Finding biomarkers of experience in animals.

At a time when there is a growing public interest in animal welfare, it is critical to have objective means to assess the way that an animal experiences a situation. Objectivity is critical to ensure appropriate animal welfare outcomes. Existing behavioural, physiological, and neurobiological indicators that are used to assess animal welfare can verify the absence of extremely negative outcomes. But welfare is more than an absence of negative outcomes and an appropriate indicator should reflect the full spectrum of experience of an animal, from negative to positive. In this review, we draw from the knowledge of human biomedical science to propose a list of candidate biological markers (biomarkers) that should reflect the experiential state of non-human animals. The proposed biomarkers can be classified on their main function as endocrine, oxidative stress, non-coding molecular, and thermobiological markers. We also discuss practical challenges that must be addressed before any of these biomarkers can become useful to assess the experience of an animal in real-life.

Metergoline Shares Properties with Atypical Antipsychotic Drugs Identified by Gene Expression Signature Screen.

Novel approaches are required to find new treatments for schizophrenia and other neuropsychiatric disorders. This study utilised a combination of in vitro transcriptomics and in silico analysis with the BROAD Institute's Connectivity Map to identify drugs that can be repurposed to treat psychiatric disorders. Human neuronal (NT2-N) cells were treated with a combination of atypical antipsychotic drugs commonly used to treat psychiatric disorders (such as schizophrenia, bipolar disorder, and major depressive disorder), and differential gene expression was analysed. Biological pathways with an increased gene expression included circadian rhythm and vascular endothelial growth factor signalling, while the adherens junction and cell cycle pathways were transcriptionally downregulated. The Connectivity Map (CMap) analysis screen highlighted drugs that affect global gene expression in a similar manner to these psychiatric disorder treatments, including several other antipsychotic drugs, confirming the utility of this approach. The CMap screen specifically identified metergoline, an ergot alkaloid currently used to treat seasonal affective disorder, as a drug of interest. In mice, metergoline dose-dependently reduced MK-801- or methamphetamine-induced locomotor hyperactivity confirming the potential of metergoline to treat positive symptoms of schizophrenia in an animal model. Metergoline had no effects on prepulse inhibition deficits induced by MK-801 or methamphetamine. Taken together, metergoline appears a promising drug for further studies to be repurposed as a treatment for schizophrenia and possibly other psychiatric disorders.

Acute exposure to high temperature affects expression of heat shock proteins in altricial avian embryos.

As the world warms, understanding the fundamental mechanisms available to organisms to protect themselves from thermal stress is becoming ever more important. Heat shock proteins are highly conserved molecular chaperones which serve to maintain cellular processes during stress, including thermal extremes. Developing animals may be particularly vulnerable to elevated temperatures, but the relevance of heat shock proteins for developing altricial birds exposed to a thermal stressor has never been investigated. Here, we sought to test whether three stress-induced genes - HSPD1, HSPA2, HSP90AA1 - and two constitutively expressed genes - HSPA8, HSP90B1 - are upregulated in response to acute thermal shock in zebra finch (Taeniopygia guttata) embryos half-way through incubation. Tested on a gradient from 37.5 °C (control) to 45 °C, we found that all genes, except HSPD1, were upregulated. However, not all genes initiated upregulation at the same temperature. For all genes, the best fitting model included a correlate of developmental stage that, although it was never significant after multiple-test correction, hints that heat shock protein upregulation might increase through embryonic development. Together, these results show that altricial avian embryos are capable of upregulating a known protective mechanism against thermal stress, and suggest that these highly conserved cellular mechanisms may be a vital component of early developmental protection under climate change.

Artificial gut and the applications in poultry: A review.

Artificial gut models including both the gastric and intestinal phases have been used in poultry research for decades to predict the digestibility of nutrients, the efficacy of feed enzymes and additives, and caecal fermentation. However, the models used in the past are static and cannot be used to predict interactions between the feed, gut environment and microbiome. It is imperative that a standard artificial gut model for poultry is established, to enable these interactions to be examined without continual reliance on animals. To ensure the validity of an artificial model, it should be validated with in vivo studies. This review describes current practices in the use of artificial guts in research, their importance in poultry nutrition studies and highlights an opportunity to develop a dynamic gut model for poultry to reduce the number of in vivo experiments.

Precision feeding and precision nutrition: a paradigm shift in broiler feed formulation?

Broiler chickens grow rapidly, and their nutrient requirements change daily. However, broilers are fed three to five diet phases, meaning nutrients are under or oversupplied throughout production. Increasing diet phases improves production efficiency as there is less time in the production cycle that nutrients are in under or over-supply. Nevertheless, the process of administering four or more diets is costly and often impractical. New technologies are now available to blend feed to match the daily nutrient requirements of broilers. Thus, the aim of this review is to evaluate previous studies measuring the impact of increasing feed phases on nutrient utilisation and growth performance, and review recent studies taking this concept to the extreme; precision nutrition - feeding a new diet for each day of the production cycle. This review will also discuss how modern precision feeding technologies have been utilised and the potential that new technologies may bring to the poultry industry. The development of a precision nutrition regime which targets daily requirements by blending dietary components on farm is anticipated to improve the efficiency of production, reduce production cost and therefore improve sustainability of the industry. There is also potential for precision feeding technology along with precision nutrition strategies to deliver a plethora of other management and economic benefits. These include increased fluidity to cope with sudden environmental or market changes, and the ability to alter diets on a farm by farm level in a large, integrated operation. Thus, the future possibilities and practical implications for such technologies to generate a paradigm shift in feed formulation within the poultry industry to meet the rising demand for animal protein is also discussed.

A field guide for the compositional analysis of any-omics data.

BACKGROUND: Next-generation sequencing (NGS) has made it possible to determine the sequence and relative abundance of all nucleotides in a biological or environmental sample. A cornerstone of NGS is the quantification of RNA or DNA presence as counts. However, these counts are not counts per se: their magnitude is determined arbitrarily by the sequencing depth, not by the input material. Consequently, counts must undergo normalization prior to use. Conventional normalization methods require a set of assumptions: they assume that the majority of features are unchanged and that all environments under study have the same carrying capacity for nucleotide synthesis. These assumptions are often untestable and may not hold when heterogeneous samples are compared. RESULTS: Methods developed within the field of compositional data analysis offer a general solution that is assumption-free and valid for all data. Herein, we synthesize the extant literature to provide a concise guide on how to apply compositional data analysis to NGS count data. CONCLUSIONS: In highlighting the limitations of total library size, effective library size, and spike-in normalizations, we propose the log-ratio transformation as a general solution to answer the question, "Relative to some important activity of the cell, what is changing?"

Anticipatory Behavior for a Mealworm Reward in Laying Hens Is Reduced by Opioid Receptor Antagonism but Not Standard Feed Intake.

It is widely accepted that the absence of suffering no longer defines animal welfare and that positive affective experiences are imperative. For example, laying hens may be housed in environments that do not cause chronic stress but may lack particular resources that promote positive affective experiences, such as conspecifics or effective enrichment. Despite a consensus of how important positive affect is for animal welfare, they are difficult to identify objectively. There is a need for valid and reliable indicators of positive affect. Pharmacological interventions can be an effective method to provide insight into affective states and can assist with the investigation of novel indicators such as associated biomarkers. We aimed to validate a pharmacological intervention that blocks the subjective hedonistic phase associated with reward in laying hens via the administration of the non-selective (µ, δ, and κ) opioid receptor antagonist, nalmafene. We hypothesized that nonfood deprived, hens that did not experience a positive affective state when presented with a mealworm food reward due to the administration of nalmefene, would show minimal anticipatory and consummatory behavior when the same food reward was later presented. Hens (n = 80) were allocated to treatment groups, receiving either nalmefene or vehicle (0.9% saline) once or twice daily, for four consecutive days. An anticipatory test (AT) was performed on all days 30 min post-drug administration. Behavioral responses during the appetitive and consummatory phase were assessed on days 1, 3 and 4. Anticipatory behavior did not differ between treatment groups the first time hens were provided with mealworm food rewards. However, antagonism of opioid receptors reduced anticipatory and consummatory behavior on days 3 and 4. Feed intake of standard layer mash was not impacted by treatment, thus nalmefene reduced non-homeostatic food consumption but not homeostatic consumption. Behavioral observations during the AT provided no evidence that nalmefene treated hens were fearful, sedated or nauseous. The results suggest that we successfully blocked the hedonistic subjective component of reward in laying hens and provide evidence that this method could be used to investigate how hens perceive their environment and identify associated novel indicators to assess hen welfare.

Solving for X: Evidence for sex-specific autism biomarkers across multiple transcriptomic studies.

Autism spectrum disorder (ASD) is a markedly heterogeneous condition with a varied phenotypic presentation. Its high concordance among siblings, as well as its clear association with specific genetic disorders, both point to a strong genetic etiology. However, the molecular basis of ASD is still poorly understood, although recent studies point to the existence of sex-specific ASD pathophysiologies and biomarkers. Despite this, little is known about how exactly sex influences the gene expression signatures of ASD probands. In an effort to identify sex-dependent biomarkers and characterize their function, we present an analysis of a single paired-end postmortem brain RNA-Seq data set and a meta-analysis of six blood-based microarray data sets. Here, we identify several genes with sex-dependent dysregulation, and many more with sex-independent dysregulation. Moreover, through pathway analysis, we find that these sex-independent biomarkers have substantially different biological roles than the sex-dependent biomarkers, and that some of these pathways are ubiquitously dysregulated in both postmortem brain and blood. We conclude by synthesizing the discovered biomarker profiles with the extant literature, by highlighting the advantage of studying sex-specific dysregulation directly, and by making a call for new transcriptomic data that comprise large female cohorts.

Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods.

BACKGROUND: Count data generated by next-generation sequencing assays do not measure absolute transcript abundances. Instead, the data are constrained to an arbitrary "library size" by the sequencing depth of the assay, and typically must be normalized prior to statistical analysis. The constrained nature of these data means one could alternatively use a log-ratio transformation in lieu of normalization, as often done when testing for differential abundance (DA) of operational taxonomic units (OTUs) in 16S rRNA data. Therefore, we benchmark how well the ALDEx2 package, a transformation-based DA tool, detects differential expression in high-throughput RNA-sequencing data (RNA-Seq), compared to conventional RNA-Seq methods such as edgeR and DESeq2. RESULTS: To evaluate the performance of log-ratio transformation-based tools, we apply the ALDEx2 package to two simulated, and two real, RNA-Seq data sets. One of the latter was previously used to benchmark dozens of conventional RNA-Seq differential expression methods, enabling us to directly compare transformation-based approaches. We show that ALDEx2, widely used in meta-genomics research, identifies differentially expressed genes (and transcripts) from RNA-Seq data with high precision and, given sufficient sample sizes, high recall too (regardless of the alignment and quantification procedure used). Although we show that the choice in log-ratio transformation can affect performance, ALDEx2 has high precision (i.e., few false positives) across all transformations. Finally, we present a novel, iterative log-ratio transformation (now implemented in ALDEx2) that further improves performance in simulations. CONCLUSIONS: Our results suggest that log-ratio transformation-based methods can work to measure differential expression from RNA-Seq data, provided that certain assumptions are met. Moreover, these methods have very high precision (i.e., few false positives) in simulations and perform well on real data too. With previously demonstrated applicability to 16S rRNA data, ALDEx2 can thus serve as a single tool for data from multiple sequencing modalities.

Understanding sequencing data as compositions: an outlook and review.

Motivation: Although seldom acknowledged explicitly, count data generated by sequencing platforms exist as compositions for which the abundance of each component (e.g. gene or transcript) is only coherently interpretable relative to other components within that sample. This property arises from the assay technology itself, whereby the number of counts recorded for each sample is constrained by an arbitrary total sum (i.e. library size). Consequently, sequencing data, as compositional data, exist in a non-Euclidean space that, without normalization or transformation, renders invalid many conventional analyses, including distance measures, correlation coefficients and multivariate statistical models. Results: The purpose of this review is to summarize the principles of compositional data analysis (CoDA), provide evidence for why sequencing data are compositional, discuss compositionally valid methods available for analyzing sequencing data, and highlight future directions with regard to this field of study. Supplementary information: Supplementary data are available at Bioinformatics online.

Impact of maternal high fat diet on hypothalamic transcriptome in neonatal Sprague Dawley rats.

Maternal consumption of a high fat diet during early development has been shown to impact the formation of hypothalamic neurocircuitry, thereby contributing to imbalances in appetite and energy homeostasis and increasing the risk of obesity in subsequent generations. Early in postnatal life, the neuronal projections responsible for energy homeostasis develop in response to appetite-related peptides such as leptin. To date, no study characterises the genome-wide transcriptional changes that occur in response to exposure to high fat diet during this critical window. We explored the effects of maternal high fat diet consumption on hypothalamic gene expression in Sprague Dawley rat offspring at postnatal day 10. RNA-sequencing enabled discovery of differentially expressed genes between offspring of dams fed a high fat diet and offspring of control diet fed dams. Female high fat diet offspring displayed altered expression of 86 genes (adjusted P-value<0.05), including genes coding for proteins of the extra cellular matrix, particularly Collagen 1a1 (Col1a1), Col1a2, Col3a1, and the imprinted Insulin-like growth factor 2 (Igf2) gene. Male high fat diet offspring showed significant changes in collagen genes (Col1a1 and Col3a1) and significant upregulation of two genes involved in regulation of dopamine availability in the brain, tyrosine hydroxylase (Th) and dopamine reuptake transporter Slc6a3 (also known as Dat1). Transcriptional changes were accompanied by increased body weight, body fat and body length in the high fat diet offspring, as well as altered blood glucose and plasma leptin. Transcriptional changes identified in the hypothalamus of offspring of high fat diet mothers could alter neuronal projection formation during early development leading to abnormalities in the neuronal circuitry controlling appetite in later life, hence priming offspring to the development of obesity.

propr: An R-package for Identifying Proportionally Abundant Features Using Compositional Data Analysis.

In the life sciences, many assays measure only the relative abundances of components in each sample. Such data, called compositional data, require special treatment to avoid misleading conclusions. Awareness of the need for caution in analyzing compositional data is growing, including the understanding that correlation is not appropriate for relative data. Recently, researchers have proposed proportionality as a valid alternative to correlation for calculating pairwise association in relative data. Although the question of how to best measure proportionality remains open, we present here a computationally efficient R package that implements three measures of proportionality. In an effort to advance the understanding and application of proportionality analysis, we review the mathematics behind proportionality, demonstrate its application to genomic data, and discuss some ongoing challenges in the analysis of relative abundance data.

Mapping genotype-phenotype associations of nsSNPs in coiled-coil oligomerization domains of the human proteome.

We assessed the impact of disease mutations (DMs) versus polymorphisms (PYs) in coiled-coil (CC) domains in UniProt by modeling the structural and functional impact of variants in silico with the CC prediction program Multicoil. The structural impact of variants was evaluated with respect to three main metrics: the oligomerization score-to determine whether the variant is stabilizing or destabilizing-the oligomerization state, and the register-specific score. The functional impact was queried indirectly in several ways. First, we examined marginally stable CCs that were either stabilized or destabilized by the variant. Second, we looked for variants that altered the register of the wild-type CC near wild-type irregularities of likely functional importance, such as skips and stammers. Third, we searched for variants that altered the oligomerization state of the CC. DMs tended to be more destabilizing than PYs; but interestingly, PYs were more frequently associated with predicted changes in the oligomerization state. The functional impact was also queried by testing the association of CC variants with multiple phenotypes, that is, pleiotropy. Mutations in CC regions of proteins cause 155 different phenotypes and are more frequently associated with pleiotropy than proteins in general. Importantly, the CC region itself often encodes the pleiotropy.

Gene expression signature: a powerful approach for drug discovery in diabetes.

Type 2 diabetes (T2D) is increasing in prevalence at an alarming rate around the world. Much effort has gone into the discovery and design of antidiabetic drugs; however, those already available are unable to combat the underlying causes of the disease and instead only moderate the symptoms. The reason for this is that T2D is a complex disease, and attempts to target one biological pathway are insufficient to combat the full extent of the disease. Additionally, the underlying pathophysiology of this disease is yet to be fully elucidated making it difficult to design drugs that target the mechanisms involved. Therefore, the approach of designing new drugs aimed at a specific molecular target is not optimal and a more expansive, unbiased approach is required. In this review, we will look at the current state of diabetes treatments and how these target the disease symptoms but are unable to combat the underlying causes. We will also review how the technique of gene expression signatures (GESs) has been used successfully for other complex diseases and how this may be applied as a powerful tool for the discovery of new drugs for T2D.

MicroRNAs in a hypertrophic heart: from foetal life to adulthood.

The heart is the first organ to form and undergoes adaptive remodelling with age. Ventricular hypertrophy is one such adaptation, which allows the heart to cope with an increase in cardiac demand. This adaptation is necessary as part of natural growth from foetal life to adulthood. It may also occur in response to resistance in blood flow due to various insults on the heart and vessels that accumulate with age. The heart can only compensate to this increase in workload to a certain extent without losing its functional architecture, ultimately resulting in heart failure. Many genes have been implicated in cardiac hypertrophy, however none have been shown conclusively to be responsible for pathological cardiac hypertrophy. MicroRNAs offer an alternative mechanism for cellular regulation by altering gene expression. Since 1993 when the function of a non-coding DNA sequence was first discovered in the model organism Caenorhabditis elegans, many microRNAs have been implicated in having a central role in numerous physiological and pathological cellular processes. The level of control these antisense oligonucleotides offer can often be exploited to manipulate the expression of target genes. Moreover, altered levels of microRNAs can serve as diagnostic biomarkers, with the prospect of diagnosing a disease process as early as during foetal life. Therefore, it is vital to ascertain and investigate the function of microRNAs that are involved in heart development and subsequent ventricular remodelling. Here we present an overview of the complicated network of microRNAs and their target genes that have previously been implicated in cardiogenesis and hypertrophy. It is interesting to note that microRNAs in both of these growth processes can be of possible remedial value to counter a similar disease pathophysiology.

Isolation and detection of microRNA from the egg of chickens.

BACKGROUND: The egg is a vital part of the chicken developmental process and an important protein source for humans. Despite the chicken egg being a subject of intense research little attention has been given to the role of microRNAs within the egg. FINDINGS: We report a method for the reproducible and reliable isolation of miRNA from the albumen and yolk of chicken eggs. We also report the detection via real-time PCR of a number of miRNAs from both of these biological fluids. CONCLUSIONS: These findings provide an interesting look into the chicken egg and raise questions as to the role that miRNAs maybe playing in the chicken egg. This method of detecting miRNAs in chicken eggs will allow researchers to investigate the presence of an additional level of epigenetic programming in chick development previously unknown and also how this impacts the nutritional value of eggs for human consumption.

Clinico-Pathological Association of Delineated miRNAs in Uveal Melanoma with Monosomy 3/Disomy 3 Chromosomal Aberrations.

PURPOSE: To correlate the differentially expressed miRNAs with clinico-pathological features in uveal melanoma (UM) tumors harbouring chromosomal 3 aberrations among South Asian Indian cohort. METHODS: Based on chromosomal 3 aberration, UM (n = 86) were grouped into monosomy 3 (M3; n = 51) and disomy 3 (D3; n = 35) by chromogenic in-situ hybridisation (CISH). The clinico-pathological features were recorded. miRNA profiling was performed in formalin fixed paraffin embedded (FFPE) UM samples (n = 6) using Agilent, Human miRNA microarray, 8x15KV3 arrays. The association between miRNAs and clinico-pathological features were studied using univariate and multivariate analysis. miRNA-gene targets were predicted using Target-scan and MiRanda database. Significantly dys-regulated miRNAs were validated in FFPE UM (n = 86) and mRNAs were validated in frozen UM (n = 10) by qRT-PCR. Metastasis free-survival and miRNA expressions were analysed by Kaplen-Meier analysis in UM tissues (n = 52). RESULTS: Unsupervised analysis revealed 585 differentially expressed miRNAs while supervised analysis demonstrated 82 miRNAs (FDR; Q = 0.0). Differential expression of 8 miRNAs: miR-214, miR-149*, miR-143, miR-146b, miR-199a, let7b, miR-1238 and miR-134 were studied. Gene target prediction revealed SMAD4, WISP1, HIPK1, HDAC8 and C-KIT as the post-transcriptional regulators of miR-146b, miR-199a, miR-1238 and miR-134. Five miRNAs (miR-214, miR146b, miR-143, miR-199a and miR-134) were found to be differentially expressed in M3/ D3 UM tumors. In UM patients with liver metastasis, miR-149* and miR-134 expressions were strongly correlated. CONCLUSION: UM can be stratified using miRNAs from FFPE sections. miRNAs predicting liver metastasis and survival have been identified. Mechanistic linkage of de-regulated miRNA/mRNA expressions provide new insights on their role in UM progression and aggressiveness.

Selection on Mitochondrial Variants Occurs between and within Individuals in an Expanding Invasion.

Mitochondria are critical for life, yet their underlying evolutionary biology is poorly understood. In particular, little is known about interaction between two levels of evolution: between individuals and within individuals (competition between cells, mitochondria or mitochondrial DNA molecules). Rapid evolution is suspected to occur frequently in mitochondrial DNA, whose maternal inheritance predisposes advantageous mutations to sweep rapidly though populations. Rapid evolution is also predicted in response to changed selection regimes after species invasion or removal of pathogens or competitors. Here, using empirical and simulated data from a model invasive bird species, we provide the first demonstration of rapid selection on the mitochondrial genome within individuals in the wild. Further, we show differences in mitochondrial DNA copy number associated with competing genetic variants, which may provide a mechanism for selection. We provide evidence for three rarely documented phenomena: selection associated with mitochondrial DNA abundance, selection on the mitochondrial control region, and contemporary selection during invasion.

Novel therapeutics for coronary artery disease from genome-wide association study data.

BACKGROUND: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD. METHODS: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (http://www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatic modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD. RESULTS: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05). CONCLUSIONS: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.