitat preferences among fossil turtles and their early ancestors, but most are tightly linked to phylogeny, thereby minimizing their predictive power. One particularly widely used model incorporates linear measurements of the forelimb (humerus + ulna + manus), but in addition to the issue of phylogenetic correlation, it does not estimate the likelihood of habitat assignment. Here, we introduce a new model that uses intramanual measurements (digit III metacarpal + non‐ungual phalanges + ungual) to statistically estimate habitat likelihood and that has greater predictive strength than prior estimators. Application of the model supports the hypothesis that stem‐turtles were primarily terrestrial in nature and recovers the nanhsiungchelyid Basilemys (a fossil crown‐group turtle) as having lived primarily on land, despite some prior claims to the contrary.