ABSTRACT
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.
ABSTRACT
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.
Subject(s)
Antipsychotic Agents , Depressive Disorder, Major , Methamphetamine , Humans , Mice , Animals , Antipsychotic Agents/pharmacology , Antipsychotic Agents/therapeutic use , Metergoline/therapeutic use , Depressive Disorder, Major/drug therapy , Dizocilpine Maleate , Transcriptome , Vascular Endothelial Growth Factor AABSTRACT
OBJECTIVES: The aim of this study was to repurpose a drug for the treatment of bipolar depression. METHODS: A gene expression signature representing the overall transcriptomic effects of a cocktail of drugs widely prescribed to treat bipolar disorder was generated using human neuronal-like (NT2-N) cells. A compound library of 960 approved, off-patent drugs were then screened to identify those drugs that affect transcription most similar to the effects of the bipolar depression drug cocktail. For mechanistic studies, peripheral blood mononuclear cells were obtained from a healthy subject and reprogrammed into induced pluripotent stem cells, which were then differentiated into co-cultured neurons and astrocytes. Efficacy studies were conducted in two animal models of depressive-like behaviours (Flinders Sensitive Line rats and social isolation with chronic restraint stress rats). RESULTS: The screen identified trimetazidine as a potential drug for repurposing. Trimetazidine alters metabolic processes to increase ATP production, which is thought to be deficient in bipolar depression. We showed that trimetazidine increased mitochondrial respiration in cultured human neuronal-like cells. Transcriptomic analysis in induced pluripotent stem cell-derived neuron/astrocyte co-cultures suggested additional mechanisms of action via the focal adhesion and MAPK signalling pathways. In two different rodent models of depressive-like behaviours, trimetazidine exhibited antidepressant-like activity with reduced anhedonia and reduced immobility in the forced swim test. CONCLUSION: Collectively our data support the repurposing of trimetazidine for the treatment of bipolar depression.
Subject(s)
Bipolar Disorder , Trimetazidine , Rats , Humans , Animals , Trimetazidine/pharmacology , Trimetazidine/therapeutic use , Bipolar Disorder/drug therapy , Bipolar Disorder/genetics , Transcriptome , Drug Repositioning , Leukocytes, Mononuclear , Disease Models, AnimalABSTRACT
Targeting ß-cell failure could prevent, delay or even partially reverse Type 2 diabetes. However, development of such drugs is limited as the molecular pathogenesis is complex and incompletely understood. Further, while ß-cell failure can be modeled experimentally, only some of the molecular changes will be pathogenic. Therefore, we used a novel approach to identify molecular pathways that are not only changed in a diabetes-like state but also are reversible and can be targeted by drugs. INS1E cells were cultured in high glucose (HG, 20 mM) for 72 h or HG for an initial 24 h followed by drug addition (exendin-4, metformin and sodium salicylate) for the remaining 48 h. RNAseq (Illumina TruSeq), gene set enrichment analysis (GSEA) and pathway analysis (using Broad Institute, Reactome, KEGG and Biocarta platforms) were used to identify changes in molecular pathways. HG decreased function and increased apoptosis in INS1E cells with drugs partially reversing these effects. HG resulted in upregulation of 109 pathways while drug treatment downregulated 44 pathways with 21 pathways in common. Interestingly, while hyperglycemia extensively upregulated metabolic pathways, they were not altered with drug treatment, rather pathways involved in the cell cycle featured more heavily. GSEA for hyperglycemia identified many known pathways validating the applicability of our cell model to human disease. However, only a fraction of these pathways were downregulated with drug treatment, highlighting the importance of considering druggable pathways. Overall, this provides a powerful approach and resource for identifying appropriate targets for the development of ß-cell drugs.
Subject(s)
Diabetes Mellitus, Type 2 , Hyperglycemia , Insulin-Secreting Cells , Metformin , Humans , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/genetics , Metformin/pharmacology , Signal TransductionABSTRACT
INTRODUCTION: Mood disorders are a major cause of disability, and current treatment options are inadequate for reducing the burden on a global scale. The aim of this project was to identify drugs suitable for repurposing to treat mood disorders. METHODS: This mixed-method study utilized gene expression signature technology and pharmacoepidemiology to investigate drugs that may be suitable for repurposing to treat mood disorders. RESULTS: The transcriptional effects of a combination of drugs commonly used to treat mood disorders included regulation of the steroid and terpenoid backbone biosynthesis pathways, suggesting a mechanism involving cholesterol biosynthesis, and effects on the thyroid hormone signaling pathway. Connectivity Map analysis highlighted metformin, an FDA-approved treatment for type 2 diabetes, as a drug having global transcriptional effects similar to the mood disorder drug combination investigated. In a retrospective cohort study, we found evidence that metformin is protective against the onset of mood disorders. DISCUSSION: These results provide proof-of-principle of combining gene expression signature technology with pharmacoepidemiology to identify potential novel drugs for treating mood disorders. Importantly, metformin may have utility in the treatment of mood disorders, warranting future randomized controlled trials to test its efficacy.
Subject(s)
Diabetes Mellitus, Type 2 , Metformin , Humans , Mood Disorders/drug therapy , Metformin/pharmacology , Metformin/therapeutic use , Diabetes Mellitus, Type 2/drug therapy , Retrospective StudiesABSTRACT
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.
Subject(s)
Heat-Shock Proteins , Songbirds , Animals , Female , Climate Change , Heat-Shock Proteins/genetics , TemperatureABSTRACT
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.
ABSTRACT
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.
ABSTRACT
Hospital-acquired infections (HAIs) are a growing concern around the world. They contribute to increasing mortality and morbidity rates and are an economic threat. All hospital patients have the potential to contract an HAI, but those with weakened or inferior immune systems are at highest risk. Most hospital patients will contract at least one HAI, but many will contract multiple ones. Bacteria are the most common cause of HAIs and contribute to 80-90% of all HAIs, with Staphylococcus aureus, Clostridium difficile, Escherichia coli, Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae accounting for the majority. Each of these bacteria are highly resistant to antibiotics and can produce a protective film, known as a biofilm, to further prevent their eradication. It has been shown that by detecting and eradicating bacteria in the environment, infection rates can be reduced. The current methods for detecting bacteria are time consuming, non-specific, and prone to false negatives or false positives. Aptamer-based biosensors have demonstrated specific, time-efficient and simple detection, highlighting the likelihood that they could be used in a similar way to detect HAI-causing bacteria.
Subject(s)
Cross Infection/diagnosis , Cross Infection/microbiology , Cross Infection/drug therapy , Cross Infection/prevention & control , Disease Management , Disease Susceptibility , Drug Resistance, Bacterial , Humans , Microbiological Techniques , Molecular Diagnostic Techniques , Sensitivity and SpecificityABSTRACT
BACKGROUND: The drugs commonly used to treat bipolar disorder have limited efficacy and drug discovery is hampered by the paucity of knowledge of the pathophysiology of this disease. This study aims to explore the role of microRNAs in bipolar disorder and understand the molecular mechanisms of action of commonly used bipolar disorder drugs. METHODS: The transcriptional effects of bipolar disorder drug combination (lithium, valproate, lamotrigine and quetiapine) in cultured human neuronal cells were studied using next generation sequencing. Differential expression of genes (n=20) and microRNAs (n=6) was assessed and the differentially expressed microRNAs were confirmed with TaqMan MicroRNA Assays. The expression of the differentially expressed microRNAs were inhibited to determine bipolar disorder drug effects on their target genes (n=8). Independent samples t-test was used for normally distributed data and Kruskal-Wallis/Mann-Whitney U test was used for data not distributed normally. Significance levels were set at p<0.05. RESULTS: We found that bipolar disorder drugs tended to increase the expression of miR-128 and miR-378 (p<0.05). Putative target genes of these microRNAs targeted pathways including those identified as "neuron projection development" and "axonogenesis". Many of the target genes are inhibitors of neurite outgrowth and neurogenesis and were downregulated following bipolar disorder drug combination treatment (all p<0.05). The bipolar disorder drug combination tended to decrease the expression of the target genes (NOVA1, GRIN3A, and VIM), however this effect could be reversed by the application of microRNA inhibitors. CONCLUSIONS: We conclude that at a transcriptional level, bipolar disorder drugs affect several genes in concert that would increase neurite outgrowth and neurogenesis and hence neural plasticity, and that this effect is mediated (at least in part) by modulation of the expression of these two key microRNAs.
Subject(s)
Gene Expression/drug effects , MicroRNAs/biosynthesis , Neuronal Outgrowth/genetics , Cells, Cultured , Drug Synergism , Humans , Lamotrigine/pharmacology , Lithium Chloride/pharmacology , Quetiapine Fumarate/pharmacology , Valproic Acid/pharmacologyABSTRACT
OBJECTIVES: To create a gene expression signature (GES) to represent the biological effects of a combination of known drugs for bipolar disorder (BD) on cultured human neuronal cells (NT2-N) and rat brains, which also has evidence of differential expression in individuals with BD. To use the GES to identify new drugs for BD using Connectivity Map (CMap).Methods: NT2-N (n = 20) cells and rats (n = 8) were treated with a BD drug combination (lithium, valproate, quetiapine and lamotrigine) or vehicle for 24 and 6 h, respectively. Following next-generation sequencing, the differential expression of genes was assessed using edgeR in R. The derived GES was compared to differentially expressed genes in post-mortem brains of individuals with BD. The GES was then used in CMap analysis to identify similarly acting drugs.Results: A total of 88 genes showed evidence of differential expression in response to the drug combination in both models, and therefore comprised the GES. Six of these genes showed evidence of differential expression in post-mortem brains of individuals with BD. CMap analysis identified 10 compounds (camptothecin, chlorambucil, flupenthixol, valdecoxib, rescinnamine, GW-8510, cinnarizine, lomustine, mifepristone and nimesulide) acting similarly to the BD drug combination.Conclusions: This study shows that GES and CMap can be used as tools to repurpose drugs for BD.
Subject(s)
Bipolar Disorder , Drug Repositioning , Pharmaceutical Preparations , Animals , Bipolar Disorder/drug therapy , Bipolar Disorder/genetics , Lamotrigine , Quetiapine Fumarate , Rats , TranscriptomeABSTRACT
An emerging novel therapeutic agent for major depressive disorder, minocycline, has the potential to influence both gut microbiome and inflammatory status. The present study showed that chronic high fat diet feeding led to changes in both behaviour and the gut microbiome in male mice, without an overt inflammatory response. The diet-induced behavioural changes were characterised as increased immobility in the forced swim test and changes in locomotor activities in the open field test. Minocycline significantly altered the gut microbiome, rendering a community distinctly different to both untreated healthy and diet-affected states. In contrast, minocycline did not reverse high fat diet-induced changes in behaviour.
Subject(s)
Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/physiology , Minocycline/pharmacology , Animals , Anxiety/metabolism , Behavior, Animal/physiology , Depression/metabolism , Depressive Disorder, Major/metabolism , Diet, High-Fat/adverse effects , Disease Models, Animal , Male , Mice , Mice, Inbred C57BL , Microbiota/drug effects , Minocycline/metabolismABSTRACT
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?"
Subject(s)
High-Throughput Nucleotide Sequencing , Animals , Base Sequence , Dendritic Cells/drug effects , Dendritic Cells/metabolism , Gene Library , Lipopolysaccharides/pharmacology , Mass Spectrometry , Mice , RNA, Messenger/metabolism , Single-Cell Analysis , SoftwareABSTRACT
Objectives: To understand the therapeutic mechanisms of bipolar disorder (BD) drugs at molecular and cellular levels.Methods: Next generation sequencing was used to determine the transcriptional effects of a combination of four commonly prescribed BD drugs (lithium, valproate, lamotrigine and quetiapine) or vehicle (0.2% DMSO) in NT2-N (human neuronal) cells and rats. Differential expression of genes and pathway analysis were performed using edgeR in R and Gene Set Enrichment Analysis software respectively. Free cholesterol levels and neurite outgrowth were quantified in NT2-N cells following combination and individual BD drug treatments.Results: Pathway analysis showed up-regulation of many elements of the cholesterol biosynthesis pathway in NT2-N cells and oxidative phosphorylation in rat brains. Intracellular cholesterol transport genes were upregulated (NPC1, NPC2 and APOE), while the cholesterol efflux gene (ABCA1) was downregulated. BD drug combination tended to increase intracellular cholesterol levels and neurite outgrowth, but these effects were not seen for the drugs when used individually.Conclusions: These data suggest that BD drug combination is increasing cholesterol biosynthesis and the newly synthesised cholesterol is being utilised within the cells, possibly for synthesis of new membranes to facilitate neurite outgrowth. This mechanism possibly underpins clinical efficacy in individuals with BD treated with polypharmacy.
Subject(s)
Antipsychotic Agents/pharmacology , Bipolar Disorder/metabolism , Cholesterol/biosynthesis , Neuronal Outgrowth/drug effects , Animals , Bipolar Disorder/drug therapy , Cholesterol/genetics , Drug Therapy, Combination , Gene Expression Profiling , Humans , Male , Rats , Rats, Sprague-DawleyABSTRACT
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.
Subject(s)
Autism Spectrum Disorder/genetics , Gene Regulatory Networks/genetics , Sex Characteristics , Autism Spectrum Disorder/physiopathology , Autistic Disorder/genetics , Autistic Disorder/physiopathology , Biomarkers , Brain/metabolism , Female , Gene Expression Profiling/methods , Humans , Male , Sequence Analysis, RNA/methods , Siblings , Transcriptome/geneticsABSTRACT
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.
ABSTRACT
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.
Subject(s)
Benchmarking , Gene Expression Profiling/methods , Sequence Analysis, RNA/methods , Software , Base Sequence , Computer Simulation , Databases, Genetic , High-Throughput Nucleotide Sequencing , Humans , RNA, Messenger/genetics , RNA, Messenger/metabolism , RNA, Ribosomal, 16S/geneticsABSTRACT
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.
Subject(s)
Sequence Analysis , Gene Library , Humans , Models, Statistical , Sequence Analysis/statistics & numerical dataABSTRACT
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.