A glimpse into the genomic outlook of the long-tailed macaque (Macaca fascicularis)

The long-tailed macaque (Macaca fascicularis) is commonly used for biomedical researches. However, genetic variation within a population or among populations can significantly affect phenotypical outcomes of treatments tested on model organisms. As such, it is important for studies involving model organisms originating from different, or even the same geographical locations to have sufficient genomic and transcriptomic background of the model organisms that is used. This paper summarises the utilisation of next-generation sequencing (NGS) technology to sequence genomes and transcriptomes of long-tailed macaques from various geographical populations in general and the Malaysian long-tailed macaque in particular, and its importance in the context of population genetic studies

RNA sequencing (RNA-Seq) of lymph node, spleen, and thymus transcriptome from wild Peninsular Malaysian cynomolgus macaque (Macaca fascicularis)

The cynomolgus macaque (Macaca fascicularis) is an extensively utilised nonhuman primate model for biomedical research due to its biological, behavioural, and genetic similarities to humans. Genomic information of cynomolgus macaque is vital for research in various fields; however, there is presently a shortage of genomic information on the Malaysian cynomolgus macaque. This study aimed to sequence, assemble, annotate, and profile the Peninsular Malaysian cynomolgus macaque transcriptome derived from three tissues (lymph node, spleen, and thymus) using RNA sequencing (RNA-Seq) technology. A total of 174,208,078 paired end 70 base pair sequencing reads were obtained from the Illumina Hi-Seq 2500 sequencer. The overall mapping percentage of the sequencing reads to the M. fascicularis reference genome ranged from 53-63%. Categorisation of expressed genes to Gene Ontology (GO) and KEGG pathway categories revealed that GO terms with the highest number of associated expressed genes include Cellular process, Catalytic activity, and Cell part, while for pathway categorisation, the majority of expressed genes in lymph node, spleen, and thymus fall under the Global overview and maps pathway category, while 266, 221, and 138 genes from lymph node, spleen, and thymus were respectively enriched in the Immune system category. Enriched Immune system pathways include Platelet activation pathway, Antigen processing and presentation, B cell receptor signalling pathway, and Intestinal immune network for IgA production. Differential gene expression analysis among the three tissues revealed 574 differentially expressed genes (DEG) between lymph and spleen, 5402 DEGs between lymph and thymus, and 7008 DEGs between spleen and thymus. Venn diagram analysis of expressed genes revealed a total of 2,630, 253, and 279 tissue-specific genes respectively for lymph node, spleen, and thymus tissues. This is the first time the lymph node, spleen, and thymus transcriptome of the Peninsular Malaysian cynomolgus macaque have been sequenced via RNA-Seq. Novel transcriptomic data will further enrich the present M. fascicularis genomic database and provide future research potentials, including novel transcript discovery, comparative studies, and molecular markers development

Evolutionary acquisition of promoter-associated non-coding RNA (pancRNA) repertoires diversifies species-dependent gene activation mechanisms in mammals

Diversity of conserved pancRNA expression profile of the five tissues in the five species. Hierarchical clustering and symmetrical heat map of Spearman correlation coefficients of conserved pancRNA (A) and their corresponding mRNA (B) expression profiles. Samples are colored according to the tissues and the species. (PDF 301 kb

Structure and evolution of the gorilla and orangutan growth hormone loci

In primates, the unigenic growth hormone (GH) locus of prosimians, expressed primarily in the anterior pituitary, evolved by gene duplications, independently in New World Monkeys (NWM) and Old World Monkeys (OWMs)/apes, to give complex clusters of genes expressed in the pituitary and placenta. In human and chimpanzee, the GH locus comprises five genes, GH-N being expressed as pituitary GH, whereas GH-V (placental GH) and CSHs (chorionic somatomammotropins) are expressed (in human and probably chimpanzee) in the placenta; the CSHs comprise CSH-A, CSH-B and the aberrant CSH-L (possibly a pseudogene) in human, and CSH-A1, CSH-A2 and CSH-B in chimpanzee. Here the GH locus in two additional great apes, gorilla (Gorilla gorilla gorilla) and orangutan (Pongo abelii), is shown to contain six and four GH-like genes respectively. The gorilla locus possesses six potentially expressed genes, gGH-N, gGH-V and four gCSHs, whereas the orangutan locus has just three functional genes, oGH-N, oGH-V and oCSH-B, plus a pseudogene, oCSH-L. Analysis of regulatory sequences, including promoter, enhancer and P-elements, shows significant variation; in particular the proximal Pit-1 element of GH-V genes differs markedly from that of other genes in the cluster. Phylogenetic analysis shows that the initial gene duplication led to distinct GH-like and CSH-like genes, and that a second duplication provided separate GH-N and GH-V. However, evolution of the CSH-like genes remains unclear. Rapid adaptive evolution gave rise to the distinct CSHs, after the first duplication, and to GH-V after the second duplication. Analysis of transcriptomic databases derived from gorilla tissues establishes that the gGH-N, gGH-V and several gCSH genes are expressed, but the significance of the many CSH genes in gorilla remains unclear

Characterizing Immune Responses to Marburg Virus Infection in Animal Hosts Using Statistical Transcriptomic Analysis

Marburg virus (MARV)–along with Ebola Virus–comprises Filoviridae, a family of virus which causes the life-threatening hemorrhagic fever in human and non-human primates for which there is no clinically approved vaccine. For this reason, this virus can potentially lend itself to pandemic and weapons of bioterrorism. Strikingly, this virus yields asymptomatic responses in its recently discovered host Rousettus aegyptiacus. Understanding of the interaction between MARV and different animal hosts will enable the improved understanding of filovirus immunology and the development of effective therapeutic agents. Although cell lines and primary cells have been used to investigate gene expression analysis of this virus, the transcriptomic view of MARV infection on the tissue samples of animal hosts has been an uncharted territory. The comprehensive analysis of transcriptome in hosts and spillover hosts will shed light on the immune responses on a molecular level and potentially allow the comparative analysis to understand the phenotypical differences. However, there have been gaps in resources necessary to carry the transcriptome research for MARV. For example, MARV host Rousettus aegyptiacus genome and transcriptome had not been available. Furthermore, the statistical machinery necessary to analyze multi-tissue/multi-time data was not available. In this dissertation, I introduce the two items that fill these gaps and show the application of the tools I built for novel biological discovery. In particular, I have built 1) the comprehensive de novo transcriptome reference of Rousettus aegyptiacus and 2) the Multilevel Analysis of Gene Expression (MAGE) pipeline to analyze the RNA-seq data with the complex experimental design. I show the application of MAGE in multi-time, multi-tissue transcriptome data of Macaca mulata infected with MARV. In this study, 15 rhesus macaques were sequentially sacrificed via aerosol exposure to MARV Angola over the course of 9 days, and 3 types of lymph node tissues (tracheobronchial, mesenteric, and inguinal) were extracted from each sample and sequenced for gene expression analysis. With MAGE pipeline, I discovered that the posterior median log2FC of genes separates the samples based on day post infection and viral load. I discovered the set of genes such as CD40LG and TMEM197 with interesting trends over time and how similar and different pathways have been influenced in three lymph nodes. I also identified the biologically meaningful clusters of genes based on the topology-based clustering algorithm known as Mapper. Using the MAGE posterior samples, I also determined the genes that are preferentially expressed in tracheobronchial lymph nodes. In addition to new analysis tools and biological findings, I built the gene expression exploration tool for biologists to examine differential gene expression over time in various immune-related pathways and contributing members of the pathways. In conclusion, I have contributed to the two important components in the transcriptome analysis in MARV research and discovered novel biological insights. The MAGE pipeline is modular and extensible and will be useful for the transcriptome research with the complex experimental designs which are becoming increasingly prevalent with the decrease in the cost of sequencing