Long walk to genomics: History and current approaches to genome sequencing and assembly

Transgene Mapping in Animals: What to Choose?

The phenomenal progress in biotechnology and genomics is both inspiring and overwhelming-a classic curse of choice, particularly when it comes to selecting methods for mapping transgene DNA integration sites. Transgene localization remains a crucial task for the validation of transgenic mouse or other animal models generated by pronuclear microinjection. Due to the inherently random nature of DNA integration, reliable characterization of the insertion site is essential. Over the years, a vast number of mapping methods have been developed, and new approaches continue to emerge, making the choice of the most suitable technique increasingly complex. Factors such as cost, required reagents, and the nature of the generated data require careful consideration. In this review, we provide a structured overview of current transgene mapping techniques, which we have broadly classified into three categories: classic PCR-based methods (such as inverse PCR and TAIL-PCR), next-generation sequencing with target enrichment, and long-read sequencing platforms (PacBio and Oxford Nanopore). To aid in decision-making, we include a comparative table summarizing approximate costs for the methods. While each approach has its own advantages and limitations, we highlight our top four recommended methods, which we believe offer the best balance of cost-effectiveness, reliability, and simplicity for identifying transgene integration sites.

Are Hospital Pharmacists Ready for Precision Medicine in Nigerian Healthcare? Insights From a Multi-Center Study

Background

Precision medicine (PM) has taken center stage in healthcare since the completion of the genomic project. Developed countries have gradually integrated PM into mainstream patient management. However, Nigeria still grapples with wide acceptance, key translational research and implementation of PM. This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.

Methods

A cross-sectional study was conducted in selected tertiary hospitals across the country. A 21-item semi-structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25. Descriptive statistics were used to summarize the data. A chi-square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.

Results

A total of 167 hospital pharmacists participated in the study. A high proportion of the participants are familiar with artificial intelligence (91.75%), Pharmacogenomics (84.5%), and precision medicine (61%). Overall, 38.9% of the pharmacists had a good knowledge while 13.2% had a poor knowledge of PM and associated terms. The level of knowledge did not correlate significantly with gender (X 2 = 3.21, p = 0.201), age (X 2 = 5, p = 0.27), marital status (X 2 = 3.21, p = 0.201), and professional level (X 2 = 6.85, p = 0.144). The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine (49%) while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.

Conclusions

There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria. Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM. Also, more research aimed at translating PM knowledge into clinical practice is recommended.

A haplotype-resolved reference genome of Quercus alba sheds light on the evolutionary history of oaks

White oak (Quercus alba) is an abundant forest tree species across eastern North America that is ecologically, culturally, and economically important. We report the first haplotype-resolved chromosome-scale genome assembly of Q. alba and conduct comparative analyses of genome structure and gene content against other published Fagaceae genomes. We investigate the genetic diversity of this widespread species and the phylogenetic relationships among oaks using whole genome data. Despite strongly conserved chromosome synteny and genome size across Quercus, certain gene families have undergone rapid changes in size, including defense genes. Unbiased annotation of resistance (R) genes across oaks revealed that the overall number of R genes is similar across species - as are the chromosomal locations of R gene clusters - but, gene number within clusters is more labile. We found that Q. alba has high genetic diversity, much of which predates its divergence from other oaks and likely impacts divergence time estimations. Our phylogenetic results highlight widespread phylogenetic discordance across the genus. The white oak genome represents a major new resource for studying genome diversity and evolution in Quercus. Additionally, we show that unbiased gene annotation is key to accurately assessing R gene evolution in Quercus.

A Segregating Structural Variant Defines Novel Venom Phenotypes in the Eastern Diamondback Rattlesnake

Of all mutational mechanisms contributing to phenotypic variation, structural variants are both among the most capable of causing major effects as well as the most technically challenging to identify. Intraspecific variation in snake venoms is widely reported, and one of the most dramatic patterns described is the parallel evolution of streamlined neurotoxic rattlesnake venoms from hemorrhagic ancestors by means of deletion of snake venom metalloproteinase (SVMP) toxins and recruitment of neurotoxic dimeric phospholipase A2 (PLA2) toxins. While generating a haplotype-resolved, chromosome-level genome assembly for the eastern diamondback rattlesnake (Crotalus adamanteus), we discovered that our genome animal was heterozygous for a ∼225 Kb deletion containing six SVMP genes, paralleling one of the two steps involved in the origin of neurotoxic rattlesnake venoms. Range-wide population-genomic analysis revealed that, although this deletion is rare overall, it is the dominant homozygous genotype near the northwestern periphery of the species' range, where this species is vulnerable to extirpation. Although major SVMP deletions have been described in at least five other rattlesnake species, C. adamanteus is unique in not additionally gaining neurotoxic PLA2s. Previous work established a superficially complementary north-south gradient in myotoxin (MYO) expression based on copy number variation with high expression in the north and low in the south, yet we found that the SVMP and MYO genotypes vary independently, giving rise to an array of diverse, novel venom phenotypes across the range. Structural variation, therefore, forms the basis for the major axes of geographic venom variation for C. adamanteus.

Bridging the gap between histopathology and genomics: Spotlighting spatial omics

Spatial biology has emerged as a transformative field, offering insights into cellular interactions and organization within tissues. The field has evolved rapidly since the coining of the term "spatial omics." Now, the ability to spatially resolve proteins, RNA, chromatin, and lipids is becoming widespread, and the technologies are continually refined. Reagents to support the analysis of veterinary species are available and more are emerging. These new tools will allow pathologists and scientists to unravel the intricate interplay between tissue architecture and diverse cellular phenotypes. By integrating histological observations with spatially resolved genomic data, spatial biology holds immense potential for advancing diagnostic and therapeutic strategies in veterinary medicine. These tools will undoubtedly equip veterinary pathologists to better decipher complex disease processes and identify novel therapeutic targets.

Guidelines for gene and genome assembly nomenclature

The rapid increase in the number of reference-quality genome assemblies presents significant new opportunities for genomic research. However, the absence of standardized naming conventions for genome assemblies and annotations across datasets creates substantial challenges. Inconsistent naming hinders the identification of correct assemblies, complicates the integration of bioinformatics pipelines, and makes it difficult to link assemblies across multiple resources. To address this, we developed a specification for standardizing the naming of reference genome assemblies, to improve consistency across datasets and facilitate interoperability. This specification was created with FAIR (Findable, Accessible, Interoperable, and Reusable) practices in mind, ensuring that reference assemblies are easier to locate, access, and reuse across research communities. Additionally, it has been designed to comply with primary genomic data repositories, including members of the International Nucleotide Sequence Database Collaboration consortium, ensuring compatibility with widely used databases. While initially tailored to the agricultural genomics community, the specification is adaptable for use across different taxa. Widespread adoption of this standardized nomenclature would streamline assembly management, better enable cross-species analyses, and improve the reproducibility of research. It would also enhance natural language processing applications that depend on consistent reference assembly names in genomic literature, promoting greater integration and automated analysis of genomic data. This is a good time to consider more consistent genomic data nomenclature as many research communities and data resources are now finding themselves juggling multiple datasets from multiple data providers.

HEK-omics: The promise of omics to optimize HEK293 for recombinant adeno-associated virus (rAAV) gene therapy manufacturing

Gene therapy is poised to transition from niche to mainstream medicine, with recombinant adeno-associated virus (rAAV) as the vector of choice. However, robust, scalable, industrialized production is required to meet demand and provide affordable patient access, which has not yet materialized. Closing the chasm between demand and supply requires innovation in biomanufacturing to achieve the essential step change in rAAV product yield and quality. Omics provides a rich source of mechanistic knowledge that can be applied to HEK293, the most commonly used cell line for rAAV production. In this review, the findings from a growing number of diverse studies that apply genomics, epigenomics, transcriptomics, proteomics, and metabolomics to HEK293 bioproduction are explored. Learnings from CHO-omics, application of omics approaches to improve CHO bioproduction, provide a framework to explore the potential of "HEK-omics" as a multi-omics-informed approach providing actionable mechanistic insights for improved transient and stable production of rAAV and other recombinant products in HEK293.

Historical examination of tuberculosis; from ancient affliction to modern challenges

Tuberculosis (TB), white plague, many other definitions is an ancient deadly infection that humans dealt with after creation. The first hypothesis refers to 150 million years ago about the appearance of TB in the Jurassic era before human creation, but documents show 9000 years ago for first appearance in human society. In 1882, Robert Koch was able to identify and describe the best possible agent of TB. After the discovery of TB's agent [Mycobacterium tuberculosis], progress was made in diagnosis and treatment rapidly, and invasive operations such as surgery were replaced with drug treatment and chemical compounds hired for treatment that were so effective before drug resistance occurrence. In this review authors done their tries to describe all aspects of TB [identification, epidemics, diagnostics, drug development, etc.] in history from ancient records to the present condition and give insight into the future of TB ending in 2030 and 2050.

De novo genome hybrid assembly and annotation of the endangered and euryhaline fish Aphanius iberus (Valenciennes, 1846) with identification of genes potentially involved in salinity adaptation

BACKGROUND

The sequencing of non-model species has increased exponentially in recent years, largely due to the advent of novel sequencing technologies. In this study, we construct the Reference Genome of the Spanish toothcarp (Aphanius iberus (Valenciennes, 1846)), a renowned euryhaline fish species. This species is native to the marshes along the Mediterranean coast of Spain and has been threatened with extinction as a result of habitat modification caused by urbanization, agriculture, and its popularity among aquarium hobbyists since the mid-twentieth century. It is also one of the first Reference Genome for Euro-Asian species within the globally distributed order Cyprinodontiformes. Additionally, this effort aims to enhance our comprehension of the species' evolutionary ecology and history, particularly its remarkable adaptations that enable it to thrive in diverse and constantly changing inland aquatic environments.

RESULTS

A hybrid assembly approach was employed, integrating PacBio long-read sequencing with Illumina short-read data. In addition to the assembly, an extensive functional annotation of the genome is provided by using AUGUSTUS, and two different approaches (InterProScan and Sma3s). The genome size (1.15 Gb) is consistent with that of the most closely related species, and its quality and completeness, as assessed with various methods, exceeded the suggested minimum thresholds, thus confirming the robustness of the assembly. When conducting an orthology analysis, it was observed that nearly all genes were grouped in orthogroups that included genes of genetically similar species. GO Term annotation revealed, among others, categories related with salinity regulation processes (ion transport, transmembrane transport, membrane related terms or calcium ion binding).

CONCLUSIONS

The integration of genomic data with predicted genes presents future research opportunities across multiple disciplines, such as physiology, reproduction, disease, and opens up new avenues for future studies in comparative genomic studies. Of particular interest is the investigation of genes potentially associated with salinity adaptation, as identified in this study. Overall, this study contributes to the growing database of Reference Genomes, provides valuable information that enhances the knowledge within the order Cyprinodontiformes, and aids in improving the conservation status of threatened species by facilitating a better understanding of their behavior in nature and optimizing resource allocation towards their preservation.

Novel insight of the SVP gene involved in pedicel length based on genomics analysis in cherry

KEY MESSAGE

PcSVP was identified based on Prunus conradinae genome and was further overexpressed in A. thaliana to comfirm it was a key factor in flower development, causing the pedicels elongation. Prunus conradinae is an endemic plant resource in China with high ornamental and economic values. To generate useful genomic resources for expanding insights into the evolutionary history of this important plant, the chromosome-level genome and organelle genomes of P. conradinae are de novo assembled and functionally annotated. The chromosome-level haploid genome of autotetraploid P. conradinae was assembled with 262.79 Mb with 27,802 protein-coding genes annotated. The complete chloroplast and mitochondrial genome of P. conradinae are found to be 157,715 bp and 434,334 bp, respectively. According to evolutionary analysis, P. conradinae was closely related to P. serrulata and P. yedoensis, and they diverged from their common ancestor approximately 6.0 million years ago. There were 108 gene families that significantly expanded during P. conradinae evolution and 56 shared positively selected genes. Selective sweep analysis based on the whole-genome resequencing of wild cherries from Fujian and Zhejiang indicated that genes involved in flower development and stress responses were potentially under selection. Pedicel length varied greatly among Prunus species and was a significant identifying characteristic. Ectopic overexpression of PcSVP in Arabidopsis thaliana suggested that it was a key factor in flower development, causing the sepals curling and pedicels elongation. These findings will contribute to the discovery of key functional genes involved in the agronomic or biological traits of P. conradinae, as well as the future development, utilisation and germplasm conservation of wild cherries.

The Society for Immunotherapy of Cancer Perspective on Tissue-Based Technologies for Immuno-Oncology Biomarker Discovery and Application

With immuno-oncology becoming the standard of care for a variety of cancers, identifying biomarkers that reliably classify patient response, resistance, or toxicity becomes the next critical barrier toward improving care. Multiparametric, multi-omics, and computational platforms generating an unprecedented depth of data are poised to usher in the discovery of increasingly robust biomarkers for enhanced patient selection and personalized treatment approaches. Deciding which developing technologies to implement in clinical settings ultimately, applied either alone or in combination, relies on weighing pros and cons, from minimizing patient sampling to maximizing data outputs, and assessing the reproducibility and representativeness of findings, while lessening data fragmentation toward harmonization. These factors are all assessed while taking into consideration the shortest turnaround time. The Society for Immunotherapy of Cancer Biomarkers Committee convened to identify important advances in biomarker technologies and to address advances in biomarker discovery using multiplexed IHC and immunofluorescence, their coupling to single-cell transcriptomics, along with mass spectrometry-based quantitative and spatially resolved proteomics imaging technologies. We summarize key metrics obtained, ease of interpretation, limitations and dependencies, technical improvements, and outward comparisons of these technologies. By highlighting the most interesting recent data contributed by these technologies and by providing ways to improve their outputs, we hope to guide correlative research directions and assist in their evolution toward becoming clinically useful in immuno-oncology.

Introducing "Identification Probability" for Automated and Transferable Assessment of Metabolite Identification Confidence in Metabolomics and Related Studies

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence─the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in the context of the chemical space being considered. Neither are they easily automated nor transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a database that matches an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multiproperty reference libraries constructed from a subset of the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

A Step-by-Step Guide to Sequencing and Assembly of Complete Bacterial Genomes Using the Oxford Nanopore MinION

The Oxford Nanopore (ONT) MinION enables sequencing of longer DNA/RNA fragments compared to other sequencers, such as Illumina, etc. This nanopore method provides distinct advantages for generating complete genome assemblies from microorganisms. Specifically, the R9.4 flow cells used for MinION sequencing have much lower error rates compared with earlier versions of the ONT platform. Coupled with base calling using Dorado software, higher-quality long reads can now be generated for complete bacterial genome assembly. In this chapter, we describe a detailed MinION method to assemble a complete genome from a microorganism, polish the final assembly, and evaluate the genome quality using various software tools. Because of the low cost for MinION sequencing, this platform could be an asset for virtually any laboratory interested in generating complete genomes from microorganisms.

Pangenome graphs and their applications in biodiversity genomics

Complete datasets of genetic variants are key to biodiversity genomic studies. Long-read sequencing technologies allow the routine assembly of highly contiguous, haplotype-resolved reference genomes. However, even when complete, reference genomes from a single individual may bias downstream analyses and fail to adequately represent genetic diversity within a population or species. Pangenome graphs assembled from aligned collections of high-quality genomes can overcome representation bias by integrating sequence information from multiple genomes from the same population, species or genus into a single reference. Here, we review the available tools and data structures to build, visualize and manipulate pangenome graphs while providing practical examples and discussing their applications in biodiversity and conservation genomics across the tree of life.

Decoding the Therapeutic Target SVEP1: Harnessing Molecular Trait GWASs to Unravel Mechanisms of Human Disease

Although human genetics has substantial potential to illuminate novel disease pathways and facilitate drug development, identifying causal variants and deciphering their mechanisms remain challenging. We believe these challenges can be addressed, in part, by creatively repurposing the results of molecular trait genome-wide association studies (GWASs). In this review, we introduce techniques related to molecular GWASs and unconventionally apply them to understanding SVEP1, a human coronary artery disease risk locus. Our analyses highlight SVEP1's causal link to cardiometabolic disease and glaucoma, as well as the surprising discovery of SVEP1 as the first known physiologic ligand for PEAR1, a critical receptor governing platelet reactivity. We further employ these techniques to dissect the interactions between SVEP1, PEAR1, and the Ang/Tie pathway, with therapeutic implications for a constellation of diseases. This review underscores the potential of molecular GWASs to guide drug discovery and unravel the complexities of human health and disease by demonstrating an integrative approach that grounds mechanistic research in human biology.

Enhancing Cellular and Enzymatic Properties Through In Vivo Continuous Evolution

Directed evolution seeks to evolve target genes at a rate far exceeding the natural mutation rate, thereby endowing cellular and enzymatic properties with desired traits. In vivo continuous directed evolution achieves these purposes by generating libraries within living cells, enabling a continuous cycle of mutant generation and selection, enhancing the exploration of gene variants. Continuous evolution has become powerful tools for unraveling evolution mechanism and improving cellular and enzymatic properties. This review categorizes current continuous evolution into three distinct classes: non-targeted chromosomal, targeted chromosomal, and extra-chromosomal hypermutation approaches. It also compares various continuous evolution strategies based on different principles, providing a reference for selecting suitable methods for specific evolutionary goals. Furthermore, this review discusses the two primary limitations for further widespread application of in vivo continuous evolution, which are lack of general applicability and insufficient mutagenic capability. We envision that developing generally applicable mutagenic components and methods to enhance mutation rates for in vivo continuous evolution are promising future directions for wide range applications of continuous evolution.

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.

Genetic structure, selective characterization and specific molecular identity cards of high-yielding Houdan chickens based on genome-wide SNP

The high-yielding Houdan chicken (GGF) is characterized by high egg production and disease resistance. This study conducted whole genome resequencing of the GGF population and compared it to data from other breeds. Genetic diversity analysis revealed higher observed heterozygosity (Ho), Polymorphism information content (PIC), number of runs of homozygosity (ROH), and inbreeding coefficient (FROH) in GGF. Linkage disequilibrium (LD) decay was slowest in GGF, indicating intensive inbreeding and strong selection. These findings suggest a need for appropriate strategies to enhance genetic diversity conservation in this breed. Population structure analysis demonstrated that GGF was genetically distinct from both the red jungle fowl (RJF) and Chinese indigenous chicken (CIC) populations, highlighting GGF as a unique genetic resource warranting intensive protection and utilization. Selective sweep analysis identified genes under selection in GGF, primarily enriched in signaling pathways related to oocyte meiosis and progesterone-mediated oocyte maturation. Key candidate genes included: CCNE1, SKP1, CDC20, CDK2, ADCY8, RPS6KA6, PPP3CB, PDE3B, HSP90AB1, and AKT3. These findings provide a theoretical foundation for their potential application in poultry breeding. Additionally, this study combined bioinformatics analysis with PCR amplification and Sanger sequencing to identify 4 SNPs that can serve as a molecular identity card (ID) for GGF: SNP1 (Chr2: 136130976), SNP3 (Chr4:11705164), SNP4 (Chr4: 63255588), and SNP5 (Chr24: 3271008). This study provides a scientific basis for effective management and conservation of GGF genetic resources, and establishes a simple, economical, and accurate set of molecular IDs to combat the proliferation of inferior breeds and protect genetic resources.

Haplotype-Based Approach Represents Locus Specificity in the Genomic Diversification Process in Humans (Homo sapiens)

BACKGROUND/OBJECTIVES

Recent progress in evolutionary genomics on human (Homo sapiens) populations has revealed complex demographic events and genomic changes. These include population expansion with complicated migration, substantial population structure, and ancient introgression from other hominins, as well as human characteristics selections. Nevertheless, the genomic regions in which such evolutionary events took place have remained unclear.

METHODS

Here, we focused on eight loci containing the haplotypes that were previously presented as atypical for the mutation pattern in sequence and/or geographic distribution pattern with the model of recent African origin, which constitute two major clusters: African only, and global. This was the consensus model before information regarding introgression from Neanderthal (Homo neanderthalensis) was available. We compared diversity in identical datasets of the modern human population genome, with the 1000 Genomes project among them.

RESULTS/CONCLUSIONS

This study identified representative genomic regions that show traces of various demographic events and genomic changes that modern humans have undergone by categorizing the relationships in sequence similarity and in worldwide geographic distribution among haplotypes.

Reaching New Heights in Genetic Code Manipulation with High Throughput Screening

The chemical and physical properties of proteins are limited by the 20 canonical amino acids. Genetic code manipulation allows for the incorporation of noncanonical amino acids (ncAAs) that enhance or alter protein functionality. This review explores advances in the three main strategies for introducing ncAAs into biosynthesized proteins, focusing on the role of high throughput screening in these advancements. The first section discusses engineering aminoacyl-tRNA synthetases (aaRSs) and tRNAs, emphasizing how novel selection methods improve characteristics including ncAA incorporation efficiency and selectivity. The second section examines high-throughput techniques for improving protein translation machinery, enabling accommodation of alternative genetic codes. This includes opportunities to enhance ncAA incorporation through engineering cellular components unrelated to translation. The final section highlights various discovery platforms for high-throughput screening of ncAA-containing proteins, showcasing innovative binding ligands and enzymes that are challenging to create with only canonical amino acids. These advances have led to promising drug leads and biocatalysts. Overall, the ability to discover unexpected functionalities through high-throughput methods significantly influences ncAA incorporation and its applications. Future innovations in experimental techniques, along with advancements in computational protein design and machine learning, are poised to further elevate this field.

Bridging Classical Methodologies in Salmonella Investigation with Modern Technologies: A Comprehensive Review

Advancements in genomics and machine learning have significantly enhanced the study of Salmonella epidemiology. Whole-genome sequencing has revolutionized bacterial genomics, allowing for detailed analysis of genetic variation and aiding in outbreak investigations and source tracking. Short-read sequencing technologies, such as those provided by Illumina, have been instrumental in generating draft genomes that facilitate serotyping and the detection of antimicrobial resistance. Long-read sequencing technologies, including those from Pacific Biosciences and Oxford Nanopore Technologies, offer the potential for more complete genome assemblies and better insights into genetic diversity. In addition to these sequencing approaches, machine learning techniques like decision trees and random forests provide powerful tools for pattern recognition and predictive modeling. Importantly, the study of bacteriophages, which interact with Salmonella, offers additional layers of understanding. Phages can impact Salmonella population dynamics and evolution, and their integration into Salmonella genomics research holds promise for novel insights into pathogen control and epidemiology. This review revisits the history of Salmonella and its pathogenesis and highlights the integration of these modern methodologies in advancing our understanding of Salmonella.

Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

Exploring the molecular aspect and updating evolutionary approaches to the DNA polymerase enzymes for biotechnological needs: A comprehensive review

DNA polymerases are essential enzymes that play a key role in living organisms, as they participate in the synthesis and maintenance of the DNA molecule. The intrinsic properties of these enzymes have been widely observed and studied to understand their functions, activities, and behavior, which has allowed their natural power in DNA synthesis to be exploited in modern biotechnology, to the point of making them true pillars of the field. In this context, the laboratory evolution of these enzymes, either by directed evolution or rational design, has led to the generation of a wide range of new DNA polymerases with novel properties, suitable for a variety of biotechnological needs. In this review, we examine DNA polymerases at the molecular level, their biotechnological use, and their evolutionary methods in relation to the novel properties sought, providing a chronological selection of evolved DNA polymerases cited in the literature that we consider to be of great interest. To our knowledge, this work is the first to bring together the molecular, functional and evolutionary aspects of the DNA polymerase enzyme. We believe it will be of great interest to researchers whose aim is to produce new lines of evolved DNA polymerases.

Advancement of Next-Generation DNA Sequencing through Ionic Blockade and Transverse Tunneling Current Methods

DNA sequencing is transforming the field of medical diagnostics and personalized medicine development by providing a pool of genetic information. Recent advancements have propelled solid-state material-based sequencing into the forefront as a promising next-generation sequencing (NGS) technology, offering amplification-free, cost-effective, and high-throughput DNA analysis. Consequently, a comprehensive framework for diverse sequencing methodologies and a cross-sectional understanding with meticulous documentation of the latest advancements is of timely need. This review explores a broad spectrum of progress and accomplishments in the field of DNA sequencing, focusing mainly on electrical detection methods. The review delves deep into both the theoretical and experimental demonstrations of the ionic blockade and transverse tunneling current methods across a broad range of device architectures, nanopore, nanogap, nanochannel, and hybrid/heterostructures. Additionally, various aspects of each architecture are explored along with their strengths and weaknesses, scrutinizing their potential applications for ultrafast DNA sequencing. Finally, an overview of existing challenges and future directions is provided to expedite the emergence of high-precision and ultrafast DNA sequencing with ionic and transverse current approaches.

Genome size and chromosome number are critical metrics for accurate genome assembly assessment in Eukaryota

The number of genome assemblies has rapidly increased in recent history, with NCBI databases reaching over 41,000 eukaryotic genome assemblies across about 2,300 species. Increases in read length and improvements in assembly algorithms have led to increased contiguity and larger genome assemblies. While this number of assemblies is impressive, only about a third of these assemblies have corresponding genome size estimations for their respective species on publicly available databases. In this paper, genome assemblies are assessed regarding their total size compared to their respective publicly available genome size estimations. These deviations in size are assessed related to genome size, kingdom, sequencing platform, and standard assembly metrics, such as N50 and BUSCO values. A large proportion of assemblies deviate from their estimated genome size by more than 10%, with increasing deviations in size with increased genome size, suggesting nonprotein coding and structural DNA may be to blame. Modest differences in performance of sequencing platforms are noted as well. While standard metrics of genome assessment are more likely to indicate an assembly approaching the estimated genome size, much of the variation in this deviation in size is not explained with these raw metrics. A new, proportional N50 metric is proposed, in which N50 values are made relative to the average chromosome size of each species. This new metric has a stronger relationship with complete genome assemblies and, due to its proportional nature, allows for a more direct comparison across assemblies for genomes with variation in sizes and architectures.

Sequence confirmation of synthetic DNA exceeding 100 nucleotides using restriction enzyme mediated digestion combined with high-resolution tandem mass spectrometry

Oligonucleotides have emerged as important therapeutic options for inherited diseases. In recent years, RNA therapeutics, especially mRNA, have been pushed to the market. Analytical methods for these molecules have been published extensively in the last few years. Notably, mass spectrometry has proven as a state-of-the-art quality control method. For RNA based therapeutics, numerous methods are available, while DNA therapeutics lack of suitable MS-based methods when it comes to molecules exceeding approximately 60 nucleotides. We present a method which combines the use of common restriction enzymes and short enzyme-directing oligonucleotides to generate DNA digestion products with the advantages of high-resolution tandem mass spectrometry. The instrumentation includes ion pair reverse phase chromatography coupled to a time-of-flight mass spectrometer with a collision induced dissociation (CID) for sequence analysis. Utilizing this approach, we increased the sequence coverage from 23.3% for a direct CID-MS/MS experiment of a 100 nucleotide DNA molecule to 100% sequence coverage using the restriction enzyme mediated approach presented in this work. This approach is suitable for research and development and quality control purposes in a regulated environment, which makes it a versatile tool for drug development.

Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

A practical introduction to holo-omics

Holo-omics refers to the joint study of non-targeted molecular data layers from host-microbiota systems or holobionts, which is increasingly employed to disentangle the complex interactions between the elements that compose them. We navigate through the generation, analysis, and integration of omics data, focusing on the commonalities and main differences to generate and analyze the various types of omics, with a special focus on optimizing data generation and integration. We advocate for careful generation and distillation of data, followed by independent exploration and analyses of the single omic layers to obtain a better understanding of the study system, before the integration of multiple omic layers in a final model is attempted. We highlight critical decision points to achieve this aim and flag the main challenges to address complex biological questions regarding the integrative study of host-microbiota relationships.

LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes

Despite the abundance of species with transcriptomic data, a significant number of species still lack sequenced genomes, making it difficult to study gene function and expression in these organisms. While de novo transcriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily selected or similar experimental conditions, which might fail to capture condition-specific transcripts. We developed the Large-Scale Transcriptome Assembly Pipeline for de novo assembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovo can (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses. LSTrAP-denovo is easy to implement, written in Python, and is freely available at https://github.com/pengkenlim/LSTrAP-denovo/.

Escherichia coli non-coding regulatory regions are highly conserved

Microbial genome sequences are rapidly accumulating, enabling large-scale studies of sequence variation. Existing studies primarily focus on coding regions to study amino acid substitution patterns in proteins. However, non-coding regulatory regions also play a distinct role in determining physiologic responses. To investigate intergenic sequence variation on a large-scale, we identified non-coding regulatory region alleles across 2350 Escherichia coli strains. This 'alleleome' consists of 117 781 unique alleles for 1169 reference regulatory regions (transcribing 1975 genes) at single base-pair resolution. We find that 64% of nucleotide positions are invariant, and variant positions vary in a median of just 0.6% of strains. Additionally, non-coding alleles are sufficient to recover E. coli phylogroups. We find that core promoter elements and transcription factor binding sites are significantly conserved, especially those located upstream of essential or highly-expressed genes. However, variability in conservation of transcription factor binding sites is significant both within and across regulons. Finally, we contrast mutations acquired during adaptive laboratory evolution with wild-type variation, finding that the former preferentially alter positions that the latter conserves. Overall, this analysis elucidates the wealth of information found in E. coli non-coding sequence variation and expands pangenomic studies to non-coding regulatory regions at single-nucleotide resolution.

Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals

Next-Generation Sequencing (NGS) techniques have revolutionized veterinary medicine for cats and dogs, offering insights across various domains. In veterinary parasitology, NGS enables comprehensive profiling of parasite populations, aiding in understanding transmission dynamics and drug resistance mechanisms. In infectious diseases, NGS facilitates rapid pathogen identification, characterization of virulence factors, and tracking of outbreaks. Moreover, NGS sheds light on metabolic processes by elucidating gene expression patterns and metabolic pathways, essential for diagnosing metabolic disorders and designing tailored treatments. In autoimmune diseases, NGS helps identify genetic predispositions and molecular mechanisms underlying immune dysregulation. Veterinary oncology benefits from NGS through personalized tumor profiling, mutation analysis, and identification of therapeutic targets, fostering precision medicine approaches. Additionally, NGS plays a pivotal role in veterinary genetics, unraveling the genetic basis of inherited diseases and facilitating breeding programs for healthier animals. Physiological investigations leverage NGS to explore complex biological systems, unraveling gene-environment interactions and molecular pathways governing health and disease. Application of NGS in treatment planning enhances precision and efficacy by enabling personalized therapeutic strategies tailored to individual animals and their diseases, ultimately advancing veterinary care for companion animals.

Comparative Genomics Unveils Functional Diversity, Pangenome Openness, and Underlying Biological Drivers among Bacillus subtilis Group

The Bacillus subtilis group (Bs group), with Bacillus subtilis as its core species, holds significant research and economic value in various fields, including science, industrial production, food, and pharmaceuticals. However, most studies have been confined to comparative genomics analyses and exploration within individual genomes at the level of species, with few conducted within groups across different species. This study focused on Bacillus subtilis, the model of Gram-positive bacteria, and 14 other species with significant research value, employing comparative pangenomics as well as population enrichment analysis to ascertain the functional enrichment and diversity. Through the quantification of pangenome openness, this work revealed the underlying biological drivers and significant correlation between pangenome openness and various factors, including the distribution of toxin-antitoxin- and integrase-related genes, as well as the number of endonucleases, recombinases, repair system-related genes, prophages, integrases, and transfer mobile elements. Furthermore, the functional enrichment results indicated the potential for secondary metabolite, probiotic, and antibiotic exploration in Bacillus licheniformis, Bacillus paralicheniformis, and Bacillus spizizenii, respectively. In general, this work systematically exposed the quantification of pangenome openness, biological drivers, the pivotal role of genomic instability factors, and mobile elements, providing targeted exploration guidance for the Bs group.

Genetic Characterization of Lumpy Skin Disease Viruses Circulating in Lesotho Cattle

Lumpy skin disease is one of the fast-spreading viral diseases of cattle and buffalo that can potentially cause severe economic impact. Lesotho experienced LSD for the first time in 1947 and episodes of outbreaks occurred throughout the decades. In this study, eighteen specimens were collected from LSD-clinically diseased cattle between 2020 and 2022 from Mafeteng, Leribe, Maseru, Berea, and Mohales' Hoek districts of Lesotho. A total of 11 DNA samples were analyzed by PCR and sequencing of the extracellular enveloped virus (EEV) glycoprotein, G-protein-coupled chemokine receptor (GPCR), 30 kDa RNA polymerase subunit (RPO30), and B22R genes. All nucleotide sequences of the above-mentioned genes confirmed that the PCR amplicons of clinical samples are truly LSDV, as they were identical to respective LSDV isolates on the NCBI GenBank. Two of the elevem samples were further characterized by whole-genome sequencing. The analysis, based on both CaPV marker genes and complete genome sequences, revealed that the LSDV isolates from Lesotho cluster with the NW-like LSDVs, which includes the commonly circulating LSDV field isolates from Africa, the Middle East, the Balkans, Turkey, and Eastern Europe.

Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score

BACKGROUND

The extent to which the relationships between clinical risk factors and coronary artery disease (CAD) are altered by CAD polygenic risk score (PRS) is not well understood. Here, we determine whether the interactions between clinical risk factors and CAD PRS further explain risk for incident CAD.

METHODS

Participants were of European ancestry from the UK Biobank without prevalent CAD. An externally trained genome-wide CAD PRS was generated and then applied. Clinical risk factors were ascertained at baseline. Cox proportional hazards models were fitted to examine the incident CAD effects of CAD PRS, risk factors, and their interactions. Next, the PRS and risk factors were stratified to investigate the attributable risk of clinical risk factors.

FINDINGS

A total of 357,144 individuals of European ancestry without prevalent CAD were included. During a median of 11.1 years of follow-up (interquartile range 10.4-14.1 years), CAD PRS was associated with 1.35-fold (95% confidence interval [CI] 1.332-1.368) risk per SD for incident CAD. The prognostic relevance of the following risk factors was relatively diminished for those with high CAD PRS on a continuous scale: type 2 diabetes (hazard ratio [HR]interaction 0.91, 95% CIinteraction 0.88-0.94), increased body mass index (HRinteraction 0.97, 95% CIinteraction 0.96-0.98), and increased C-reactive protein (HRinteraction 0.98, 95% CIinteraction 0.96-0.99). However, a high CAD PRS yielded joint risk increases with low-density lipoprotein cholesterol (HRinteraction 1.05, 95% CIinteraction 1.04-1.06) and total cholesterol (HRinteraction 1.05, 95% CIinteraction 1.03-1.06).

CONCLUSION

The CAD PRS is associated with incident CAD, and its application improves the prognostic relevance of several clinical risk factors.

FUNDING

P.N. (R01HL127564, R01HL151152, and U01HG011719) is supported by the National Institutes of Health.

Translating genomic advances into biodiversity conservation

A key action of the new Global Biodiversity Framework is the maintenance of genetic diversity in all species to safeguard their adaptive potential. To achieve this goal, a translational mindset, which aims to convert results of basic research into direct practical benefits, needs to be applied to biodiversity conservation. Despite much discussion on the value of genomics to conservation, a disconnect between those generating genomic resources and those applying it to biodiversity management remains. As global efforts to generate reference genomes for non-model species increase, investment into practical biodiversity applications is critically important. Applications such as understanding population and multispecies diversity and longitudinal monitoring need support alongside education for policymakers on integrating the data into evidence-based decisions. Without such investment, the opportunity to revolutionize global biodiversity conservation using genomics will not be fully realized.

The promise and pitfalls of synteny in phylogenomics

Reconstructing the tree of life remains a central goal in biology. Early methods, which relied on small numbers of morphological or genetic characters, often yielded conflicting evolutionary histories, undermining confidence in the results. Investigations based on phylogenomics, which use hundreds to thousands of loci for phylogenetic inquiry, have provided a clearer picture of life's history, but certain branches remain problematic. To resolve difficult nodes on the tree of life, 2 recent studies tested the utility of synteny, the conserved collinearity of orthologous genetic loci in 2 or more organisms, for phylogenetics. Synteny exhibits compelling phylogenomic potential while also raising new challenges. This Essay identifies and discusses specific opportunities and challenges that bear on the value of synteny data and other rare genomic changes for phylogenomic studies. Synteny-based analyses of highly contiguous genome assemblies mark a new chapter in the phylogenomic era and the quest to reconstruct the tree of life.

Detection accuracy and clinical applications of DP-TOF mass spectrometry

OBJECTIVE

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently used in clinical microbiology laboratories. This study aimed to determine whether dual-polarity time-of-flight mass spectrometry (DP-TOF MS) could be applied to clinical nucleotide detection.

METHODS

This prospective study included 40 healthy individuals and 110 patients diagnosed with cardiovascular diseases. We used DP-TOF MS and Sanger sequencing to evaluate 17 loci across 11 genes associated with cardiovascular drug responses. In addition, we used DP-TOF MS to test 998 retrospectively collected clinical DNA samples with known results.

RESULTS

A, T, and G nucleotide detection by DP-TOF MS and Sanger sequencing revealed 100% concordance, whereas the C nucleotide concordance was 99.86%. Genotyping based on the results of the two methods showed 99.96% concordance. Regarding clinical applications, DP-TOF MS yielded a 99.91% concordance rate for known loci. The minimum detection limit for DNA was 0.4 ng; the inter-assay and intra-assay precision rates were both 100%. Anti-interference analysis showed that aerosol contamination greater than 1013 copies/µL in the laboratory environment could influence the results of DP-TOF MS.

CONCLUSIONS

The DP-TOF MS platform displayed good detection performance, as demonstrated by its 99.96% concordance rate with Sanger sequencing. Thus, it may be applied to clinical nucleotide detection.

Genomic and phenotypic analyses reveal Paenibacillus polymyxa PJH16 is a potential biocontrol agent against cucumber fusarium wilt

In recent years, bacterial-based biocontrol agents (BCA) have become a new trend for the control of fungal diseases such as fusarium wilt that seriously threaten the yield and quality of cucumber, which are transmitted through infested soil and water. This study was set out with the aim of figuring the mechanism of the isolated rhizobacterial strain Paenibacillus polymyxa PJH16 in preventing Fusarium oxysporum f. sp. cucumerinum (Foc). Biocontrol and growth-promoting experiments revealed that bacterial strain causes effective inhibition of the fungal disease through a significant growth-promoting ability of plants, and had activities of β-1,3-glucanase, cellulase, amylase and protease. It could produce siderophore and indole-3-acetic acid, too. Using the high-throughput sequencing tool PacBio Sequel II system and the database annotation, the bacterial strain was identified as P. polymyxa PJH16 and contained genes encoding for presence of biofilm formation, antimicrobial peptides, siderophores and hydrolyases. From comparing data between the whole genome of P. polymyxa PJH16 with four closely related P. polymyxa strains, findings revealed markedly the subtle differences in their genome sequences and proposed new antifungal substances present in P. polymyxa PJH16. Therefore, P. polymyxa PJH16 could be utilized in bioengineering a microbial formulation for application as biocontrol agent and bio-stimulant, in the future.

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

Recent advances in plant translational genomics for crop improvement

The growing population, climate change, and limited agricultural resources put enormous pressure on agricultural systems. A plateau in crop yields is occurring and extreme weather events and urbanization threaten the livelihood of farmers. It is imperative that immediate attention is paid to addressing the increasing food demand, ensuring resilience against emerging threats, and meeting the demand for more nutritious, safer food. Under uncertain conditions, it is essential to expand genetic diversity and discover novel crop varieties or variations to develop higher and more stable yields. Genomics plays a significant role in developing abundant and nutrient-dense food crops. An alternative to traditional breeding approach, translational genomics is able to improve breeding programs in a more efficient and precise manner by translating genomic concepts into practical tools. Crop breeding based on genomics offers potential solutions to overcome the limitations of conventional breeding methods, including improved crop varieties that provide more nutritional value and are protected from biotic and abiotic stresses. Genetic markers, such as SNPs and ESTs, contribute to the discovery of QTLs controlling agronomic traits and stress tolerance. In order to meet the growing demand for food, there is a need to incorporate QTLs into breeding programs using marker-assisted selection/breeding and transgenic technologies. This chapter primarily focuses on the recent advances that are made in translational genomics for crop improvement and various omics techniques including transcriptomics, metagenomics, pangenomics, single cell omics etc. Numerous genome editing techniques including CRISPR Cas technology and their applications in crop improvement had been discussed.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

Wildlife endogenous retroviruses: colonization, consequences, and cooption

Endogenous retroviruses (ERVs) are inherited genomic remains of past germline retroviral infections. Research on human ERVs has focused on medical implications of their dysregulation on various diseases. However, recent studies incorporating wildlife are yielding remarkable perspectives on long-term retrovirus-host interactions. These initial forays into broader taxonomic analysis, including sequencing of multiple individuals per species, show the incredible plasticity and variation of ERVs within and among wildlife species. This demonstrates that stochastic processes govern much of the vertebrate genome. In this review, we elaborate on discoveries pertaining to wildlife ERV origins and evolution, genome colonization, and consequences for host biology.

De Novo Assembly of the Genome of the Sea Urchin Paracentrotus lividus (Lamarck 1816)

The Mediterranean purple sea urchin Paracentrotus lividus (Lamarck 1816) is a remarkable model system for molecular, evolutionary and cell biology studies, particularly in the field of developmental biology. We sequenced the genome, performed a de novo assembly, and analysed the assembly content. The genome of P. lividus was sequenced using Illumina NextSeq 500 System (Illumina) in a 2 × 150 paired-end format. More than 30,000 open reading frames (ORFs), (more than 8000 are unique), were identified and analysed to provide molecular tools accessible for the scientific community. In particular, several genes involved in complex innate immune responses, oxidative metabolism, signal transduction, and kinome, as well as genes regulating the membrane receptors, were identified in the P. lividus genome. In this way, the employment of the Mediterranean sea urchin for investigations and comparative analyses was empowered, leading to the explanation of cis-regulatory networks and their evolution in a key developmental model occupying an important evolutionary position with respect to vertebrates and humans.

Unraveling metagenomics through long-read sequencing: a comprehensive review

The study of microbial communities has undergone significant advancements, starting from the initial use of 16S rRNA sequencing to the adoption of shotgun metagenomics. However, a new era has emerged with the advent of long-read sequencing (LRS), which offers substantial improvements over its predecessor, short-read sequencing (SRS). LRS produces reads that are several kilobases long, enabling researchers to obtain more complete and contiguous genomic information, characterize structural variations, and study epigenetic modifications. The current leaders in LRS technologies are Pacific Biotechnologies (PacBio) and Oxford Nanopore Technologies (ONT), each offering a distinct set of advantages. This review covers the workflow of long-read metagenomics sequencing, including sample preparation (sample collection, sample extraction, and library preparation), sequencing, processing (quality control, assembly, and binning), and analysis (taxonomic annotation and functional annotation). Each section provides a concise outline of the key concept of the methodology, presenting the original concept as well as how it is challenged or modified in the context of LRS. Additionally, the section introduces a range of tools that are compatible with LRS and can be utilized to execute the LRS process. This review aims to present the workflow of metagenomics, highlight the transformative impact of LRS, and provide researchers with a selection of tools suitable for this task.

Recent insights into crosstalk between genetic parasites and their host genome

The bulk of higher order organismal genomes is comprised of transposable element (TE) copies, i.e. genetic parasites. The host-parasite relation is multi-faceted, varying across genomic region (genic versus intergenic), life-cycle stages, tissue-type and of course in health versus pathological state. The reach of functional genomics though, in investigating genotype-to-phenotype relations, has been limited when TEs are involved. The aim of this review is to highlight recent progress made in understanding how TE origin biochemical activity interacts with the central dogma stages of the host genome. Such interaction can also bring about modulation of the immune context and this could have important repercussions in disease state where immunity has a role to play. Thus, the review is to instigate ideas and action points around identifying evolutionary adaptations that the host genome and the genetic parasite have evolved and why they could be relevant.

ToxCodAn-Genome: an automated pipeline for toxin-gene annotation in genome assembly of venomous lineages

BACKGROUND

The rapid development of sequencing technologies resulted in a wide expansion of genomics studies using venomous lineages. This facilitated research focusing on understanding the evolution of adaptive traits and the search for novel compounds that can be applied in agriculture and medicine. However, the toxin annotation of genomes is a laborious and time-consuming task, and no consensus pipeline is currently available. No computational tool currently exists to address the challenges specific to toxin annotation and to ensure the reproducibility of the process.

RESULTS

Here, we present ToxCodAn-Genome, the first software designed to perform automated toxin annotation in genomes of venomous lineages. This pipeline was designed to retrieve the full-length coding sequences of toxins and to allow the detection of novel truncated paralogs and pseudogenes. We tested ToxCodAn-Genome using 12 genomes of venomous lineages and achieved high performance on recovering their current toxin annotations. This tool can be easily customized to allow improvements in the final toxin annotation set and can be expanded to virtually any venomous lineage. ToxCodAn-Genome is fast, allowing it to run on any personal computer, but it can also be executed in multicore mode, taking advantage of large high-performance servers. In addition, we provide a guide to direct future research in the venomics field to ensure a confident toxin annotation in the genome being studied. As a case study, we sequenced and annotated the toxin repertoire of Bothrops alternatus, which may facilitate future evolutionary and biomedical studies using vipers as models.

CONCLUSIONS

ToxCodAn-Genome is suitable to perform toxin annotation in the genome of venomous species and may help to improve the reproducibility of further studies. ToxCodAn-Genome and the guide are freely available at https://github.com/pedronachtigall/ToxCodAn-Genome.

How to make DNA data storage more applicable

The storage of digital data is becoming a worldwide problem. DNA has been recognized as a biological solution due to its ability to store genetic information without alteration over long periods. The first demonstrations of high-capacity long-lasting DNA digital data storage have been shown. However, high storage costs and slow retrieval of the data must be overcome to make DNA data storage more applicable and marketable. Herein, we discuss the issues and recent advances in DNA data storage methods and highlight pathways to make this technology more applicable to real-world digital data storage. We envision that a combination of molecular biology, nanotechnology, novel polymers, electronics, and automation with systematic development will allow DNA data storage sufficient for everyday use.

Whole-genome sequencing provides novel insights into the evolutionary history and genetic adaptation of reindeer populations in northern Eurasia

Domestic reindeer (Rangifer tarandus) play a vital role in the culture and livelihoods of indigenous people across northern Eurasia. These animals are well adapted to harsh environmental conditions, such as extreme cold, limited feed availability and long migration distances. Therefore, understanding the genomics of reindeer is crucial for improving their management, conservation and utilisation. In this study, we have generated a new genome assembly for the Fennoscandian domestic reindeer with high contiguity, making it the most complete reference genome for reindeer to date. The new genome assembly was utilised to explore genetic diversity, population structure and selective sweeps in Eurasian Rangifer tarandus populations which was based on the largest population genomic dataset for reindeer, encompassing 58 individuals from diverse populations. Phylogenetic analyses revealed distinct genetic clusters, with the Finnish wild forest reindeer (Rangifer tarandus fennicus) standing out as a unique subspecies. Divergence time estimates suggested a separation of ~ 52 thousand years ago (Kya) between the northern European Rangifer tarandus fennicus and Rangifer tarandus tarandus. Our study identified four main genetic clusters: Fennoscandian, the eastern/northern Russian and Alaskan group, the Finnish forest reindeer, and the Svalbard reindeer. Furthermore, two independent reindeer domestication processes were inferred, suggesting separate origins for the domestic Fennoscandian and eastern/northern Russian reindeer. Notably, shared genes under selection, including retroviral genes, point towards molecular domestication processes that aided adaptation of this species to diverse environments.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Current technical advancements in plant epitranscriptomic studies

The growth and development of plants are the result of the interplay between the internal developmental programming and plant-environment interactions. Gene expression regulations in plants are made up of multi-level networks. In the past few years, many studies were carried out on co- and post-transcriptional RNA modifications, which, together with the RNA community, are collectively known as the "epitranscriptome." The epitranscriptomic machineries were identified and their functional impacts characterized in a broad range of physiological processes in diverse plant species. There is mounting evidence to suggest that the epitranscriptome provides an additional layer in the gene regulatory network for plant development and stress responses. In the present review, we summarized the epitranscriptomic modifications found so far in plants, including chemical modifications, RNA editing, and transcript isoforms. The various approaches to RNA modification detection were described, with special emphasis on the recent development and application potential of third-generation sequencing. The roles of epitranscriptomic changes in gene regulation during plant-environment interactions were discussed in case studies. This review aims to highlight the importance of epitranscriptomics in the study of gene regulatory networks in plants and to encourage multi-omics investigations using the recent technical advancements.