The sequence of the human genome

The genomic history and global migration of a windborne pest

Many insect pests, including the brown planthopper (BPH), undergo windborne migration that is challenging to observe and track. It remains controversial about their migration patterns and largely unknown regarding the underlying genetic basis. By analyzing 360 whole genomes from around the globe, we clarify the genetic sources of worldwide BPHs and illuminate a landscape of BPH migration showing that East Asian populations perform closed-circuit journeys between Indochina and the Far East, while populations of Malay Archipelago and South Asia undergo one-way migration to Indochina. We further find round-trip migration accelerates population differentiation, with highly diverged regions enriching in a gene desert chromosome that is simultaneously the speciation hotspot between BPH and related species. This study not only shows the power of applying genomic approaches to demystify the migration in windborne migrants but also enhances our understanding of how seasonal movements affect speciation and evolution in insects.

Clinical Genetic and Genomic Testing in Congenital Heart Disease and Cardiomyopathy

Congenital heart disease (CHD) and cardiomyopathies are the leading cause of morbidity and mortality worldwide. These conditions are often caused by genetic factors, and recent research has shown that genetic and genomic testing can provide valuable information for patient care. By identifying genetic causes, healthcare providers can screen for other related health conditions, offer early interventions, estimate prognosis, select appropriate treatments, and assess the risk for family members. Genetic and genomic testing is now the standard of care in patients with CHD and cardiomyopathy. However, rapid advances in technology and greater availability of testing options have led to changes in recommendations for the most appropriate testing method. Several recent studies have investigated the utility of genetic testing in this changing landscape. This review summarizes the literature surrounding the clinical utility of genetic evaluation in patients with CHD and cardiomyopathy.

Inference of genomic landscapes using ordered Hidden Markov Models with emission densities (oHMMed)

BACKGROUND

Genomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim to quantify this variation, account for it during inference procedures, and ultimately determine the causal processes behind it. Since sequential observations along chromosomes are not independent, it is unsurprising that autocorrelation patterns have been observed e.g., in human base composition. In this article, we develop a class of Hidden Markov Models (HMMs) called oHMMed (ordered HMM with emission densities, the corresponding R package of the same name is available on CRAN): They identify the number of comparably homogeneous regions within autocorrelated observed sequences. These are modelled as discrete hidden states; the observed data points are realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are inferred.

RESULTS

We apply our oHMMed algorithms to the proportion of G and C bases (modelled as a mixture of normal distributions) and the number of genes (modelled as a mixture of poisson-gamma distributions) in windows along the human, mouse, and fruit fly genomes. This results in a partitioning of the genomes into regions by statistically distinguishable averages of these features, and in a characterisation of their continuous patterns of variation. In regard to the genomic G and C proportion, this latter result distinguishes oHMMed from segmentation algorithms based in isochore or compositional domain theory. We further use oHMMed to conduct a detailed analysis of variation of chromatin accessibility (ATAC-seq) and epigenetic markers H3K27ac and H3K27me3 (modelled as a mixture of poisson-gamma distributions) along the human chromosome 1 and their correlations.

CONCLUSIONS

Our algorithms provide a biologically assumption free approach to characterising genomic landscapes shaped by continuous, autocorrelated patterns of variation. Despite this, the resulting genome segmentation enables extraction of compositionally distinct regions for further downstream analyses.

Plant genome information facilitates plant functional genomics

MAIN CONCLUSION

In this review, we give an overview of plant sequencing efforts and how this impacts plant functional genomics research. Plant genome sequence information greatly facilitates the studies of plant biology, functional genomics, evolution of genomes and genes, domestication processes, phylogenetic relationships, among many others. More than two decades of sequencing efforts have boosted the number of available sequenced plant genomes. The first plant genome, of Arabidopsis, was published in the year 2000 and currently, 4604 plant genomes from 1482 plant species have been published. Various large sequence initiatives are running, which are planning to produce tens of thousands of sequenced plant genomes in the near future. In this review, we give an overview on the status of sequenced plant genomes and on the use of genome information in different research areas.

The Diverse Evolutionary Histories of Domesticated Metaviral Capsid Genes in Mammals

Selfish genetic elements comprise significant fractions of mammalian genomes. In rare instances, host genomes domesticate segments of these elements for function. Using a complete human genome assembly and 25 additional vertebrate genomes, we re-analyzed the evolutionary trajectories and functional potential of capsid (CA) genes domesticated from Metaviridae, a lineage of retrovirus-like retrotransposons. Our study expands on previous analyses to unearth several new insights about the evolutionary histories of these ancient genes. We find that at least five independent domestication events occurred from diverse Metaviridae, giving rise to three universally retained single-copy genes evolving under purifying selection and two gene families unique to placental mammals, with multiple members showing evidence of rapid evolution. In the SIRH/RTL family, we find diverse amino-terminal domains, widespread loss of protein-coding capacity in RTL10 despite its retention in several mammalian lineages, and differential utilization of an ancient programmed ribosomal frameshift in RTL3 between the domesticated CA and protease domains. Our analyses also reveal that most members of the PNMA family in mammalian genomes encode a conserved putative amino-terminal RNA-binding domain (RBD) both adjoining and independent from domesticated CA domains. Our analyses lead to a significant correction of previous annotations of the essential CCDC8 gene. We show that this putative RBD is also present in several extant Metaviridae, revealing a novel protein domain configuration in retrotransposons. Collectively, our study reveals the divergent outcomes of multiple domestication events from diverse Metaviridae in the common ancestor of placental mammals.

A comprehensive review of lncRNA CRNDE in cancer progression and pathology, with a specific glance at the epithelial-mesenchymal transition (EMT) process

It has been suggested that the long non-coding RNAs (lncRNAs), such as colorectal neoplasia differentially expressed (CRNDE), may contribute to the formation of human cancer. It is yet unknown, though, what therapeutic significance CRNDE expression has for different forms of cancer. CRNDE has recently been proposed as a possible diagnostic biomarker and prognostic pred for excellent specificity and sensitivity in cancer tissues and plasma. To provide the groundwork for potential future therapeutic uses of CRNDE, we briefly overview its biological action and related cancer-related pathways. Next, we mainly address the impact of CRNDE on the epithelial-mesenchymal transition (EMT). The epithelial-mesenchymal transition, or EMT, is an essential biological mechanism involved in the spread of cancer.

Exploring the patterns of evolution: Core thoughts and focus on the saltational model

The Modern Synthesis, a pillar in biological thought, united Darwin's species origin concepts with Mendel's laws of character heredity, providing a comprehensive understanding of evolution within species. Highlighting phenotypic variation and natural selection, it elucidated the environment's role as a selective force, shaping populations over time. This framework integrated additional mechanisms, including genetic drift, random mutations, and gene flow, predicting their cumulative effects on microevolution and the emergence of new species. Beyond the Modern Synthesis, the Extended Evolutionary Synthesis expands perspectives by recognizing the role of developmental plasticity, non-genetic inheritance, and epigenetics. We suggest that these aspects coexist in the plant evolutionary process; in this context, we focus on the saltational model, emphasizing how saltation events, such as dichotomous saltation, chromosomal mutations, epigenetic phenomena, and polyploidy, contribute to rapid evolutionary changes. The saltational model proposes that certain evolutionary changes, such as the rise of new species, may result suddenly from single macromutations rather than from gradual changes in DNA sequences and allele frequencies within a species over time. These events, observed in domesticated and wild higher plants, provide well-defined mechanistic bases, revealing their profound impact on plant diversity and rapid evolutionary events. Notably, next-generation sequencing exposes the likely crucial role of allopolyploidy and autopolyploidy (saltational events) in generating new plant species, each characterized by distinct chromosomal complements. In conclusion, through this review, we offer a thorough exploration of the ongoing dissertation on the saltational model, elucidating its implications for our understanding of plant evolutionary processes and paving the way for continued research in this intriguing field.

Recent advances in Alzheimer disease genetics

PURPOSE OF REVIEW

Genetics studies provide important insights into Alzheimer disease (AD) etiology and mechanisms. Critical advances have been made recently, mainly thanks to the access to novel techniques and larger studies.

RECENT FINDINGS

In monogenic AD, progress has been made with a better understanding of the mechanisms associated with pathogenic variants and the input of clinical studies in presymptomatic individuals. In complex AD, increasing sample sizes in both DNA chip-based (genome-wide association studies, GWAS) and exome/genome sequencing case-control studies unveiled novel common and rare risk factors, while the understanding of their combined effect starts to suggest the existence of rare families with oligogenic inheritance of early-onset, nonmonogenic, AD.

SUMMARY

Most genetic risk factors with a known consequence designate the aggregation of the Aβ peptide as a core etiological factor in complex AD thus confirming that the research based on monogenic AD - where the amyloid cascade seems more straightforward - is relevant to complex AD as well. Novel mechanistic insights and risk factor studies unveiling novel factors and attempting to combine the effect of common and rare variants will offer promising perspectives for future AD prevention, at least regarding early-onset AD, and probably in case of later onset as well.

If it's a target, it's a pan-cancer target: Tissue is not the issue

Cancer is traditionally diagnosed and treated on the basis of its organ of origin (e.g., lung or colon cancer). However, organ-of-origin diagnostics does not reveal the underlying oncogenic drivers. Fortunately, molecular diagnostics have advanced at a breathtaking pace, and it is increasingly apparent that cancer is a disease of the genome. Hence, we now have multiple genomic biomarker-based, tissue-agnostic Food and Drug Administration approvals for both gene- and immune-targeted therapies (larotrectinib/entrectinib, for NTRK fusions; selpercatinib, RET fusions; dabrafenib plus trametinib, BRAFV600E mutations; pembrolizumab/dostarlimab, microsatellite instability; and pembrolizumab for high tumor mutational burden; pemigatinib is also approved for FGFR1-rearranged myeloid/lymphoid neoplasms). There are emerging targets as well, including but not limited to ALK, BRCA and/or homologous repair deficiency, ERBB2 (HER2), IDH1/2, KIT, KRASG12C, NRG1, and VHL. Many tissue-agnostic approvals center on rare/ultra-rare biomarkers (often < 1 % of cancers), necessitating screening hundreds of tumors to find a single one harboring the cognate molecular alteration. Approval has generally been based on small single-arm studies (<30-100 patients) with high response rates (>30 % to > 75 %) of remarkable durability. Because of biomarker rarity, single-gene testing is not practical; next generation sequencing of hundreds of genes must be performed to obtain timely answers. Resistance to biomarker-driven therapeutics is often due to secondary mutations or co-driver gene defects; studies are now addressing the need for customized drug combinations matched to the complex molecular alteration portfolio in each tumor. Future investigation should expand tissue-agnostic therapeutics to encompass both hematologic and solid malignancies and include biomarkers beyond those that are DNA-based.

The transition from genomics to phenomics in personalized population health

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Regulation and function of transposable elements in cancer genomes

Over half of human genomic DNA is composed of repetitive sequences generated throughout evolution by prolific mobile genetic parasites called transposable elements (TEs). Long disregarded as "junk" or "selfish" DNA, TEs are increasingly recognized as formative elements in genome evolution, wired intimately into the structure and function of the human genome. Advances in sequencing technologies and computational methods have ushered in an era of unprecedented insight into how TE activity impacts human biology in health and disease. Here we discuss the current views on how TEs have shaped the regulatory landscape of the human genome, how TE activity is implicated in human cancers, and how recent findings motivate novel strategies to leverage TE activity for improved cancer therapy. Given the crucial role of methodological advances in TE biology, we pair our conceptual discussions with an in-depth review of the inherent technical challenges in studying repeats, specifically related to structural variation, expression analyses, and chromatin regulation. Lastly, we provide a catalog of existing and emerging assays and bioinformatic software that altogether are enabling the most sophisticated and comprehensive investigations yet into the regulation and function of interspersed repeats in cancer genomes.

[mRNA vaccination, a model of transition from basic biology to medicine]

Sixty years elapsed between the discovery of messenger RNA (mRNA) and the use of this molecule in an unprecedented global vaccination campaign that brought the Covid-19 pandemic under control. Sixty years of doubts for some and certainties for others about the possibility of using mRNA-an example of synthetic biology-in therapeutic medicine and vaccinology. Years of "translational" research and development have culminated in the success of anti-Covid-19 mRNA vaccines and the promise of more to come against emerging pathogens. A new paradigm in vaccinology, enabling pandemics to be tackled as they emerge. A lesson to be learned: medical progress is less a question of time than of the critical nature of the biological discovery that underpins it. Before leaving us, François Gros, who played a key role in the discovery of mRNA, was able to appreciate the relevance of this obvious fact.

Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Transcription-induced active forces suppress chromatin motion

The organization of interphase chromosomes in a number of species is starting to emerge thanks to advances in a variety of experimental techniques. However, much less is known about the dynamics, especially in the functional states of chromatin. Some experiments have shown that the motility of individual loci in human interphase chromosome decreases during transcription and increases upon inhibiting transcription. This is a counterintuitive finding because it is thought that the active mechanical force (F) on the order of ten piconewtons, generated by RNA polymerase II (RNAPII) that is presumably transmitted to the gene-rich region of the chromatin, would render it more open, thus enhancing the mobility. We developed a minimal active copolymer model for interphase chromosomes to investigate how F affects the dynamical properties of chromatin. The movements of the loci in the gene-rich region are suppressed in an intermediate range of F and are enhanced at small F values, which has also been observed in experiments. In the intermediate F, the bond length between consecutive loci increases, becoming commensurate with the distance at the minimum of the attractive interaction between nonbonded loci. This results in a transient disorder-to-order transition, leading to a decreased mobility during transcription. Strikingly, the F-dependent change in the locus dynamics preserves the organization of the chromosome at [Formula: see text]. Transient ordering of the loci, which is not found in the polymers with random epigenetic profiles, in the gene-rich region might be a plausible mechanism for nucleating a dynamic network involving transcription factors, RNAPII, and chromatin.

Structurally divergent and recurrently mutated regions of primate genomes

We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.

Human exons and introns classification using pre-trained Resnet-50 and GoogleNet models and 13-layers CNN model

BACKGROUND

Examining functions and characteristics of DNA sequences is a highly challenging task. When it comes to the human genome, which is made up of exons and introns, this task is more challenging. Human exons and introns contain millions to billions of nucleotides, which contributes to the complexity observed in this sequences. Considering how complicated the subject of genomics is, it is obvious that using signal processing techniques and deep learning tools to build a strong predictive model can be very helpful for the development of the research of the human genome.

RESULTS

After representing human exons and introns with color images using Frequency Chaos Game Representation, two pre-trained convolutional neural network models (Resnet-50 and GoogleNet) and a proposed CNN model having 13 hidden layers were used to classify our obtained images. We have reached a value of 92% for the accuracy rate for Resnet-50 model in about 7 h for the execution time, a value of 91.5% for the accuracy rate for the GoogleNet model in 2 h and a half for the execution time. For our proposed CNN model, we have reached 91.6% for the accuracy rate in 2 h and 37 min.

CONCLUSIONS

Our proposed CNN model is faster than the Resnet-50 model in terms of execution time. It was able to slightly exceed the GoogleNet model for the accuracy rate value.

RNA-binding proteins in breast cancer: Biological implications and therapeutic opportunities

RNA-binding proteins (RBPs) refer to a class of proteins that participate in alternative splicing, RNA stability, polyadenylation, localization and translation of RNAs, thus regulating gene expression in post-transcriptional manner. Dysregulation of RNA-RBP interaction contributes to various diseases, including cancer. In breast cancer, disorders in RBP expression and function influence the biological characteristics of tumor cells. Targeting RBPs has fostered the development of innovative therapies for breast cancer. However, the RBP-related mechanisms in breast cancer are not completely clear. In this review, we summarize the regulatory mechanisms of RBPs and their signaling crosstalk in breast cancer. Specifically, we emphasize the potential of certain RBPs as prognostic factors due to their effects on proliferation, invasion, apoptosis, and therapy resistance of breast cancer cells. Most importantly, we present a comprehensive overview of the latest RBP-related therapeutic strategies and novel therapeutic targets that have proven to be useful in the treatment of breast cancer.

Vault RNAs (vtRNAs): Rediscovered non-coding RNAs with diverse physiological and pathological activities

The physicochemical characteristics of RNA admit non-coding RNAs to perform a different range of biological acts through various mechanisms and are involved in regulating a diversity of fundamental processes. Notably, some reports of pathological conditions have proved abnormal expression of many non-coding RNAs guides the ailment. Vault RNAs are a class of non-coding RNAs containing stem regions or loops with well-conserved sequence patterns that play a fundamental role in the function of vault particles through RNA-ligand, RNA-RNA, or RNA-protein interactions. Taken together, vault RNAs have been proposed to be involved in a variety of functions such as cell proliferation, nucleocytoplasmic transport, intracellular detoxification processes, multidrug resistance, apoptosis, and autophagy, and serve as microRNA precursors and signaling pathways. Despite decades of investigations devoted, the biological function of the vault particle or the vault RNAs is not yet completely cleared. In this review, the current scientific assertions of the vital vault RNAs functions were discussed.

A pathway to strengthening open science: comments on the draft South African Ethics in Health Research Guidelines

The recently released draft South African Ethics in Health Research Guidelines: Principles, Processes and Structures (Draft Guidelines) by the National Health Research Ethics Council recognize open data and provide guiding principles for this in the context of health research in South Africa. While its inclusion is a positive development, there is room for improvement. Although the Draft Guidelines leverage the Draft National Policy on Data and Cloud, it lacks incorporation of other relevant government policies, notably the Draft National Open Science Policy, and fails to sufficiently detail the principles of open science and open access. This limited scope and lack of comprehensive definition and detailed guidance present challenges for researchers in conducting ethical and responsible health research in South Africa. It constrains the Draft Guidelines from fully aligning with national imperatives and from fostering African-centric approaches. To address these issues, it is recommended that the Draft Guidelines integrate broader policies and principles, enhance clarity through comprehensive definitions, provide detailed guidance on open access, and promote African-centric approaches. Implementing these solutions will strengthen the Draft Guidelines, aligning them with national visions of open science, and thereby harnessing the full potential of South Africa's diverse scientific community in advancing health research.

The Multiple Odysseys in Research and Clinical Care for Neurogenetic Conditions

Neurogenetic conditions (NGC; e.g., fragile X, Angelman, Prader-Willi syndromes) represent the cause for intellectual or developmental disabilities in up to 60% of cases. With expanded diagnostic options and an increasing focus on the development of gene therapies comes the potential of improved quality of life for individuals with NGCs and their families. However, these emerging initiatives also bring new challenges and considerations for NGC researchers and clinicians, including considerations for supporting caregivers and assuring outcome measures for clinical trials adequately reflect the lived experiences of people with NGCs. This paper summarizes the advances and current and future challenges of research and clinical service provision for people with NGCs and their caregivers.

Scrambling the genome in cancer: causes and consequences of complex chromosome rearrangements

Complex chromosome rearrangements, known as chromoanagenesis, are widespread in cancer. Based on large-scale DNA sequencing of human tumours, the most frequent type of complex chromosome rearrangement is chromothripsis, a massive, localized and clustered rearrangement of one (or a few) chromosomes seemingly acquired in a single event. Chromothripsis can be initiated by mitotic errors that produce a micronucleus encapsulating a single chromosome or chromosomal fragment. Rupture of the unstable micronuclear envelope exposes its chromatin to cytosolic nucleases and induces chromothriptic shattering. Found in up to half of tumours included in pan-cancer genomic analyses, chromothriptic rearrangements can contribute to tumorigenesis through inactivation of tumour suppressor genes, activation of proto-oncogenes, or gene amplification through the production of self-propagating extrachromosomal circular DNAs encoding oncogenes or genes conferring anticancer drug resistance. Here, we discuss what has been learned about the mechanisms that enable these complex genomic rearrangements and their consequences in cancer.

Genetic and molecular architecture of complex traits

Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.

A 25-year odyssey of genomic technology advances and structural variant discovery

This perspective focuses on advances in genome technology over the last 25 years and their impact on germline variant discovery within the field of human genetics. The field has witnessed tremendous technological advances from microarrays to short-read sequencing and now long-read sequencing. Each technology has provided genome-wide access to different classes of human genetic variation. We are now on the verge of comprehensive variant detection of all forms of variation for the first time with a single assay. We predict that this transition will further transform our understanding of human health and biology and, more importantly, provide novel insights into the dynamic mutational processes shaping our genomes.

Precise genome-editing in human diseases: mechanisms, strategies and applications

Precise genome-editing platforms are versatile tools for generating specific, site-directed DNA insertions, deletions, and substitutions. The continuous enhancement of these tools has led to a revolution in the life sciences, which promises to deliver novel therapies for genetic disease. Precise genome-editing can be traced back to the 1950s with the discovery of DNA's double-helix and, after 70 years of development, has evolved from crude in vitro applications to a wide range of sophisticated capabilities, including in vivo applications. Nonetheless, precise genome-editing faces constraints such as modest efficiency, delivery challenges, and off-target effects. In this review, we explore precise genome-editing, with a focus on introduction of the landmark events in its history, various platforms, delivery systems, and applications. First, we discuss the landmark events in the history of precise genome-editing. Second, we describe the current state of precise genome-editing strategies and explain how these techniques offer unprecedented precision and versatility for modifying the human genome. Third, we introduce the current delivery systems used to deploy precise genome-editing components through DNA, RNA, and RNPs. Finally, we summarize the current applications of precise genome-editing in labeling endogenous genes, screening genetic variants, molecular recording, generating disease models, and gene therapy, including ex vivo therapy and in vivo therapy, and discuss potential future advances.

Species-Specific Transcription Factors Associated with Long Terminal Repeat Promoters of Endogenous Retroviruses: A Comprehensive Review

Endogenous retroviruses (ERVs) became a part of the eukaryotic genome through endogenization millions of years ago. Moreover, they have lost their innate capability of virulence or replication. Nevertheless, in eukaryotic cells, they actively engage in various activities that may be advantageous or disadvantageous to the cells. The mechanisms by which transcription is triggered and implicated in cellular processes are complex. Owing to the diversity in the expression of transcription factors (TFs) in cells and the TF-binding motifs of viruses, the comprehensibility of ERV initiation and its impact on cellular functions are unclear. Currently, several factors are known to be related to their initiation. TFs that bind to the viral long-terminal repeat (LTR) are critical initiators. This review discusses the TFs shown to actively associate with ERV stimulation across species such as humans, mice, pigs, monkeys, zebrafish, Drosophila, and yeast. A comprehensive summary of the expression of previously reported TFs may aid in identifying similarities between animal species and endogenous viruses. Moreover, an in-depth understanding of ERV expression will assist in elucidating their physiological roles in eukaryotic cell development and in clarifying their relationship with endogenous retrovirus-associated diseases.

TREX tetramer disruption alters RNA processing necessary for corticogenesis in THOC6 Intellectual Disability Syndrome

THOC6 variants are the genetic basis of autosomal recessive THOC6 Intellectual Disability Syndrome (TIDS). THOC6 is critical for mammalian Transcription Export complex (TREX) tetramer formation, which is composed of four six-subunit THO monomers. The TREX tetramer facilitates mammalian RNA processing, in addition to the nuclear mRNA export functions of the TREX dimer conserved through yeast. Human and mouse TIDS model systems revealed novel THOC6-dependent, species-specific TREX tetramer functions. Germline biallelic Thoc6 loss-of-function (LOF) variants result in mouse embryonic lethality. Biallelic THOC6 LOF variants reduce the binding affinity of ALYREF to THOC5 without affecting the protein expression of TREX members, implicating impaired TREX tetramer formation. Defects in RNA nuclear export functions were not detected in biallelic THOC6 LOF human neural cells. Instead, mis-splicing was detected in human and mouse neural tissue, revealing novel THOC6-mediated TREX coordination of mRNA processing. We demonstrate that THOC6 is required for key signaling pathways known to regulate the transition from proliferative to neurogenic divisions during human corticogenesis. Together, these findings implicate altered RNA processing in the developmental biology of TIDS neuropathology.

Comprehensive characterization of ERV-K (HML-8) in the chimpanzee genome revealed less genomic activity than humans

Endogenous retroviruses (ERVs) originate from ancestral germline infections caused by exogenous retroviruses. Throughout evolution, they have become fixed within the genome of the animals into which they were integrated. As ERV elements coevolve with the host, they are normally epigenetically silenced and can become upregulated in a series of physiological and pathological processes. Generally, a detailed ERV profile in the host genome is critical for understanding the evolutionary history and functional performance of the host genome. We previously characterized and cataloged all the ERV-K subtype HML-8 loci in the human genome; however, this has not been done for the chimpanzee, the nearest living relative of humans. In this study, we aimed to catalog and characterize the integration of HML-8 in the chimpanzee genome and compare it with the integration of HML-8 in the human genome. We analyzed the integration of HML-8 and found that HML-8 pervasively invaded the chimpanzee genome. A total of 76 proviral elements were characterized on 23/24 chromosomes, including detailed elements distribution, structure, phylogeny, integration time, and their potential to regulate adjacent genes. The incomplete structure of HML-8 proviral LTRs will undoubtedly affect their activity. Moreover, the results indicated that HML-8 integration occurred before the divergence between humans and chimpanzees. Furthermore, chimpanzees include more HML-8 proviral elements (76 vs. 40) and fewer solo long terminal repeats (LTR) (0 vs. 5) than humans. These results suggested that chimpanzee genome activity is less than the human genome and that humans may have a better ability to shape and screen integrated proviral elements. Our work is informative in both an evolutionary and a functional context for ERVs.

Recent Progress of Protein Tertiary Structure Prediction

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure prediction performance to new heights, regularly competitive with experimental structures in the 14th Critical Assessment of Protein Structure Prediction (CASP14). To provide a comprehensive understanding and guide future research in the field of protein structure prediction for researchers, this review describes various methodologies, assessments, and databases in protein structure prediction, including traditionally used protein structure prediction methods, such as template-based modeling (TBM) and template-free modeling (FM) approaches; recently developed deep learning-based methods, such as contact/distance-guided methods, end-to-end folding methods, and protein language model (PLM)-based methods; multi-domain protein structure prediction methods; the CASP experiments and related assessments; and the recently released AlphaFold Protein Structure Database (AlphaFold DB). We discuss their advantages, disadvantages, and application scopes, aiming to provide researchers with insights through which to understand the limitations, contexts, and effective selections of protein structure prediction methods in protein-related fields.

Homeostasis and information processing: The key frames for the thermodynamics of biological systems

Life is a natural phenomenon ineluctably subject to the laws and principles of physics. In this framework, thermodynamics has a crucial role, since living beings are structured on a molecular and cellular basis that can only be maintained with extensive energy consumption. This imposes that living beings are necessarily open systems. But the survival of each type of organism depends on the relative stability of certain essential variables, even in the presence of the disturbances to which they are subjected. The stability of these variables is relative in the sense that they have a narrow range of variation. This stability of the essential variables is a consequence of refined control mechanisms developed in the course of evolution, that lead to the condition called homeostasis. This homeostasis requires that control mechanisms process the various types of information related to the internal structure of the organism and its environment. Consequently, a biological system, through information processing aimed at guiding the mechanisms that maintain its homeostasis, manages the conditions imposed by the principles of thermodynamics, obtaining the most efficient use of energy possible and keeping entropic degradation controlled. In this article, we discuss the close links between thermodynamics, homeostasis and the information processing necessary to maintain homeostasis.

Whole-genome sequencing in medicinal plants: current progress and prospect

Advancements in genomics have dramatically accelerated the research on medicinal plants, and the development of herbgenomics has promoted the "Project of 1K Medicinal Plant Genome" to decipher their genetic code. However, it is difficult to obtain their high-quality whole genomes because of the prevalence of polyploidy and/or high genomic heterozygosity. Whole genomes of 123 medicinal plants were published until September 2022. These published genome sequences were investigated in this review, covering their classification, research teams, ploidy, medicinal functions, and sequencing strategies. More than 1,000 institutes or universities around the world and 50 countries are conducting research on medicinal plant genomes. Diploid species account for a majority of sequenced medicinal plants. The whole genomes of plants in the Poaceae family are the most studied. Almost 40% of the published papers studied species with tonifying, replenishing, and heat-cleaning medicinal effects. Medicinal plants are still in the process of domestication as compared with crops, thereby resulting in unclear genetic backgrounds and the lack of pure lines, thus making their genomes more difficult to complete. In addition, there is still no clear routine framework for a medicinal plant to obtain a high-quality whole genome. Herein, a clear and complete strategy has been originally proposed for creating a high-quality whole genome of medicinal plants. Moreover, whole genome-based biological studies of medicinal plants, including breeding and biosynthesis, were reviewed. We also advocate that a research platform of model medicinal plants should be established to promote the genomics research of medicinal plants.

A Massive Proteogenomic Screen Identifies Thousands of Novel Peptides From the Human "Dark" Proteome

Although the human gene annotation has been continuously improved over the past 2 decades, numerous studies demonstrated the existence of a "dark proteome", consisting of proteins that were critical for biological processes but not included in widely used gene catalogs. The Genotype-Tissue Expression project generated more than 15,000 RNA-seq datasets from multiple tissues, which modeled 30 million transcripts in the human genome. To provide a resource of high-confidence novel proteins from the dark proteome, we screened 50,000 mass spectrometry runs from over 900 projects to identify proteins translated from the Genotype-Tissue Expression transcript model with proteomic support. We also integrated 3.8 million common genetic variants from the gnomAD database to improve peptide identification. As a result, we identified 170,529 novel peptides with proteomic evidence, of which 6048 passed the strictest standard we defined and were supported by PepQuery. We provided a user-friendly website (https://ncorf.genes.fun/) for researchers to check the evidence of novel peptides from their studies. The findings will improve our understanding of coding genes and facilitate genomic data interpretation in biomedical research.

Giving bodies to ghosts: locating molecules in the very place where they exert their biological roles

This paper reviews some of the goals of our investigations published over the years on Rivista di Istochimica Normale e Patologica, Basic and Applied Histochemistry, and the European Journal of Histochemistry - EJH. In a series of papers, we published some of the basic cytochemical features of the sperm cytodifferentiation process for the first time. This was a conceptual and practical prerequisite to the in situ quantitative evaluation of sperm DNA content. We showed that the discrepancy between the expected 1:2 ratio when comparing sperm versus somatic cell DNA content (sperm DNA content is always far low from the theoretical value) is due to DNA losses caused by the hydrochloric treatment entailed by the Feulgen reaction. The knowledge of the specific losses that occur during the various steps of the Feulgen reaction has allowed us to use it critically in Genome Size studies to highlight: - sperm aneuploidy in chromosomally derived subfertility; - the broad variability range of Mammalian genome sizes; - that termites are roaches (after decades of discussion on this topic). In addition, in a seminal paper on human oocytes, we showed (by transmission electron microscopy) a specific chromatin and cytoplasmic organization (both essential for further embryo development) linked to oocyte maturation arrest, a datum quite relevant to treating unmet therapeutic needs in human and veterinary reproduction.

Whole genome sequencing in clinical practice

Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.

Illuminating the brain-genetically encoded single wavelength fluorescent biosensors to unravel neurotransmitter dynamics

Understanding how neuronal networks generate complex behavior is one of the major goals of Neuroscience. Neurotransmitter and Neuromodulators are crucial for information flow between neurons and understanding their dynamics is the key to unravel their role in behavior. To understand how the brain transmits information and how brain states arise, it is essential to visualize the dynamics of neurotransmitters, neuromodulators and neurochemicals. In the last five years, an increasing number of single-wavelength biosensors either based on periplasmic binding proteins (PBPs) or on G-protein-coupled receptors (GPCR) have been published that are able to detect neurotransmitter release in vitro and in vivo with high spatial and temporal resolution. Here we review and discuss recent progress in the development of these sensors, their limitations and future directions.

Current insights into genome-based personalized nutrition technology: a patent review

Unlike general nutritional ranges that meet the nutritional needs essential for maintaining the life of an entire population, personalized nutrition is characterised by maintaining health through providing customized nutrition according to individuals' lifestyles or genetic characteristics. The development of technology and services for personalized nutrition is increasing, owing to the acquisition of knowledge about the differences in nutritional requirements according to the diversity of individuals and an increase in health interest. Regarding genetics, technology is being developed to distinguish the various characteristics of individuals and provide customized nutrition. Therefore, to understand the current state of personalized nutrition technology, understanding genomics is necessary to acquire information on nutrition research based on genomics. We reviewed patents related to personalized nutrition-targeting genomics and examined their mechanisms of action. Using the patent database, we searched 694 patents on nutritional genomics and extracted 561 highly relevant valid data points. Furthermore, an in-depth review was conducted by selecting core patents related to genome-based personalized nutrition technology. A marked increase was observed in personalized nutrition technologies using methods such as genetic scoring and disease-specific dietary recommendations.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Molecular Mechanisms and the Significance of Synonymous Mutations

Synonymous mutations result from the degeneracy of the genetic code. Most amino acids are encoded by two or more codons, and mutations that change a codon to another synonymous codon do not change the amino acid in the gene product. Historically, such mutations have been considered silent because they were assumed to have no to very little impact. However, research in the last few decades has produced several examples where synonymous mutations play important roles. These include optimizing expression by enhancing translation initiation and accelerating or decelerating translation elongation via codon usage and mRNA secondary structures, stabilizing mRNA molecules and preventing their breakdown before translation, and faulty protein folding or increased degradation due to enhanced ubiquitination and suboptimal secretion of proteins into the appropriate cell compartments. Some consequences of synonymous mutations, such as mRNA stability, can lead to different outcomes in prokaryotes and eukaryotes. Despite these examples, the significance of synonymous mutations in evolution and in causing disease in comparison to nonsynonymous mutations that do change amino acid residues in proteins remains controversial. Whether the molecular mechanisms described by which synonymous mutations affect organisms can be generalized remains poorly understood and warrants future research in this area.

Overcoming Microbiome-Acquired Gemcitabine Resistance in Pancreatic Ductal Adenocarcinoma

Gastrointestinal cancers (GICs) are one of the most recurrent diseases in the world. Among all GICs, pancreatic cancer (PC) is one of the deadliest and continues to disrupt people's lives worldwide. The most frequent pancreatic cancer type is pancreatic ductal adenocarcinoma (PDAC), representing 90 to 95% of all pancreatic malignancies. PC is one of the cancers with the worst prognoses due to its non-specific symptoms that lead to a late diagnosis, but also due to the high resistance it develops to anticancer drugs. Gemcitabine is a standard treatment option for PDAC, however, resistance to this anticancer drug develops very fast. The microbiome was recently classified as a cancer hallmark and has emerged in several studies detailing how it promotes drug resistance. However, this area of study still has seen very little development, and more answers will help in developing personalized medicine. PC is one of the cancers with the highest mortality rates; therefore, it is crucial to explore how the microbiome may mold the response to reference drugs used in PDAC, such as gemcitabine. In this article, we provide a review of what has already been investigated regarding the impact that the microbiome has on the development of PDAC in terms of its effect on the gemcitabine pathway, which may influence the response to gemcitabine. Therapeutic advances in this type of GIC could bring innovative solutions and more effective therapeutic strategies for other types of GIC, such as colorectal cancer (CRC), due to its close relation with the microbiome.

Conserved chromatin and repetitive patterns reveal slow genome evolution in frogs

Frogs are an ecologically diverse and phylogenetically ancient group of anuran amphibians that include important vertebrate cell and developmental model systems, notably the genus Xenopus. Here we report a high-quality reference genome sequence for the western clawed frog, Xenopus tropicalis, along with draft chromosome-scale sequences of three distantly related emerging model frog species, Eleutherodactylus coqui, Engystomops pustulosus, and Hymenochirus boettgeri. Frog chromosomes have remained remarkably stable since the Mesozoic Era, with limited Robertsonian (i.e., arm-preserving) translocations and end-to-end fusions found among the smaller chromosomes. Conservation of synteny includes conservation of centromere locations, marked by centromeric tandem repeats associated with Cenp-a binding surrounded by pericentromeric LINE/L1 elements. This work explores the structure of chromosomes across frogs, using a dense meiotic linkage map for X. tropicalis and chromatin conformation capture (Hi-C) data for all species. Abundant satellite repeats occupy the unusually long (~20 megabase) terminal regions of each chromosome that coincide with high rates of recombination. Both embryonic and differentiated cells show reproducible associations of centromeric chromatin and of telomeres, reflecting a Rabl-like configuration. Our comparative analyses reveal 13 conserved ancestral anuran chromosomes from which contemporary frog genomes were constructed.

DrosOMA: the Drosophila Orthologous Matrix browser

Background

Comparative genomic analyses to delineate gene evolutionary histories inform the understanding of organismal biology by characterising gene and gene family origins, trajectories, and dynamics, as well as enabling the tracing of speciation, duplication, and loss events, and facilitating the transfer of gene functional information across species. Genomic data are available for an increasing number of species from the genus Drosophila, however, a dedicated resource exploiting these data to provide the research community with browsable results from genus-wide orthology delineation has been lacking.

Methods

Using the OMA Orthologous Matrix orthology inference approach and browser deployment framework, we catalogued orthologues across a selected set of Drosophila species with high-quality annotated genomes. We developed and deployed a dedicated instance of the OMA browser to facilitate intuitive exploration, visualisation, and downloading of the genus-wide orthology delineation results.

Results

DrosOMA - the Drosophila Orthologous Matrix browser, accessible from https://drosoma.dcsr.unil.ch/ - presents the results of orthology delineation for 36 drosophilids from across the genus and four outgroup dipterans. It enables querying and browsing of the orthology data through a feature-rich web interface, with gene-view, orthologous group-view, and genome-view pages, including comprehensive gene name and identifier cross-references together with available functional annotations and protein domain architectures, as well as tools to visualise local and global synteny conservation.

Conclusions

The DrosOMA browser demonstrates the deployability of the OMA browser framework for building user-friendly orthology databases with dense sampling of a selected taxonomic group. It provides the Drosophila research community with a tailored resource of browsable results from genus-wide orthology delineation.

Machine learning and multi-omics data in chronic lymphocytic leukemia: the future of precision medicine?

Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of high-throughput multi-omics technologies has significantly influenced chronic lymphocytic leukemia research and paved the way for precision medicine approaches. In this review, we explore the role of machine learning in the analysis of multi-omics data in this hematological malignancy. We discuss recent literature on different machine learning models applied to single omic studies in chronic lymphocytic leukemia, with a special focus on the potential contributions to precision medicine. Finally, we highlight the recently published machine learning applications in multi-omics data in this area of research as well as their potential and limitations.

Identification of hub genes in heart failure by integrated bioinformatics analysis and machine learning

Objective

To screen feature genes of heart failure patients through machine learning methods, in order to identify characteristic genes driving heart failure and investigate the progression of heart failure.

Methods

Heart failure patient samples were downloaded from the public database GEO (Gene Expression Omnibus), including the datasets GSE116250, GSE120895, and GSE59867. GSE116250 and GSE120895 were used as the testing set, while GSE59867 was used as the validation set. LASSO regression analysis and SVM-RFE were utilized to identify feature genes.

Results

Analysis showed that among the differentially expressed genes between normal and heart failure patients, 9 genes were upregulated and 10 genes were downregulated. ROC curve analysis in the training set showed that TAGLN and SGPP2 had AUC values greater than 0.7. Moreover, SDSL and SMTNL2 had even higher AUC values of greater than 0.9. However, further analysis in the validation set showed that only SDSL had an AUC value greater than 0.7. Western blot experiments, RT-PCR, and ISO-induced experiments confirmed that SDSL was highly expressed in heart failure patients and promoted heart failure progression. In addition, SDSL promoted PARP1 expression and knockdown of SDSL expression led to decreased Cleaved-PARP1 expression and reduced cardiomyocyte apoptosis. Conversely, overexpression of SDSL resulted in increased PARP1 expression and myocardial cell apoptosis. These results suggest that elevated expression of SDSL in cardiomyocytes from heart failure patients may be an important factor promoting the occurrence and development of heart failure.

Conclusions

Using machine learning methods and experimental validation, it has been demonstrated that SDSL is a driving gene in patients with heart failure, providing a new treatment direction for clinical treatment.

Bayesian Methods for Information Borrowing in Basket Trials: An Overview

Basket trials allow simultaneous evaluation of a single therapy across multiple cancer types or subtypes of the same cancer. Since the same treatment is tested across all baskets, it may be desirable to borrow information across them to improve the statistical precision and power in estimating and detecting the treatment effects in different baskets. We review recent developments in Bayesian methods for the design and analysis of basket trials, focusing on the mechanism of information borrowing. We explain the common components of these methods, such as a prior model for the treatment effects that embodies an assumption of exchangeability. We also discuss the distinct features of these methods that lead to different degrees of borrowing. Through simulation studies, we demonstrate the impact of information borrowing on the operating characteristics of these methods and discuss its broader implications for drug development. Examples of basket trials are presented in both phase I and phase II settings.

Recent advances in stimuli-responsive tailored nanogels for cancer therapy; from bench to personalized treatment

To improve the quality of health in a personalized manner, better control over pharmacologically relevant cargo formulation, organ-specific targeted delivery, and on-demand release of therapeutic agents is crucial. Significant work has been put into designing and developing revolutionary nanotherapeutics approaches for the effective monitoring and personalized treatment of disease. Nanogel (NG) has attracted significant interest because of its tremendous potential in cancer therapy and its environmental stimuli responsiveness. NG is considered a next-generation delivery technology due to its benefits like as size tunability, high loading, stimuli responsiveness, prolonged drug release via in situ gelling mechanisms, stability, and its potential to provide personalized therapy from the investigation of human genes and the genes in various types of cancers and its association with a selective anticancer drug. Stimuli-responsive NGs can be used as smart nanomedicines to detect and treat cancer and can be tuned as personalized medicine as well. This comprehensive review article's major objectives include the challenges of NGs' clinical translation for cancer treatment as well as its early preclinical successes and prospects.

Text mining for contexts and relationships in cancer genomics literature

MOTIVATION

Scientific advances build on the findings of existing research. The 2001 publication of the human genome has led to the production of huge volumes of literature exploring the context-specific functions and interactions of genes. Technology is needed to perform large-scale text mining of research papers to extract the reported actions of genes in specific experimental contexts and cell states, such as cancer, thereby facilitating the design of new therapeutic strategies.

RESULTS

We present a new corpus and Text Mining methodology that can accurately identify and extract the most important details of cancer genomics experiments from biomedical texts. We build a Named Entity Recognition model that accurately extracts relevant experiment details from PubMed abstract text, and a second model that identifies the relationships between them. This system outperforms earlier models and enables the analysis of gene function in diverse and dynamically evolving experimental contexts.

AVAILABILITY AND IMPLEMENTATION

Code and data are available here: https://github.com/cambridgeltl/functional-genomics-ie.

Bioactive Exploration in Functional Foods: Unlocking Nature's Treasures

BACKGROUND

Functional foods offer an appealing way to improve health and prevent chronic diseases, and this subject has received much attention lately. They are effective in preventing chronic diseases like cancer, diabetes, heart disease, and obesity, according to research.

OBJECTIVE

This work presents an in-depth analysis of functional foods, covering key challenges from a scientific, legal, and commercial perspective.

METHODS

Multiple databases were searched to find studies on functional foods included in the systematic literature review. Various aspects of functional foods, from their classification, impact on human wellness, effectiveness in inhibiting chronic diseases, the regulatory environment, global market trends, and industry challenges, are all clarified in this thorough review.

RESULTS

This study aims to enhance understanding and establish a pathway for functional foods to be acknowledged as valid choices in the field of dietary supplements. It provides a thorough investigation of bioactive compounds present in functional foods, including but not limited to polyphenols, carotenoids, omega fatty acids, prebiotics, probiotics, and dietary fiber, along with an overview of their potential to mitigate chronic illnesses. We engage in an in-depth exploration of regulatory frameworks, shed light on groundbreaking research advancements, and meticulously examine strategies for commercialization and the variety of global challenges that accompany them. Establishing scientific consensus, navigating complex regulatory processes, dealing with skeptical consumers, and rising levels of competition are all problems that need to be solved in this field.

CONCLUSION

The field of functional foods can advance further, promoting better public health outcomes, by deeply comprehending and addressing these complex dimensions.