Between a chicken and a grape: estimating the number of human genes

Probiotics/prebiotics effect on chicken gut microbiota and immunity in relation to heat-stress and climate-change mitigation

Heat stress is a serious hazard that threatens world poultry production. The avian gut microbiome plays a critical role in improving nutrient utilization, competing with pathogens, stimulating an immune response, and reducing inflammatory reactions. Hence, the gut microbiome has a positive impact on the host's health which appears in the shape of improved body weight, feed conversion rate, and increased birds' productivity (meat or eggs). Accordingly, this review shed light on the chicken gut microbiome, its correlation with the immunity of chicken, and how this affects the general health condition of the bird as well as, the role of prebiotics and probiotics in improving the gut health and increasing birds' productivity, especially under climate change and heat stress condition. The review aims to focus on the significance of maintaining healthy chickens in order to increase the production of poultry meat to satisfy human needs. A robust microbiota and a well-functioning immune system synergistically contribute to the optimal health and productivity of chickens.

More than 2,500 coding genes in the human reference gene set still have unsettled status

In 2018 we analysed the three main repositories for the human proteome, Ensembl/GENCODE, RefSeq and UniProtKB. They disagreed on the coding status of one of every eight annotated coding genes. The analysis inspired bilateral collaborations between annotation groups. Here we have repeated our analysis with updated versions of the three reference coding gene sets. Superficially, little appears to have changed. Although there are slightly fewer genes predicted as coding overall, the three groups still disagree on the status of 2,606 annotated genes. However, a comparison without read-through genes and immunoglobulin fragments shows that the three reference sets have merged or reclassified more than 700 genes since the last analysis and that just 0.6% of Ensembl/GENCODE coding genes are not also annotated by the other two reference sets. We used eight features indicative of non-coding genes to examine the 21,873 coding genes annotated across the three reference sets. We found that more than 2,000 had one or more potential non-coding features. While some of these genes will be protein coding, we believe that most are likely to be non-coding genes or pseudogenes. Our results suggest that annotators still vastly overestimate the number of true coding genes.

Omics-Enhanced Nanomedicine for Cancer Therapy

Cancer nanomedicine has emerged as a promising approach to overcome the limitations of conventional cancer therapies, offering enhanced efficacy and safety in cancer management. However, the inherent heterogeneity of tumors presents increasing challenges for the application of cancer nanomedicine in both diagnosis and treatment. This heterogeneity necessitates the integration of advanced and high-throughput analytical techniques to tailor nanomedicine strategies to individual tumor profiles. Omics technologies, encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and more, provide unparalleled insights into the molecular and cellular mechanisms underlying cancer. By dissecting tumor heterogeneity across multiple levels, these technologies offer robust support for the development of personalized and precise cancer nanomedicine strategies. In this review, the principles, techniques, and applications of key omics technologies are summarized. Especially, the synergistic integration of omics and nanomedicine in cancer therapy is explored, focusing on enhanced diagnostic accuracy, optimized therapeutic strategies and the assessment of nanomedicine-mediated biological responses. Moreover, this review addresses current challenges and outlines future directions in the field of omics-enhanced nanomedicine. By offering valuable insights and guidance, this review aims to advance the integration of omics with nanomedicine, ultimately driving improved diagnostic and therapeutic strategies for cancer.

Beyond probiotics, uses of their next-generation for poultry and humans: A review

The production of healthy food is one of the basic requirements and challenges. Research efforts have been introduced in the human's food industry to reduce the microbial resistance and use safe and healthy alternatives with a high durability. However, the conducted work about these issues in the field of livestock animal production have been started since 2015. Inappropriate and extensive use of antibiotics has resulted in the increase of antimicrobial resistance, presence of drug residues in tissues, and destruction of the gut microbiome. Therefore, discovering and developing antibiotic substitutes were urgent demands. Probiotic compounds containing living micro-organisms are important antibiotic alternative that have been beneficially and extensively used in humans, animals, and poultry. However, some probiotics show some obstacles during production and applications. Accordingly, this review article proposes a comprehensive description of the next-generation of probiotics including postbiotics, proteobiotics, psychobiotics, immunobiotics and paraprobiotics and their effects on poultry production and human's therapy. These compounds proved great efficiency in terms of restoring gut health, improving performance and general health conditions, modulating the immune response and reducing the pathogenic micro-organisms. However, more future research work should be carried out regarding this issue.

Modalization and Transcendence of Health in the Coming Decade: Emphasizing the Human Cognitive System in the Stories of Prophets in the Holy Quran

In this study, the progression and importance of health knowledge is explored, projecting its future path. We do this by comparing the stages of evolution of the human cognitive system from birth to old age (inner intellect) with the stages of intellectual modalization in divine messengers (external intellect), as depicted in the stories of the prophets in the Holy Quran. This comparison aims to articulate the course of evolution, which includes sensory perception, apprehension, imaginalization, intellection, and intuition. Future medicine will consider the influence of spiritual factors (soul) in the form of human cognition and intention, as well as material effects (genes and biology). The seven medical domains of the future will encompass the field of 'sprito-epigenetico psycho-neuro-endocrino-immuno-pharmacology'. This perspective emphasizes the need for a transcendent outlook in health and medicine. This study employed a library research method, including studies in medical journals from the last forty years.

The Physiological Inorganic Polymers Biosilica and Polyphosphate as Key Drivers for Biomedical Materials in Regenerative Nanomedicine

There is a need for novel nanomaterials with properties not yet exploited in regenerative nanomedicine. Based on lessons learned from the oldest metazoan phylum, sponges, it has been recognized that two previously ignored or insufficiently recognized principles play an essential role in tissue regeneration, including biomineral formation/repair and wound healing. Firstly, the dependence on enzymes as a driving force and secondly, the availability of metabolic energy. The discovery of enzymatic synthesis and regenerative activity of amorphous biosilica that builds the mineral skeleton of siliceous sponges formed the basis for the development of successful strategies for the treatment of osteochondral impairments in humans. In addition, the elucidation of the functional significance of a second regeneratively active inorganic material, namely inorganic polyphosphate (polyP) and its amorphous nanoparticles, present from sponges to humans, has pushed forward the development of innovative materials for both soft (skin, cartilage) and hard tissue (bone) repair. This energy-rich molecule exhibits a property not shown by any other biopolymer: the delivery of metabolic energy, even extracellularly, necessary for the ATP-dependent tissue regeneration. This review summarizes the latest developments in nanobiomaterials based on these two evolutionarily old, regeneratively active materials, amorphous silica and amorphous polyP, highlighting their specific, partly unique properties and mode of action, and discussing their possible applications in human therapy. The results of initial proof-of-concept studies on patients demonstrating complete healing of chronic wounds are outlined.

GeLC-FAIMS-MS workflow for in-depth middle-down proteomics

Middle-down proteomics (MDP) is an analytical approach in which protein samples are digested with proteases such as Glu-C to generate large peptides (>3 kDa) that are analyzed by mass spectrometry (MS). This method is useful for characterizing high-molecular-weight proteins that are difficult to detect by top-down proteomics (TDP), in which intact proteins are analyzed by MS. In this study, we applied GeLC-FAIMS-MS, a multidimensional separation workflow that combines gel-based prefractionation with LC-FAIMS MS, for deep MDP. Middle-down peptides generated by optimized limited Glu-C digestion conditions were first size-fractionated by polyacrylamide gel electrophoresis, followed by C4 reversed-phase liquid chromatography separation and additional ion mobility fractionation, resulting in a significant increase in peptide length detectable by MS. In addition to global analysis, the GeLC-FAIMS-MS concept can also be applied to targeted MDP, where only proteins in the desired molecular weight range are gel-fractionated and their Glu-C digestion products are analyzed, as demonstrated by targeted analysis of integrins in exosomes. In-depth MDP achieved by global and targeted GeLC-FAIMS-MS supports the exploration of proteoform information not covered by conventional TDP by increasing the number of detectable protein groups or post-translational modifications (PTMs) and improving the sequence coverage.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

Understanding PTM Cross Talk Through a Visualization Tool, PTMViz

The advancement of sequencing technologies has expanded our understanding of biological complexity through mechanisms such as allelic variations, alternative splicing of RNA, degradation of RNA by microRNAs, and posttranslational modifications (PTMs). In this chapter, we describe a method, PTMViz, for analyzing proteoforms identified by mass spectrometry. This interactive platform provides differential abundance analysis and visualization of protein and posttranslational modifications. We describe the detailed steps to prepare mass spectrometry database search results into the necessary format for PTMViz, how to set up the experimental conditions for differential abundance analysis, and the visualization of the results. The application is freely available at https://github.com/ByrumLab/PTMViz .

Anti-Idiotypic mRNA Vaccine to Treat Autoimmune Disorders

The 80+ existing autoimmune disorders (ADs) affect billions with little prevention or treatment options, except for temporary symptomatic management, leading to enormous human suffering and a monumental financial burden. The autoantibodies formed in most ADs have been identified, allowing the development of novel anti-idiotypic antibodies to mute the autoantibodies using vaccines. Nucleoside vaccines have been successfully tested as antigen-specific immunotherapies (ASI), with mRNA technology offering multi-epitope targeting to mute multiple autoantibodies. This paper proposes using mRNA technology to produce anti-idiotypic antibodies with broad effectiveness in preventing and treating them. This paper delves into the state-of-the-art mRNA design strategies used to develop novel ASIs by selecting appropriate T cell and B cell epitopes to generate anti-idiotypic antibodies. The low cost and fast development of mRNA vaccines make this technology the most affordable for the global control of ADs.

The status of the human gene catalogue

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

The status of the human gene catalogue

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants.

Pre-mRNA splicing-associated diseases and therapies

Precursor mRNA (pre-mRNA) splicing is an essential step in human gene expression and is carried out by a large macromolecular machine called the spliceosome. Given the spliceosome's role in shaping the cellular transcriptome, it is not surprising that mutations in the splicing machinery can result in a range of human diseases and disorders (spliceosomopathies). This review serves as an introduction into the main features of the pre-mRNA splicing machinery in humans and how changes in the function of its components can lead to diseases ranging from blindness to cancers. Recently, several drugs have been developed that interact directly with this machinery to change splicing outcomes at either the single gene or transcriptome-scale. We discuss the mechanism of action of several drugs that perturb splicing in unique ways. Finally, we speculate on what the future may hold in the emerging area of spliceosomopathies and spliceosome-targeted treatments.

Genomics in Treatment Development

The Human Genome Project mapped the 3 billion base pairs in the human genome, which ushered in a new generation of genomically focused treatment development. While this has been very successful in other areas, neuroscience has been largely devoid of such developments. This is in large part because there are very few neurological or mental health conditions that are related to single-gene variants. While developments in pharmacogenomics have been somewhat successful, the use of genetic information in practice has to do with drug metabolism and adverse reactions. Studies of drug metabolism related to genetic variations are an important part of drug development. However, outside of cancer biology, the actual translation of genomic information into novel therapies has been limited. Epigenetics, which relates in part to the effects of the environment on DNA, is a promising newer area of relevance to CNS disorders. The environment can induce chemical modifications of DNA (e.g., cytosine methylation), which can be induced by the environment and may represent either shorter- or longer-term changes. Given the importance of environmental influences on CNS disorders, epigenetics may identify important treatment targets in the future.

The orchestration of gene expression and the editing role of microRNA

In this short educational communication the ESPU Research Committee presents the role of non-coding RNA and how these can affect gene expression. In particular we discuss the role of microRNA on post transcriptional changes and how these may cause pathological conditions within Pediatric Urology and how microRNA could be useful in future clinical practice.

Comparison of Metagenomics and Metatranscriptomics Tools: A Guide to Making the Right Choice

The study of microorganisms is a field of great interest due to their environmental (e.g., soil contamination) and biomedical (e.g., parasitic diseases, autism) importance. The advent of revolutionary next-generation sequencing techniques, and their application to the hypervariable regions of the 16S, 18S or 23S ribosomal subunits, have allowed the research of a large variety of organisms more in-depth, including bacteria, archaea, eukaryotes and fungi. Additionally, together with the development of analysis software, the creation of specific databases (e.g., SILVA or RDP) has boosted the enormous growth of these studies. As the cost of sequencing per sample has continuously decreased, new protocols have also emerged, such as shotgun sequencing, which allows the profiling of all taxonomic domains in a sample. The sequencing of hypervariable regions and shotgun sequencing are technologies that enable the taxonomic classification of microorganisms from the DNA present in microbial communities. However, they are not capable of measuring what is actively expressed. Conversely, we advocate that metatranscriptomics is a "new" technology that makes the identification of the mRNAs of a microbial community possible, quantifying gene expression levels and active biological pathways. Furthermore, it can be also used to characterise symbiotic interactions between the host and its microbiome. In this manuscript, we examine the three technologies above, and discuss the implementation of different software and databases, which greatly impact the obtaining of reliable results. Finally, we have developed two easy-to-use pipelines leveraging Nextflow technology. These aim to provide everything required for an average user to perform a metagenomic analysis of marker genes with QIMME2 and a metatranscriptomic study using Kraken2/Bracken.

Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures

Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.

Molecular Biosimilarity—An AI-Driven Paradigm Shift

Scientific, technical, and bioinformatics advances have made it possible to establish analytics-based molecular biosimilarity for the approval of biosimilars. If the molecular structure is identical and other product- and process-related attributes are comparable within the testing limits, then a biosimilar candidate will have the same safety and efficacy as its reference product. Classical testing in animals and patients is much less sensitive in terms of identifying clinically meaningful differences, as is reported in the literature. The recent artificial intelligence (AI)-based protein structure prediction model, AlphaFold-2, has confirmed that the primary structure of proteins always determines their 3D structure; thus, we can deduce that a biosimilar with an identical primary structure will have the same efficacy and safety. Further confirmation of the thesis has been established using technologies that are now much more sensitive. For example, mass spectrometry (MS) is thousands of times more sensitive and accurate when compared to any form of biological testing. While regulatory agencies have begun waiving animal testing and, in some cases, clinical efficacy testing, the removal of clinical pharmacology profiling brings with it a dramatic paradigm shift, reducing development costs without compromising safety or efficacy. A list of 160+ products that are ready to enter as biosimilars has been shared. Major actions from regulatory agencies and developers are required to facilitate this paradigm shift.

Synthetic Proteins behind the Plasma Barrier: Molecular Spies

There is a continuous demand to improve our understanding of fundamental processes that underlie human health and disease. Therefore, novel strategies that can assist in these efforts are required. For example, molecular biology and genetic approaches have revolutionized our understanding of protein-mediated processes by facilitating their direct visualization and analyses in living cells. Despite these developments, genetic manipulation has limitations in controlling events that occur after translation such as posttranslational modifications (PTMs), which are imperative regulatory elements. As a result, developing new methods to study PTMs in live cells is a major bottleneck in deciphering their exact roles in the myriad cellular processes.

Synthetic and semisynthetic proteins are prepared by combining solid phase peptide synthesis (SPPS) and chemoselective ligation approaches with synthetic or recombinant peptides. Employing protein synthesis allows chemists to incorporate natural and unnatural modifications with virtually unlimited number of functional groups into the protein’s sequence, such as PTMs and their mimics. In addition, synthetic proteins can include additional elements such as fluorescent tags, reactive groups, caged units, and enrichment handles. Therefore, harnessing the power of chemical protein synthesis offers great opportunities to study fundamental biological processes.

Unfortunately, the low cell permeability of proteins limits their applications mainly to in vitro settings, excluding live cell studies. As a result, chemical biologists have been attempting to overcome these limitations by developing protein delivery methods that would enable the study of custom-made proteins in a biological context. Success with these strategies should enable accurate determination of protein localization, degradation, folding, interactions, and involvement in the assembly of membrane-less organelles formed by liquid–liquid phase separation inside cells. Importantly, protein delivery approaches are complementary to genetic manipulations, and combining these approaches should pave the way to new discoveries.

In this Account, we describe recent developments in protein delivery methods, with emphasis on those most compatible with synthetic proteins. We highlight experimental approaches and conceptual adaptations required to design and study synthetic proteins in live cells, with or without genetic manipulation. In addition, we highlight the strength and weakness of these approaches for both the delivery and the subsequent studies. We also describe our endeavors to deliver synthetic proteins to cells via cell penetrating peptides (CPPs) and multiplexed bead loading (MBL), as showcases of the applications of these methods to shed light on biological processes. Lastly, we contemplate other future applications of synthetic proteins to answer questions that are currently unapproachable.

From society to cells and back again: new opportunities for discovery at the biosocial interface

A new generation of community- and population-based research is combining measures of social context, experience, and behavior with direct measures of physiology, gene sequence and function, and health. Studies drawing on models and methods from the social and biological sciences have the potential to illuminate the multilevel mechanisms through which experience becomes biology, and to move past decontextualized and reductionistic approaches to human development, behavior, and health. In this perspective we highlight challenges and opportunities at the biosocial interface, and briefly discuss COVID-19 as a case study demonstrating the importance of linking across levels of analysis.

Comparison of Aptamer-Based and Antibody-Based Assays for Protein Quantification in Chronic Kidney Disease

BACKGROUND AND OBJECTIVES

Novel aptamer-based technologies can identify >7000 analytes per sample, offering a high-throughput alternative to traditional immunoassays in biomarker discovery. However, the specificity for distinct proteins has not been thoroughly studied in the context of CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We assessed the use of SOMAscan, an aptamer-based technology, for the quantification of eight immune activation biomarkers and cystatin C among 498 African American Study of Kidney Disease and Hypertension (AASK) participants using immunoassays as the gold standard. We evaluated correlations of serum proteins as measured by SOMAscan versus immunoassays with each other and with iothalamate-measured GFR. We then compared associations between proteins measurement with risks of incident kidney failure and all-cause mortality.

RESULTS

Six biomarkers (IL-8, soluble TNF receptor superfamily member 1B [TNFRSF1B], cystatin C, soluble TNF receptor superfamily member 1A [TNFRSF1A], IL-6, and soluble urokinase-type plasminogen activator receptor [suPAR]) had non-negligible correlations (r=0.94, 0.93, 0.89, 0.85, 0.46, and 0.23, respectively) between SOMAscan and immunoassay measurements, and three (IL-10, IFN-γ, and TNF-α) were uncorrelated (r=0.08, 0.07, and 0.02, respectively). Of the six biomarkers with non-negligible correlations, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were negatively correlated with measured GFR and associated with higher risk of kidney failure. IL-8, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were associated with a higher risk of mortality via both methods. On average, immunoassay measurements were more strongly associated with adverse outcomes than their SOMAscan counterparts.

CONCLUSIONS

SOMAscan is an efficient and relatively reliable technique for quantifying IL-8, TNFRSF1B, cystatin C, and TNFRSF1A in CKD and detecting their potential associations with clinical outcomes.

PODCAST

This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_02_23_CJN11700921.mp3.

The genome of the zebra mussel, Dreissena polymorpha: a resource for comparative genomics, invasion genetics, and biocontrol

The zebra mussel, Dreissena polymorpha, continues to spread from its native range in Eurasia to Europe and North America, causing billions of dollars in damage and dramatically altering invaded aquatic ecosystems. Despite these impacts, there are few genomic resources for Dreissena or related bivalves. Although the D. polymorpha genome is highly repetitive, we have used a combination of long-read sequencing and Hi-C-based scaffolding to generate a high-quality chromosome-scale genome assembly. Through comparative analysis and transcriptomics experiments, we have gained insights into processes that likely control the invasive success of zebra mussels, including shell formation, synthesis of byssal threads, and thermal tolerance. We identified multiple intact steamer-like elements, a retrotransposon that has been linked to transmissible cancer in marine clams. We also found that D. polymorpha have an unusual 67 kb mitochondrial genome containing numerous tandem repeats, making it the largest observed in Eumetazoa. Together these findings create a rich resource for invasive species research and control efforts.

Comparison of proteomic methods in evaluating biomarker-AKI associations in cardiac surgery patients

Although immunoassays are the most widely used protein measurement method, aptamer-based methods such as the SomaScan platform can quantify up to 7000 proteins per biosample, creating new opportunities for unbiased discovery. However, there is limited research comparing the consistency of biomarker-disease associations between immunoassay and aptamer-based platforms. In a substudy of the TRIBE-AKI cohort, preoperative and postoperative plasma samples from 294 patients with previous immunoassay measurements were analyzed using the SomaScan platform. Inter-platform Spearman correlations (r_s) and biomarker-AKI associations were compared across 30 preoperative and 34 postoperative immunoassay-aptamer pairs. Possible factors contributing to inter-platform differences were examined including target protein characteristics, immunoassay, and SomaScan coefficients of variation, other assay characteristics, and sample storage time. The median r_s was 0.54 (interquartile range [IQR] 0.34-0.83) in postoperative samples and 0.41 (IQR 0.21-0.69) in preoperative samples. We observed a trend of greater r_s in biomarkers with greater concentrations; the Spearman correlation between the concentration of protein and the inter-platform correlation was 0.64 in preoperative pairs and 0.53 in postoperative pairs. Of proteins measured by immunoassays, we observed significant biomarker-AKI associations for 13 proteins preop and 24 postop; of all corresponding aptamers, 8 proteins preop and 12 postop. All proteins significantly associated with AKI as measured by SomaScan were also significantly associated with AKI as measured by immunoassay. All biomarker-AKI odds ratios were significantly different (P < 0.05) between platforms in 14% of aptamer-immunoassay pairs, none of which had high (r_s > 0.50) inter-platform correlations. Although similar biomarker-disease associations were observed overall, biomarkers with high physiological concentrations tended to have the highest-confidence inter-platform operability in correlations and biomarker-disease associations. Aptamer assays provide excellent precision and an unprecedented coverage and promise for disease associations but interpretation of results should keep in mind a broad range of correlations with immunoassays.

A systematic review of proteomic biomarkers in oral squamous cell cancer

BACKGROUND

Head and neck squamous cell cancer (HNSCC) is the most common cancer associated with chewing tobacco, in the world. As this is divided in to sites and subsites, it does not make it to top 10 cancers. The most common subsite is the oral cancer. At the time of diagnosis, more than 50% of patients with oral squamous cell cancers (OSCC) had advanced disease, indicating the lack of availability of early detection and risk assessment biomarkers. The new protein biomarker development and discovery will aid in early diagnosis and treatment which lead to targeted treatment and ultimately a good prognosis.

METHODS

This systematic review was performed as per PRISMA guidelines. All relevant studies assessing characteristics of oral cancer and proteomics were considered for analysis. Only human studies published in English were included, and abstracts, incomplete articles, and cell line or animal studies were excluded.

RESULTS

A total of 308 articles were found, of which 112 were found to be relevant after exclusion. The present review focuses on techniques of cancer proteomics and discovery of biomarkers using these techniques. The signature of protein expression may be used to predict drug response and clinical course of disease and could be used to individualize therapy with such knowledge.

CONCLUSIONS

Prospective use of these markers in the clinical setting will enable early detection, prediction of response to treatment, improvement in treatment selection, and early detection of tumor recurrence for disease monitoring. However, most of these markers for OSCC are yet to be validated.

A laminar augmented cascading flexible neural forest model for classification of cancer subtypes based on gene expression data

BACKGROUND

Correctly classifying the subtypes of cancer is of great significance for the in-depth study of cancer pathogenesis and the realization of personalized treatment for cancer patients. In recent years, classification of cancer subtypes using deep neural networks and gene expression data has gradually become a research hotspot. However, most classifiers may face overfitting and low classification accuracy when dealing with small sample size and high-dimensional biology data.

RESULTS

In this paper, a laminar augmented cascading flexible neural forest (LACFNForest) model was proposed to complete the classification of cancer subtypes. This model is a cascading flexible neural forest using deep flexible neural forest (DFNForest) as the base classifier. A hierarchical broadening ensemble method was proposed, which ensures the robustness of classification results and avoids the waste of model structure and function as much as possible. We also introduced an output judgment mechanism to each layer of the forest to reduce the computational complexity of the model. The deep neural forest was extended to the densely connected deep neural forest to improve the prediction results. The experiments on RNA-seq gene expression data showed that LACFNForest has better performance in the classification of cancer subtypes compared to the conventional methods.

CONCLUSION

The LACFNForest model effectively improves the accuracy of cancer subtype classification with good robustness. It provides a new approach for the ensemble learning of classifiers in terms of structural design.

MicroRNAs hsa-miR-618 and hsa-miR-297 Might Modulate the Pleiotropic Effects Exerted by Statins in Endothelial Cells Through the Inhibition of ROCK2 Kinase: in-silico Approach

Several studies show that statin therapy improves endothelial function by cholesterol-independent mechanisms called “pleiotropic effects.” These are due to the inhibition of the RhoA/ROCK kinase pathway, its inhibition being an attractive atheroprotective treatment. In addition, recent work has shown that microRNAs, posttranscriptional regulators of gene expression, can affect the response of statins and their efficacy. For this reason, the objective of this study was to identify by bioinformatic analysis possible new microRNAs that could modulate the pleiotropic effects exerted by statins through the inhibition of ROCK kinases. A bioinformatic study was performed in which the differential expression of miRNAs in endothelial cells was compared under two conditions: Control and treated with simvastatin at 10 μM for 24 h, using a microarray. Seven miRNAs were differentially expressed, three up and four down. Within the up group, the miRNAs hsa-miR-618 and hsa-miR-297 present as a predicted target to ROCK2 kinase. Also, functional and enriched pathway analysis showed an association with mechanisms associated with atheroprotective effects. This work shows an in-silico approach of how posttranscriptional regulation mediated by miRNAs could modulate the pleiotropic effects exerted by statins on endothelial cells, through the inhibition of ROCK2 kinase and its effects.

Direct molecular evidence for an ancient, conserved developmental toolkit controlling post-transcriptional gene regulation in land plants

In plants, miRNA production is orchestrated by a suite of proteins that control transcription of the pri-miRNA gene, post-transcriptional processing and nuclear export of the mature miRNA. Post-transcriptional processing of miRNAs is controlled by a pair of physically interacting proteins, hyponastic leaves 1 (HYL1) and Dicer-like 1 (DCL1). However, the evolutionary history and structural basis of the HYL1–DCL1 interaction is unknown. Here we use ancestral sequence reconstruction and functional characterization of ancestral HYL1 in vitro and in Arabidopsis thaliana to better understand the origin and evolution of the HYL1–DCL1 interaction and its impact on miRNA production and plant development. We found the ancestral plant HYL1 evolved high affinity for both double-stranded RNA (dsRNA) and its DCL1 partner before the divergence of mosses from seed plants (∼500 Ma), and these high-affinity interactions remained largely conserved throughout plant evolutionary history. Structural modeling and molecular binding experiments suggest that the second of two dsRNA-binding motifs (DSRMs) in HYL1 may interact tightly with the first of two C-terminal DCL1 DSRMs to mediate the HYL1–DCL1 physical interaction necessary for efficient miRNA production. Transgenic expression of the nearly 200 Ma-old ancestral flowering-plant HYL1 in A. thaliana was sufficient to rescue many key aspects of plant development disrupted by HYL1⁻ knockout and restored near-native miRNA production, suggesting that the functional partnership of HYL1–DCL1 originated very early in and was strongly conserved throughout the evolutionary history of terrestrial plants. Overall, our results are consistent with a model in which miRNA-based gene regulation evolved as part of a conserved plant “developmental toolkit.”

Long non-coding RNA: An immune cells perspective

Long non-coding RNAs (lncRNAs) were considered as accumulated genetic waste until they were found to be gene expression regulators by highly sensitive modern genomics platforms. It is a huge class of non-coding transcripts with an arbitrary length of >200 nucleotides, which has gained much attention in the past few years. Increasing evidence from several experimental studies unraveled the expression of lncRNA linked to immune response and disease progression. However, only a small number of lncRNAs have robust evidence of their function. Differential expression of lncRNAs in different immune cells is also evident. In this review, we focused on how lncRNAs expression assist in shaping immune cells (Macrophages, Dendritic cells, NK cells, T cells, B cells, eosinophils, neutrophils, and microglial cells) function and their response to the diseased conditions. Emerging evidence revealed lncRNAs may serve as key regulators in the innate and adaptive immune response system. So, the molecular mechanism insight into the function of lncRNAs in immune response may contribute to the development of potential therapeutic targets for various disease treatments. Therefore, it is imperative to explore the expression of lncRNAs and understand its relevance associated with the immune system.

Comparing de novo transcriptome assembly tools in di- and autotetraploid non-model plant species

Background

Polyploidy is very common in plants and can be seen as one of the key drivers in the domestication of crops and the establishment of important agronomic traits. It can be the main source of genomic repatterning and introduces gene duplications, affecting gene expression and alternative splicing. Since fully sequenced genomes are not yet available for many plant species including crops, de novo transcriptome assembly is the basis to understand molecular and functional mechanisms. However, in complex polyploid plants, de novo transcriptome assembly is challenging, leading to increased rates of fused or redundant transcripts. Since assemblers were developed mainly for diploid organisms, they may not well suited for polyploids. Also, comparative evaluations of these tools on higher polyploid plants are extremely rare. Thus, our aim was to fill this gap and to provide a basic guideline for choosing the optimal de novo assembly strategy focusing on autotetraploids, as the scientific interest in this type of polyploidy is steadily increasing.

Results

We present a comparison of two common (SOAPdenovo-Trans, Trinity) and one recently published transcriptome assembler (TransLiG) on diploid and autotetraploid species of the genera Acer and Vaccinium using Arabidopsis thaliana as a reference. The number of assembled transcripts was up to 11 and 14 times higher with an increased number of short transcripts for Acer and Vaccinium, respectively, compared to A. thaliana. In diploid samples, Trinity and TransLiG performed similarly good while in autotetraploids, TransLiG assembled most complete transcriptomes with an average of 1916 assembled BUSCOs vs. 1705 BUSCOs for Trinity. Of all three assemblers, SOAPdenovo-Trans performed worst (1133 complete BUSCOs).

Conclusion

All three assembly tools produced complete assemblies when dealing with the model organism A. thaliana, independently of its ploidy level, but their performances differed extremely when it comes to non-model autotetraploids, where specifically TransLiG and Trinity produced a high number of redundant transcripts. The recently published assembler TransLiG has not been tested yet on any plant organism but showed highest completeness and full-length transcriptomes, especially in autotetraploids. Including such species during the development and testing of new assembly tools is highly appreciated and recommended as many important crops are polyploid.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04078-8.

LncRNAs and Immunity: Coding the Immune System with Noncoding Oligonucleotides

Long noncoding RNAs (lncRNAs) represent key regulators of gene transcription during the inflammatory response. Recent findings showed lncRNAs to be dysregulated in human diseases, such as inflammatory bowel disease, diabetes, allergies, asthma, and cancer. These noncoding RNAs are crucial for immune mechanism, as they are involved in differentiation, cell migration and in the production of inflammatory mediators through regulating protein–protein interactions or their ability to assemble with RNA and DNA. The last interaction can occur in cis or trans and is responsible for all the possible lncRNAs biological effects. Our proposal is to provide an overview on lncRNAs roles and functions related to immunity and immune mediated diseases, since these elucidations could be beneficial to untangle the complex bond between them.

Comprehensive Biological Evaluation of Biomaterials Used in Spinal and Orthopedic Surgery

Biological acceptance is one of the most important aspects of a biomaterial and forms the basis for its clinical use. The aim of this study was a comprehensive biological evaluation (cytotoxicity test, bacterial colonization test, blood platelets adhesion test and transcriptome and proteome analysis of Saos-2 cells after contact with surface of the biomaterial) of biomaterials used in spinal and orthopedic surgery, namely, Ti6Al4V ELI (Extra Low Interstitials), its modified version obtained as a result of melting by electron beam technology (Ti6Al4V ELI-EBT), polyether ether ketone (PEEK) and polished medical steel American Iron and Steel Institute (AISI) 316L (the reference material). Biological tests were carried out using the osteoblasts-like cells (Saos-2, ATCC HTB-85) and bacteria Escherichia coli (DH5α). Results showed lack of cytotoxicity of all materials and the surfaces of both Ti6Al4V ELI and PEEK exhibit a significantly higher resistance to colonization with E. coli cells, while the more porous surface of the same titanium alloy produced by electron beam technology (EBT) is more susceptible to microbial colonization than the control surface of polished medical steel. None of the tested materials showed high toxicity in relation to E. coli cells. Susceptibility to platelet adhesion was very high for polished medical steel AISI 316L, whilst much lower for the other biomaterials and can be ranked from the lowest to the highest as follows: PEEK < Ti6Al4V ELI < Ti6Al4V ELI-EBT. The number of expressed genes in Saos-2 cells exposed to contact with the examined biomaterials reached 9463 genes in total (ranging from 8455 genes expressed in cells exposed to ELI to 9160 genes in cells exposed to PEEK). Whereas the number of differentially expressed proteins detected on two-dimensional electrophoresis gels in Saos-2 cells after contact with the examined biomaterials was 141 for PEEK, 223 for Ti6Al4V ELI and 133 for Ti6Al4V ELI-EBT. Finally, 14 proteins with altered expression were identified by mass spectrometry. In conclusion, none of the tested biomaterials showed unsatisfactory levels of cytotoxicity. The gene and protein expression analysis, that represents a completely new approach towards characterization of these biomaterials, showed that the polymer PEEK causes much more intense changes in gene and protein expression and thus influences cell metabolism.

Therapeutic potential of FLANC, a novel primate-specific long non-coding RNA in colorectal cancer

OBJECTIVE

To investigate the function of a novel primate-specific long non-coding RNA (lncRNA), named FLANC, based on its genomic location (co-localised with a pyknon motif), and to characterise its potential as a biomarker and therapeutic target.

DESIGN

FLANC expression was analysed in 349 tumours from four cohorts and correlated to clinical data. In a series of multiple in vitro and in vivo models and molecular analyses, we characterised the fundamental biological roles of this lncRNA. We further explored the therapeutic potential of targeting FLANC in a mouse model of colorectal cancer (CRC) metastases.

RESULTS

FLANC, a primate-specific lncRNA feebly expressed in normal colon cells, was significantly upregulated in cancer cells compared with normal colon samples in two independent cohorts. High levels of FLANC were associated with poor survival in two additional independent CRC patient cohorts. Both in vitro and in vivo experiments demonstrated that the modulation of FLANC expression influenced cellular growth, apoptosis, migration, angiogenesis and metastases formation ability of CRC cells. In vivo pharmacological targeting of FLANC by administration of 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine nanoparticles loaded with a specific small interfering RNA, induced significant decrease in metastases, without evident tissue toxicity or pro-inflammatory effects. Mechanistically, FLANC upregulated and prolonged the half-life of phosphorylated STAT3, inducing the overexpression of VEGFA, a key regulator of angiogenesis.

CONCLUSIONS

Based on our findings, we discovered, FLANC as a novel primate-specific lncRNA that is highly upregulated in CRC cells and regulates metastases formation. Targeting primate-specific transcripts such as FLANC may represent a novel and low toxic therapeutic strategy for the treatment of patients.

TGFam-Finder: a novel solution for target-gene family annotation in plants

Whole-genome annotation error that omits essential protein-coding genes hinders further research. We developed Target Gene Family Finder (TGFam-Finder), an alternative tool for the structural annotation of protein-coding genes containing target domain(s) of interest in plant genomes. TGFam-Finder took considerably reduced annotation run-time and improved accuracy compared to conventional annotation tools. Large-scale re-annotation of 50 plant genomes identified an average of 150, 166 and 86 additional far-red-impaired response 1, nucleotide-binding and leucine-rich-repeat, and cytochrome P450 genes, respectively, that were missed in previous annotations. We detected significantly higher number of translated genes in the new annotations using mass spectrometry data from seven plant species compared to previous annotations. TGFam-Finder along with the new gene models can provide an optimized platform for comprehensive functional, comparative, and evolutionary studies in plants.

Exploring the functional impact of alternative splicing on human protein isoforms using available annotation sources

In recent years, the emphasis of scientific inquiry has shifted from whole-genome analyses to an understanding of cellular responses specific to tissue, developmental stage or environmental conditions. One of the central mechanisms underlying the diversity and adaptability of the contextual responses is alternative splicing (AS). It enables a single gene to encode multiple isoforms with distinct biological functions. However, to date, the functions of the vast majority of differentially spliced protein isoforms are not known. Integration of genomic, proteomic, functional, phenotypic and contextual information is essential for supporting isoform-based modeling and analysis. Such integrative proteogenomics approaches promise to provide insights into the functions of the alternatively spliced protein isoforms and provide high-confidence hypotheses to be validated experimentally. This manuscript provides a survey of the public databases supporting isoform-based biology. It also presents an overview of the potential global impact of AS on the human canonical gene functions, molecular interactions and cellular pathways.

RPmirDIP: Reciprocal Perspective improves miRNA targeting prediction

MicroRNAs (miRNAs) are short, non-coding RNAs that interact with messenger RNA (mRNA) to accomplish critical cellular activities such as the regulation of gene expression. Several machine learning methods have been developed to improve classification accuracy and reduce validation costs by predicting which miRNA will target which gene. Application of these predictors to large numbers of unique miRNA-gene pairs has resulted in datasets comprising tens of millions of scored interactions; the largest among these is mirDIP. We here demonstrate that miRNA target prediction can be significantly improved ([Formula: see text]) through the application of the Reciprocal Perspective (RP) method, a cascaded, semi-supervised machine learning method originally developed for protein-protein interaction prediction. The RP method, aptly named RPmirDIP, augments the original mirDIP prediction scores by leveraging local thresholds from the two complimentary views available to each miRNA-gene pair, rather than apply a traditional global decision threshold. Application of this novel RPmirDIP predictor promises to help identify new, unexpected miRNA-gene interactions. A dataset of RPmirDIP-scored interactions are made available to the scientific community at cu-bic.ca/RPmirDIP and https://doi.org/10.5683/SP2/LD8JKJ.

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.

Response to a DNA vaccine against the H5N1 virus depending on the chicken line and number of doses

Background

Avian influenza virus infections cause significant economic losses on poultry farms and pose the threat of a possible pandemic outbreak. Routine vaccination of poultry against avian influenza is not recommended in Europe, however it has been ordered in some other countries, and more countries are considering use of the avian influenza vaccine as a component of their control strategy. Although a variety of such vaccines have been tested, most research has concentrated on specific antibodies and challenge experiments.

Methods

We monitored the transcriptomic response to a DNA vaccine encoding hemagglutinin from the highly pathogenic H5N1 avian influenza virus in the spleens of broiler and layer chickens. Moreover, in layer chickens the response to one and two doses of the vaccine was compared.

Results

All groups of birds immunized with two doses of the vaccine responded at the humoral level by producing specific anti-hemagglutinin antibodies. A response to the vaccine was also detected in the spleen transcriptomes. Differential expression of many genes encoding noncoding RNA and proteins functionally connected to the neuroendocrine-immune system was observed in different immunized groups.

Conclusion

Broiler chickens showed a higher number and wider range of fold-changes in the transcriptional response than laying hens.

Metabolome-Microbiome Crosstalk and Human Disease

In this review, we discuss the growing literature demonstrating robust and pervasive associations between the microbiome and metabolome. We focus on the gut microbiome, which harbors the taxonomically most diverse and the largest collection of microorganisms in the human body. Methods for integrative analysis of these "omics" are under active investigation and we discuss the advances and challenges in the combined use of metabolomics and microbiome data. Findings from large consortia, including the Human Microbiome Project and Metagenomics of the Human Intestinal Tract (MetaHIT) and others demonstrate the impact of microbiome-metabolome interactions on human health. Mechanisms whereby the microbes residing in the human body interact with metabolites to impact disease risk are beginning to be elucidated, and discoveries in this area will likely be harnessed to develop preventive and treatment strategies for complex diseases.

A Novel Prognostic Index Based on Alternative Splicing in Papillary Renal Cell Carcinoma

Background

Papillary renal cell carcinoma (pRCC) is a heterogeneous multifocal or isolated tumor with an invasive phenotype. Previous studies presented that alternative splicing, as a crucial posttranscriptional regulator in gene expression, is associated with tumorigenesis. However, the association between alternative splicing and pRCC has not been clarified

Methods

The RNA sequencing data and clinical information were downloaded from The Cancer Genome Atlas database and mRNA splicing profiles from TCGASpliceSeq. The percent spliced in data of alternative splicing merged with survival information was firstly calculated by univariate Cox regression analysis to screen for survival‐associated alternative splicing events, and survival‐associated alternative splicing events were then analyzed by Gene Ontology categories using Kyoto Encyclopedia of Genes and Genomes. Meanwhile, the least absolute shrinkage and selection operator Cox analysis and multivariate Cox analysis were performed to calculate the prognostic index for each alternative splicing type. In addition, clinical factors were introduced to assess the performance of prognostic index.

Results

A total of 4,084 candidate survival-associated alternative splicing events in 2,558 genes were screened out. Patients were divided into the low-risk group and the high-risk group based on the median prognostic index value. The Kaplan-Meier survival analysis (p < 0.05) and receiver operating characteristics curves (AUC>0.9) indicated that prognostic index was effective and stable for predicting the prognosis of pRCC patients. Furthermore, a regulatory network was constructed incorporating alternative splicing events and survival-associated splicing factors.

Conclusion

Our study provides new insights into the mechanism of alternative splicing events in tumorigenesis and their clinical potential for pRCC.

Genomic data mining for functional annotation of human long noncoding RNAs

Life may have begun in an RNA world, which is supported by increasing evidence of the vital role that RNAs perform in biological systems. In the human genome, most genes actually do not encode proteins; they are noncoding RNA genes. The largest class of noncoding genes is known as long noncoding RNAs (lncRNAs), which are transcripts greater in length than 200 nucleotides, but with no protein-coding capacity. While some lncRNAs have been demonstrated to be key regulators of gene expression and 3D genome organization, most lncRNAs are still uncharacterized. We thus propose several data mining and machine learning approaches for the functional annotation of human lncRNAs by leveraging the vast amount of data from genetic and genomic studies. Recent results from our studies and those of other groups indicate that genomic data mining can give insights into lncRNA functions and provide valuable information for experimental studies of candidate lncRNAs associated with human disease.

Metabolomics for Investigating Physiological and Pathophysiological Processes

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the "bricks and mortar" of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.

Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits

Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect size genes could cumulatively play a substantial role in pathway function. Here, we determine the number, strength, and identity of all non-essential test genes that affect two quantitative galactose-responsive traits in addition to re-analyzing two previously screened quantitative traits. We find that over a quarter of assayed genes have a detectable, quantitative effect on phenotype. Despite their ubiquity, these genes are enriched in core cellular processes in a trait-specific manner. In a simulated population with 50% frequency of all-or-none alleles, we show that small effect size alleles are capable of contributing more to trait variation than alleles in a canonical, large effect size pathway. In total, by demonstrating that the genes effecting quantitative traits can be highly distributed and interconnected, this work challenges the concept of pathways as modular and independent.

The Protein-Coding Human Genome: Annotating High-Hanging Fruits

The major transcript variants of human protein-coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes-they can be protein-coding, noncoding, or pseudogenes-and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro-exons and wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re-assignments. The emerging human pan-genome is necessitating distinctive annotations incorporating differences between individuals and between populations.

Navigating the non-coding genome in heart development and Congenital Heart Disease

Congenital Heart Disease (CHD) is characterised by a wide range of cardiac defects, from mild to life-threatening, which occur in babies worldwide. To date, there is no cure to CHD, however, progress in surgery has reduced its mortality allowing children affected by CHD to reach adulthood. In an effort to understand its genetic basis, several studies involving whole-genome sequencing (WGS) of patients with CHD have been undertaken and generated a great wealth of information. The majority of putative causative mutations identified in WGS studies fall into the non-coding part of the genome. Unfortunately, due to the lack of understanding of the function of these non-coding mutations, it is challenging to establish a causal link between the non-coding mutation and the disease. Thus, here we review the state-of-the-art approaches to interpret non-coding mutations in the context of CHD and address the following questions: What are the non-coding sequences important for cardiac function? Which technologies are used to identify them? Which resources are available to analyse them? What mutations are expected in these non-coding sequences? Learning from developmental process, what is their expected role in CHD?

Long Non-Coding RNAs and the Innate Immune Response

Innate immunity provides the initial defence against infection and it is now clear that long non-coding RNAs (lncRNAs) are important regulators of this response. Following activation of the innate response, we commonly see rapid induction of these lncRNAs and this is often mediated via the pro-inflammatory transcription factor, nuclear factor-κB (NF-κB). Knockdown studies have shown that lncRNAs tend to act in trans to regulate the expression of multiple inflammatory mediators and other responses. Mechanistically, many lncRNAs have demonstrated acting through heterogeneous nuclear ribonucleoproteins, complexes that are implicated chromatin re-modelling, transcription process and translation. In addition, these lncRNAs have also been shown to interact with multiple other proteins involved in the regulation of chromatin re-modelling, as well as those proteins involved in intracellular immune signalling, which include NF-κB. In this review, we will describe the evidence that supports this emerging role of lncRNA in the innate immune response.

Genomic Interventions in Medicine

Lately, the term "genomics" has become ubiquitous in many scientific articles. It is a rapidly growing aspect of the biomedical sciences that studies the genome. The human genome contains a torrent of information that gives clues about human origin, evolution, biological function, and diseases. In a bid to demystify the workings of the genome, the Human Genome Project (HGP) was initiated in 1990, with the chief goal of sequencing the approximately 3 billion nucleotide base pairs of the human DNA. Since its completion in 2003, the HGP has opened new avenues for the application of genomics in clinical practice. This review attempts to overview some milestone discoveries that paved way for the initiation of the HGP, remarkable revelations from the HGP, and how genomics is influencing a paradigm shift in routine clinical practice. It further highlights the challenges facing the implementation of genomic medicine, particularly in Africa. Possible solutions are also discussed.