Cross-species Method Research Articles

Cross-species transcriptomics reveals bifurcation point during the arterial-to-hemogenic transition

Hemogenic endothelium (HE) with hematopoietic stem cell (HSC)-forming potential emerge from specialized arterial endothelial cells (AECs) undergoing the endothelial-to-hematopoietic transition (EHT) in the aorta-gonad-mesonephros (AGM) region. Characterization of this AECs subpopulation and whether this phenomenon is conserved across species remains unclear. Here we introduce HomologySeeker, a cross-species method that leverages refined mouse information to explore under-studied human EHT. Utilizing single-cell transcriptomic ensembles of EHT, HomologySeeker reveals a parallel developmental relationship between these two species, with minimal pre-HSC signals observed in human cells. The pre-HE stage contains a conserved bifurcation point between the two species, where cells progress towards HE or late AECs. By harnessing human spatial transcriptomics, we identify ligand modules that contribute to the bifurcation choice and validate CXCL12 in promoting hemogenic choice using a human in vitro differentiation system. Our findings advance human arterial-to-hemogenic transition understanding and offer valuable insights for manipulating HSC generation using in vitro models.

Reinforcer value moderates the effects of prenatal alcohol exposure on learning and reversal.

Fetal Alcohol Spectrum Disorders (FASD) are the leading cause of preventable developmental disability and are commonly characterized by alterations in executive function. Reversal learning tasks are reliable, cross-species methods for testing a frequently impaired aspect of executive control, behavioral flexibility. Pre-clinical studies commonly require the use of reinforcers to motivate animals to learn and perform the task. While there are several reinforcers available, the most commonly employed are solid (food pellets) and liquid (sweetened milk) rewards. Previous studies have examined the effects of different solid rewards or liquid dietary content on learning in instrumental responding and found that rodents on liquid reward with higher caloric content performed better with increased response and task acquisition rate. The influence of reinforcer type on reversal learning and how this interacts with developmental insults such as prenatal alcohol exposure (PAE) has not been explored. We tested whether reinforcer type during learning or reversal would impact an established deficit in PAE mice. We found that all male and female mice on liquid reward, regardless of prenatal exposure were better motivated to learn task behaviors during pre-training. Consistent with previous findings, both male and female PAE mice and Saccharine control mice were able to learn the initial stimulus reward associations irrespective of the reinforcer type. During the initial reversal phase, male PAE mice that received pellet rewards exhibited maladaptive perseverative responding whereas male mice that received liquid rewards performed comparable to their control counterparts. Female PAE mice that received either reinforcer types did not exhibit any deficits on behavioral flexibility. Female saccharine control mice that received liquid, but not pellet, rewards showed increased perseverative responding during the early reversal phase. These data suggest that reinforcer type can have a major impact on motivation, and therefore performance, during reversal learning. Highly motivating rewards may mask behavioral deficits seen with more moderately sought rewards and gestational exposure to the non-caloric sweetener, saccharine, can impact behavior motivated by those reinforcers in a sex-dependent manner.

Decreasing Species Richness with Increase in Elevation and Positive Rapoport Effects of Crambidae (Lepidoptera) on Mount Taibai.

Rapoport's rule proposes that a species' range size increases with the increase in a gradient (such as latitude, altitude or water depth). However, altitudinal distributions and Rapoport's rule have rarely been tested for Asian Lepidoptera. Pyraustinae and Spilomelinae (Lepidoptera: Crambidae) are extremely diverse in temperate Asia, including on Mount Taibai, which is considered a hotspot area for studying the vertical distribution patterns of insect species. Based on the investigation of altitudinal distribution data with identification by using both DNA barcoding and the morphological classification of Pyraustinae and Spilomelinae, this paper determines the altitudinal gradient pattern for these two subfamilies on the north slope of Mount Taibai, and provides a test of the universality of Rapoport's rule in Lepidoptera by using four methods, including Stevens' method, Pagel's method, Rohde's method, and the cross-species method. Our results show that the alpha diversity of Pyraustinae and Spilomelinae both decrease with rising altitude. By contrast, the species' ranges increase with rising altitude. Three of the four methods used to test Rapoport's rule yielded positive results, while Rohde's results show a unimodal distribution model and do not support Rapoport's rule. Our findings fill the research gap on the elevational diversity of Lepidoptera in temperate Asia.

StackRAM: a cross-species method for identifying RNA N6-methyladenosine sites based on stacked ensemble

N6-methyladenosine (m6A) is a prevalent RNA methylation modification, which plays an important role in various biological processes. Accurate identification of the m6A sites is fundamental to understand the biological functions and mechanisms of the modification deeply. However, the experimental methods for detecting m6A sites are usually time-consuming and expensive, and various computational methods have been developed to identify m6A sites in RNA. This paper proposes a novel cross-species computational method StackRAM using machine learning algorithms to identify the m6A sites in Saccharomyces cerevisiae (S. cerevisiae), Homo sapiens (H. sapiens), Arabidopsis thaliana (A. thaliana) and Mus musculus (M. musculus). First, the RNA sequence features are extracted through binary encoding, chemical property, nucleotide frequency, k-mer nucleotide frequency, pseudo dinucleotide composition, and position-specific trinucleotide propensity, and the initial feature dataset is obtained by feature fusion. Second, the Elastic Net is used for the first time to filter redundant and noisy information and retain important features for m6A sites classification. Finally, the base-classifiers output probabilities and the optimal feature subset corresponding to the Elastic Net are combined, and the combination feature is put into the second-stage meta-classifier SVM. The result of jackknife test on training dataset S. cerevisiae indicates that the prediction performance of StackRAM is superior to the current state-of-the-art methods. Prediction accuracy of StackRAM for independent test datasets H. sapiens, A. thaliana and M. musculus reach 92.30%, 87.06% and 91.86%, respectively. Therefore, StackRAM has developing potential in cross-species prediction and can be a useful method for identifying m6A sites.

MUNDO: protein function prediction embedded in a multispecies world.

Leveraging cross-species information in protein function prediction can add significant power to network-based protein function prediction methods, because so much functional information is conserved across at least close scales of evolution. We introduce MUNDO, a new cross-species co-embedding method that combines a single-network embedding method with a co-embedding method to predict functional annotations in a target species, leveraging also functional annotations in a model species network. Across a wide range of parameter choices, MUNDO performs best at predicting annotations in the mouse network, when trained on mouse and human protein-protein interaction (PPI) networks, in the human network, when trained on human and mouse PPIs, and in Baker's yeast, when trained on Fission and Baker's yeast, as compared to competitor methods. MUNDO also outperforms all the cross-species methods when predicting in Fission yeast when trained on Fission and Baker's yeast; however, in this single case, discarding the information from the other species and using annotations from the Fission yeast network alone usually performs best. All code is available and can be accessed here: github.com/v0rtex20k/MUNDO. Supplementary data are available at Bioinformatics Advances online. Additional experimental results are on our github site.

Exploiting genomic synteny in Felidae: cross-species genome alignments and SNV discovery can aid conservation management

BackgroundWhile recent advances in genomics has enabled vast improvements in the quantification of genome-wide diversity and the identification of adaptive and deleterious alleles in model species, wildlife and non-model species have largely not reaped the same benefits. This has been attributed to the resources and infrastructure required to develop essential genomic datasets such as reference genomes. In the absence of a high-quality reference genome, cross-species alignments can provide reliable, cost-effective methods for single nucleotide variant (SNV) discovery. Here, we demonstrated the utility of cross-species genome alignment methods in gaining insights into population structure and functional genomic features in cheetah (Acinonyx jubatas), snow leopard (Panthera uncia) and Sumatran tiger (Panthera tigris sumatrae), relative to the domestic cat (Felis catus).ResultsAlignment of big cats to the domestic cat reference assembly yielded nearly complete sequence coverage of the reference genome. From this, 38,839,061 variants in cheetah, 15,504,143 in snow leopard and 13,414,953 in Sumatran tiger were discovered and annotated. This method was able to delineate population structure but limited in its ability to adequately detect rare variants. Enrichment analysis of fixed and species-specific SNVs revealed insights into adaptive traits, evolutionary history and the pathogenesis of heritable diseases.ConclusionsThe high degree of synteny among felid genomes enabled the successful application of the domestic cat reference in high-quality SNV detection. The datasets presented here provide a useful resource for future studies into population dynamics, evolutionary history and genetic and disease management of big cats. This cross-species method of variant discovery provides genomic context for identifying annotated gene regions essential to understanding adaptive and deleterious variants that can improve conservation outcomes.

DNN-m6A: A Cross-Species Method for Identifying RNA N6-Methyladenosine Sites Based on Deep Neural Network with Multi-Information Fusion.

As a prevalent existing post-transcriptional modification of RNA, N6-methyladenosine (m6A) plays a crucial role in various biological processes. To better radically reveal its regulatory mechanism and provide new insights for drug design, the accurate identification of m6A sites in genome-wide is vital. As the traditional experimental methods are time-consuming and cost-prohibitive, it is necessary to design a more efficient computational method to detect the m6A sites. In this study, we propose a novel cross-species computational method DNN-m6A based on the deep neural network (DNN) to identify m6A sites in multiple tissues of human, mouse and rat. Firstly, binary encoding (BE), tri-nucleotide composition (TNC), enhanced nucleic acid composition (ENAC), K-spaced nucleotide pair frequencies (KSNPFs), nucleotide chemical property (NCP), pseudo dinucleotide composition (PseDNC), position-specific nucleotide propensity (PSNP) and position-specific dinucleotide propensity (PSDP) are employed to extract RNA sequence features which are subsequently fused to construct the initial feature vector set. Secondly, we use elastic net to eliminate redundant features while building the optimal feature subset. Finally, the hyper-parameters of DNN are tuned with Bayesian hyper-parameter optimization based on the selected feature subset. The five-fold cross-validation test on training datasets show that the proposed DNN-m6A method outperformed the state-of-the-art method for predicting m6A sites, with an accuracy (ACC) of 73.58–83.38% and an area under the curve (AUC) of 81.39–91.04%. Furthermore, the independent datasets achieved an ACC of 72.95–83.04% and an AUC of 80.79–91.09%, which shows an excellent generalization ability of our proposed method.

Mass spectrometry based detection of common vitellogenin peptides across fish species for assessing exposure to estrogenic compounds in aquatic environments

The identification of myriad of chemicals in the environment that mimic hormones and affect the endocrine functions of exposed organism is a daunting analytical challenge for environmental scientists and engineers. Many of these endocrine disrupting chemicals (EDCs) are present at very low concentrations in the aquatic systems, but yet affect the metabolic, developmental, and reproductive functions in exposed fish and wildlife. Vitellogenin (VTG) protein is a widely used biomarker in fish for assessing exposure to EDCs, and is commonly measured using species-specific immunochemical techniques. In this study, we developed a liquid chromatography tandem mass spectrometry (LC-MS/MS) method that can measure common peptides from digested VTG in multiple fish species. In the initial experiments using high resolution mass spectrometry, two peptides (ALHPELR and FIELIQLLR) were identified as common fragments in the digested VTG protein isolated from three different fish species (Pimephales promelas, Micropterus salmoides, and Fundulus heteroclitus). Then, a quantitative analysis using LC-MS/MS under selected reaction monitoring mode was developed for the detection of these two peptides in trypsin-digested plasma from female fish (positive control), estrogen-exposed male fish (test sample), and unexposed male fish (negative control) using two of the same species used for identifying the common peptides (P. promelas, and M. salmoides) and one new species (Ameiurus nebulosus) that was not included during the selection of peptides. Results from this study demonstrate the potential of LC-MS/MS as an effective cross-species method to detect VTG in fish, which can be an alternative analytical technique for assessing endocrine disruption in multiple fish species.

Development of Microsatellites: A Powerful Genetic Marker

The tandem repeats, conserved short segments of DNA, which are found in all prokaryotic and eukaryotic genomes, are called microsatellites. It is also known as variable number tandem repeats (VNTRs), simple sequence repeats (SSRs) and short tandem repeats (STRs). Microsatellites present in both coding and non-coding regions of a genome. The high polymorphism of microsatellites makes them powerful genetic markers for genome mapping of many organisms. It is also suitable for ancient and forensic DNA studies for population genetics and conservation of biological resources. The major disadvantage of microsatellites is that for the first time they need to be isolated de novo from most species being examined. The task of microsatellite isolation is quite cumbersome involving in terms of effort and time, because it traditionally involves screening of genomic libraries. Cross-species amplification, Mining microsatellites from nucleotide sequenced data and Genomic library- based method are general methods of microsatellite isolation. Cross-species method may not effective for all species, Data mining is not applicable if there is no or limited data of DNA sequence. Genomic library based method is the best choice. Traditional protocol, primer extension protocol, selective hybridization, and Fast Isolation by AFLP of Sequences containing repeats (FIASCO) are the protocols of microsatellite development based on genomic library. FIASCO is the best protocol ever developed.The Agriculturists 2015; 13(1) 152-172

Effect of cytokinins on delaying petunia flower senescence: a transcriptome study approach.

Flower senescence is a fascinating natural process that represents the final developmental stage in the life of a flower. Plant hormones play an important role in regulating the timing of flower senescence. Ethylene is a trigger and usually accelerates the senescence rate, while cytokinins are known to delay it. The aim of this work was to study the effect of 6-benzylaminopurine (BA) on petal senescence by transcript profile comparison after 3 or 6 h using a cross-species method by hybridizing petunia samples to a 4 × 44 K Agilent tomato array. The relative content of ethylene, abscisic acid, anthocyanins, total carotenoids and total phenols that determine the physiological behaviours of the petal tissue were measured. BA treatment prolonged the flower life and increased the concentrations of phenols and anthocyanins, while total carotenoids did not increase and were lower than the control. The ethylene biosynthetic and perception gene expressions were studied immediately after treatment until 24 h and all genes were repressed, while ethylene production was strongly induced after 4 days. The microarray analyses highlighted that BA strongly affected gene regulation after 3 h, but only 14% of genes remained differentially expressed after 6 h. The most affected pathways and genes were those related to stress, such as heat shock proteins, abscisic acid (ABA) catabolism and its signalling pathway, lipid metabolism and antioxidant defence systems. A gene annotation enrichment analysis using DAVID showed that the most important gene clusters were involved in energy generation and conservation processes. In addition to the ethylene pathway, cytokinins seem to be strongly involved the regulation of the ABA response in flower tissues.

A cross-species analysis method to analyze animal models' similarity to human's disease state

BackgroundAnimal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism.ResultsWe developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery.We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning.ConclusionsWe developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology.

Fusion of the Mycobacterium tuberculosis Antigen 85A to an Oligomerization Domain Enhances Its Immunogenicity in Both Mice and Non-Human Primates

To prevent important infectious diseases such as tuberculosis, malaria and HIV, vaccines inducing greater T cell responses are required. In this study, we investigated whether fusion of the M. tuberculosis antigen 85A to recently described adjuvant IMX313, a hybrid avian C4bp oligomerization domain, could increase T cell responses in pre-clinical vaccine model species. In mice, the fused antigen 85A showed consistent increases in CD4+ and CD8+ T cell responses after DNA and MVA vaccination. In rhesus macaques, higher IFN-γ responses were observed in animals vaccinated with MVA-Ag85A IMX313 after both primary and secondary immunizations. In both animal models, fusion to IMX313 induced a quantitative enhancement in the response without altering its quality: multifunctional cytokines were uniformly increased and differentiation into effector and memory T cell subsets was augmented rather than skewed. An extensive in vivo characterization suggests that IMX313 improves the initiation of immune responses as an increase in antigen 85A specific cells was observed as early as day 3 after vaccination. This report demonstrates that antigen multimerization using IMX313 is a simple and effective cross-species method to improve vaccine immunogenicity with potentially broad applicability.

Do Rapoport's rule, mid-domain effect or environmental factors predict latitudinal range size patterns of terrestrial mammals in China?

BackgroundExplaining species range size pattern is a central issue in biogeography and macroecology. Although several hypotheses have been proposed, the causes and processes underlying range size patterns are still not clearly understood. In this study, we documented the latitudinal mean range size patterns of terrestrial mammals in China, and evaluated whether that pattern conformed to the predictions of the Rapoport's rule several analytical methods. We also assessed the influence of the mid-domain effect (MDE) and environmental factors on the documented range size gradient.Methodology/Principal FindingsDistributions of 515 terrestrial mammals and data on nine environmental variables were compiled. We calculated mean range size of the species in each 5° latitudinal band, and created a range size map on a 100 km×100 km quadrat system. We evaluated Rapoport's rule according to Steven's, mid-point, Pagel's and cross-species methods. The effect of the MDE was tested based on a Monte Carlo simulation and linear regression. We used stepwise generalized linear models and correlation analyses to detect the impacts of mean climate condition, climate variability, ambient energy and topography on range size. The results of the Steven's, Pagel's and cross-species methods supported Rapoport's rule, whereas the mid-point method resulted in a hump-shaped pattern. Our range size map showed that larger mean latitudinal extents emerged in the mid-latitudes. We found that the MDE explained 80.2% of the range size variation, whereas, environmental factors accounted for <30% of that variation.Conclusions/SignificanceLatitudinal range size pattern of terrestrial mammals in China supported Rapoport's rule, though the extent of that support was strongly influenced by methodology. The critical factor underlying the observed gradient was the MDE, and the effects of climate, energy and topography were limited. The mean climate condition hypothesis, climate variability hypothesis, ambient energy hypotheses and topographical heterogeneity hypotheses were not supported.

Animal models of deficient sensorimotor gating: what we know, what we think we know, and what we hope to know soon.

Sensorimotor gating of the startle reflex can be studied in humans and laboratory animals using measures of prepulse inhibition (PPI) of the startle reflex. PPI is reduced in patients with specific neuropsychiatric disorders and in rats after manipulation of the limbic cortex, striatum, pallidum or pontine tegmentum. Studies are rapidly identifying the neurochemical and neuroanatomical substrates regulating PPI in laboratory animals; this detailed circuit information has been used as a 'blueprint' to identify possible candidate substrates responsible for PPI deficits in psychiatrically disordered humans. In parallel, studies have also begun to assess the homology of pharmacological effects on PPI across species, as an initial step towards translating detailed neural circuit information from rats to humans. Despite this rapid progress, there is an increasing danger of overlooking important methodological and interpretative issues that could impact either positively or negatively on the ultimate utility of models based on measures of PPI. Some of these issues--ranging from the cross-species methods for quantifying specific variables to the relevance of genetic drift to animal and human studies of PPI--and their implications for future studies are the focus of this review.

The Evolution of Mammalian Blood Parameters: Patterns and Their Interpretation

Taxonomic and allometric differences in blood parameters were studied in 206 species of mammals. Interspecific tests using the standard cross-species method and recently developed comparative methods that control for phylogenetic effects due to nonindependence of species emphasized the need for correct analytical methods. Contrary to previous studies, this study found that body mass was a signifcant predictor of blood parameters among mammals; body mass was positively and significantly correlated with red-cell volume and cell hemoglobin content and negatively correlated with red-cell count, platelet count, and percentage reticulocytes. Red-cell count and cell size were inversely correlated, such that hemoglobin levels tended to be relatively constant across species. Furthermore, this work suggests that, within species, high hemoglobin levels are maintained through high cell count rather than through large cell volume. The hypothesis is suggested that small cell size in mammals evolved as a means of facilitating rapid increase in blood hemoglobin through facultative increase in total erythrocyte number, possibly via splenic contraction, without the risk of reaching critical levels of viscosity.