von Willebrand disease (VWD) is the most common inherited bleeding disorder. VWD is caused by deficiencies in von Willebrand factor (VWF), a critical adhesive haemostatic protein. This review provides an overview of VWD diagnosis and treatment, special considerations in treating women with VWD, and current genomic approaches to VWD. For diagnosis and treatment in VWD, an accurate diagnosis is critical to providing effective treatments, determining appropriate laboratory monitoring and for counselling the patient and family. Diagnosis of VWD begins with the clinical assessment for the bleeding phenotype, which is usually characterized by mucocutaneous and provoked bleeding. The diagnosis of VWD is then made by laboratory investigation. Multiple assays are used to assess VWF levels and functions. The mainstays of VWD treatment are tailored by VWD type and symptoms, and can include antifibrinolytic treatment, desmopressin and VWF replacement treatment. Women with VWD are also at risk for excessive uterine bleeding, such as with menses and childbirth. In addition to standard VWD treatments, heavy menstrual bleeding can be treated with hormones. Interdisciplinary management of childbirth and prophylaxis in the postpartum period are needed to reduce the risk of postpartum haemorrhage. Genomic approaches to VWD can inform VWD diagnosis, treatment, test assay selection, reproductive planning and family counselling. Most VWD patients have an identifiable VWF gene DNA variant. Next-generation sequencing is rapidly being adopted to provide more comprehensive VWF sequence information for patients with known or suspected VWD.
Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.
Metabonomics can be used to quantitatively measure dynamic biochemical responses of living organisms to physiological or pathological stimuli. A range of analytical tools such as high-resolution nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) combined with multivariate statistical analysis can be employed to create comprehensive metabolic signatures of biological samples including urine, plasma, faecal water and tissue extracts. These metabolic signatures can reflect the physiological or pathological condition of the organism and indicate imbalances in the homeostatic regulation of tissues and extracellular fluids. This technology has been employed in a diverse range of application areas including investigation of disease mechanisms, diagnosis/prognosis of pathologies, nutritional interventions and drug toxicity. Metabolic profiling is becoming increasingly important in identifying biomarkers of disease progression and drug intervention, and can provide additional information to support or aid the interpretation of genomic and proteomic data. With the new generation of postgenomic technologies, the paradigm in many biological fields has shifted to either top down systems biology approaches, aiming to achieve a general understanding of the global and integrated response of an organism or to bottom up modelling of specific pathways and networks using a priori knowledge based on mining large bodies of literature. Whilst metabolic profiling lends itself to either approach, using it in an exploratory and hypothesis generating capacity clearly allows new mechanisms to be uncovered.
Chromosomal translocations are a genomic hallmark of many hematologic malignancies. Often as initiating events, these structural abnormalities result in fusion proteins involving transcription factors important for hematopoietic differentiation and/or signaling molecules regulating cell proliferation and cell cycle. In contrast, epigenetic regulator genes are more frequently targeted by somatic sequence mutations, possibly as secondary events to further potentiate leukemogenesis. Through comprehensive whole-transcriptome sequencing of 231 children with acute lymphoblastic leukemia (ALL), we identified 58 putative functional and predominant fusion genes in 54.1% of patients (n = 125), 31 of which have not been reported previously. In particular, we described a distinct ALL subtype with a characteristic gene expression signature predominantly driven by chromosomal rearrangements of the ZNF384 gene with histone acetyltransferases EP300 and CREBBP ZNF384-rearranged ALL showed significant up-regulation of CLCF1 and BTLA expression, and ZNF384 fusion proteins consistently showed higher activity to promote transcription of these target genes relative to wild-type ZNF384 in vitro. Ectopic expression of EP300-ZNF384 and CREBBP-ZNF384 fusion altered differentiation of mouse hematopoietic stem and progenitor cells and also potentiated oncogenic transformation in vitro. EP300- and CREBBP-ZNF384 fusions resulted in loss of histone lysine acetyltransferase activity in a dominant-negative fashion, with concomitant global reduction of histone acetylation and increased sensitivity of leukemia cells to histone deacetylase inhibitors. In conclusion, our results indicate that gene fusion is a common class of genomic abnormalities in childhood ALL and that recurrent translocations involving EP300 and CREBBP may cause epigenetic deregulation with potential for therapeutic targeting.
Bartonella elizabethae has been known to cause endocarditis and neuroretinitis in humans. The genomic features and virulence profiles of a B. elizabethae strain (designated as BeUM) isolated from the spleen of a wild rat in Kuala Lumpur, Malaysia are described in this study. The BeUM strain has a genome size of 1,932,479bp and GC content of 38.3%. There is a high degree of conservation between the genomes of strain BeUM with B. elizabethae type strains (ATCC 49927 and F9251) and a rat-borne strain, Re6043vi. Of 2137 gene clusters identified from B. elizabethae strains, 2064 (96.6%) are indicated as the core gene clusters. Comparative genome analysis of B. elizabethae strains reveals virulence genes which are known in other pathogenic Bartonella species, including VirB2-11, vbhB2-B11, VirD4, trw, vapA2-5, hbpA-E, bepA-F, bepH, badA/vomp/brp, ialB, omp43/89 and korA-B. A putative intact prophage has been identified in the strain BeUM, in addition to a 8kb pathogenicity island. The whole genome analysis supports the zoonotic potential of the rodent-borne B. elizabethae, and provides basis for future functional and pathogenicity studies of B. elizabethae.
Burkholderia pseudomallei, a soil-dwelling Gram-negative bacterium, is the causative agent of the endemic tropical disease melioidosis. Clinical manifestations of B. pseudomallei infection range from acute or chronic localized infection in a single organ to fulminant septicaemia in multiple organs. The diverse clinical manifestations are attributed to various factors, including the genome plasticity across B. pseudomallei strains. We previously characterized B. pseudomallei strains isolated in Malaysia and noted different levels of virulence in model hosts. We hypothesized that the difference in virulence might be a result of variance at the genome level. In this study, we sequenced and assembled four Malaysian clinical B. pseudomallei isolates, UKMR15, UKMPMC2000, UKMD286 and UKMH10. Phylogenomic analysis showed that Malaysian subclades emerged from the Asian subclade, suggesting that the Malaysian strains originated from the Asian region. Interestingly, the low-virulence strain, UKMH10, was the most distantly related compared to the other Malaysian isolates. Genomic island (GI) prediction analysis identified a new island of 23 kb, GI9c, which is present in B. pseudomallei and Burkholderia mallei, but not Burkholderia thailandensis. Genes encoding known B. pseudomallei virulence factors were present across all four genomes, but comparative analysis of the total gene content across the Malaysian strains identified 104 genes that are absent in UKMH10. We propose that these genes may encode novel virulence factors, which may explain the reduced virulence of this strain. Further investigation on the identity and role of these 104 proteins may aid in understanding B. pseudomallei pathogenicity to guide the design of new therapeutics for treating melioidosis.
In industry, the yeast Rhodotorula mucilaginosa is commonly used for the production of carotenoids. The production of carotenoids is important because they are used as natural colorants in food and some carotenoids are precursors of retinol (vitamin A). However, the identification and molecular characterization of the carotenoid pathway/s in species belonging to the genus Rhodotorula is scarce due to the lack of genomic information thus potentially impeding effective metabolic engineering of these yeast strains for improved carotenoid production. In this study, we report the isolation, identification, characterization and the whole nuclear genome and mitogenome sequence of the endophyte R. mucilaginosa RIT389 isolated from Distemonanthus benthamianus, a plant known for its anti-fungal and antibacterial properties and commonly used as chewing sticks. The assembled genome of R. mucilaginosa RIT389 is 19 Mbp in length with an estimated genomic heterozygosity of 9.29%. Whole genome phylogeny supports the species designation of strain RIT389 within the genus in addition to supporting the monophyly of the currently sequenced Rhodotorula species. Further, we report for the first time, the recovery of the complete mitochondrial genome of R. mucilaginosa using the genome skimming approach. The assembled mitogenome is at least 7,000 bases larger than that of Rhodotorula taiwanensis which is largely attributed to the presence of large intronic regions containing open reading frames coding for homing endonuclease from the LAGLIDADG and GIY-YIG families. Furthermore, genomic regions containing the key genes for carotenoid production were identified in R. mucilaginosa RIT389, revealing differences in gene synteny that may play a role in the regulation of the biotechnologically important carotenoid synthesis pathways in yeasts.
The new millennium has been regarded as a genomic era. A lot of researchers and pathologists are beginning to understand the scientific basis of molecular genetics and relates with the progression of the diseases. Central nervous system (CNS) tumours are among the most rapidly fatal of all cancers. It has been proposed that the progression of malignant tumours may result from multi-step of genetic alterations, including activation of oncogenes, inactivation of tumour suppressor genes and also the presence of certain molecular marker such as telomerase activity. In this paper, we review some recent data from the literature, including our own studies, on the molecular genetics analysis in CNS tumours. Our studies have shown that two types of tumour suppressor genes, p53 and PTEN were involved in the development of these tumours but not in p16 gene among the patients from Hospital Universiti Sains Malaysia (HUSM). Telomerase activity also has been detected in various types of CNS tumours. Thus, it is important to assemble all data which related to this study and may provide as a vital information in a new approach to neuro-oncology studies in Malaysia.
With the growing use of comprehensive tumor molecular profiling (CTMP), the therapeutic landscape of cancer is rapidly evolving. NGS produces large amounts of genomic data requiring complex analysis and subsequent interpretation. We sought to determine the utility of publicly available knowledge bases (KB) for the interpretation of the cancer mutational profile in clinical practice. Analysis was performed across patients who previously underwent CTMP. Independent interpretation of the CTMP was performed manually, and then, the recommendations were compared to ones present in KBs (OncoKB, CIViC, CGI, CGA, VICC, MolecularMatch). A total of 222 CTMP reports from 222 patients with 932 genomic alterations (GA) were identified. For 368 targetable GA identified in 171 (77%) of the patients, 1381 therapy recommendations were compiled. Except for CGA, therapy ESCAT LOE I, II, IIIA and IIIB therapy options were equally represented in the majority of KB. Personalized treatment options with ESCAT LOE I-II were provided for 35 patients (16%); MolecularMatch/CIViC allowed to collect ESCAT I-II treatment options for 34 of them (97%), OncoKB/CGI-for 33 of them (94%). Employing VICC and CGA 6 (17%) and 20 (57%) of patients were left without ESCAT I or II treatment options. For 88 patients with ESCAT level III-B therapy recommendations: only 2 (2%), 3 (3%), 4 (5%) and 6 (7%) of patients were left without options with CIViC, MolecularMatch, CGI and OncoKB, and with VICC-12 (14%). Highest overlap ratio was observed for IIIA (0.81) biomarkers, with the comparable results for LOE I-II. Meanwhile, overlap ratio for ESCAT LOE IV was 0.22. Public KBs provide substantial information on ESCAT-I/R1 biomarkers, but the information on ESCAT II-IV and resistance biomarkers is underrepresented. Manual curation should be considered the gold standard for the CTMP interpretation.
Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution.
Maximizing the research output from a limited investment is often the major challenge for minor and underutilized crops. However, such crops may be tolerant to biotic and abiotic stresses and are adapted to local, marginal, and low-input environments. Their development through breeding will provide an important resource for future agricultural system resilience and diversification in the context of changing climates and the need to achieve food security. The African Orphan Crops Consortium recognizes the values of genomic resources in facilitating the improvement of such crops. Prior to beginning genome sequencing there is a need for an assessment of line varietal purity and to estimate any residual heterozygosity. Here we present an example from bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilized drought tolerant African legume. Two released varieties from Zimbabwe, identified as potential genotypes for whole genome sequencing (WGS), were genotyped with 20 species-specific SSR markers. The results indicate that the cultivars are actually a mix of related inbred genotypes, and the analysis allowed a strategy of single plant selection to be used to generate non-heterogeneous DNA for WGS. The markers also confirmed very low levels of heterozygosity within individual plants. The application of a pre-screen using co-dominant microsatellite markers is expected to substantially improve the genome assembly, compared to a cultivar bulking approach that could have been adopted.
Brassica napus (canola/oilseed rape/rapeseed) is an economically important crop, mostly found in temperate and sub-tropical regions, that is cultivated widely for its edible oil. Major diseases of Brassica crops such as Blackleg, Clubroot, Sclerotinia Stem Rot, Downy Mildew, Alternaria Leaf Spot and White Rust have caused significant yield and economic losses in rapeseed-producing countries worldwide, exacerbated by global climate change, and, if not remedied effectively, will threaten global food security. To gain further insights into the host-pathogen interactions in relation to Brassica diseases, it is critical that we review current knowledge in this area and discuss how omics technologies can offer promising results and help to push boundaries in our understanding of the resistance mechanisms. Omics technologies, such as genomics, proteomics, transcriptomics and metabolomics approaches, allow us to understand the host and pathogen, as well as the interaction between the two species at a deeper level. With these integrated data in multi-omics and systems biology, we are able to breed high-quality disease-resistant Brassica crops in a more holistic, targeted and accurate way.
Candida albicans is an opportunistic fungal pathogen, which causes a plethora of superficial, as well as invasive, infections in humans. The ability of this fungus in switching from commensalism to active infection is attributed to its many virulence traits. Biofilm formation is a key process, which allows the fungus to adhere to and proliferate on medically implanted devices as well as host tissue and cause serious life-threatening infections. Biofilms are complex communities of filamentous and yeast cells surrounded by an extracellular matrix that confers an enhanced degree of resistance to antifungal drugs. Moreover, the extensive plasticity of the C. albicans genome has given this versatile fungus the added advantage of microevolution and adaptation to thrive within the unique environmental niches within the host. To combat these challenges in dealing with C. albicans infections, it is imperative that we target specifically the molecular pathways involved in biofilm formation as well as drug resistance. With the advent of the -omics era and whole genome sequencing platforms, novel pathways and genes involved in the pathogenesis of the fungus have been unraveled. Researchers have used a myriad of strategies including transcriptome analysis for C. albicans cells grown in different environments, whole genome sequencing of different strains, functional genomics approaches to identify critical regulatory genes, as well as comparative genomics analysis between C. albicans and its closely related, much less virulent relative, C. dubliniensis, in the quest to increase our understanding of the mechanisms underlying the success of C. albicans as a major fungal pathogen. This review attempts to summarize the most recent advancements in the field of biofilm and antifungal resistance research and offers suggestions for future directions in therapeutics development.
Eucheuma denticulatum or commonly known as "Spinosum", is an economically important red alga that naturally grows on coral reefs with moderately strong currents in tropical and sub-tropical areas. This species is the primary source of iota-carrageenan which has high demands in the food, pharmaceutical and manufacturing industries, and as such it has been widely cultivated. The increasing global demand for carrageenan has led to extensive commercial cultivation of carrageenophytes mainly in the tropics. The carrageenophyte seaweeds including E. denticulatum are indigenous to Sabah, Malaysia. To enrich the information on the genes involved in carrageenan biosynthesis, RNA sequencing has been performed and transcriptomic dataset has been generated using Illumina HiSeq™ 2000 sequencer. The raw data and transcriptomic data have been deposited in NCBI database with the accession number PRJNA477734. These data will provide valuable resources for functional genomics annotation and investigation of mechanisms underlying the regulations of genes in this algal species.
Functional genomics research can give us valuable insights into bacterial gene function. RNA Sequencing (RNA-seq) can generate information on transcript abundance in bacteria following abiotic stress treatments. In this study, we used the RNA-seq technique to study the transcriptomes of the opportunistic nosocomial pathogen Pseudomonas aeruginosa PAO1 following heat shock. Samples were grown at both the human body temperature (37 °C) and an arbitrarily-selected temperature of 46 °C. In this work using RNA-seq, we identified 133 genes that are differentially expressed at 46 °C compared to the human body temperature. Our work identifies some key P. aeruginosa PAO1 genes whose products have importance in both environmental adaptation as well as in vivo infection in febrile hosts. More importantly, our transcriptomic results show that many genes are only expressed when subjected to heat shock. Because the RNA-seq can generate high throughput gene expression profiles, our work reveals many unanticipated genes with further work to be done exploring such genes products.
High-depth next generation sequencing data provide valuable insights into the number and distribution of RNA editing events. Here, we report the RNA editing events at cellular level of human primary monocyte using high-depth whole genomic and transcriptomic sequencing data. We identified over a ten thousand putative RNA editing sites and 69% of the sites were A-to-I editing sites. The sites enriched in repetitive sequences and intronic regions. High-depth sequencing datasets revealed that 90% of the canonical sites were edited at lower frequencies (<0.7). Single and multiple human monocytes and brain tissues samples were analyzed through genome sequence independent approach. The later approach was observed to identify more editing sites. Monocytes was observed to contain more C-to-U editing sites compared to brain tissues. Our results establish comparable pipeline that can address current limitations as well as demonstrate the potential for highly sensitive detection of RNA editing events in single cell type.
Malaysia, experienced two epidemic waves of HPAI; its fi rst outbreak of HP H5N1 in August 2004 that occurred in the state of Kelantan and the second and subsequent outbreaks in February–March 2006 in three states on the west coast of Malaysia namely Wilayah Persekutuan
Kuala Lumpur, Perak and Penang. Five outbreaks occurred in village chickens and one in a multi-species enclosure of birds in a bird park resort facility. Molecular epidemiological studies by genomic sequencing and phylogenetic analyses of the viruses isolated showed that the
virus isolated from WP Kuala Lumpur is of the V-genotype and it originated from Hunan China, two viruses were found to be similar to the Fujian/Hunan strains and other viruses were similar to the Vietnam/ Thailand strains.
Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine.
High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.