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Purpose: Previous research identified a measurement gap in the individual assessment of social misconduct in the workplace related to gender. This gap implies that women respond to comparable self-reported acts of bullying or sexual discrimination slightly more often than men with the selflabeling as "bullied" or "sexually discriminated and/or harassed." This study tests this hypothesis for women and men in the scientific workplace and explores patterns of gender-related differences in self-reporting behavior. Basic design: The hypotheses on the connection between gender and the threshold for self-labeling as having been bullied or sexually discriminated against were tested based on a sample from a large German research organization. The sample includes 5,831 responses on bullying and 6,987 on sexual discrimination (coverage of 24.5 resp. 29.4 percentage of all employees). Due to a large number of cases and the associated high statistical power, this sample for the first time allows a detailed analysis of the "gender-related measurement gap." The research questions formulated in this study were addressed using two hierarchical regression models to predict the mean values of persons who self-labeled as having been bullied or sexually discriminated against. The status of the respondents as scientific or non-scientific employees was included as a control variable. Results: According to a self-labeling approach, women reported both bullying and sexual discrimination more frequently. This difference between women and men disappeared for sexual discrimination when, in addition to the gender of a person, self-reported behavioral items were considered in the prediction of self-labeling. For bullying, the difference between the two genders remained even in this extended prediction. No statistically significant relationship was found between the frequency of self-reported items and the effect size of their interaction with gender for either bullying or sexual discrimination. When comparing bullying and sexual discrimination, it should be emphasized that, on average, women report experiencing a larger number of different behavioral items than men. Interpretation and relevance: The results of the study support the current state of research. However, they also show how volatile the measurement instruments for bullying and sexual discrimination are. For example, the gender-related measurement gap is considerably influenced by single items in the Negative Acts Questionnaire and Sexual Experience Questionnaire. The results suggest that women are generally more likely than men to report having experienced bullying and sexual discrimination. While an unexplained "gender gap" in the understanding of bullying was found for bullying, this was not the case for sexual discrimination.

Extended version of RECOMB 2022 paper Decomposing a network flow into weighted paths is a problem with numerous applications, ranging from networking, transportation planning, to bioinformatics. In some applications we look for a decomposition that is optimal with respect to some property, such as the number of paths used, robustness to edge deletion, or length of the longest path. However, in many bioinformatic applications, we seek a specific decomposition where the paths correspond to some underlying data that generated the flow. In these cases, no optimization criteria guarantee the identification of the correct decomposition. Therefore, we propose to instead report the safe paths, which are subpaths of at least one path in every flow decomposition. In this work, we give the first local characterization of safe paths for flow decompositions in directed acyclic graphs, leading to a practical algorithm for finding the complete set of safe paths. In addition, we evaluate our algorithm on RNA transcript data sets against a trivial safe algorithm (extended unitigs), the recently proposed safe paths for path covers (TCBB 2021) and the popular heuristic greedy-width. On the one hand, we found that besides maintaining perfect precision, our safe and complete algorithm reports a significantly higher coverage (≈50 compared with the other safe algorithms. On the other hand, the greedy-width algorithm although reporting a better coverage, it also reports a significantly lower precision on complex graphs (for genes expressing a large number of transcripts). Overall, our safe and complete algorithm outperforms (by ≈20 greedy-width on a unified metric (F-score) considering both coverage and precision when the evaluated data set has a significant number of complex graphs. Moreover, it also has a superior time (4−5×) and space performance (1.2−2.2×), resulting in a better and more practical approach for bioinformatic applications of flow decomposition.

Motivation Single-cell/nuclei RNA-sequencing (scRNA-seq) technologies can simultaneously quantify gene expression in thousands of cells across the genome. However, the majority of the noncoding RNAs, such as microRNAs (miRNAs), cannot currently be profiled at the same scale. MiRNAs are a class of small noncoding RNAs and play an important role in gene regulation. MiRNAs originate from the processing of primary transcripts, known as primary-microRNAs (pri-miRNAs). The pri-miRNA transcripts, independent of their cognate miRNAs, can also function as long noncoding RNAs, code for micropeptides or even interact with DNA, acting like enhancers. Therefore, it is apparent that the significance of scRNA-seq pri-miRNA profiling expands beyond using pri-miRNA as proxies of mature miRNAs. However, there are no computational methods that allow profiling and quantification of pri-miRNAs at the single-cell-type resolution. Results We have developed a simple yet effective computational framework to profile pri-MiRNAs from single-cell RNA-sequencing datasets (PPMS). Based on user input, PPMS can profile pri-miRNAs at cell-type resolution. PPMS can be applied to both newly produced and publicly available datasets obtained via single cell or single-nuclei RNA-seq. It allows users to (i) investigate the distribution of pri-miRNAs across cell types and cell states and (ii) establish a relationship between the number of cells/reads sequenced and the detection of pri-miRNAs. Here, to demonstrate its efficacy, we have applied PPMS to publicly available scRNA-seq data generated from (i) individual chambers (ventricles and atria) of the human heart, (ii) human pluripotent stem cells during their differentiation into cardiomyocytes (the heart beating cells) and (iii) hiPSCs-derived cardiomyocytes infected with severe acute respiratory syndrome coronavirus 2.

Platelets are generated and released into the bloodstream from their precursor cells, megakaryocytes that reside in the bone marrow. Though platelets have no nucleus or DNA, they contain a full transcriptome that, during platelet formation, is transported from the megakaryocyte to the platelet. It has been described that transcripts in platelets can be translated into proteins that influence platelet response. The platelet transcriptome is highly dynamic and has been extensively studied using microarrays and, more recently, RNA sequencing (RNA-seq) in relation to diverse conditions (inflammation, obesity, cancer, pathogens and others). In this review, we focus on bulk and single-cell RNA-seq studies that have aimed to characterize the coding transcriptome of healthy megakaryocytes and platelets in humans. It has been noted that bulk RNA-seq has limitations when studying in vitro-generated megakaryocyte cultures that are highly heterogeneous, while single-cell RNA-seq has not yet been applied to platelets due to their very limited RNA content. Next, we illustrate how these methods can be applied in the field of inherited platelet disorders for gene discovery and for unraveling novel disease mechanisms using RNA from platelets and megakaryocytes and rare disease bioinformatics. Next, future perspectives are discussed on how this field of coding transcriptomics can be integrated with other next-generation technologies to decipher unexplained inherited platelet disorders in a multiomics approach. ispartof: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES vol:23 issue:14 ispartof: location:Switzerland status: published

Las proyecciones para el Cambio Climático Global (CCG) en Patagonia norte indican un aumento de la temperatura y disminución de las precipitaciones, así como también un incremento en la ocurrencia de fenómenos extremos. En este contexto, un interrogante abierto es qué capacidad poseen las especies vegetales para subsistir en condiciones climáticas diferentes, como las predichas por el CCG. Esto es de especial relevancia para los árboles, cuyos largos tiempos generacionales se asocian a un bajo recambio poblacional. El estudio de caracteres adaptativos bajo diferentes escenarios climáticos, como los existentes a lo largo de gradientes ambientales, constituye un abordaje particularmente útil, ya que permite evaluar las potenciales respuestas de poblaciones actuales frente a diversas condiciones. El género Nothofagus comprende especies forestales dominantes del bosque andino-patagónico, las cuales cubren gran parte del gradiente pluviométrico y todo el gradiente altitudinal de la Patagonia andina argentina. En particular, hacia los 40o S, Nothofagus obliqua, N. alpina y N. pumilio se distribuyen marcadamente a lo largo de un gradiente altitudinal. Mientras que N. obliqua domina los pisos altitudinales entre 600 y 900 msnm, N. alpina se distribuye desde los 800 hasta los 1000 msnm y N. pumilio desde los 1000 msnm y hasta el límite altitudinal del bosque. En este gradiente, el factor ambiental que presenta la mayor variación con la altitud es la temperatura. Es por ello que la distribución en estratos altitudinales sugiere una preferencia diferencial de nichos térmicos por parte de las especies. En esta tesis, mediante la articulación de experimentos en el bosque en combinación con abordajes ecofisiológicos y genómicos, se estudió el comportamiento de plantas de especies del género Nothofagus en distintos ambientes naturales, establecidos a lo largo de un gradiente altitudinal. En el capítulo 2, se estudió el comportamiento de regeneración de N. obliqua, N. alpina y N. pumilio, mediante la instalación de transplantes recíprocos en un bosque ubicado en Patagonia norte. En forma general, los resultados indican que el ambiente local, es decir el embiente que experimentan los individuos, influye sobre la emergencia y la supervivencia de las plántulas. También aportan evidenciasfavor de que, en N. pumilio y en cierta medida en N. obliqua, la fenología de la germinación es un carácter plástico, que se ajusta a las ventanas climáticas de mayor supervivencia de las plántulas. Por otro lado, el análisis de las dinámicas de mortalidad de plántulas con respecto a variables térmicas e hídricas de los distintos ambientes estudiados indicaron que la mortalidad de plántulas de N. obliqua y N. alpina mostró una mayor influencia por factores relacionados con la temperatura y la sequía, mientras que para N. pumilio solamente los factores térmicos resultaron más adecuados para explicar este comportamiento, sugiriendo la existencia de diferencias inter-específicas en la respuesta de la regeneración al ambiente natural. Para todas las especies, la supervivencia estuvo fuertemente influenciada por la etapa ontogenética de la plántula, con mayores porcentajes de mortalidad durante los primeros meses de vida. En el capítulo 3, se estudió la variación fenotípica de caracteres de importancia adaptativa en individuos de N. pumilio y N. obliqua en un estadio posterior (plantas de 3 años de edad) dentro y fuera de sus áreas de distribución. Se midió el diámetro a la altura del cuello, el contenido foliar de clorofilas a y b, carotenoides y antocianinas y la fluorescencia de la clorofila, ya que, como se explica en esta tesis, estos caracteres se consideran adaptativos, de acuerdo a diversos estudios de fisiología y ecología vegetal. Se encontró que, tanto los individuos de N. pumilio como los de N. obliqua mostraron una variación en los caracteres, relacionada con los diferentes ambientes en los que se evaluaron las plantas. Por último, en el capítulo 4 se realizó una caracterización genética de los individuos correspondientes a este ensayo, utilizando datos de secuenciación del genoma reducido (ddRAD-seq). Se identificaron 202702 y 216749 polimorfismos en las lecturas R1 y R2 de N. obliqua, respectivamente, de los cuales 6114 y 7601 superaron los filtros para ser utilizados en los análisis de asociación subsiguientes. En el caso de N. pumilio, el número de polimorfismos identificados en las lecturas R1 y R2 fue de 190126 y 198391, respectivamente, de los cuales 1644 y 1670 superaron los filtros. Se detectaron niveles de variabilidad moderados a altos y similares para ambas especies. Finalmente, en base a la información genética y fenotípica relevada en el ensayo presentado en el capítulo 3, se realizó una prueba de concepto para establecer relaciones entre polimorfismos nucleotídicos y variaciones en caracteres de importancia adaptativa. Mediante la utilización de modelos de asociación genómica, se identificaron 5 SNPs de N. obliqua y 7 de N. pumilio asociados significativamente a rasgos de interés. El análisis del contexto genómico de este conjunto de marcadores reveló que, 7 de ellos, se encuentran en regiones vinculadas con funciones de respuesta frente a ciertas condiciones de estrés abiótico o comunicación celular Estos resultados representan los primeros análisis genómicos de N. obliqua y N. pumilio, contribuyen a la ampliación de los escasos recursos genéticos de estas especies emblemáticas del bosque andinopatagónico y proveen una estrategia robusta para futuros estudios de mapeo por asociación. Global Climate Change (GCC) projectionsin northern Patagonia indicate a raise in temperature and a decrease in rainfall, as well as an increase in the occurrence of extreme phenomena. In this context, an open question is what is plant species’ capacity to survive under different climatic conditions, such as those predicted by CCG. This is especially relevant for trees, which long generation times is associated with low population turnover. The study of adaptive characters under different climatic scenarios, such as those existing along environmental gradients, constitutes a particularly useful approach, since it allows the evaluation of potential responses of current populations under different conditions. The genus Nothofagus includes dominant forestry species of the Andean-Patagonian forest, which cover a large part of the pluviometric gradient and the entire altitudinal gradient of the Argentine Andean Patagonia. In particular, towards 40o S, Nothofagus obliqua, N. alpina and N. pumilio are markedly distributed along an altitudinal gradient. While N. obliqua dominates the elevation floors between 600 and 900 meters above sea level (masl), N. alpina is found from 800 to 1000 masl and N. pumilio from 1000 masl and up to the treeline. In this gradient, the environmental factor that exhibits the greatest variation with altitude is temperature. Therefore, this particular distribution across altitude suggests that these species could have differential preference for thermal niches. In this thesis, the behavior of Nothofagus seedlings was studied across different natural environments, established along an altitudinal gradient, through the combination of experiments in the forest with ecophysiological and genomic approaches. In chapter 2, the regeneration behavior of N. obliqua, N. alpina and N. pumilio was studied through the installation of reciprocal transplantations in a natural forest located in northern Patagonia. In general, the results indicate that the local environment, which means the environment that the seedlings experience during the experiment, influences seedlings’ emergence and survival. They also provide evidence in favor of the fact that, in N. pumilio and to a certain extent in N. obliqua, the phenology of germination is a plastic character, which adjusts to the climatic windows of greater survival of seedlings. The analysis of relationships between thermal and hydric variables of the different environments with the dynamics of seedling mortality indicated that seedlings’ mortality of N. obliqua and N. alpina was greatly influenced by factors related to temperature and drought, while in N. pumilio only thermal factors were the most adequate to explain this behavior, suggesting the existence of interspecific differences in the response of regeneration to the natural environment. In all three species, survival was strongly influenced by the ontogenetic stage of the seedling, with higher percentages of mortality during the firsts months of life. In Chapter 3, the phenotypic variation in traits of adaptive importance was studied in individuals of N. pumilio and N. obliqua at a later stage (3-year-old plants), inside and outside their natural ranges. Root collar diameter, foliar content of chlorophylls a and b, carotenoids and anthocyanins, and chlorophyll fluorescence were measured, in view that, as discussed in this thesis, these plant traits are considered adaptive traits according to diverse ecological and physiological studies. It was found that both the individuals of N. pumilio and N. obliqua showed a variation in the traits of interest, related to the different environments in which the plants were tested. In chapter 4, a genetic characterization of the individuals planted in this essay was carried out, using sequencing data from a reduced representation of the genome (ddRAD-seq). In N. obliqua, 202702 and 216749 polymorphisms were identified from the R1 and R2 reads, respectively, of which 6114 and 7601 passed the filters to be used in subsequent association analysis. In N. pumilio, the number of identified SNPs from the R1 and R2 reads was 190126 and 198391, respectively, of which 1644 and 1670 passed the filters. Variability was found to be moderate to high for both species, which showed similar levels. Finally, based on the genetic and phenotypic information obtained in the saplings’ essay, a concept test was carried out to establish relationships between nucleotide polymorphisms and variations in traits of adaptive importance. Using genomic association models, a set of 5 SNPs from N. obliqua and 7 from N. pumilio was associated with traits of interest. The analysis of the genomic context of this set of markers revealed that 7 of them are found in regions linked to functions related the response to certain conditions of abiotic stress or cell communication. These results represent the first genomic analysis in N. obliqua and N. pumilio, contribute to the expansion of the scarce genetic resources of these emblematic species of the Andean-Patagonian forest and provide a robust strategy for future association mapping studies. Fil: Cagnacci, Julieta María. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.

Single-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues and other batch effects make scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. We present FIRM, a re-scaling algorithm which accounts for the effects of cell type compositions, and achieve accurate integration of scRNA-seq datasets across multiple tissue types, platforms and experimental batches. Compared with existing state-of-the-art integration methods, FIRM provides accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. FIRM is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.

Engineering and computational advances have opened many new avenues in cancer research, particularly when being exploited in interdisciplinary approaches. For example, the combination of microfluidics, novel sequencing technologies, and computational analyses has been crucial to enable single-cell assays, giving a detailed picture of tumor heterogeneity for the very first time. In a similar way, these 'tech' disciplines have been elementary for generating large data sets in multidimensional cancer 'omics' approaches, cell-cell interaction screens, 3D tumor models, and tissue level analyses. In this review we summarize the most important technology and computational developments that have been or will be instrumental for transitioning classical cancer research to a large data-driven, high-throughput, high-content discipline across all biological scales.

Global warming is causing plastic and evolutionary changes in the phenotypes of ectotherms. Yet, we have limited knowledge on how the interplay between plasticity and evolution shapes thermal responses and underlying gene expression patterns. We assessed thermal reaction norm patterns across the transcriptome and identified associated molecular pathways in northern and southern populations of the damselfly Ischnura elegans. Larvae were reared in a common garden experiment at the mean summer water temperatures experienced at the northern (20°C) and southern (24°C) latitudes. This allowed a space-for-time substitution where the current gene expression levels at 24°C in southern larvae are a proxy for the expected responses of northern larvae under gradual thermal evolution to the predicted 4°C warming. Most differentially expressed genes showed fixed differences across temperatures between latitudes, suggesting that thermal genetic adaptation will mainly evolve through changes in constitutive gene expression. Northern populations also frequently showed plastic responses in gene expression to mild warming, while southern populations were much less responsive to temperature. Thermal responsive genes in northern populations showed to a large extent a pattern of genetic compensation, namely gene expression that was induced at 24°C in northern populations remained at a lower constant level in southern populations, and were associated with metabolic and translation pathways. There was instead little evidence for genetic assimilation of an initial plastic response to mild warming. Our data therefore suggest that genetic compensation rather than genetic assimilation may drive the evolution of plasticity in response to mild warming in this damselfly species. ispartof: MOLECULAR ECOLOGY vol:29 issue:24 pages:4823-4834 ispartof: location:England status: published

Complex cell-to-cell communication underlies the basic processes essential for homeostasis in the given tissue architecture. Obtaining quantitative gene-expression of cells in their native context has significantly advanced through single-cell RNA sequencing technologies along with mechanical and enzymatic tissue manipulation. This approach, however, is largely reliant on the physical dissociation of individual cells from the tissue, thus, resulting in a library with unaccounted positional information. To overcome this, positional information can be obtained by integrating imaging and positional barcoding. Collectively, spatial transcriptomics strategies provide tissue architecture-dependent as well as position-dependent cellular functions. This review discusses the current technologies for spatial transcriptomics ranging from the methods combining mechanical dissociation and single-cell RNA sequencing to computational spatial re-mapping.

Bacterial processes necessary for adaption to stressful host environments are potential targets for new antimicrobials. Here, we report large-scale transcriptomic analyses of 32 human bacterial pathogens grown under 11 stress conditions mimicking human host environments. The potential relevance of the in vitro stress conditions and responses is supported by comparisons with available in vivo transcriptomes of clinically important pathogens. Calculation of a probability score enables comparative cross-microbial analyses of the stress responses, revealing common and unique regulatory responses to different stresses, as well as overlapping processes participating in different stress responses. We identify conserved and species-specific ‘universal stress responders’, that is, genes showing altered expression in multiple stress conditions. Non-coding RNAs are involved in a substantial proportion of the responses. The data are collected in a freely available, interactive online resource (PATHOgenex)., Nature Communications, 12 (1), ISSN:2041-1723

Whole-genome duplications (WGD) have been considered as springboards that potentiate lineage diversification through increasing functional redundancy. Divergence in gene regulatory elements is a central mechanism for evolutionary diversification, yet the patterns and processes governing regulatory divergence following events that lead to massive functional redundancy, such as WGD, remain largely unknown. We studied the patterns of divergence and strength of natural selection on regulatory elements in the Atlantic salmon (Salmo salar) genome, which has undergone WGD 100–80 Ma. Using ChIPmentation, we first show that H3K27ac, a histone modification typical to enhancers and promoters, is associated with genic regions, tissue-specific transcription factor binding motifs, and with gene transcription levels in immature testes. Divergence in transcription between duplicated genes from WGD (ohnologs) correlated with difference in the number of proximal regulatory elements, but not with promoter elements, suggesting that functional divergence between ohnologs after WGD is mainly driven by enhancers. By comparing H3K27ac regions between duplicated genome blocks, we further show that a longer polyploid state post-WGD has constrained regulatory divergence. Patterns of genetic diversity across natural populations inferred from resequencing indicate that recent evolutionary pressures on H3K27ac regions are dominated by largely neutral evolution. In sum, our results suggest that post-WGD functional redundancy in regulatory elements continues to have an impact on the evolution of the salmon genome, promoting largely neutral evolution of regulatory elements despite their association with transcription levels. These results highlight a case where genome-wide regulatory evolution following an ancient WGD is dominated by genetic drift.

CRISPR/Cas9 is a powerful genome-editing tool, but spurious off-target edits present a barrier to therapeutic applications. To understand how CRISPR/Cas9 discriminates between on-targets and off-targets, we have developed a single-molecule assay combining optical tweezers with fluorescence to monitor binding to λ-DNA. At low forces, the Streptococcus pyogenes Cas9 complex binds and cleaves DNA specifically. At higher forces, numerous off-target binding events appear repeatedly at the same off-target sites in a guide-RNA-sequence-dependent manner, driven by the mechanical distortion of the DNA. Using single-molecule Förster resonance energy transfer (smFRET) and cleavage assays, we show that DNA bubbles induce off-target binding and cleavage at these sites, even with ten mismatches, as well as at previously identified in vivo off-targets. We propose that duplex DNA destabilization during cellular processes (for example, transcription, replication, etc.) can expose these cryptic off-target sites to Cas9 activity, highlighting the need for improved off-target prediction algorithms.

Funder: National Institute for Health Research; Id: http://dx.doi.org/10.13039/501100014338, Funder: NHS Blood and Transplant; Id: http://dx.doi.org/10.13039/100009033, Funder: Bristol‐Myers Squibb; Id: http://dx.doi.org/10.13039/100002491, Funder: European Commission; Id: http://dx.doi.org/10.13039/100013273, Background: Megakaryocytes (MKs) originate from cells immuno‐phenotypically indistinguishable from hematopoietic stem cells (HSCs), bypassing intermediate progenitors. They mature within the adult bone marrow and release platelets into the circulation. Until now, there have been no transcriptional studies of primary human bone marrow MKs. Objectives: To characterize MKs and HSCs from human bone marrow using single‐cell RNA sequencing, to investigate MK lineage commitment, maturation steps, and thrombopoiesis. Results: We show that MKs at different levels of polyploidization exhibit distinct transcriptional states. Although high levels of platelet‐specific gene expression occur in the lower ploidy classes, as polyploidization increases, gene expression is redirected toward translation and posttranslational processing transcriptional programs, in preparation for thrombopoiesis. Our findings are in keeping with studies of MK ultrastructure and supersede evidence generated using in vitro cultured MKs. Additionally, by analyzing transcriptional signatures of a single HSC, we identify two MK‐biased HSC subpopulations exhibiting unique differentiation kinetics. We show that human bone marrow MKs originate from these HSC subpopulations, supporting the notion that they display priming for MK differentiation. Finally, to investigate transcriptional changes in MKs associated with stress thrombopoiesis, we analyzed bone marrow MKs from individuals with recent myocardial infarction and found a specific gene expression signature. Our data support the modulation of MK differentiation in this thrombotic state. Conclusions: Here, we use single‐cell sequencing for the first time to characterize the human bone marrow MK transcriptome at different levels of polyploidization and investigate their differentiation from the HSC.

Aim The aim of this study was to explore the benefits of data integration from different platforms for single nucleus transcriptomics profiling to characterize cell populations in human liver. Methods We generated single-nucleus RNA sequencing data from Chromium 10X Genomics and Drop-seq for a human liver sample. We utilized state of the art bioinformatics tools to undertake a rigorous quality control and to integrate the data into a common space summarizing the gene expression variation from the respective platforms, while accounting for known and unknown confounding factors. Results Analysis of single nuclei transcriptomes from both 10X and Drop-seq allowed identification of the major liver cell types, while the integrated set obtained enough statistical power to separate a small population of inactive hepatic stellate cells that was not characterized in either of the platforms. Conclusions Integration of droplet-based single nucleus transcriptomics data enabled identification of a small cluster of inactive hepatic stellate cells that highlights the potential of our approach. We suggest single-nucleus RNA sequencing integrative approaches could be utilized to design larger and cost-effective studies.

Azoospermia is a condition defined as the absence of spermatozoa in the ejaculate, but the testicular phenotype of men with azoospermia may be very variable, ranging from full spermatogenesis, through arrested maturation of germ cells at different stages, to completely degenerated tissue with ghost tubules. Hence, information regarding the cell-type-specific expression patterns is needed to prioritise potential pathogenic variants that contribute to the pathogenesis of azoospermia. Thanks to technological advances within next-generation sequencing, it is now possible to obtain detailed cell-type-specific expression patterns in the testis by single-cell RNA sequencing. However, to interpret single-cell RNA sequencing data properly, substantial knowledge of the highly sophisticated data processing and visualisation methods is needed. Here we review the complex cellular structure of the human testis in different types of azoospermia and outline how known genetic alterations affect the pathology of the testis. We combined the currently available single-cell RNA sequencing datasets originating from the human testis into one dataset covering 62,751 testicular cells, each with a median of 2637 transcripts quantified. We show what effects the most common data-processing steps have, and how different visualisation methods can be used. Furthermore, we calculated expression patterns in pseudotime, and show how splicing rates can be used to determine the velocity of differentiation during spermatogenesis. With the combined dataset we show expression patterns and network analysis of genes known to be involved in the pathogenesis of azoospermia. Finally, we provide the combined dataset as an interactive online resource where expression of genes and different visualisation methods can be explored ( https://testis.cells.ucsc.edu/ ).

Contemporary speciation provides a unique opportunity to directly observe the traits and environmental responses of a new species. Cardamine insueta is an allotriploid species that appeared within the past 150 years in a Swiss village, Urnerboden. In contrast to its two progenitor species, C. amara and C. rivularis that live in wet and open habitats, respectively, C. insueta is found in-between their habitats with temporal water level fluctuation. This triploid species propagates clonally and serves as a triploid bridge to form higher ploidy species. Although niche separation is observed in field studies, the mechanisms underlying the environmental robustness of C. insueta are not clear. To characterize responses to a fluctuating environment, we performed a time-course analysis of homeolog gene expression in C. insueta in response to submergence treatment. For this purpose, the two parental (C. amara and C. rivularis) genome sequences were assembled with a reference-guided approach, and homeolog-specific gene expression was quantified by using HomeoRoq software. We found that C. insueta and C. rivularis initiated vegetative propagation by forming ectopic meristems on leaves, while C. amara did not. We examined homeolog-specific gene expression of three species at nine time points during the treatment. The genome-wide expression ratio of homeolog pairs was 2:1 over the time-course, consistent with the ploidy number. By searching the genes with high coefficient of variation of expression over time-course transcriptome data, we found many known key transcriptional factors related to meristem development and formation upregulated in both C. rivularis and rivularis-homeolog of C. insueta, but not in C. amara. Moreover, some amara-homeologs of these genes were also upregulated in the triploid, suggesting trans-regulation. In turn, Gene Ontology analysis suggested that the expression pattern of submergence tolerant genes in the triploid was inherited from C. amara. These results suggest that the triploid C. insueta combined advantageous patterns of parental transcriptomes to contribute to its establishment in a new niche along a water-usage gradient.

Uncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin). Dynamic molecular analysis at in vivo drug exposure levels reveal a network of 175 disease-associated proteins and identify common modules of anthracycline cardiotoxicity in vitro, related to mitochondrial and sarcomere function as well as remodeling of extracellular matrix. These in vitro-identified modules are transferable and are evaluated with biopsies of cardiomyopathy patients. This to our knowledge most comprehensive study on anthracycline cardiotoxicity demonstrates a reproducible workflow for molecular medicine and serves as a template for detecting adverse drug responses from complex omics data., Using a network propagation approach with integrated multi-omic data, Selevsek et al. develop a reproducible workflow for identifying drug toxicity effects in cellular systems. This is demonstrated with the analysis of anthracycline cardiotoxicity in cardiac microtissues under the effect of multiple drugs.

Transcription factors (TFs) often function as a module including both master factors and mediators binding at cis-regulatory regions to modulate nearby gene transcription. ChIP-seq profiling of multiple TFs makes it feasible to infer functional TF modules. However, when inferring TF modules based on co-localization of ChIP-seq peaks, often many weak binding events are missed, especially for mediators, resulting in incomplete identification of modules. To address this problem, we develop a ChIP-seq data-driven Gibbs Sampler to infer Modules (ChIP-GSM) using a Bayesian framework that integrates ChIP-seq profiles of multiple TFs. ChIP-GSM samples read counts of module TFs iteratively to estimate the binding potential of a module to each region and, across all regions, estimates the module abundance. Using inferred module-region probabilistic bindings as feature units, ChIP-GSM then employs logistic regression to predict active regulatory elements. Validation of ChIP-GSM predicted regulatory regions on multiple independent datasets sharing the same context confirms the advantage of using TF modules for predicting regulatory activity. In a case study of K562 cells, we demonstrate that the ChIP-GSM inferred modules form as groups, activate gene expression at different time points, and mediate diverse functional cellular processes. Hence, ChIP-GSM infers biologically meaningful TF modules and improves the prediction accuracy of regulatory region activities., Author summary Investigating TF binding to different types of regulatory regions can help reveal underlying activation mechanisms. However, accurately inferring modules among a large set of TFs is challenging due to the existence of weak, noisy, and context-sensitive binding signals. To reliably infer TF modules, here we describe ChIP-GSM, a Gibbs sampler built upon a Bayesian framework, that can further predict active regulatory elements. A comparison with other methods demonstrates ChIP-GSM’s improved performance on module identification and active regulatory element prediction. Experimental results demonstrate that TF modules identified by ChIP-GSM are likely mediating distinct cellular functions by activating regulatory regions at different time points.

Feline infectious peritonitis (FIP) is a coronavirus-induced disease of cats, in which the immune system is known to play a crucial, but complex, role in the pathogenesis. This role is still incompletely understood, with involvement of both host and viral factors. To evaluate differential gene expression and pathway involvement in feline coronavirus (FCoV) infection and FIP, we applied next-generation RNA-sequencing of the mesenteric lymph nodes from cats with naturally-acquired FIP, as well as those with systemic FCoV infection without FIP, and those with neither. Viral infection was associated with upregulation of viral defenses regardless of the disease state, but to a greater degree in FIP. FIP was associated with higher pro-inflammatory pathway enrichment, whilst non-FIP FCoV-positive cats showed lower enrichment of humoral immunity pathways, below that of uninfected cats in the case of immunoglobulin production pathways. This host response is presumed to be protective. In FIP, downregulation of T cell-related processes was observed, which did not occur in non-FIP FCoV-positive cats. These results emphasize the importance of the host&rsquo, s immune balance in determining the outcome of the FCoV infection.

BackgroundIn gene expression studies, RNA sample pooling is sometimes considered because of budget constraints or lack of sufficient input material. Using microarray technology, RNA sample pooling strategies have been reported to optimize both the cost of data generation as well as the statistical power for differential gene expression (DGE) analysis. For RNA sequencing, with its different quantitative output in terms of counts and tunable dynamic range, the adequacy and empirical validation of RNA sample pooling strategies have not yet been evaluated. In this study, we comprehensively assessed the utility of pooling strategies in RNA-seq experiments using empirical and simulated RNA-seq datasets.ResultThe data generating model in pooled experiments is defined mathematically to evaluate the mean and variability of gene expression estimates. The model is further used to examine the trade-off between the statistical power of testing for DGE and the data generating costs. Empirical assessment of pooling strategies is done through analysis of RNA-seq datasets under various pooling and non-pooling experimental settings. Simulation study is also used to rank experimental scenarios with respect to the rate of false and true discoveries in DGE analysis. The results demonstrate that pooling strategies in RNA-seq studies can be both cost-effective and powerful when the number of pools, pool size and sequencing depth are optimally defined.ConclusionFor high within-group gene expression variability, small RNA sample pools are effective to reduce the variability and compensate for the loss of the number of replicates. Unlike the typical cost-saving strategies, such as reducing sequencing depth or number of RNA samples (replicates), an adequate pooling strategy is effective in maintaining the power of testing DGE for genes with low to medium abundance levels, along with a substantial reduction of the total cost of the experiment. In general, pooling RNA samples or pooling RNA samples in conjunction with moderate reduction of the sequencing depth can be good options to optimize the cost and maintain the power. This study was sponsored by a Gent University Special Research Fund Concerted Research Actions (GOA grant number BOF16-GOA-023). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Assefa, AT (corresponding author), Univ Ghent, Dept Data Anal & Math Modeling, Ghent 9000, Belgium. alemutakele.assefa@UGent.be

To study the genetic structure of clonal plant populations, genotyping and genet detection using genetic markers are necessary to assign ramets to corresponding genets. Assignment is difficult as it involves setting a robust threshold of genetic distance for genet distinction as neighbouring genets in a plant population are often genetically related. Here, we used restriction site-associated DNA sequencing (RAD-seq) for a rhizomatous clonal herb, Cardamine leucantha [Brassicaceae] to accurately determine genet structure in a natural population. We determined a draft genome sequence of this species for the first time, which resulted in 66 617 scaffolds with N50 = 6086 bp and an estimated genome size of approximately 253 Mbp. Using genetic distances based on the RAD-seq analysis, we successfully distinguished ramets that belonged to distinct genets even from a half-sib family. We applied these methods to 372 samples of C. leucantha collected at 1-m interval grids within a 20 × 20 m plot in a natural population in Hokkaido, Japan. From these samples, we identified 61 genets with high inequality in terms of genet size and patchy distribution. Spatial autocorrelation analyses indicated significant aggregation within 7 and 4 m at ramet and genet levels, respectively. An analysis of parallel DNA microsatellite loci (simple sequence repeats) suggested that RAD-seq can provide data that allows robust genet assignment. It remains unclear whether the large genets identified here became dominant stochastically or deterministically. Precise identification of genets will assist further study and characterization of dominant genets., Clonal plants produce genetically identical offspring through vegetative growth. A ‘ramet’ refers to a single physiological individual produced by clonal propagation; a ‘genet’ refers to a group of ramets that originate from a single seed. Here we investigated how ramets that belong to different genets distribute in a natural population of Carrdamine leucantha using a genome-wide SNP markers. We applied the method to 372 samples collected at 1-m interval grids within a 20 × 20 m plot, and identified 61 genets with high inequality in terms of genet size and patchy distribution.