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The yak (Bos grunniens), renowned for its adaptability to extreme cold and hypoxic conditions, stands as a remarkable domestic animal crucial for sustaining livelihoods in harsh climates. We conducted a comprehensive analysis of the whole genome sequence data from three distinct Indian yak populations: Arunachali yak (n = 10), Himachali yak (n = 10), and Ladakhi yak (n = 10). The genomic data for Indian yaks were meticulously generated by our laboratory and compared with their Chinese counterpart, the Jinchuan yak (n = 8), for a more nuanced understanding. Our investigation revealed a total of 37,437 runs of homozygosity (ROH) segments in 34 animals representing four distinct yak populations. The Jinchuan yak population exhibited the highest proportion, constituting 80.8 % of total ROHs, predominantly as small segments (<0.1 Mb), accounting for 63 % of the overall ROHs. Further analysis uncovered a significantly higher degree of inbreeding in Chinese yaks compared to their Indian counterparts. The Indian yak populations, in contrast, demonstrated relatively lower and consistent levels of inbreeding. Moreover, we identified ROH hotspots that covered at least 60 % of individuals in our study, indicating their pivotal role in environmental adaptation. A total of five hotspot regions were detected, housing genes such as ENSBGRG00000015023 (WNT2), YIPF4, SPAST, TLN2, and DSG4. These genes are associated with traits including hair follicle initiation, nutrient stress response, microtubule assembly, development of cardiac muscle, hair follicle, and coat color. This observation strongly suggests that there is substantial selection acting on these genes, emphasizing their important role in environmental adaptation among yak populations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Data irregularity in cancer genomics studies has been widely observed in the form of outliers and heavy-tailed distributions in the complex traits. In the past decade, robust variable selection methods have emerged as powerful alternatives to the nonrobust ones to identify important genes associated with heterogeneous disease traits and build superior predictive models. In this study, to keep the remarkable features of the quantile LASSO and fully Bayesian regularized quantile regression while overcoming their disadvantage in the analysis of high-dimensional genomics data, we propose the spike-and-slab quantile LASSO through a fully Bayesian spike-and-slab formulation under the robust likelihood by adopting the asymmetric Laplace distribution (ALD). The proposed robust method has inherited the prominent properties of selective shrinkage and self-adaptivity to the sparsity pattern from the spike-and-slab LASSO (Roc̆ková and George, J Am Stat Associat, 2018, 113(521): 431-444). Furthermore, the spike-and-slab quantile LASSO has a computational advantage to locate the posterior modes via soft-thresholding rule guided Expectation-Maximization (EM) steps in the coordinate descent framework, a phenomenon rarely observed for robust regularization with nondifferentiable loss functions. We have conducted comprehensive simulation studies with a variety of heavy-tailed errors in both homogeneous and heterogeneous model settings to demonstrate the superiority of the spike-and-slab quantile LASSO over its competing methods. The advantage of the proposed method has been further demonstrated in case studies of the lung adenocarcinomas (LUAD) and skin cutaneous melanoma (SKCM) data from The Cancer Genome Atlas (TCGA)., (© 2024 John Wiley & Sons Ltd.)

Chloroviruses exhibit a close relationship with their hosts with the phenotypic aspect of their ability to form lytic plaques having primarily guided the taxonomy. However, with the isolation of viruses that are only able to complete their replication cycle in one strain of Chlorella variabilis , systematic challenges emerged. In this study, we described the genomic features of 53 new chlorovirus isolates and used them to elucidate part of the evolutionary history and taxonomy of this clade. Our analysis revealed new chloroviruses with the largest genomes to date (>400 kbp) and indicated that four genomic features are statistically different in the viruses that only infect the Syngen 2-3 strain of C. variabilis (OSy viruses). We found large regions of dissimilarity in the genomes of viruses PBCV-1 and OSy-NE5 when compared with the other genomes. These regions contained genes related to the interaction with the host cell machinery and viral capsid proteins, which provided insights into the evolution of the replicative and structural modules in these giant viruses. Phylogenetic analysis using hallmark genes of Nucleocytoviricota revealed that OSy-viruses evolved from the NC64A-viruses, possibly emerging as a result of the strict relationship with their hosts. Merging phylogenetics and nucleotide identity analyses, we propose strategies to demarcate viral species, resulting in seven new species of chloroviruses. Collectively, our results show how genomic data can be used as lines of evidence to demarcate viral species. Using the chloroviruses as a case study, we expect that similar initiatives will emerge using the basis exhibited here.IMPORTANCEChloroviruses are a group of giant viruses with long dsDNA genomes that infect different species of Chlorella- like green algae. They are host-specific, and some isolates can only replicate within a single strain of Chlorella variabilis . The genomics of these viruses is still poorly explored, and the characterization of new isolates provides important data on their genetic diversity and evolution. In this work, we describe 53 new chlorovirus genomes, including many isolated from alkaline lakes for the first time. Through comparative genomics and molecular phylogeny, we provide evidence of genomic gigantism in chloroviruses and show that a subset of viruses became highly specific for their hosts at a particular point in evolutionary history. We propose criteria to demarcate species of chloroviruses, paving the way for an update in the taxonomy of other groups of viruses. This study is a new and important piece in the complex puzzle of giant algal viruses., Competing Interests: The authors declare no conflict of interest.

Under some conditions, dengue virus (DENV) can hijack IgG antibodies to facilitate its uptake into target cells expressing Fc gamma receptors (FcgR)-a process known as antibody-dependent enhancement (ADE) of infection. Beyond a requirement for FcgR, host dependency factors for this unusual IgG-mediated infection route remain unknown. To identify cellular factors exclusively required for ADE, here, we performed CRISPR knockout (KO) screens in an in vitro system poorly permissive to infection in the absence of IgG antibodies. Validating our approach, a top hit was FcgRIIa, which facilitates the binding and internalization of IgG-bound DENV but is not required for canonical infection. Additionally, we identified host factors with no previously described role in DENV infection, including TBC1D24 and SV2B, which have known functions in regulated secretion. Using genetic knockout and trans -complemented cells, we validated a functional requirement for these host factors in ADE assays performed with monoclonal antibodies and polyclonal sera in multiple cell lines and using all four DENV serotypes. We show that knockout of TBC1D24 or SV2B impaired the binding of IgG-DENV complexes to cells without affecting FcgRIIa expression levels. Thus, we identify cellular factors beyond FcgR that promote efficient ADE of DENV infection. Our findings represent a first step toward advancing fundamental knowledge behind the biology of a non-canonical infection route implicated in disease.IMPORTANCEAntibodies can paradoxically enhance rather than inhibit dengue virus (DENV) infection in some cases. To advance knowledge of the functional requirements of antibody-dependent enhancement (ADE) of infection beyond existing descriptive studies, we performed a genome-scale CRISPR knockout (KO) screen in an optimized in vitro system permissive to efficient DENV infection only in the presence of IgG. In addition to FcgRIIa, a known receptor that facilitates IgG-mediated uptake of IgG-bound, but not naked DENV particles, our screens identified TBC1D24 and SV2B, cellular factors with no known role in DENV infection. We validated a functional role for TBC1D24 and SV2B in mediating ADE of all four DENV serotypes in different cell lines and using various antibodies. Thus, we identify cellular factors beyond Fc gamma receptors that promote ADE mechanisms. This study represents a first step toward advancing fundamental knowledge beyond a poorly understood non-canonical viral entry mechanism., Competing Interests: The authors declare no conflict of interest.

Genomic surveillance enables the early detection of pathogen transmission in healthcare facilities and contributes to the reduction of substantial patient harm. Fast turnaround times, flexible multiplexing, and low capital requirements make Nanopore sequencing well suited for genomic surveillance purposes; the analysis of Nanopore data, however, can be challenging. We present NanoCore, a user-friendly method for Nanopore-based genomic surveillance in healthcare facilities, enabling the calculation and visualization of cgMLST-like (core-genome multilocus sequence typing) sample distances directly from unassembled Nanopore reads. NanoCore implements a mapping, variant calling, and multilevel filtering strategy and also supports the analysis of Illumina data. We validated NanoCore on two 24-isolate data sets of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE). In the Nanopore-only mode, NanoCore-based pairwise distances between closely related isolates were near-identical to Illumina-based SeqSphere + distances, a gold standard commercial method (average differences of 0.75 and 0.81 alleles for MRSA and VRE; sd = 0.98 and 1.00), and gave an identical clustering into closely related and non-closely related isolates. In the "hybrid" mode, in which only Nanopore data are used for some isolates and only Illumina data for others, increased average pairwise isolate distance differences were observed (average differences of 3.44 and 1.95 for MRSA and VRE, respectively; sd = 2.76 and 1.34), while clustering results remained identical. NanoCore is computationally efficient (<15 hours of wall time for the analysis of a 24-isolate data set on a workstation), available as free software, and supports installation via conda. In conclusion, NanoCore enables the effective use of the Nanopore technology for bacterial pathogen surveillance in healthcare facilities., Importance: Genomic surveillance involves sequencing the genomes and measuring the relatedness of bacteria from different patients or locations in the same healthcare facility, enabling an improved understanding of pathogen transmission pathways and the detection of "silent" outbreaks that would otherwise go undetected. It has become an indispensable tool for the detection and prevention of healthcare-associated infections and is routinely applied by many healthcare institutions. The earlier an outbreak or transmission chain is detected, the better; in this context, the Oxford Nanopore sequencing technology has important potential advantages over traditionally used short-read sequencing technologies, because it supports "real-time" data generation and the cost-effective "on demand" sequencing of small numbers of bacterial isolates. The analysis of Nanopore sequencing data, however, can be challenging. We present NanoCore, a user-friendly software for genomic surveillance that works directly based on Nanopore sequencing reads in FASTQ format, and demonstrate that its accuracy is equivalent to traditional gold standard short read-based analyses., Competing Interests: The authors declare no conflict of interest.

Quantifying the features of mitochondrial genome structural variation is crucial for understanding its contribution to complexity. Accurate quantification and interpretation of organizational diversity can help uncover biological evolutionary laws and patterns. The current qMGR approach accumulates the changes in two adjacent genes to calculate the rearrangement frequency RF of each single gene and the rearrangement score RS for specific taxa in the mitogenomes of a given taxonomic group. However, it may introduce bias, as it assigns scores to adjacent genes rather than to rearranged genes. To overcome this limitation, we propose a novel statistical method called qGO to quantify the diversity of gene organization. The qGO method, which is based on the homology of gene order, provides a more accurate representation of genome organizational diversity by partitioning gene strings and individually assigning weights to genes spanning different regions. Additionally, a comprehensive approach is employed for distance computation, generating an extensive matrix of rearrangement distances. Through experiments on more than 5500 vertebrate mitochondrial genomes, we demonstrated that the qGO method outperforms existing methods in terms of accuracy and interpretability. This method improves the comparability of genomes and allows a more accurate comparison of the diversity of mitochondrial genome organization across taxa. These findings have significant implications for unraveling genome evolution, exploring genome function, and investigating the process of molecular evolution., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

This study focuses on the genetic diversity and population structure of Prunus dulcis (almond tree), a crucial agricultural component with widespread cultivation and commercial importance, particularly in Iran, a region with a longstanding tradition of almond cultivation. The diverse almond collection in Iran encompasses many local varieties, breeding selections, rootstocks, and international cultivars. This diversity necessitates advanced genotyping techniques to gain insights into genetic diversity, population structure, and linkage disequilibrium (LD). In this paper, genotyping-by-sequencing (GBS) was employed to analyze 62 almond germplasm samples, identifying approximately 63,537 high-quality single nucleotide polymorphisms (SNPs) distributed across the eight chromosomes of the almond genome. On average, there were 30,225 SNPs per chromosome. The analysis yielded an average polymorphism information content (PIC) of 0.315 and an expected heterozygosity (He) rate of 0.28, indicating a significant level of genetic diversity within the studied almond germplasm. The LD analysis demonstrated a rapid decline, with an average LD decay spanning approximately 300 kb for an r 2 value of 0.2. This suggests substantial hybridization among the sampled almond varieties. Principal Component Analysis (PCA) and structure analysis could not differentiate genotypes based on geographical origin, providing further evidence of genetic mixing among the studied almond populations. An Analysis of Molecular Variance (AMOVA) highlighted significant genetic diversity within populations but revealed minimal differences. This comprehensive study of Iran's almond genotypes offers valuable insights for future breeding and conservation efforts, emphasizing this agriculturally significant species abundant genetic diversity and intricate population structure., Competing Interests: Declarations Ethics approval and consent to participate This article does not contain any research with human participants or animals performed by any of the authors. Consent for publication Not Applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary hepatic malignancy after hepatocellular carcinoma, with poor prognosis and limited treatment options. The genomic features of ICC in Chinese patients remain largely unknown. In this study, we perform deep whole-exome sequencing of 204 Chinese primary ICCs and characterize genomic alterations and clonal evolution, and reveal their associations with patient outcomes. We identify six mutational signatures, including Signatures A and F, which are highly similar to previously described signatures linked to aristolochic acid and aflatoxin exposures, respectively. We also identify 13 significantly mutated genes in the ICC samples, including SAV1. We find that SAV1 was mutated in 2.9% (20/672) of 672 ICC samples. SAV1 mutation is associated with lower SAV1 protein levels, higher rates of tumor recurrence, and shorter overall patient survival. Biofunctional investigations reveal a tumor-suppressor role of SAV1: its inactivation suppresses Hippo signaling, leading to YAP activation, thereby promoting tumor growth and metastasis. Collectively, our results delineate the genomic landscape of Chinese ICCs and identify SAV1 as a potential driver of ICC., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Key Message: Approaches for constructing training sets in genomic selection are proposed to efficiently identify top-performing genotypes from a breeding population. Identifying superior genotypes from a candidate population is a key objective in plant breeding programs. This study evaluates various methods for the training set optimization in genomic selection, with the goal of enhancing efficiency in discovering top-performing genotypes from a breeding population. Additionally, two approaches, inspired by classical optimal design criteria, are proposed to expand the search space for the best genotypes and compared with methods focusing on maximizing accuracy in breeding value prediction. Evaluation metrics such as normalized discounted cumulative gain, Spearman's rank correlation, and Pearson's correlation are employed to assess performance in both simulation studies and real trait analyses. Overall, for candidate populations lacking a strong subpopulation structure, a ridge regression-based method, referred to as MSPE Ridge , is recommended. For candidate populations with a strong subpopulation structure, a heuristic-based version of generalized coefficient of determination CD mean ( v 2 ) and a D-optimality-like method that maximizes overall genomic variation ( GV overall ) are preferred approaches for the primary objective of plant breeding. For populations with a large number of candidates, a proposed ranking method ( GV average ) can first be used to down-scale the candidate population, after which a heuristic-based method is employed to identify the best genotypes. Notably, the proposed CD mean ( v 2 ) has been verified to be equivalent to the original version, known as CD mean , but its implementation is much more computationally efficient., Competing Interests: Declarations Conflict of interest The authors declare that there is no conflict of interest., (© 2024. The Author(s).)

At the dawn of new millennium, policy makers and researchers focused on sustainable agricultural growth, aiming for food security and enhanced food quality. Several emerging scientific innovations hold the promise to meet the future challenges. Nanotechnology presents a promising avenue to tackle the diverse challenges in agriculture. By leveraging nanomaterials, including nano fertilizers, pesticides, and sensors, it provides targeted delivery methods, enhancing efficacy in both crop production and protection. This integration of nanotechnology with agriculture introduces innovations like disease diagnostics, improved nutrient uptake in plants, and advanced delivery systems for agrochemicals. These precision-based approaches not only optimize resource utilization but also reduce environmental impact, aligning well with sustainability objectives. Concurrently, genetic innovations, including genome editing and advanced breeding techniques, enable the development of crops with improved yield, resilience, and nutritional content. The emergence of precision gene-editing technologies, exemplified by CRISPR/Cas9, can transform the realm of genetic modification and enabled precise manipulation of plant genomes while avoiding the incorporation of external DNAs. Integration of nanotechnology and genetic innovations in agriculture presents a transformative approach. Leveraging nanoparticles for targeted genetic modifications, nanosensors for early plant health monitoring, and precision nanomaterials for controlled delivery of inputs offers a sustainable pathway towards enhanced crop productivity, resource efficiency, and food safety throughout the agricultural lifecycle. This comprehensive review outlines the pivotal role of nanotechnology in precision agriculture, emphasizing soil health improvement, stress resilience against biotic and abiotic factors, environmental sustainability, and genetic engineering., Competing Interests: Declarations Consent for publication Not applicable. Conflict of interest The authors declare no competing interests. Consent to participate Not applicable. Ethics approval Not applicable., (© 2024. The Author(s).)

Unveiling functional relationships between various molecular cell phenotypes from data using machine learning models is a key promise of multiomics. Existing methods either use flexible but hard-to-interpret models or simpler, misspecified models. VI-VS (Variational Inference for Variable Selection) balances flexibility and interpretability to identify relevant feature relationships in multiomic data. It uses deep generative models to identify conditionally dependent features, with false discovery rate control. VI-VS is available as an open-source Python package, providing a robust solution to identify features more likely representing genuine causal relationships., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests N.Y. is an advisor and/or has equity in Cellarity, Celsius Therapeutics, and Rheos Medicine., (© 2024. The Author(s).)

Artificial intelligence models have been increasingly used in the analysis of tumor histology to perform tasks ranging from routine classification to identification of molecular features. These approaches distill cancer histologic images into high-level features, which are used in predictions, but understanding the biologic meaning of such features remains challenging. We present and validate a custom generative adversarial network-HistoXGAN-capable of reconstructing representative histology using feature vectors produced by common feature extractors. We evaluate HistoXGAN across 29 cancer subtypes and demonstrate that reconstructed images retain information regarding tumor grade, histologic subtype, and gene expression patterns. We leverage HistoXGAN to illustrate the underlying histologic features for deep learning models for actionable mutations, identify model reliance on histologic batch effect in predictions, and demonstrate accurate reconstruction of tumor histology from radiographic imaging for a "virtual biopsy."

The global population surge demands increased food production and nutrient-rich options to combat rising food insecurity. Climate-resilient crops are vital, with millets emerging as superfoods due to nutritional richness and stress tolerance. Given limited genomic information, a comprehensive genetic resource is crucial to advance millet research. Whole-genome sequencing provides an unprecedented opportunity, and molecular genetic methodologies, particularly simple sequence repeats (SSRs), play a pivotal role in DNA fingerprinting, constructing linkage maps, and conducting population genetic studies. SSRs are composed of repetitive DNA sequences where one to six nucleotides are repeated in tandem and distributed throughout the genome. Different millet species exhibit genomic variations attributed to the presence of SSRs. While SSRs have been identified in a few millet species, the existing information only covers some of the sequenced genomes. Moreover, there is an absence of complete gene annotation and visualization features for SSRs. Addressing this disparity and leveraging the de-novo millet genome assembly available from the NCBI, we have developed the Genomic SSR Millets Database (GSMDB; https://bioinfo.icgeb.res.in/gsmdb/). This open-access repository provides a web-based tool offering search functionalities and comprehensive details on 6.747645 million SSRs mined from the genomic sequences of seven millet species. The database, featuring unrestricted public access and JBrowse visualization, is a pioneering resource for the research community dedicated to advancing millet cultivars and related species. GSMDB holds immense potential to support myriad studies, including genetic diversity assessments, genetic mapping, marker-assisted selection, and comparative population investigations aiming to facilitate the millet breeding programs geared toward ensuring global food security. Database URL: https://bioinfo.icgeb.res.in/gsmdb/., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Cephalanthera nanchuanica is a terrestrial orchid species and has been red listed as a second-grade protected plant due to its limited distributions in China. Initially classified within a monotypic genus Tangtsinia, this species was later reassigned to Cephalanthera based on morphological and molecular data. However, previous phylogenetic analyses of Cephalanthera using several segment sequences exhibited a low discriminatory power in delineating its relationships., Results: In this study, we characterized and comparatively analyzed the complete chloroplast (cp) genome of C. nanchuanica with those of six previously reported Cephalanthera species. Our findings revealed that the cp genome of C. nanchuanica had the typical quadripartite structure, with a size of 161,365 bp and a GC content of 37.27%. A total of 113 unique genes were annotated, among which nearly half of protein-encoding genes (RSCU > 1) showed a preference in codon usage. No structural rearrangements were observed among the cp genomes of Cephalanthera species, except for C. humilis, which displayed structural alterations due to gene loss, relocation, and inverted repeat (IR) expansion/contraction. The cp genomes of Cephalanthera species were highly conserved, with only a small number of SSRs detected, most of which preferred A/T bases. Comparative analysis of cp genomes indicated that IR and coding regions were less divergent than single copy and non-coding regions and eight mutational hotspots were identified. Phylogenetic analysis suggested that the tribe Neottieae was a monophyletic group, divided into five clades. Palmorchis was the earliest-diverging lineage, followed by Cephalanthera. Diplandrorchis was deeply nested within Neottia, forming a clade. Aphyllorchis and Limodorum formed another clade, sister to Epipactis. Within the Cephalanthera clade, C. nanchuanica was sister to C. falcata with a strong support., Conclusions: This study demonstrated that the cp genome characters of C. nanchuanica are highly similar to those of other Cephalanthera species, except for the mycoheterotrophic species C. humilis. Although the cp genomes of Cephalanthera species (excluding C. humilis) exhibited conservation in genome structure and sequence, SSR repeats and mutational hotspots were identified, which could potentially serve as as molecular markers for distinguishing Cephalanthera species. The phylogenetic analysis based on the protein-coding genes provided high-resolution support for the infrageneric classification. Therefore, cp genome data will be instrumental in resolving the phylogeny of the genus Cephalanthera., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background: Nematodes of the genus Steinernema and their Xenorhabdus bacterial symbionts are lethal entomopathogens that are useful in the biocontrol of insect pests, as sources of diverse natural products, and as research models for mutualism and parasitism. Xenorhabdus play a central role in all aspects of the Steinernema lifecycle, and a deeper understanding of their genomes therefore has the potential to spur advances in each of these applications., Results: Here, we report a comparative genomics analysis of Xenorhabdus griffiniae, including the symbiont of Steinernema hermaphroditum nematodes, for which genetic and genomic tools are being developed. We sequenced and assembled circularized genomes for three Xenorhabdus strains: HGB2511, ID10 and TH1. We then determined their relationships to other Xenorhabdus and delineated their species via phylogenomic analyses, concluding that HGB2511 and ID10 are Xenorhabdus griffiniae while TH1 is a novel species. These additions to the existing X. griffiniae landscape further allowed for the identification of two subspecies within the clade. Consistent with other Xenorhabdus, the analysed X. griffiniae genomes each encode a wide array of antimicrobials and virulence-related proteins. Comparative genomic analyses, including the creation of a pangenome, revealed that a large amount of the intraspecies variation in X. griffiniae is contained within the mobilome and attributable to prophage loci. In addition, CRISPR arrays, secondary metabolite potential and toxin genes all varied among strains within the X. griffiniae species., Conclusions: Our findings suggest that phage-related genes drive the genomic diversity in closely related Xenorhabdus symbionts, and that these may underlie some of the traits most associated with the lifestyle and survival of entomopathogenic nematodes and their bacteria: virulence and competition. This study establishes a broad knowledge base for further exploration of not only the relationships between X. griffiniae species and their nematode hosts but also the molecular mechanisms that underlie their entomopathogenic lifestyle., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Rectal neuroendocrine neoplasms (rNENs) are among the most frequent gastrointestinal neuroendocrine neoplasms and pose a serious challenge for clinical management. The size of the primary neoplasm is considered to be the most important predictor of disease progression, but the genetic alterations that occur during the progression of rNENs remain unknown. Here, we performed a comprehensive whole-exome sequencing study on 54 tumor-normal paired, formalin-fixed paraffin-embedded specimens from patients locally diagnosed with rNENs. Of these, 81.5% (n = 44) were classified as small-sized (≤2 cm) rNENs, while the remainder (18.5%, n = 10) were classified as large-sized (>2 cm) rNEN samples. Comparative analysis revealed marked disparities in the mutational landscape between small- and large-sized rNEN samples, and between large-sized rNEN samples with or without lymph node metastases. The high-confidence driver genes RHPN2, MUC16, and MUC4 were significantly mutated in both small- and large-sized rNEN specimens, whereas mutations in MAN2A1, and BAG2 were only identified in large-sized specimens diagnosed with lymph node metastases. Correspondingly, we observed that the mTOR and MAPK pathways were preferentially enriched in the large-sized rNEN specimens. Signature-based analysis revealed that mutational processes associated with defective DNA base excision repair (SBS30) significantly accumulated in large-sized rNEN samples with lymph node metastases, highlighting the important role of this mutagenic process in promoting rNEN progression. We further found that most rNEN subjects, regardless of tumor size, harbored at least one alteration with targeted therapeutic implications. Taken together, these results elucidate the genetic features associated with tumor size and lymphatic metastasis in rNEN patients, which will deepen our understanding of the genetic changes during rNEN progression and potentially directing improvements in rNEN treatment strategies., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Despite advancements in treating cutaneous melanoma, patients with acral and mucosal (A/M) melanomas still have limited therapeutic options and poor prognoses. We analyzed 156 melanomas (101 cutaneous, 28 acral, and 27 mucosal) using the Foundation One cancer-gene specific clinical testing platform and identified new, potentially targetable genomic alterations (GAs) in specific anatomic sites of A/M melanomas. Using novel pre-clinical models of A/M melanoma, we demonstrate that several GAs and corresponding oncogenic pathways associated with cutaneous melanomas are similarly targetable in A/M melanomas. Other alterations, including MYC and CRKL amplifications, were unique to A/M melanomas and susceptible to indirect targeting using the BRD4 inhibitor JQ1 or Src/ABL inhibitor dasatinib, respectively. We further identified new, actionable A/M-specific alterations, including an inactivating NF2 fusion in a mucosal melanoma responsive to dasatinib in vivo. Our study highlights new molecular differences between cutaneous and A/M melanomas, and across different anatomic sites within A/M, which may change clinical testing and treatment paradigms for these rare melanomas., (© 2024 UICC.)

As rice has no physiological capacity of fixing nitrogen in the soil, its production had always been reliant on the external application of nitrogen (N) to ensure enhanced productivity. In the light of improving nitrogen use efficiency (NUE) in rice, several advanced agronomic strategies have been proposed. However, the soared increase of the prices of N fertilizers and subsequent environmental downfalls caused by the excessive use of N fertilizers, reinforces the prerequisite adaptation of other sustainable, affordable, and globally acceptable strategies. An appropriate alternative approach would be to develop rice cultivars with better NUE. Conventional breeding techniques, however, have had only sporadic success in improving NUE, and hence, this paper proposes a new schema that employs the wholesome benefits of the recent advancements in omics technologies. The suggested approach promotes multidisciplinary research, since such cooperation enables the synthesis of many viewpoints, approaches, and data that result in a comprehensive understanding of NUE in rice. Such collaboration also encourages innovation that leads to developing rice varieties that use nitrogen more effectively, facilitate smart technology transfer, and promotes the adoption of NUE practices by farmers and stakeholders to minimize ecological impact and contribute to a sustainable agricultural future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Evidence has indicated that Enterococcus plays a vital role in non-alcoholic fatty liver disease (NAFLD) development. However, the microbial genetic basis and metabolic potential in the disease are yet unknown. We previously isolated a bacteria Enterococcus faecium B6 (E. faecium B6) from children with NAFLD for the first time. Here, we aim to systematically investigate the potential of strain B6 in lipogenic effects. The lipogenic effects of strain B6 were explored in vitro and in vivo. The genomic and functional characterizations were investigated by whole-genome sequencing and comparative genomic analysis. Moreover, the metabolite profiles were unraveled by an untargeted metabolomic analysis. We demonstrated that strain B6 could effectively induce lipogenic effects in the liver of mice. Strain B6 contained a circular chromosome and two circular plasmids and posed various functions. Compared to the other two probiotic strains of E. faecium, strain B6 exhibited unique functions in pathways of ABC transporters, phosphotransferase system, and amino sugar and nucleotide sugar metabolism. Moreover, strain B6 produced several metabolites, mainly enriched in the protein digestion and absorption pathway. The unique potential of strain B6 in lipogenic effects was probably associated with glycolysis, fatty acid synthesis, and glutamine and choline transport. This study pioneeringly revealed the metabolic characteristics and specific detrimental traits of strain B6. The findings provided new insights into the underlying mechanisms of E. faecium in lipogenic effects, and laid essential foundations for further understanding of E. faecium-related disease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Indigenous buffaloes, as the important livestock species contributing to economy of the country, are the lifeline of livelihood in Nepal. They are distributed across diverse geographical regions of the country and have adapted to various feeding, breeding, and management conditions. The larger group of these native buffalo breeds are present in narrow and stiff hilly terrains. Their dispersal indicates a possible environmental adaptation mechanism, which is crucial for the conservation of these breeds., Results: We utilized whole-genome sequencing (WGS) to investigate the genetic diversity, population structure, and selection signatures of Nepalese indigenous buffaloes. We compared 66 whole-genome sequences with 118 publicly available sequences from six river and five swamp buffalo breeds. Genomic diversity parameters indicated genetic variability level in the Nepalese buffaloes comparable to those of Indian breeds, and population genetic structure revealed distinct geography-mediated genetic differentiation among these breeds. We used locus-specific branch length analysis (LSBL) for genome-wide scan, which revealed a list of potentially selected genes in Lime and Parkote breeds that inhabit the hilly region. A gene ontology (GO) analysis discovered that many GO terms were associated with cardiac function regulation. Furthermore, complementary analyses of local selection signatures, tissue expression profiles, and haplotype differences identified candidate genes, including KCNE1, CSF1R, and PDGFRB, related to the regulation of cardiac and pulmonary functions., Conclusions: This study is a comprehensive WGS-based genetic analysis of the native Nepalese buffalo breeds. Our study suggested that the Nepalese "hilly" buffaloes, especially the Lime and Parkote breeds, have undergone some characteristic genetic changes and evolved increased cardiac and pulmonary function for their adaptation to the steep hilly terrains of the country., Competing Interests: Declarations Ethics approval and consent to participate The animal study protocol was approved by the Animal Welfare Committee of China Agricultural University (protocol code AW42303202-2-1, March 24, 2023). We obtained informed consent from each owner to use the animals in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Genomic prediction (GP) has been evaluated in durum wheat breeding programs for several years, but prediction accuracy (PA) remains insufficient for some traits. Recently, multivariate (MV) analysis has gained much attention due to its potential to significantly improve PA. In this study, PA was evaluated for several agronomic traits using a univariate (UV) model in durum wheat, subsequently, different multivariate genomic prediction models were performed to attempt to increase PA. The panel was phenotyped for 10 agronomic traits over two consecutive crop seasons and under two different field conditions: high nitrogen and well-watered (HNW), and low nitrogen and rainfed (LNR). Multivariate GP was implemented using two cross-validation (CV) schemes: MV-CV1, testing the model for each target trait using only the markers, and MV-CV2, testing the model for each target trait using additional phenotypic information. These two MV-CVs were applied in two different analyses: modelling the same trait under both HNW and LNR conditions, and modelling grain yield together with the five most genetically correlated traits. PA for all traits in HNW was higher than LNR for the same trait, except for the trait yellow index. Among all traits, PA ranged from 0.34 (NDVI in LNR) to 0.74 (test weight in HNW). In modelling the same traits in both HNW and LNR, MV-CV1 produced improvements in PA up to 12.45% (NDVI in LNR) compared to the univariate model. By contrast, MV-CV2 increased PA up to 56.72% (thousand kernel weight in LNR). The MV-CV1 scheme did not improve PA for grain yield when it was modelled with the five most genetically correlated traits, whereas MV-CV2 significantly improved PA by up to ~18%. This study demonstrated that increases in prediction accuracy for agronomic traits can be achieved by modelling the same traits in two different field conditions using MV-CV2. In addition, the effectiveness of MV-CV2 was established when grain yield was modelled with additional correlated traits., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

The human armpit microbiome is metabolically entangled with skin cell physiology. This "meta-organism" symbiotic mutualism results in sweat either with or without odor (osmidrosis), depending on host ABCC11 gene haplotypes. Apocrine metabolism produces odorless S-glutathione conjugate that is transferred by ABCC11 transporters into secretory vesicles, deglutamylated to S-Cys-Gly-3M3SH thiol, and exuded to skin surface. An anthropogenic clade of skin bacteria then takes up the thiol and bioconverts it to malodorous 3-methyl-3-sulfanylhexan-1-ol (3M3SH). We hypothesized a familial meta-organism association of human ABCC11 gene non-synonymous SNP rs17822931 interplaying with skin microbiome 3M3SH biosynthesis. Subjects were genotyped for ABCC11 SNPs, and their haplotypes were correlated with axilla microbiome DNA sequencing profiles and predicted metagenome functions. A multigeneration family pedigree revealed a Mendelian autosomal recessive pattern: the C allele of ABCC11 correlated with bacterial Cys-S-conjugate β-lyase (PatB) gene known for Staphylococcus hominis biosynthesis of 3M3SH from human precursor; PatB was rescinded in hosts with homozygous TT alleles encoding ABCC11 loss-of-function mutation. We posit that a C allele encoding functional ABCC11 is key to delivering host conjugate precursors that shape heritable skin niche conditions favorable to harboring Staphylococcus having genomics of odor thiol production. This provides existential insights into human evolution and global regional population ancestries., Competing Interests: Declarations Competing interests The authors declare no competing interests. Ethics declaration of IRB approval for human subjects The project protocol was approved as a non‑intervention observational study of samples obtained from human subjects by the Institutional Review Board of the University of Florida, in accordance with the guidelines and regulations of the Declaration of Helsinki. Signed informed consent to participate and consent to publish deidentified data was obtained from all subjects., (© 2024. The Author(s).)

Background: Recently, there has been a growing interest in combining causal inference with machine learning algorithms. Double machine learning model (DML), as an implementation of this combination, has received widespread attention for their expertise in estimating causal effects within high-dimensional complex data. However, the DML model is sensitive to the presence of outliers and heavy-tailed noise in the outcome variable. In this paper, we propose the robust double machine learning (RDML) model to achieve a robust estimation of causal effects when the distribution of the outcome is contaminated by outliers or exhibits symmetrically heavy-tailed characteristics., Results: In the modelling of RDML model, we employed median machine learning algorithms to achieve robust predictions for the treatment and outcome variables. Subsequently, we established a median regression model for the prediction residuals. These two steps ensure robust causal effect estimation. Simulation study show that the RDML model is comparable to the existing DML model when the data follow normal distribution, while the RDML model has obvious superiority when the data follow mixed normal distribution and t-distribution, which is manifested by having a smaller RMSE. Meanwhile, we also apply the RDML model to the deoxyribonucleic acid methylation dataset from the Alzheimer's disease (AD) neuroimaging initiative database with the aim of investigating the impact of Cerebrospinal Fluid Amyloid β 42 (CSF A β 42) on AD severity., Conclusion: These findings illustrate that the RDML model is capable of robustly estimating causal effect, even when the outcome distribution is affected by outliers or displays symmetrically heavy-tailed properties., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests No Conflict of interest is declared., (© 2024. The Author(s).)

Surveillance is essential in the fight against antimicrobial resistance (AMR), to monitor the extent of resistance, inform prevention, control measures, and evaluate intervention progress. Traditional surveillance methods based on phenotypic antimicrobial susceptibility data offer important but limited insights into resistance mechanisms, transmission networks, and spread patterns of resistant bacterial strains. Fortunately, genomic technologies are increasingly accessible and can overcome these limitations. Genomics has the potential to advance traditional bacteriology in routine diagnosis and surveillance, it often relies on the initial isolation of bacterial strains from clinical specimens using conventional culture methods. Culture-based phenotypic characteristics are essential for making inferences about newly recognized genomic patterns. The Africa CDC Pathogen Genomics Initiative (Africa PGI) aims to enhance disease surveillance and public health partnerships through integrated, cross-continent laboratory networks equipped with the tools, human resource capacity and data infrastructure to fully leverage critical genomic sequencing technologies. For genomic surveillance of AMR, it is essential to optimize routine clinical microbiology laboratory services that are weak in many African countries. In this review, we outline shortcomings in clinical microbiology laboratories across Africa that compromise pathogen genomic epidemiology. We emphasize the necessity of investing in bacteriology and enhancing leadership capacity to fully capitalize on the advantages offered by genomic antimicrobial resistance (AMR) surveillance., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Pancreatic cancer exhibits a high degree of malignancy with a poor prognosis, lacking effective prognostic targets. Utilizing histopathological methodologies, this study endeavors to predict the expression of pathological features in pancreatic ductal adenocarcinoma (PAAD) and investigate their underlying molecular mechanisms. Pathological images, transcriptomic, and clinical data from TCGA-PAAD were collected for survival analysis. Image segmentation using unsupervised machine learning was employed to extract features, perform clustering, and establish models. The prognostic value of pathological features and associated clinical risk factors were evaluated; the correlation between pathological features and molecular mechanisms, gene mutations, and immune infiltration was analyzed. By clustering 45 effective pathological features, we divided PAAD patients into two groups: cluster 1 and cluster 2. Significant associations with poor prognosis were found for cluster 2 in both the training group (n = 113) and validation group (n = 75) (p = 0.006), with pathological stages II-IV identified as potential synergistic risk factors (HR = 2.421, 95% CI = 1.263-4.639, p = 0.008). Subsequently, through multi-omics correlation analysis, we further revealed a close association between cluster 2 and the oxidative phosphorylation mechanism. Within the cluster 2 group, 28 oxidative phosphorylation genes exhibited reduced expression, CDKN2A gene mutations were upregulated, and there was significant downregulation of Tregs infiltration and related immune gene expression. The pathomic model constructed using machine learning serves as a valuable prognostic target for PAAD. The histopathological features cluster 2 are closely associated with the downregulation of oxidative phosphorylation levels and Tregs immune infiltration., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Repeat expansions in the C9orf72 gene are the most common genetic cause of (ALS) and frontotemporal dementia (FTD). Like other genetic forms of neurodegeneration, pinpointing the precise mechanism(s) by which this mutation leads to neuronal death remains elusive, and this lack of knowledge hampers the development of therapy for C9orf72-related disease. We used an agnostic approach based on genomic data (n = 41,273 ALS and healthy samples, and n = 1,516 C9orf72 carriers) to overcome these bottlenecks. Our drug-repurposing screen, based on gene- and expression-pattern matching and information about the genetic variants influencing onset age among C9orf72 carriers, identified acamprosate, a γ-aminobutyric acid analog, as a potentially repurposable treatment for patients carrying C9orf72 repeat expansions. We validated its neuroprotective effect in cell models and showed comparable efficacy to riluzole, the current standard of care. Our work highlights the potential value of genomics in repurposing drugs in situations where the underlying pathomechanisms are inherently complex. VIDEO ABSTRACT., Competing Interests: Declaration of interests B.J.T. holds patents on clinical testing and therapeutic intervention for the hexanucleotide repeat expansion of C9orf72., (Published by Elsevier Inc.)

Mycobacteria is a diverse genus that includes both innocuous environmental species and serious pathogens like Mycobacterium tuberculosis, Mycobacterium leprae, and Mycobacterium ulcerans, the causative agents of tuberculosis, leprosy, and Buruli ulcer, respectively. This study focuses on Mycobacterium marinum, a closely related species known for its larger genome and ability to infect ectothermic species and cooler human extremities. Utilizing whole-genome sequencing, we conducted a comprehensive pan-genome analysis of 100 M. marinum strains, exploring genetic diversity and its impact on pathogenesis and host specificity. Our findings highlight significant genomic diversity, with clear distinctions in core, dispensable, and unique genes among the isolates. Phylogenetic analysis revealed a broad distribution of genetic lineages, challenging previous classifications into distinct clusters. Additionally, we examined the synteny and diversity of the virulence factor CpnT, noting a wide range of C-terminal domain variations across strains, which points to potential adaptations in pathogenic mechanisms. This study enhances our understanding of M. marinum's genomic architecture and its evolutionary relationship with other mycobacterial pathogens, providing insights that could inform disease control strategies for M. tuberculosis and other mycobacteria., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Precise regulation of gene expression is crucial to development. Enhancers, the core of gene regulation, determine the spatiotemporal pattern of gene transcription. Since many disease-associated mutations are characterized in enhancers, the research on enhancer will provide clues to precise medicine. Rapid advances in high-throughput sequencing technology facilitate the characterization of enhancers at genome wide, but understanding the functional mechanisms of enhancers remains challenging. Herein, we provide a panorama of enhancer characteristics, including epigenetic modifications, enhancer transcripts, and enhancer-promoter interaction patterns. Furthermore, we outline the applications of high-throughput sequencing technology and functional genomics methods in enhancer research. Finally, we discuss the role of enhancers in human disease and their potential as targets for disease prevention and treatment strategies., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background: The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and significant computational challenges. As the cost of next-generation sequencing (NGS) has decreased, the amount of genomic data has surged globally. However, the cost and complexity of the computational resources required continue to be substantial barriers to leveraging big data. A promising solution to these computational challenges is cloud computing, which provides researchers with the necessary CPUs, memory, storage, and software tools., Results: Here, we present Closha 2.0, a cloud computing service that offers a user-friendly platform for analyzing massive genomic datasets. Closha 2.0 is designed to provide a cloud-based environment that enables all genomic researchers, including those with limited or no programming experience, to easily analyze their genomic data. The new 2.0 version of Closha has more user-friendly features than the previous 1.0 version. Firstly, the workbench features a script editor that supports Python, R, and shell script programming, enabling users to write scripts and integrate them into their pipelines. This functionality is particularly useful for downstream analysis. Second, Closha 2.0 runs on containers, which execute each tool in an independent environment. This provides a stable environment and prevents dependency issues and version conflicts among tools. Additionally, users can execute each step of a pipeline individually, allowing them to test applications at each stage and adjust parameters to achieve the desired results. We also updated a high-speed data transmission tool called GBox that facilitates the rapid transfer of large datasets., Conclusions: The analysis pipelines on Closha 2.0 are reproducible, with all analysis parameters and inputs being permanently recorded. Closha 2.0 simplifies multi-step analysis with drag-and-drop functionality and provides a user-friendly interface for genomic scientists to obtain accurate results from NGS data. Closha 2.0 is freely available at https://www.kobic.re.kr/closha2 ., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background: Primary mitochondrial diseases (PMD) are one of the most common metabolic genetic disorders. They are due to pathogenic variants in the mitochondrial genome (mtDNA) or nuclear genome (nDNA) that impair mitochondrial function and/or structure. We hypothesize that there is overlap between PMD and other genetic diseases that are mimicking PMD. For this reason, we performed a retrospective cohort study., Methods: All individuals with suspected PMD that underwent molecular genetic and genomic investigations were included. Individuals were grouped for comparison: (1) individuals with mtDNA-PMD; (2) individuals with nDNA-PMD; (3) individuals with other genetic diseases mimicking PMD (non-PMD); (4) individuals without a confirmed genetic diagnosis., Results: 297 individuals fulfilled inclusion criteria. The diagnostic yield of molecular genetics and genomic investigations was 31.3%, including 37% for clinical exome sequencing and 15.8% for mitochondrial genome sequencing. We identified 71 individuals with PMD (mtDNA n = 41, nDNA n = 30) and 22 individuals with non-PMD. Adults had higher percentage of mtDNA-PMD compared to children (p-value = 0.00123). There is a statistically significant phenotypic difference between children and adults with PMD., Conclusion: We report a large cohort of individuals with PMD and the diagnostic yield of urine mitochondrial genome sequencing (16.1%). We think liver phenotype might be progressive and should be studied further in PMD. We showed a relationship between non-PMD genes and their indirect effects on mitochondrial machinery. Differentiation of PMD from non-PMD can be achieved using specific phenotypes as there was a statistically significant difference for muscular, cardiac, and ophthalmologic phenotypes, seizures, hearing loss, peripheral neuropathy in PMD group compared to non-PMD group., Competing Interests: Declarations Ethics approval and consent to participate The Research Ethics Office, Health Research Ethics Board, University of Alberta (Study ID: Pro00112487) approved this study. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests., (© 2024. The Author(s).)

Clinical biomedical applications of genomic technologies are extensive and provide possibilities to enhance healthcare covering the span of medical talents. Genome disorder prediction is an important issue in biomedical research. Genome disorders cause multivariate diseases such as cancer, dementia, diabetes, Leigh syndrome, etc. Existing machine and deep learning-based methods were introduced to forecast genome disorders. However, the genome prediction outcomes were not sufficient. To address this issue, propose a new method called Quadratic Feynman Polynomial Interpolated and Vector Nearest Centroid-based (QFPI-VNC) for acutely predicting the genome disorder with improved sensitivity and specificity. First, we utilized medical data about children from a public genomes dataset and applied it to Linear Quadratic and Feynman Kac Genome filtering to obtain computationally efficient filtered results. Next, the results are fed to the Concordance Correlated Polynomial Interpolation with the purpose of extracting genome wide data in an accurate manner. Finally, the features extracted are fused and fed to the Support Vector and Nearest Centroid model for genome disorder prediction. Experimental investigations of the proposed method employing the genome dataset confirm that the performance of the proposed method is prospective and in the scope of acceptance with relative to state-of-the-art methods in terms of convergence speed, recognition rate, sensitivity, and specificity. Results suggest that the QFPI-VNC method produces the best performance with a higher genome disease detection rate by 14%, accuracy by 11%, sensitivity by 14% specificity by 12%, and lesser convergence speed by 29% than compared to state-of-the-art methods., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. A "contamination episode" refers to one or more contamination events from a single source over a period of time. We examine clusters of sequenced clinical isolates of Salmonella , Escherichia coli , Campylobacter , and Listeria that differ by only a small number of mutations (SNPs) to identify features of the underlying contamination episodes. These analyses provide additional evidence that the youngest age groups have greater susceptibility to infection by Salmonella , E. coli , and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. A large fraction of the contamination episodes causing sickness appear to have a long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost 3 y. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. Salmonella infections in infants under 3 mo are predominantly acquired from the same contaminated food, pet food, or environmental sources as older individuals, rather than infant formula contaminated during production., Competing Interests: Competing interests statement:The authors declare no competing interest.

Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modeling of gene expression networks that involve large amounts of data. The amalgamation of data concerning DNA, RNA, and protein functions bears similarity to pharmacogenomics, a crucial aspect in crafting cancer therapeutics. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Broadening the exploration and utilization of functional genomics holds significant potential for advancing drug discovery and repurposing, particularly within the realm of oncology., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests., (© 2024. The Author(s).)

Background: Single-cell RNA sequencing experiments commonly use 10x Genomics (10x) kits due to their high-throughput capacity and standardized protocols. Recently, Parse Biosciences (Parse) introduced an alternative technology that uses multiple in-situ barcoding rounds within standard 96-well plates. Parse enables the analysis of more cells from multiple samples in a single run without the need for additional reagents or specialized microfluidics equipment. To evaluate the performance of both platforms, we conducted a benchmark study using biological and technical replicates of mouse thymus as a complex immune tissue., Results: We found that Parse detected nearly twice the number of genes compared to 10x, with each platform detecting a distinct set of genes. The comparison of multiplexed samples generated from 10x and Parse techniques showed 10x data to have lower technical variability and more precise annotation of biological states in the thymus compared to Parse., Conclusion: Our results provide a comprehensive comparison of the suitability of both single-cell platforms for immunological studies., Competing Interests: Declarations Ethics approval and consent to participate This study was conducted in accordance to the permission from the Ministry of Regional Affairs and Agriculture (Estonia) and approved by the Animal Experiments Ethics Committee at the Ministry (Protocol No. 224). All methods were performed in accordance with relevant guidelines and regulations. This study was carried out in compliance with the ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments). Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background: Compatibility between plant parasites and their hosts is genetically determined {Citation}both interacting organisms. For example, plants may carry resistance (R) genes or deploy chemical defences. Aphid saliva contains many proteins that are secreted into host tissues. Subsets of these proteins are predicted to act as effectors, either subverting or triggering host immunity. However, associating particular effectors with virulence or avirulence outcomes presents challenges due to the combinatorial complexity. Here we use defined aphid and host genetics to test for co-segregation of expressed aphid transcripts and proteins with virulent or avirulent phenotypes., Results: We compared virulent and avirulent pea aphid parental genotypes, and their bulk segregant F1 progeny on Medicago truncatula genotypes carrying or lacking the RAP1 (Resistance to Acyrthosiphon pisum 1) resistance quantitative trait locus. Differential gene expression analysis of whole body and head samples, in combination with proteomics of saliva and salivary glands, enabled us to pinpoint proteins associated with virulence or avirulence phenotypes. There was relatively little impact of host genotype, whereas large numbers of transcripts and proteins were differentially expressed between parental aphids, likely a reflection of their classification as divergent biotypes within the pea aphid species complex. Many fewer transcripts intersected with the equivalent differential expression patterns in the bulked F1 progeny, providing an effective filter for removing genomic background effects. Overall, there were more upregulated genes detected in the F1 avirulent dataset compared with the virulent one. Some genes were differentially expressed both in the transcriptome and in the proteome datasets, with aminopeptidase N proteins being the most frequent differentially expressed family. In addition, a substantial proportion (27%) of salivary proteins lack annotations, suggesting that many novel functions remain to be discovered., Conclusions: Especially when combined with tightly controlled genetics of both insect and host plant, multi-omics approaches are powerful tools for revealing and filtering candidate lists down to plausible genes for further functional analysis as putative aphid effectors., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

A wealth of high-throughput biological data, of which omics constitute a significant fraction, has been made publicly available in repositories over the past decades. These data come in various formats and cover a range of species and research areas providing insights into the complexities of biological systems; the public repositories hosting these data serve as multifaceted resources. The potentially greater value of these data lies in their secondary utilization as the deployment of data science and artificial intelligence in biology advances. Here, we critically evaluate challenges in secondary data use, focusing on omics data of human embryonic kidney cell lines available in public repositories. The emerging issues are obstacles faced by secondary data users across diverse domains as they concern platforms and repositories, which accept deposition of data irrespective of their species type. The evolving landscape of data-driven research in biology prompts re-evaluation of open access data curation and submission procedures to ensure that these challenges do not impede novel research opportunities through data exploitation. This paper aims to draw attention to widespread issues with data reporting and encourages data owners to meticulously curate submissions to maximize not only their immediate research impact but also the long-term legacy of datasets., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Non-typhoidal Salmonella (NTS) is one of the leading causes of foodborne outbreaks worldwide, especially in low- and middle-income countries such as Peru. To understand the dynamics of NTS serotypes circulating in the country, the whole genomes of 1122 NTS strains from 1998 to 2018 were analyzed using phylogenomic and comparative genomics tools. A total of 40 different Sequences Type (STs) were identified, the five most frequent being ST-32 (S. Infantis, 37.25%), ST-11 (S. Enteritidis, 23.8%), ST-19 (S. Typhimurium, 14.17%), ST-31 (S. Newport, 6.77%), and ST-413 (S. Mbandaka, 4.72%). Furthermore, the maximum likelihood phylogeny showed high clonality between strains from the same ST recovered from different isolation sources, as well as a variable recombination rate, when comparing each ST individually. Moreover, several virulence factors involved in adherence and invasion, as well as plasmids and prophages, are strongly associated with the most frequent STs, while multidrug resistance markers are mostly linked to ST-32. This work provides an overview of the main genomic characteristics linked to the high-frequency ST, which have undergone few genetic modifications over time, suggesting a high adaptation of these NTS circulating clones in Peru., (© 2024. The Author(s).)

Understanding the interplay between genetic drift, natural selection, gene flow, and demographic history in driving phenotypic and genomic differentiation of insular populations can help us gain insight into the speciation process. Comparing patterns across different insular taxa subjected to similar selective pressures upon colonizing oceanic islands provides the opportunity to study repeated evolution and identify shared patterns in their genomic landscapes of differentiation. We selected four species of passerine birds (Common Chaffinch Fringilla coelebs/canariensis, Red-billed Chough Pyrrhocorax pyrrhocorax, House Finch  Haemorhous mexicanus and Dark-eyed/island Junco Junco hyemalis/insularis) that have both mainland and insular populations. Changes in body size between island and mainland populations were consistent with the island rule. For each species, we sequenced whole genomes from mainland and insular individuals to infer their demographic history, characterize their genomic differentiation, and identify the factors shaping them. We estimated the relative (F st ) and absolute (d xy ) differentiation, nucleotide diversity (π), Tajima's D, gene density and recombination rate. We also searched for selective sweeps and chromosomal inversions along the genome. All species shared a marked reduction in effective population size (N e ) upon island colonization. We found diverse patterns of differentiated genomic regions relative to the genome average in all four species, suggesting the role of selection in island-mainland differentiation, yet the lack of congruence in the location of these regions indicates that each species evolved differently in insular environments. Our results suggest that the genomic mechanisms involved in the divergence upon island colonization-such as chromosomal inversions, and historical factors like recurrent selection-differ in each species, despite the highly conserved structure of avian genomes and the similar selective factors involved. These differences are likely influenced by factors such as genetic drift, the polygenic nature of fitness traits and the action of case-specific selective pressures., (© 2024. The Author(s).)

Objectives: Mint oil is used in various commercial applications world-wide. Mint oil is typically harvested from commercial clones of peppermint or spearmints. Spearmints are the product of a cross between two diploid species: Mentha longifolia (horse mint) and Mentha suaveolens (apple mint). Peppermints are the product of an additional hybridization step between spearmint and an octoploid Mentha aquatica (water mint). Here, we present a chromosome-scale assembly of the genome of a clone of M. suaveolens. Together with the previously assembled genome of M. longifolia, these assemblies are instrumental in addressing questions regarding the origins of spearmint and peppermint oil and the genomic composition of commercial spearmints, and to start elaborating strategies for mint cultivar improvement., Data Description: A Falcon assembly of the genome of M. suaveolens was generated from 103X coverage of PacBio long reads. Additional scaffolding was conducted by Dovetail Genomics, using a Chicago library, and a HiC library. The resulting assembly had an N50 of 44.7 Mb, and 98.45% of the 536 Mb of the assembly were contained within 12 large superscaffolds. Finally, a genetic map was applied to correct persistent misjoins. Illumina RNA-Seq libraries from a variety of tissues were used to annotate the genome., (© 2024. The Author(s).)

Background: In the context of pathogen surveillance, it is crucial to ensure interoperability and harmonized data. Several surveillance systems are designed to compare bacteria and identify outbreak clusters based on core genome MultiLocus Sequence Typing (cgMLST). Among the different approaches available to generate bacterial cgMLST, our research used an assembly-based approach (chewBBACA tool)., Methods: Simulations of short-read sequencing were conducted for 5 genomes of 27 pathogens of interest in animal, plant, and human health to evaluate the repeatability and reproducibility of cgMLST. Various quality parameters, such as read quality and depth of sequencing were applied, and several read simulations and genome assemblies were repeated using three tools: SPAdes, Unicycler and Shovill. In vitro sequencing were also used to evaluate assembly impact on cgMLST results, for six bacterial species: Bacillus thuringiensis, Listeria monocytogenes, Salmonella enterica, Staphylococcus aureus, Vibrio parahaemolyticus and Xylella fastidiosa., Results: The results highlighted variability in cgMLST, which not only related to the assembly tools, but also induced by the intrinsic composition of the genomes themselves. This variability observed in simulated sequencing was further validated with real data for six of the bacterial pathogens studied., Conclusion: This highlights that the intrinsic genome composition affects assembly and resulting cgMLST profiles, and that variability in bioinformatics tools can induce a bias in cgMLST profiles. In conclusion, we propose that the completeness of cgMLST schemes should be considered when clustering strains., (© 2024. The Author(s).)

Background: Xinglong buffalo, as an indigenous breed in Hainan province of China, possesses characteristics such as high humidity tolerance, disease resistance and high reproductive capacity. Combined with whole genome sequencing technology, comprehensive investigation can be undertaken to elucidate the genomic characteristics, functions and genetic variation of Xinglong buffalo population., Results: Xinglong buffalo has the highest genetic diversity, lowest runs of homozygosity average length, and fasted decay of linkage disequilibrium in our study population. Phylogenetic tree results revealed that Xinglong buffalo was gathered together with Fuzhong buffalo firstly. The population genetic structure analysis indicates that at K = 3, the Xinglong buffalo for the first time showed a distinct ancestral origin from other water buffalo. Furthermore, compared to different populations, candidate genes displaying significantly distinct patterns of single nucleotide polymorphisms (SNPs) (e.g., RYR2, COX15, PCDH9, DTWD2, FCRL5) distribution have been identified in the Xinglong buffalo., Conclusions: Based on the whole genome sequencing data, this study identified a substantial number of SNPs and assessed the genetic diversity and selection signatures within the Xinglong buffalo population. These results contribute to understanding the genomic characteristics of Xinglong buffalo and their genetic evolutionary status. However, the practical significance of these signatures for genetic enhancement still requires confirmation through additional samples and further experimental validation., (© 2024. The Author(s).)

Background: The Nakaseomyces clade is formed by at least nine described species among which three can be pathogenic to humans, namely Nakaseomyces glabratus (Candida glabrata), the second most-common cause of candidiasis worldwide, and two rarer emerging pathogens: Nakaseomyces (Candida) nivarensis and Nakaseomyces (Candida) bracarensis. Early comparative genomics analyses identified parallel expansions of subtelomeric adhesin genes in N. glabratus and N. nivarensis/bracarensis, and suggested possible links with the emergence of the virulence potential in these species. However, as shown for N. glabratus, the proper assessment of subtelomeric genes is hindered by the use of incomplete assemblies and reliance on a single isolate., Results: Here we sequenced seven N. bracarensis isolates and reconstructed chromosome level assemblies of two divergent strains. We show that N. bracarensis isolates belong to two diverging clades that have slightly different genomic structures. We identified the set of encoded adhesins in the two complete assemblies, and uncovered the presence of a novel adhesin motif, found mainly in N. bracarensis. Our analysis revealed a larger adhesin content in N. bracarensis than previously reported, and similar in size to that of N. glabratus. We confirm the independent adhesin expansion in these two species, which could relate to their different levels of virulence., Conclusion: N. bracarensis clinical isolates belong to at least two differentiated clades. We describe a novel repeat motif found in N. bracarensis adhesins, which helps in their identification. Adhesins underwent independent expansions in N. glabratus and N. bracarensis, leading to repertoires that are qualitatively different but quantitatively similar. Given that adhesins are considered virulence factors, some of the observed differences could contribute to variations in virulence capabilities between N. glabratus and N. bracarensis., (© 2024. The Author(s).)

Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype-phenotype analysis. This shift has led to precise and efficient crop development through genomics-based approaches, including molecular markers, genomic selection, and genome editing. Molecular markers, such as SNPs, are crucial for identifying genomic regions linked to important traits, enhancing breeding accuracy and efficiency. Genomic resources viz. genetic markers, reference genomes, sequence and protein databases, transcriptomes, and gene expression profiles, are vital in plant breeding and aid in the identification of key traits, understanding genetic diversity, assist in genomic mapping, support marker-assisted selection and speeding up breeding programs. Advanced techniques like CRISPR/Cas9 allow precise gene modification, accelerating breeding processes. Key techniques like Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), and Genomic Selection (GS) enable precise trait selection and prediction of breeding outcomes, improving crop yield, disease resistance, and stress tolerance. These tools are handy for complex traits influenced by multiple genes and environmental factors. This paper explores new genomic technologies like molecular markers, genomic selection, and genome editing for plant breeding showcasing their impact on developing new plant varieties., (© 2024. The Author(s).)

Pathogenic constitutional APC variants underlie familial adenomatous polyposis, the most common hereditary gastrointestinal polyposis syndrome. To improve variant classification and resolve the interpretative challenges of variants of uncertain significance (VUSs), APC-specific variant classification criteria were developed by the ClinGen-InSiGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP) based on the criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). A streamlined algorithm using the APC-specific criteria was developed and applied to assess all APC variants in ClinVar and the International Society for Gastrointestinal Hereditary Tumours (InSiGHT) international reference APC Leiden Open Variation Database (LOVD) variant database, which included a total of 10,228 unique APC variants. Among the ClinVar and LOVD variants with an initial classification of (likely) benign or (likely) pathogenic, 94% and 96% remained in their original categories, respectively. In contrast, 41% ClinVar and 61% LOVD VUSs were reclassified into clinically meaningful classes, the vast majority as (likely) benign. The total number of VUSs was reduced by 37%. In 24 out of 37 (65%) promising APC variants that remained VUS despite evidence for pathogenicity, a data-mining-driven work-up allowed their reclassification as (likely) pathogenic. These results demonstrated that the application of APC-specific criteria substantially reduced the number of VUSs in ClinVar and LOVD. The study also demonstrated the feasibility of a systematic approach to variant classification in large datasets, which might serve as a generalizable model for other gene- or disease-specific variant interpretation initiatives. It also allowed for the prioritization of VUSs that will benefit from in-depth evidence collection. This subset of APC variants was approved by the VCEP and made publicly available through ClinVar and LOVD for widespread clinical use., Competing Interests: Declaration of interests S.E.P. is a member of the scientific advisory panel of Baylor Genetics Laboratories., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

The Haloferacaceae are a family of extremely halophilic archaea with many species producing enzymes and products beneficial for industrial biotechnology. They are, however, relatively under-characterised with regards to genetics and gene products. This study aims to use existing sequence data to highlight genetic diversity, create pangenomes for three genera, and provide secondary metabolite and pathway analysis. This will establish current knowledge and identify key gaps in research. We show that the Haloferacaceae have significant genetic diversity between genera, with numerous gene gain and loss events in key genera. It also found that the model genus, Haloferax, has relatively low identified secondary metabolites compared to other genera within the family. Additionally, this study has identified potential biotechnology targets for heterologous expression in model organisms., (© 2024. The Author(s).)

Genetically determined disorders are highly heterogenous in clinical presentation and underlying molecular mechanism. The evidence underpinning these conditions in the peer-reviewed literature requires robust critical evaluation for diagnostic use. Here, we present a structured curation process for Gene2Phenotype (G2P). This draws on multiple lines of clinical, bioinformatic and functional evidence. The process utilises and extends existing terminologies, allows for precise definition of the molecular basis of disease, and confidence levels to be attributed to a given gene-disease assertion. In-depth disease curation using this process will prove useful in applications including in diagnostics, research and development of targeted therapeutics. G2P: www.ebi.ac.uk/gene2phenotype ., (© 2024. The Author(s).)

Background: Although metabarcoding and metagenomic approaches have generated large datasets on worldwide phytoplankton species diversity, the intraspecific genetic diversity underlying the genetic adaptation of marine phytoplankton to specific environmental niches remains largely unexplored. This is mainly due to the lack of biological resources and tools for monitoring the dynamics of this diversity in space and time., Results: To gain insight into population diversity, a novel method based on INDEL markers was developed on Bathycoccus prasinos (Mamiellophyceae), an abundant and cosmopolitan species with strong seasonal patterns. Long read sequencing was first used to characterize structural variants among the genomes of six B. prasinos strains sampled from geographically distinct regions in the world ocean. Markers derived from identified insertions/deletions were validated by PCR then used to genotype 55 B. prasinos strains isolated during the winter bloom 2018-2019 in the bay of Banyuls-sur-Mer (Mediterranean Sea, France). This led to their classification into eight multi-loci genotypes and the sequencing of strains representative of local diversity, further improving the available genetic diversity of B. prasinos. Finally, selected markers were directly tracked on environmental DNA sampled during 3 successive blooms from 2018 to 2021, showcasing a fast and cost-effective approach to follow local population dynamics., Conclusions: This method, which involves (i) pre-identifying the genetic diversity of B. prasinos in environmental samples by PCR, (ii) isolating cells from selected environmental samples and (iii) identifying genotypes representative of B. prasinos diversity for sequencing, can be used to comprehensively describe the diversity and population dynamics not only in B. prasinos but also potentially in other generalist phytoplankton species., (© 2024. The Author(s).)

Key Message: Genetic gain in Nordic spring barley varieties was estimated to 1.07% per year. Additionally, genomic predictive ability for yield was 0.61 in a population of breeding lines. Barley is one of the most important crops in Europe and meeting the growing demand for food and feed requires continuous increase in yield. Genomic prediction (GP) has the potential to be a cost-efficient tool in breeding for complex traits; however, the rate of yield improvement in current barley varieties is unknown. This study therefore investigated historical and current genetic gains in spring barley and how accounting for row-type population stratification in a breeding population influences GP results. The genetic gain in yield was estimated using historical data from field trials from 2014 to 2022, with 22-60 market varieties grown yearly. The genetic gain was estimated to 1.07% per year for all varieties, serving as a reference point for future breeding progress. To analyse the potential of using GP in spring barley a population of 375 breeding lines of two-row and six-row barley were tested in multi-environment trials in 2019-2022. The genetic diversity of the row-types was examined and used as a factor in the predictions, and the potential to predict untested locations using yield data from other locations was explored. This resulted in an overall predictive ability of 0.61 for yield (kg/ha), with 0.57 and 0.19 for the separate two-row and the six-row breeding lines, respectively. Together this displays the potential of implementing GP in breeding programs and the genetic gain in spring barley market varieties developed through GP will help in quantifying the benefit of GP over conventional breeding in the future., (© 2024. The Author(s).)

The sugarcane aphid, Melanaphis sacchari, is an agricultural pest that causes damage to plants in the Poaceae (the grasses) family, such as sorghum and sugarcane. In this study, we used nanopore long reads and a high-throughput chromosome conformation capture chromatin interaction maps to generate a chromosome-level assembly with a total length of 356.1 Mb, of which 85.5% (304.6 Mb) is contained within the 3 autosomes and the X chromosome. Repetitive sequences accounted for 16.29% of the chromosomes, and a total of 12,530 protein-coding genes were annotated, achieving 95.8% Benchmarking Universal Single-Copy Ortholog gene completeness. This offered a substantial improvement compared with previous low-quality genomic resources. A phylogenomic analysis by comparing M. sacchari with 24 published aphid genomes representing 3 aphid tribes revealed that M. sacchari belonged to the tribe Aphidini and maintained a conserved chromosome structure with other Aphidini species. The high-quality genomic resources reported in this study are useful for understanding the evolution of aphid genomes and studying pest management of M. sacchari., Competing Interests: Conflicts of interest The author(s) declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)