Genome integrity as a potential index of longevity in Ashkenazi Centenarian's families.

The aging process, or senescence, is characterized by age-specific decline in physical and physiological function, and increased frailty and genomic changes, including mutation accumulation. However, the mechanisms through which changes in genomic architecture influence human longevity have remained obscure. Copy number variants (CNVs), an abundant class of genomic variants, offer unique opportunities for understanding age-related genomic changes. Here we report the spectrum of CNVs in a cohort of 670 Ashkenazi Jewish centenarians, their progeny, and unrelated controls. The average ages of these groups were 97.4 ± 2.8, 69.2 ± 9.2, and 66.5 ± 7.0 respectively. For the first time, we compared different size classes of CNVs, from 1 kB to 100 MB in size. Using a high-resolution custom Affymetrix array, targeting 44,639 genomic regions, we identified a total of 12,166, 22,188, and 10,285 CNVs in centenarians, their progeny, and control groups, respectively. Interestingly, the offspring group showed the highest number of unique CNVs, followed by control and centenarians. While both gains and losses were found in all three groups, centenarians showed a significantly higher average number of both total gains and losses relative to their controls (p < 0.0327, 0.0182, respectively). Moreover, centenarians showed a lower total length of genomic material lost, suggesting that they may maintain superior genomic integrity over time. We also observe a significance fold increase of CNVs among the offspring, implying greater genomic integrity and a putative mechanism for longevity preservation. Genomic regions that experienced loss or gains appear to be distributed across many sites in the genome and contain genes involved in DNA transcription, cellular transport, developmental pathways, and metabolic functions. Our findings suggest that the exceptional longevity observed in centenarians may be attributed to the prolonged maintenance of functionally important genes. These genes are intrinsic to specific genomic regions as well as to the overall integrity of the genomic architecture. Additionally, a strong association between longer CNVs and differential gene expression observed in this study supports the notion that genomic integrity could positively influence longevity.

Preliminary evidence for chaotic signatures in host-microbe interactions.

Host-microbe interactions constitute dynamical systems that can be represented by mathematical formulations that determine their dynamic nature and are categorized as deterministic, stochastic, or chaotic. Knowing the type of dynamical interaction is essential for understanding the system under study. Very little experimental work has been done to determine the dynamical characteristics of host-microbe interactions, and its study poses significant challenges. The most straightforward experimental outcome involves an observation of time to death upon infection. However, in measuring this outcome, the internal parameters and the dynamics of each particular host-microbe interaction in a population of interactions are hidden from the experimentalist. To investigate whether a time-to-death (time-to-event) data set provides adequate information for searching for chaotic signatures, we first determined our ability to detect chaos in simulated data sets of time-to-event measurements and successfully distinguished the time-to-event distribution of a chaotic process from a comparable stochastic one. To do so, we introduced an inversion measure to test for a chaotic signature in time-to-event distributions. Next, we searched for chaos in the time-to-death of Caenorhabditis elegans and Drosophila melanogaster infected with Pseudomonas aeruginosa or Pseudomonas entomophila, respectively. We found suggestions of chaotic signatures in both systems but caution that our results are preliminary and highlight the need for more fine-grained and larger data sets in determining dynamical characteristics. If validated, chaos in host-microbe interactions would have important implications for the occurrence and outcome of infectious diseases, the reproducibility of experiments in the field of microbial pathogenesis, and the prediction of microbial threats.IMPORTANCEIs microbial pathogenesis a predictable scientific field? At a time when we are dealing with coronavirus disease 2019, there is intense interest in knowing about the epidemic potential of other microbial threats and new emerging infectious diseases. To know whether microbial pathogenesis will ever be a predictable scientific field requires knowing whether a host-microbe interaction follows deterministic, stochastic, or chaotic dynamics. If randomness and chaos are absent from virulence, there is hope for prediction in the future regarding the outcome of microbe-host interactions. Chaotic systems are inherently unpredictable, although it is possible to generate short-term probabilistic models, as is done in applications of stochastic processes and machine learning to weather forecasting. Information on the dynamics of a system is also essential for understanding the reproducibility of experiments, a topic of great concern in the biological sciences. Our study finds preliminary evidence for chaotic dynamics in infectious diseases.

Haematopoietic stem cell numbers are not solely determined by niche availability.

Haematopoietic stem cells (HSCs) reside in specialized microenvironments, also referred to as niches, and it has been widely believed that HSC numbers are determined by the niche size alone 1-5 . However, the vast excess of the number of niche cells over that of HSCs raises questions about this model. We initially established a mathematical model of niche availability and occupancy, which predicted that HSC numbers are restricted at both systemic and local levels. To address this question experimentally, we developed a femoral bone transplantation system, enabling us to increase the number of available HSC niches. We found that the addition of niches does not alter total HSC numbers in the body, regardless of whether the endogenous (host) niche is intact or defective, suggesting that HSC numbers are limited at the systemic level. Additionally, HSC numbers in transplanted wild-type femurs did not increase beyond physiological levels when HSCs were mobilized from defective endogenous niches to the periphery, indicating that HSC numbers are also constrained at the local level. Our study demonstrates that HSC numbers are not solely determined by niche availability, thereby rewriting the long-standing model for the regulation of HSC numbers.

Phenotypic pliancy and the breakdown of epigenetic polycomb mechanisms.

Epigenetic regulatory mechanisms allow multicellular organisms to develop distinct specialized cell identities despite having the same total genome. Cell-fate choices are based on gene expression programs and environmental cues that cells experience during embryonic development, and are usually maintained throughout the life of the organism despite new environmental cues. The evolutionarily conserved Polycomb group (PcG) proteins form Polycomb Repressive Complexes that help orchestrate these developmental choices. Post-development, these complexes actively maintain the resulting cell fate, even in the face of environmental perturbations. Given the crucial role of these polycomb mechanisms in providing phenotypic fidelity (i.e. maintenance of cell fate), we hypothesize that their dysregulation after development will lead to decreased phenotypic fidelity allowing dysregulated cells to sustainably switch their phenotype in response to environmental changes. We call this abnormal phenotypic switching phenotypic pliancy. We introduce a general computational evolutionary model that allows us to test our systems-level phenotypic pliancy hypothesis in-silico and in a context-independent manner. We find that 1) phenotypic fidelity is an emergent systems-level property of PcG-like mechanism evolution, and 2) phenotypic pliancy is an emergent systems-level property resulting from this mechanism's dysregulation. Since there is evidence that metastatic cells behave in a phenotypically pliant manner, we hypothesize that progression to metastasis is driven by the emergence of phenotypic pliancy in cancer cells as a result of PcG mechanism dysregulation. We corroborate our hypothesis using single-cell RNA-sequencing data from metastatic cancers. We find that metastatic cancer cells are phenotypically pliant in the same manner as predicted by our model.

Chaotic signatures in host-microbe interactions.

Host-microbe interactions constitute dynamical systems that can be represented by mathematical formulations that determine their dynamic nature, and are categorized as deterministic, stochastic, or chaotic. Knowing the type of dynamical interaction is essential for understanding the system under study. Very little experimental work has been done to determine the dynamical characteristics of host-microbe interactions and its study poses significant challenges. The most straightforward experimental outcome involves an observation of time to death upon infection. However, in measuring this outcome, the internal parameters, and the dynamics of each particular host-microbe interaction in a population of interactions are hidden from the experimentalist. To investigate whether a time-to-death (time to event) dataset provides adequate information for searching for chaotic signatures, we first determined our ability to detect chaos in simulated data sets of time-to-event measurements and successfully distinguished the time-to-event distribution of a chaotic process from a comparable stochastic one. To do so, we introduced an inversion measure to test for a chaotic signature in time-to-event distributions. Next, we searched for chaos, in time-to-death of Caenorhabditis elegans and Drosophila melanogaster infected with Pseudomonas aeruginosa or Pseudomonas entomophila, respectively. We found suggestions of chaotic signatures in both systems, but caution that our results are preliminary and highlight the need for more fine-grained and larger data sets in determining dynamical characteristics. If validated, chaos in host-microbe interactions would have important implications for the occurrence and outcome of infectious diseases, the reproducibility of experiments in the field of microbial pathogenesis and the prediction of microbial threats.

Bet-hedging antimicrobial strategies in macrophage phagosome acidification drive the dynamics of Cryptococcus neoformans intracellular escape mechanisms.

The fungus Cryptococcus neoformans is a major human pathogen with a remarkable intracellular survival strategy that includes exiting macrophages through non-lytic exocytosis (Vomocytosis) and transferring between macrophages (Dragotcytosis) by a mechanism that involves sequential events of non-lytic exocytosis and phagocytosis. Vomocytosis and Dragotcytosis are fungal driven processes, but their triggers are not understood. We hypothesized that the dynamics of Dragotcytosis could inherit the stochasticity of phagolysosome acidification and that Dragotcytosis was triggered by fungal cell stress. Consistent with this view, fungal cells involved in Dragotcytosis reside in phagolysosomes characterized by low pH and/or high oxidative stress. Using fluorescent microscopy, qPCR, live cell video microscopy, and fungal growth assays we found that the that mitigating pH or oxidative stress reduced Dragotcytosis frequency, whereas ROS susceptible mutants of C. neoformans underwent Dragotcytosis more frequently. Dragotcytosis initiation was linked to phagolysosomal pH, oxidative stresses, and macrophage polarization state. Dragotcytosis manifested stochastic dynamics thus paralleling the dynamics of phagosomal acidification, which correlated with the inhospitality of phagolysosomes in differently polarized macrophages. Hence, randomness in phagosomal acidification randomly created a population of inhospitable phagosomes where fungal cell stress triggered stochastic C. neoformans non-lytic exocytosis dynamics to escape a non-permissive intracellular macrophage environment.

Genomic surveillance of SARS-CoV-2 during the first year of the pandemic in the Bronx enabled clinical and epidemiological inference.

The Bronx was an early epicenter of the COVID-19 pandemic in the USA. We conducted temporal genomic surveillance of 104 SARS-CoV-2 genomes across the Bronx from March October 2020. Although the local structure of SARS-CoV-2 lineages mirrored those of New York City and New York State, temporal sampling revealed a dynamic and changing landscape of SARS-CoV-2 genomic diversity. Mapping the trajectories of mutations, we found that while some became 'endemic' to the Bronx, other, novel mutations rose in prevalence in the late summer/early fall. Geographically resolved genomes enabled us to distinguish between cases of reinfection and persistent infection in two pediatric patients. We propose that limited, targeted, temporal genomic surveillance has clinical and epidemiological utility in managing the ongoing COVID pandemic.

Genomic surveillance of SARS-CoV-2 during the first year of the pandemic in the Bronx enabled clinical and epidemiological inference.

The Bronx was an early epicenter of the COVID-19 pandemic in the USA. We conducted temporal genomic surveillance of SARS-CoV-2 genomes across the Bronx from March-October 2020. Although the local structure of SARS-CoV-2 lineages mirrored those of New York City and New York State, temporal sampling revealed a dynamic and changing landscape of SARS-CoV-2 genomic diversity. Mapping the trajectories of variants, we found that while some became 'endemic' to the Bronx, other, novel variants rose in prevalence in the late summer/early fall. Geographically resolved genomes enabled us to distinguish between cases of reinfection and persistent infection in two pediatric patients. We propose that limited, targeted, temporal genomic surveillance has clinical and epidemiological utility in managing the ongoing COVID pandemic. One sentence summary: Temporally and geographically resolved sequencing of SARS-CoV-2 genotypes enabled surveillance of novel genotypes, identification of endemic viral variants, and clinical inferences, in the first wave of the COVID-19 pandemic in the Bronx.

Access to and safety of COVID-19 convalescent plasma in the United States Expanded Access Program: A national registry study.

BACKGROUND: The United States (US) Expanded Access Program (EAP) to coronavirus disease 2019 (COVID-19) convalescent plasma was initiated in response to the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. While randomized clinical trials were in various stages of development and enrollment, there was an urgent need for widespread access to potential therapeutic agents. The objective of this study is to report on the demographic, geographical, and chronological characteristics of patients in the EAP, and key safety metrics following transfusion of COVID-19 convalescent plasma. METHODS AND FINDINGS: Mayo Clinic served as the central institutional review board for all participating facilities, and any US physician could participate as a local physician-principal investigator. Eligible patients were hospitalized, were aged 18 years or older, and had-or were at risk of progression to-severe or life-threatening COVID-19; eligible patients were enrolled through the EAP central website. Blood collection facilities rapidly implemented programs to collect convalescent plasma for hospitalized patients with COVID-19. Demographic and clinical characteristics of all enrolled patients in the EAP were summarized. Temporal patterns in access to COVID-19 convalescent plasma were investigated by comparing daily and weekly changes in EAP enrollment in response to changes in infection rate at the state level. Geographical analyses on access to convalescent plasma included assessing EAP enrollment in all national hospital referral regions, as well as assessing enrollment in metropolitan areas and less populated areas that did not have access to COVID-19 clinical trials. From April 3 to August 23, 2020, 105,717 hospitalized patients with severe or life-threatening COVID-19 were enrolled in the EAP. The majority of patients were 60 years of age or older (57.8%), were male (58.4%), and had overweight or obesity (83.8%). There was substantial inclusion of minorities and underserved populations: 46.4% of patients were of a race other than white, and 37.2% of patients were of Hispanic ethnicity. Chronologically and geographically, increases in the number of both enrollments and transfusions in the EAP closely followed confirmed infections across all 50 states. Nearly all national hospital referral regions enrolled and transfused patients in the EAP, including both in metropolitan and in less populated areas. The incidence of serious adverse events was objectively low (<1%), and the overall crude 30-day mortality rate was 25.2% (95% CI, 25.0% to 25.5%). This registry study was limited by the observational and pragmatic study design that did not include a control or comparator group; thus, the data should not be used to infer definitive treatment effects. CONCLUSIONS: These results suggest that the EAP provided widespread access to COVID-19 convalescent plasma in all 50 states, including for underserved racial and ethnic minority populations. The study design of the EAP may serve as a model for future efforts when broad access to a treatment is needed in response to an emerging infectious disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT#: NCT04338360.

Emerging Adaptive Strategies Under Temperature Fluctuations in a Laboratory Evolution Experiment of Escherichia Coli.

Generalists and specialists are types of strategies individuals can employ that can evolve in fluctuating environments depending on the extremity and periodicity of the fluctuation. To evaluate whether the evolution of specialists or generalists occurs under environmental fluctuation regimes with different levels of periodicity, 24 populations of Escherichia coli underwent laboratory evolution with temperatures alternating between 15 and 43°C in three fluctuation regimes: two periodic regimes dependent on culture's cell density and one random (non-periodic) regime with no such dependency, serving as a control. To investigate contingencies on the genetic background, we seeded our experiment with two different strains. After the experiment, growth rate measurements at the two temperatures showed that the evolution of specialists was favored in the random regime, while generalists were favored in the periodic regimes. Whole genome sequencing demonstrated that several gene mutations were selected in parallel in the evolving populations with some dependency on the starting genetic background. Given the genes mutated, we hypothesized that the driving force behind the observed adaptations is the restoration of the internal physiology of the starting strains' unstressed states at 37°C, which may be a means of improving fitness in the new environments. Phenotypic array measurements supported our hypothesis by demonstrating a tendency of the phenotypic response of the evolved strains to move closer to the starting strains' response at the optimum of 37°C, especially for strains classified as generalists.

Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors.

The coronavirus disease 2019 (COVID-19) pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produced each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response, and diagnosis and reporting. Both new daily cases and daily mortality data in the United States exhibit periodic oscillatory patterns. By analyzing New York City (NYC) and Los Angeles (LA) testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses, such as increased infections on certain days of the week, as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the U.S. data are mostly an artifact of reporting, which disappears in data sets that record death by episode date, such as the NYC and LA data sets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting biological mechanisms.IMPORTANCE The incidence and mortality data for the COVID-19 data in the United States show periodic oscillations, giving the curve a distinctive serrated pattern. In this study, we show that these periodic highs and lows in incidence and mortality data are due to daily differences in testing for the virus and death reporting, respectively. These findings are important because they provide an explanation based on public health practices and shortcomings rather than biological explanations, such as infection dynamics. In other words, when oscillations occur in epidemiological data, a search for causes should begin with how the public health system produces and reports the information before considering other causes, such as infection cycles and higher incidences of events on certain days. Our results suggest that when oscillations occur in epidemiological data, this may be a signal that there are shortcomings in the public health system generating that information.

Single-molecule imaging of transcription dynamics in somatic stem cells.

Molecular noise is a natural phenomenon that is inherent to all biological systems1,2. How stochastic processes give rise to the robust outcomes that support tissue homeostasis remains unclear. Here we use single-molecule RNA fluorescent in situ hybridization (smFISH) on mouse stem cells derived from haematopoietic tissue to measure the transcription dynamics of three key genes that encode transcription factors: PU.1 (also known as Spi1), Gata1 and Gata2. We find that infrequent, stochastic bursts of transcription result in the co-expression of these antagonistic transcription factors in the majority of haematopoietic stem and progenitor cells. Moreover, by pairing smFISH with time-lapse microscopy and the analysis of pedigrees, we find that although individual stem-cell clones produce descendants that are in transcriptionally related states-akin to a transcriptional priming phenomenon-the underlying transition dynamics between states are best captured by stochastic and reversible models. As such, a stochastic process can produce cellular behaviours that may be incorrectly inferred to have arisen from deterministic dynamics. We propose a model whereby the intrinsic stochasticity of gene expression facilitates, rather than impedes, the concomitant maintenance of transcriptional plasticity and stem cell robustness.

Macrophages use a bet-hedging strategy for antimicrobial activity in phagolysosomal acidification.

Microbial ingestion by a macrophage results in the formation of an acidic phagolysosome but the host cell has no information on the pH susceptibility of the ingested organism. This poses a problem for the macrophage and raises the fundamental question of how the phagocytic cell optimizes the acidification process to prevail. We analyzed the dynamical distribution of phagolysosomal pH in murine and human macrophages that had ingested live or dead Cryptococcus neoformans cells, or inert beads. Phagolysosomal acidification produced a range of pH values that approximated normal distributions, but these differed from normality depending on ingested particle type. Analysis of the increments of pH reduction revealed no forbidden ordinal patterns, implying that the phagosomal acidification process was a stochastic dynamical system. Using simulation modeling, we determined that by stochastically acidifying a phagolysosome to a pH within the observed distribution, macrophages sacrificed a small amount of overall fitness to gain the benefit of reduced variation in fitness. Hence, chance in the final phagosomal pH introduces unpredictability to the outcome of the macrophage-microbe, which implies a bet-hedging strategy that benefits the macrophage. While bet hedging is common in biological systems at the organism level, our results show its use at the organelle and cellular level.

Mutation of the ATPase Domain of MutS Homolog-5 (MSH5) Reveals a Requirement for a Functional MutSγ Complex for All Crossovers in Mammalian Meiosis.

During meiosis, induction of DNA double strand breaks (DSB) leads to recombination between homologous chromosomes, resulting in crossovers (CO) and non-crossovers (NCO). In the mouse, only 10% of DSBs resolve as COs, mostly through a class I pathway dependent on MutSγ (MSH4/ MSH5) and MutLγ (MLH1/MLH3), the latter representing the ultimate marker of these CO events. A second Class II CO pathway accounts for only a few COs, but is not thought to involve MutSγ/ MutLγ, and is instead dependent on MUS81-EME1. For class I events, loading of MutLγ is thought to be dependent on MutSγ, however MutSγ loads very early in prophase I at a frequency that far exceeds the final number of class I COs. Moreover, loss of MutSγ in mouse results in apoptosis before CO formation, preventing the analysis of its CO function. We generated a mutation in the ATP binding domain of Msh5 (Msh5GA ). While this mutation was not expected to affect MutSγ complex formation, MutSγ foci do not accumulate during prophase I. However, most spermatocytes from Msh5GA/GA mice progress to late pachynema and beyond, considerably further than meiosis in Msh5-/- animals. At pachynema, Msh5GA/GA spermatocytes show persistent DSBs, incomplete homolog pairing, and fail to accumulate MutLγ. Unexpectedly, Msh5GA/GA diakinesis-staged spermatocytes have no chiasmata at all from any CO pathway, indicating that a functional MutSγ complex is critical for all CO events regardless of their mechanism of generation.

The evolutionary dynamics of metabolic protocells.

Protocell multilevel selection models have been proposed to study the evolutionary dynamics of vesicles encapsulating a set of replicating, competing and mutating sequences. The frequency of the different sequence types determines protocell survival through a fitness function. One of the defining features of these models is the genetic load generated when the protocell divides and its sequences are assorted between the offspring vesicles. However, these stochastic assortment effects disappear when the redundancy of each sequence type is sufficiently high. The fitness dependence of the vesicle with its sequence content is usually defined without considering a realistic account on how the lower level dynamics would specify the protocell fitness. Here, we present a protocell model with a fitness function determined by the output flux of a simple metabolic network with the aim of understanding how the evolution of both kinetic and topological features of metabolism would have been constrained by the particularities of the protocell evolutionary dynamics. In our model, the sequences inside the vesicle are both the carriers of information and Michaelis-Menten catalysts exhibiting saturation. We found that the saturation of the catalysts controlling the metabolic fluxes, achievable by modifying the kinetic or stoichiometric parameters, provides a mechanism to ameliorate the assortment load by increasing the redundancy of the catalytic sequences required to achieve the maximum flux. Regarding the network architecture, we conclude that combinations of parallel network motifs and bimolecular catalysts are a robust way to increase the complexity of the metabolism enclosed by the protocell.

ECM Cross-Linking Regulates Invadopodia Dynamics.

Invadopodia are membrane protrusions dynamically assembled by invasive cancer cells in contact with the extracellular matrix (ECM). Invadopodia are enriched by the structural proteins actin and cortactin as well as metalloproteases such as MT1-MMP, whose function is to degrade the surrounding ECM. During metastasis, invadopodia are necessary for cancer cell intravasation and extravasation. Although signaling pathways involved in the assembly and function of invadopodia are well studied, few studies address invadopodia dynamics and how the cell-ECM interactions contribute to cell invasion. Using iterative analysis based on time-lapse microscopy and mathematical modeling of invasive cancer cells, we found that cells oscillate between invadopodia presence and cell stasis-termed the "invadopodia state"-and invadopodia absence during cell translocation-termed the "migration state." Our data suggest that ß1-integrin-ECM binding and ECM cross-linking control the duration of each of the two states. By changing the concentration of cross-linkers in two-dimensional and three-dimensional cultures, we generate an ECM in which 0-0.92 of total lysine residues are cross-linked. Using an ECM with a range of cross-linking degrees, we demonstrate that the dynamics of invadopodia-related functions have a biphasic relationship to ECM cross-linking. At intermediate levels of ECM cross-linking (0.39), cells exhibit rapid invadopodia protrusion-retraction cycles and rapid calcium spikes, which lead to more frequent MT1-MMP delivery, causing maximal invadopodia-mediated ECM degradation. In contrast, both extremely high or low levels of cross-linking lead to slower invadopodia-related dynamics and lower ECM degradation. Additionally, ß1-integrin inhibition modifies the dynamics of invadopodia-related functions as well as the length of time cells spend in either of the states. Collectively, these data suggest that ß1-integrin-ECM binding nonlinearly translates small physical differences in the extracellular environment to differences in the dynamics of cancer cell behaviors. Understanding the conditions under which invadopodia can be reduced by subtle environment-targeting treatments may lead to combination therapies for preventing metastatic spread.

The origin and evolution of cell types.

Cell types are the basic building blocks of multicellular organisms and are extensively diversified in animals. Despite recent advances in characterizing cell types, classification schemes remain ambiguous. We propose an evolutionary definition of a cell type that allows cell types to be delineated and compared within and between species. Key to cell type identity are evolutionary changes in the 'core regulatory complex' (CoRC) of transcription factors, that make emergent sister cell types distinct, enable their independent evolution and regulate cell type-specific traits termed apomeres. We discuss the distinction between developmental and evolutionary lineages, and present a roadmap for future research.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

Fetal liver hematopoietic stem cell niches associate with portal vessels.

Whereas the cellular basis of the hematopoietic stem cell (HSC) niche in the bone marrow has been characterized, the nature of the fetal liver niche is not yet elucidated. We show that Nestin(+)NG2(+) pericytes associate with portal vessels, forming a niche promoting HSC expansion. Nestin(+)NG2(+) cells and HSCs scale during development with the fractal branching patterns of portal vessels, tributaries of the umbilical vein. After closure of the umbilical inlet at birth, portal vessels undergo a transition from Neuropilin-1(+)Ephrin-B2(+) artery to EphB4(+) vein phenotype, associated with a loss of periportal Nestin(+)NG2(+) cells and emigration of HSCs away from portal vessels. These data support a model in which HSCs are titrated against a periportal vascular niche with a fractal-like organization enabled by placental circulation.

Cancer as the Disintegration of Robustness: Population-Level Variance in Gene Expression Identifies Key Differences Between Tobacco- and HPV-Associated Oropharyngeal Carcinogenesis.

CONTEXT: Oropharyngeal squamous cell carcinoma is associated both with tobacco use and with human papillomavirus (HPV) infection. It is argued that carcinogen-driven tumorigenesis is a distinct disease from its virally driven counterpart. We hypothesized that tumorigenesis is the result of a loss of genotypic robustness resulting in an increase in phenotypic variation in tumors compared with adjacent histologically normal tissues, and that carcinogen-driven tumorigenesis results in greater variation than its virally driven counterpart. OBJECTIVES: To examine the loss of robustness in carcinogen-driven and virally driven oropharyngeal squamous cell carcinoma samples, and to identify potential pathways involved. DESIGN: We used coefficients of variation for messenger RNA and microRNA expression to measure the loss of robustness in oropharyngeal squamous cell carcinoma samples. Tumors were compared with matched normal tissues, and were further categorized by HPV and patient smoking status. Weighted gene coexpression networks were constructed for genes with highly variable expression among the HPV⁻ tumors from smokers. RESULTS: We observed more genes with variable messenger RNA expression in tumors compared with normal tissues, regardless of HPV and smoking status, and more microRNAs with variable expression in HPV⁻ and HPV⁺ tumors from smoking patients than from nonsmokers. For both the messenger RNA and microRNA data, we observed more variance among HPV⁻ tumors from smokers compared with HPV⁺ tumors from nonsmokers. The gene coexpression network construction highlighted pathways that have lost robustness in carcinogen-induced tumors but appear stable in virally induced tumors. CONCLUSIONS: Using coefficients of variation and coexpression networks, we identified multiple altered pathways that may play a role in carcinogen-driven tumorigenesis.