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BackgroundSleep phenotypes have been reported to be associated with cognitive ageing outcomes. However, there is limited research using genetic variants as proxies for sleep traits to study their associations. We estimated associations between Polygenic Risk Scores (PRSs) for sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnoea (OSA) and measures of cogntive ageing in Hispanic/Latino adults.MethodsWe used summary statistics from published genome-wide association studies to construct PRSs representing the genetic basis of each sleep trait, then we studied the association of the PRSs of the sleep phenotypes with cognitive outcomes in the Hispanic Community Healthy Study/Study of Latinos. The primary model adjusted for age, sex, study centre, and measures of genetic ancestry. Associations are highlighted if their p-value

Tertiary wastewater treatment could provide a reliable source of water for reuse. Amongst these types of wastewater treatment, deep-bed filtration of secondary effluents can effectively remove particles and organic matter, however, NH4+ and NO2&minus, are not easily removed. This study examined the feasibility of stimulating microbial activity using hydrogen peroxide (H2O2) as a bio-specific and clean oxygen source that leaves no residuals in the water and is advantageous upon aeration due to the solubility limitations of the oxygen. The performance of a pilot bio-filtration system at a filtration velocity of 5&ndash, 6 m/h, was enhanced by the addition of H2O2 for particle, organic matter, NH4+, and NO2&minus, removal. Hydrogen peroxide provided the oxygen demand for full nitrification. As a result, influent concentrations of 4.2 &plusmn, 2.5 mg/L N-NH4+ and 0.65 &plusmn, 0.4 mg/L N-NO2 were removed during the short hydraulic residence time (HRT). In comparison, filtration without H2O2 addition only removed up to 0.6 mg/L N-NH4+ and almost no N-NO2&minus, A DNA metagenome analysis of the functional genes of the media biomass reflected a significant potential for simultaneous nitrification and denitrification activity. It is hypothesized that the low biodegradability of the organic carbon and H2O2 addition stimulated oxygen utilization in favor of nitrification, followed by the enhancement of anoxic activity.

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a given trait. However, the standard PRS fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). Machine learning algorithms can be used to account for such non-linearities and interactions. We trained and validated polygenic prediction models for five complex phenotypes in a multi-ancestry population: total cholesterol, triglycerides, systolic blood pressure, sleep duration, and height. We used an ensemble method of LASSO for feature selection and gradient boosted trees (XGBoost) for non-linearities and interaction effects. In an independent test set, we found that combining a standard PRS as a feature in the XGBoost model increases the percentage variance explained (PVE) of the prediction model compared to the standard PRS by 25% for sleep duration, 26% for height, 44% for systolic blood pressure, 64% for triglycerides, and 85% for total cholesterol. Machine learning models trained in specific racial/ethnic groups performed similarly in multi-ancestry trained models, despite smaller sample sizes. The predictions of the machine learning models were superior to the standard PRS in each of the racial/ethnic groups in our study. However, among Blacks the PVE was substantially lower than for other groups. For example, the PVE for total cholesterol was 8.1%, 12.9%, and 17.4% for Blacks, Whites, and Hispanics/Latinos, respectively. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.

Epidemiological sleep research strives to identify the interactions and causal mechanisms by which sleep affects human health, and to design intervention strategies for improving sleep throughout the lifespan. These goals can be advanced by further focusing on the environmental and genetic etiology of sleep disorders, and by development of risk stratification algorithms, to identify people who are at risk or are affected by, sleep disorders. These studies rely on comprehensive sleep-related data which often contains complex multi-dimensional physiological and molecular measurements across multiple timepoints. Thus, sleep research is well-suited for the application of computational approaches that can handle high-dimensional data. Here, we survey recent advances in machine and deep learning together with the availability of large human cohort studies with sleep data that can jointly drive the next breakthroughs in the sleep-research field. We describe sleep-related data types and datasets, and present some of the tasks in the field that can be targets for algorithmic approaches, as well as the challenges and opportunities in pursuing them. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13311-021-01014-9.

Introduction Obstructive sleep apnea (OSA) often co-occurs with other health outcomes. The respiratory event index (REI), often used to define OSA, is similarly correlated with several health phenotypes. Genetic data provide an opportunity to explain the nature of these associations. Methods We used data from the Hispanic Community Healthy Study/Study of Latinos (HCHS/SOL) to estimate genetic correlations (i.e., the correlation between phenotypes that is due to genetic effects) between OSA severity as measured by the REI and 56 anthropometric, glycemic, cardiometabolic, and pulmonary traits. Genetically-correlated traits (>0.2 and p-value30). Results The dataset included 11,155 participants (mean age: 46.2 (SD =13.8) years; 41.1% males) from the baseline HCHS/SOL exam who underwent home sleep apnea testing. 30.65% had OSA. 22 traits were genetically correlated with REI. Without BMI adjustment, the PRSs of BMI, waist-to-hip ratio (WHR), diastolic blood pressure (DBP), pulse pressure (PP), HbA1c, triglycerides (TG), FEV1/FVC and insomnia were significantly associated with REI/OSA. The associations of WHR, DBP, PP, HbA1c and insomnia PRSs and REI/OSA remained in BMI adjusted analysis. In obesity-stratified analysis, PRS of BMI, WHR and DBP were associated with REI/OSA in individuals with obesity, while PRSs of FEV1/FVC, HbA1c, insomnia, PP, TG, and WHR were associated with REI/OSA in individuals without obesity. MR analysis identified robust causal effect of increased BMI on OSA, and suggestive causal effects of WHR, DBP, and PP on OSA. Conclusion Our results support shared genetic basis of anthropometric traits, blood pressure traits, and insomnia with OSA, with potential differences in disease mechanisms in individuals with and without obesity. Support (If Any) Funding: R35HL135818, R21HL145425.

Unlike recent progress in cellular reprogramming, the mechanisms and requirements for misspecification of entire organs are largely unknown. A canonic model for organ “reprogramming” was provided by the induction of haltere-to-wing transformations in response to early exposure of fly embryos to ether. Using this model, we identify a mechanistic chain of events explaining why and how stage-specific exposure leads to organ transformation at a later stage. We show that ether interferes with protein integrity and compromisesTrithorax-mediated establishment of H3K4 tri-methylations. The altered pattern of H3K4me3 pre-disposes early-methylated Ubx targets and wing genes for later up-regulation in the larval haltere disc, hence the wing-like outcome. Consistent with protein destabilization by ether, this transformation is enhanced by reduced function ofHsp90and emerges spontaneously by joint deficiency inHsp90andTrithorax. The morphogenetic impact of chaperone response at the onset of epigenetic patterning may comprise a general scheme for organ reprogramming by environmental cues.

BackgroundMost of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region and the resolution of profiling is inherently limited. Platforms that offer ultra long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others, all allow different ways to circumvent this problem yet suffer various shortcomings. There is need for a simple and low cost 16S rRNA gene based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.ResultsThis manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. Thede factoamplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution byin silicosimulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about two-fold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200bp (80%) of the 16S rRNA gene we were able to achieve ~100 fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, profiling of aDrosophila melanogastermicrobiome using the set of six primer pairs provided a ~100 fold increase in resolution, and thus enabling efficient downstream analysis.ConclusionsSMURF enables identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of Formalin-fixed and Paraffin-embedded samples, fossil-derived DNA or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in Multilocus Sequence Typing (MLST).

It is becoming increasingly clear that most, if not all, animals and plants are associated with a diverse array of resident gut microbiota. This symbiosis is regulated by host-microbiome interactions which influence the development, homeostasis, adaptation and evolution of the host. Recent evidence indicated that these interactions can also affect the host germline and have a potential of supporting transgenerational effects, including inheritance of acquired characteristics. Taken together, the influence of gut bacteria on the host soma and germline could potentially give rise to emergent phenotypes, which may be partially inherited by three distinguishable modes of transgenerational influence of gut bacteria: 1) "soma-to-soma" 2) "soma-to-germline" and 3) "soma-germline-soma". Here, we discuss these possibilities in light of evidence supporting bacterial-mediated modes of transgenerational inheritance.

Unlike vertically transmitted endosymbionts, which have broad effects on their host's germ line, the extracellular gut microbiota is transmitted horizontally and is not known to influence the germ line. Here we provide evidence supporting the influence of these gut bacteria on the germ line of Drosophila melanogaster. Removal of the gut bacteria represses oogenesis, expedites maternal-to-zygotic-transition in the offspring and unmasks hidden phenotypic variation in mutants. We further show that the main impact on oogenesis is linked to the lack of gut Acetobacter species, and we identify the Drosophila Aldehyde dehydrogenase (Aldh) gene as an apparent mediator of repressed oogenesis in Acetobacter-depleted flies. The finding of interactions between the gut microbiota and the germ line has implications for reproduction, developmental robustness and adaptation., The gut microbiota can play various roles in the host's physiology, but is not known to influence the germ line. Here, Elgart et al. show that certain extracellular gut bacteria can affect oogenesis and embryo development in the fruit fly.

Background During the lifetime of an organism, every individual encounters many combinations of diverse changes in the somatic genome, epigenome and microbiome. This gives rise to many novel combinations of internal failures which are unique to each individual. How any individual can tolerate this high load of new, individual-specific scenarios of failure is not clear. While stress-induced plasticity and hidden variation have been proposed as potential mechanisms of tolerance, the main conceptual problem remains unaddressed, namely: how largely non-beneficial random variation can be rapidly and safely organized into net benefits to every individual. Presentation of the hypothesis We propose an organizational principle which explains how every individual can alleviate a high load of novel stressful scenarios using many random variations in flexible and inherently less harmful traits. Random changes which happen to reduce stress, benefit the organism and decrease the drive for additional changes. This adaptation (termed ‘Adaptive Improvisation’) can be further enhanced, propagated, stabilized and memorized when beneficial changes reinforce themselves by auto-regulatory mechanisms. This principle implicates stress not only in driving diverse variations in cells tissues and organs, but also in organizing these variations into adaptive outcomes. Specific (but not exclusive) examples include stress reduction by rapid exchange of mobile genetic elements (or exosomes) in unicellular, and rapid changes in the symbiotic microorganisms of animals. In all cases, adaptive changes can be transmitted across generations, allowing rapid improvement and assimilation in a few generations. Testing the hypothesis We provide testable predictions derived from the hypothesis. Implications of the hypothesis The hypothesis raises a critical, but thus far overlooked adaptation problem and explains how random variation can self-organize to confer a wide range of individual-specific adaptations beyond the existing outcomes of natural selection. It portrays gene regulation as an inseparable synergy between natural selection and adaptation by improvisation. The latter provides a basis for Lamarckian adaptation that is not limited to a specific mechanism and readily accounts for the remarkable resistance of tumors to treatment. Reviewers This article was reviewed by Eugene V. Koonin, Yuri Wolf and Itai Yanai.

Organisms have to be sufficiently robust to environmental and genetic perturbations, yet plastic enough to cope with stressful scenarios to which they are not fully adapted. How this apparent conflict between robustness and plasticity is resolved at the cellular and whole organism levels is not clear. Here we review and discuss evidence in flies suggesting that the environment can modulate the balance between robustness and plasticity. The outcomes of this modulation can vary from mild sensitizations that are hardly noticeable, to overt qualitative changes in phenotype. The effects could be at both the cellular and whole organism levels and can include cellular de-/trans-differentiation ('Cellular reprogramming') and gross disfigurements such as homeotic transformations ('Tissue/whole organism reprogramming'). When the stress is mild enough, plastic changes in some processes may prevent drastic changes in more robust traits such as cell identity and tissue integrity. However, when the stress is sufficiently severe, this buffering may no longer be able to prevent such overt changes, and the resulting phenotypic variability could be subjected to selection and might assist survival at the population level. This article is part of a Special Issue entitled: Stress as a fundamental theme in cell plasticity.

Commensal gut bacteria in many species including flies are integral part of their host, and are known to influence its development and homeostasis within generation. Here we report an unexpected impact of host-microbe interactions, which mediates multi-generational, non-Mendelian inheritance of a stress-induced phenotype. We have previously shown that exposure of fly larvae to G418 antibiotic induces transgenerationally heritable phenotypes, including a delay in larval development, gene induction in the gut and morphological changes. We now show that G418 selectively depletes commensal Acetobacter species and that this depletion explains the heritable delay, but not the inheritance of the other phenotypes. Notably, the inheritance of the delay was mediated by a surprising trans-generational effect. Specifically, bacterial removal from F1 embryos did not induce significant delay in F1 larvae, but nonetheless led to a considerable delay in F2. This effect maintains a delay induced by bacterial-independent G418 toxicity to the host. In line with these findings, reintroduction of isolated Acetobacter species prevented the inheritance of the delay. We further show that this prevention is partly mediated by vitamin B2 (Riboflavin) produced by these bacteria; exogenous Riboflavin led to partial prevention and inhibition of Riboflavin synthesis compromised the ability of the bacteria to prevent the inheritance.These results identify host-microbe interactions as a hitherto unrecognized factor capable of mediating non-Mendelian inheritance of a stress-induced phenotype.

The coupling between cell-cycle exit and onset of differentiation is a common feature throughout the developing nervous system, but the mechanisms that link these processes are mostly unknown. Although the transcription factor Pax6 has been implicated in both proliferation and differentiation of multiple regions within the central nervous system (CNS), its contribution to the transition between these successive states remains elusive. To gain insight into the role of Pax6 during the transition from proliferating progenitors to differentiating precursors, we investigated cell-cycle and transcriptomic changes occurring in Pax6 (-) retinal progenitor cells (RPCs). Our analyses revealed a unique cell-cycle phenotype of the Pax6-deficient RPCs, which included a reduced number of cells in the S phase, an increased number of cells exiting the cell cycle, and delayed differentiation kinetics of Pax6 (-) precursors. These alterations were accompanied by coexpression of factors that promote (Ccnd1, Ccnd2, Ccnd3) and inhibit (P27 (kip1) and P27 (kip2) ) the cell cycle. Further characterization of the changes in transcription profile of the Pax6-deficient RPCs revealed abrogated expression of multiple factors which are known to be involved in regulating proliferation of RPCs, including the transcription factors Vsx2, Nr2e1, Plagl1 and Hedgehog signaling. These findings provide novel insight into the molecular mechanism mediating the pleiotropic activity of Pax6 in RPCs. The results further suggest that rather than conveying a linear effect on RPCs, such as promoting their proliferation and inhibiting their differentiation, Pax6 regulates multiple transcriptional networks that function simultaneously, thereby conferring the capacity to proliferate, assume multiple cell fates and execute the differentiation program into retinal lineages.

Throughout the developing central nervous system, pre-patterning of the ventricular zone into discrete neural progenitor domains is one of the predominant strategies used to produce neuronal diversity in a spatially coordinated manner. In the retina, neurogenesis proceeds in an intricate chronological and spatial sequence, yet it remains unclear whether retinal progenitor cells (RPCs) display intrinsic heterogeneity at any given time point. Here, we performed a detailed study of RPC fate upon temporally and spatially confined inactivation of Pax6. Timed genetic removal of Pax6 appeared to unmask a cryptic divergence of RPCs into qualitatively divergent progenitor pools. In the more peripheral RPCs under normal circumstances, Pax6 seemed to prevent premature activation of a photoreceptor-differentiation pathway by suppressing expression of the transcription factor Crx. More centrally, Pax6 contributed to the execution of the comprehensive potential of RPCs: Pax6 ablation resulted in the exclusive generation of amacrine interneurons. Together, these data suggest an intricate dual role for Pax6 in retinal neurogenesis, while pointing to the cryptic divergence of RPCs into distinct progenitor pools.