SEARCH · Search bioRxiv

Results for “genomics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15Linked to original sources

bioRxiv2020

A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes. We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level. We show that these core regions are very likely to contain all or almost all essential genes. We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species. ImportanceThe pan-genome approach presented in this paper can be used to determine core regions of a genome and has many possible applications. Synthetic engineering design can be informed by which genes/regions are more conserved (core) versus less conserved. The level of conservation of adjacent non-core genes tends to define cassettes of genes which may be part of a pathway or system that can inform researchers about possible functional significance. The pattern of gene presence across the different genomes of a species can inform the understanding of evolution and horizontal gene acquisition. The approach saves considerable time and effort relative to laboratory methods used to identify essential genes in species.

evolutionary biology↗

bioRxiv2020

Comparative Genomic Analysis of Fifty-Two Staphylococcus aureus Isolates Identified from Uncharacterized Staphylococcus Genomes in the NCBI database

BackgroundStaphylococcus aureus is a major bacterial pathogen that causes a variety of diseases, ranging from wound infections to severe bacteremia or food poisoning. The course and severity of the disease are mainly dependent on the bacterium genotype as well as host factors. Whole-genome sequencing (WGS) is currently the most extensive genotyping method available, followed by bioinformatic sequence analysis. MethodsA total of 253 uncharacterized staphylococcus genome sequences were downloaded from the National Center for Biotechnology Information (NCBI) (August 2012 to March 2020) from different studies. Samples were clustered based on core and accessory pairwise distances between isolates and then analyzed by multilocus sequence typing tool (MLST). Staphylococcal Cassette Chromosome mec (SCCmec), spa typing, variant calling, core genome alignment, and recombination sites prediction were performed on detected S. aureus isolates. S. aureus isolates were also analyzed for the presence of genes coding for virulence factors and antibiotic resistance. Results and conclusionUncategorized genome sequences were clustered into 24 groups. About 182 uncharacterized Staphylococcus genomes were identified at the species level based on MLST, including 32 S. lugdunensis genome sequence, thus doubling the number of the publicly accessible S. lugdunensis genome sequence in Genbank. MLST identified another four species (S. epidermidis (33/253), S. lugdunensis (32/253), S. haemolyticus (41/253), S. hominis (24/253) and S. aureus (52/253)). Among the 52 S. aureus isolates, 21 (40.38%) isolates carried mecA gene, with 57.14% classified as SCCmec IV. The results of this study provide knowledge that facilitates evolutionary studies of staphylococcal species and other bacteria at the genome level.

microbiology↗

bioRxiv2021

Comparative genomic and pan-genomic characteristion of Staphylococcus epidermidis from different sources unveils the molecular basis and potential biomarkers of pathogenic strains

Coagulase-negative Staphylococcus (CoNS) is the most common pathogen causing traumatic endophthalmitis, Staphylococcus epidermidis is the most common species which colonizes human skin, eye surfaces and nasal cavity and is the main cause of nosocomial infection, specially foreign body-related bloodstream infections (FBR-BSIs). Although some studies have reported the genome characteristics of S. epidermidis, a comprehensive understanding of its pathogenicity and the genome of ocular trauma-sourced strains is still lacking. In this study, we sequenced, analyzed and reported the whole genomes of 11 ocular trauma-sourced samples of S. epidermidis that caused traumatic endophthalmitis. By integrating publicly available genomes, we obtained a total of 187 S. epidermidis samples from healthy and diseased eyes, skin, respiratory tract and blood. Combined with pangenome, phylogenetic and comparative genomic analyses, our study supported that S. epidermidis, regardless of niche source, exhibits two founder lineages with different pathogenicities. Moreover, we identified potential biomarkers associated with the virulence of S. epidermidis, namely, essD, uhpt, sdrF, sdrG, fbe and icaABCDR. The essD and uhpt genes have high homology with esaD and hpt in Staphylococcus aureus, showing that the genomes of S. epidermidis and S. aureus may have communicated during evolution, while the sdrF, sdrG, fbe, and icaABCDR genes are related to biofilm formation. Compared to S. epidermidis from blood sources, ocular-sourced strains causing intraocular infection had no direct relationship with biofilm formation. In conclusion, this study not only provided additional data resources for studies on S. epidermidisis, but also improved understanding of the evolution and pathogenicity of different source strains. ImportantsIn this study, we comprehensively analysied and reported the whole genome sequence (WGS) of the strains that caused traumatic endophthalmitis. Through comparative genomic analyses among 187 S. epidermidis samples from healthy and diseased eyes, skin, respiratory tract and blood, we identified 10 potential biomarkers of pathogenic strains. Finally, we revealed S. epidermidis-induced traumatic endophthalmitis may be independent of biofilm formation. Overall, our data may facilitate comparative research of S. epidermidis and provide clinical value for identifying pathogenic or contaminating strains.

microbiology↗

bioRxiv2021

Integrative Genome Modeling Platform reveals essentialityof rare contact events in 3D genome organizations

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional (3D) organization of genomes and key regulatory processes of genome function. However, it remains a major challenge to systematically integrate all available data sources to characterize the nuclear organization of genomes across different spatial scales. Here, we develop a multi-modal data integration approach to produce genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction, and spatial segregation of functionally related chromatin. By performing a quantitative assessment of the predictive power of genome structures generated from different data combinations, we demonstrate that multimodal data integration can compensate for systematic errors and missing values in some of the data and thus, greatly increases accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency inter-chromosomal contacts (e.g., "rare" contact events) to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multi-modal data integration for genome structure analysis, available through the Integrative Genome structure Modeling (IGM) software package that we introduce here.

biophysics↗

bioRxiv2021

Comprehensive comparative genomics analysis for the emerging human pathogen Streptococcus dysgalactiae subsp. equisimilis (SDSE): A case study and Pan-subspecies genomic analysis

BackgroundStreptococcus dysgalactiae subsp. equisimilis (SDSE) is the causal agent of various diseases that include wound infection, erysipelas, cellulitis, life-threatening necrotizing fasciitis, and streptococcal toxic shock syndrome. It is capable of infecting both humans and animals. In this investigation, we present a comprehensive genomic analysis for the SDSE strain SCDR1 that belongs to Lancefield group G, emm type (stG6) and (MLST) sequence type (ST44) that is the first time to be documented in Saudi Arabia and the middle east. Besides, we present the most comprehensive comparative genomics analysis for the emerging human pathogen SDSE. MethodologyWe utilized next-generation sequencing techniques (NGS), bioinformatics, phylogenetic analysis, and comparative pathogenomics to characterize SCDR1 and all publicly available SDES genomes. ResultsWe found that SCDR1 consisted of a circular genome of 2179136 bp. Comparative analyses among bacterial genomes indicated that SCDR1 was most closely related to AC-2713 and GGS_124. Genome annotation of SCDR-1 strain showed that it contains many genes with homology to known virulence factors, including genes involved in cellular invasion, Antiphagocytosis, immune evasion, invasion of skin and soft tissue, host mortality and tissue damage, toxins, pore-forming proteins, cytotoxins, beta-hemolysis agents. Two CRISPR arrays were identified in SCDR1 that are consist of 35 CRISPR repeats and 33 CRISPR spacers. Two CAS systems were observed in the SCDR-1 genome, namely, CAS-TypeIIA and CAS-TypeIC. SDSE core Resistome is consisting of 22 genes, including folA, gyrA, gyrB, and FabK. SDSE core Virulome consisting of 38 genes including, fba, fbp54, gidA, and lsp. ConclusionOur study confirmed that the SDSE strains possess different characteristics in producing virulence factors for pathogenicity to humans and based on its genome sequence and close relationship with GAS. Our study shed light on the proposed pathogenic mechanisms of SDSE and may form the basis of molecular epidemiological research on these highly virulent bacteria.

microbiology↗

bioRxiv2022

GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification

Whole genome sequencing of clinical bacterial isolates has the potential to transform the fields of medicine and public health, with particular impact on molecular epidemiology, infection control and assessing the spread of antibiotic resistance. To realize this potential, bioinformatic software needs to be developed that meets the quality standards of a diagnostic test to allow the reporting of identification results. Our research group has developed a methodology (GAMBIT: Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on whole genome sequence reads. GAMBIT incorporates this algorithm with a highly curated searchable database of genomes, which is a subset of the NCBI RefSeq assembly database. In this manuscript, we describe the validation of the scoring methodology, robustness to chosen parameters, establishment of confidence thresholds and the curation of the reference database. We discuss a validation set with GAMBIT deployed as a laboratory-developed test at the Alameda County Public Health Laboratory in Oakland, California. Three advancements were required to build upon existing k-mer based strategies to allow GAMBIT to possess the quality control parameters desired for its use as a diagnostic laboratory-developed test. Firstly, we innovated the data structure used to store the database of known bacterial genomes. This allowed us to store 48,224 bacterial genomes in a k-mer based database--a majority of the bacterial genomes in the NCBI RefSeq database at the time of development. Secondly, curation of the NCBI RefSeq database was required to remove ambiguous or potentially incorrectly labeled bacterial genomes to greatly increase confidence in positive matches. Lastly, we used this curated version of the NCBI RefSeq database and our scoring method to generate confidence thresholds for identification. Thus, the end-user does not rely simply on the closest match, but is informed whether that closest match exceeds a threshold for highly confident identification. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting.

bioinformatics↗

bioRxiv2022

Bipartite viral RNA genome heterodimerization influences genome packaging and virion thermostability

Diverse RNA-RNA interactions occur throughout the lifecycle of RNA viruses, including genome dimerization or multimerization through non-covalent association of two or more genomic segments. Both homo-dimerization of retrovirus genomic RNA and hetero-multimerization of genomic segments of multipartite viruses are recognized as important factors that govern genome packaging. The heterodimer of the bipartite alphanodaviruses represents a unique case as its formation is conserved among different virus species but is only observed within the context of fully assembled virus particles. In spite of this, the RNA sequences involved in heterodimerization are unknown. It also remains unclear whether the formation of this heterodimer might impact any stage of the virus lifecycle. In this study, we used Flock House virus (FHV) as a model system to uncover the nucleotide composition of the heterodimer and dissected the impact of heterodimer formation upon numerous stages of the virus lifecycle. We developed a novel Next-Generation Sequencing (NGS) approach called "XL-ClickSeq" to probe candidate heterodimer sequences. We found that the heterodimer is formed via intermolecular base-pairing and its formation is retained in defective virus particles. One heterodimer site was identified by thermodynamic prediction that, upon mutagenic disruption, exhibited significant deficiencies in genome packaging and encapsidation specificity to viral genomic RNA. Furthermore, we demonstrate that disruption of this RNA secondary structure directly impacts the thermostability of mature virus particles. These results demonstrated that the intermolecular RNA-RNA interactions within the encapsidated genome of an RNA virus can have an important impact on virus particle integrity and stability and thus its transmission to a new host.

molecular biology↗

bioRxiv2023

An imputed ancestral reference genome for the Mycobacterium tuberculosis complex better captures structural genomic diversity for reference-based alignment workflows

Reference-based alignment of short-reads is a widely used technique in genomic analysis of the Mycobacterium tuberculosis complex (MTBC) and the choice of reference sequence impacts the interpretation of analyses. The most widely used reference genomes include the ATCC type strain (H37Rv) and the putative MTBC ancestral sequence of Comas et al. both of which are based on a lineage 4 sequence. As such, these referents do not capture the complete structural variation now known to be present in the MTBC. To better represent the base of the MTBC, we generated an imputed ancestral genomic sequence, termed MTBC0 from reference-free alignments of closed MTBC genomes. When used as a reference sequence in alignment workflows, MTBC0 mapped more short sequencing reads and called more SNPs relative to the Comas et al. sequence while exhibiting minimal impact on the overall phylogeny of MTBC. The results also show that MTBC0 provides greater fidelity in capturing genomic variation and allows for the inclusion of regions absent in H37Rv such as the TbD1 and RvD4496/RD7/RD713 regions in standard MTBC workflows without additional steps. The use of MTBC0 as an ancestral reference sequence into a standard workflows modestly improved read mapping, SNP calling and intuitively facilitates the study of structural variation and evolution in MTBC. Data SummaryThe MTBC0 sequence, is available in the online data supplement in FASTA format at https://github.com/lukebharrison/MTBC0. Included with the MTBC0 sequence in the data supplement are: the reference-free alignment of MTBC closed genomes in hierarchical alignment (HAL) format, control files for cactus, annotations for H37Rv and L8, a BED file of regions excluded from SNP calls lifted over onto MTBC0, as well as the scripts used to call SNPs and the phylogenetic trees generated in this article. All previously published sequence data is available at the NCBI nucleotide and SRA databases, accession number for sequences used in this manuscript are available in Supplementary Tables 1 and 2. Impact StatementThis article describes an imputed ancestral genomic sequence (MTBC0) at the base of the MTBC for use as a reference sequence for Mycobacterium tuberculosis genomic workflows. Widely used reference sequences are limited to the structural diversity present in H37Rv, a lineage 4 isolate. MTBC0 obviates this limitation by incorporating the structural variation present at the base of the Mycobacterium tuberculosis complex (MTBC) by encompassing a wide sample of human and animal lineages including newly discovered lineages (L8, M. orygis). Use of MTBC0 enables the mapping of more reads and calling of more SNPs and allows for the investigation of structural variation not present in the current used reference sequences within this important group of animal and human pathogens.

microbiology↗

bioRxiv2023

Maternal H3.3-Mediated Paternal Genome Reprogramming Contributes to Minor Zygotic Genome Activation

In mice, zygotic genome activation (ZGA) is initiated at the late-one-cell stage, accompanied by an extensive incorporation of the histone variant H3.3 into the parental genomes. However, it is unclear how H3.3 engages in the onset of ZGA. Here, using the H3.3B-HA-tagged mouse model, we found that the paternal and maternal genomes are activated asynchronously. Paternally expressed H3.3 begins deposition on the zygotic genome at the early two-cell stage, whereas the deposition of maternally expressed H3.3 is delayed until the four-cell stage. Oocyte-stored maternal H3.3 (mH3.3) is crucial for cleavage development and minor ZGA. Deposition of mH3.3 on the paternal genome occurs globally during the protamine-to-histone transition but shows preferential enrichment at CpG-rich TSSs after the initial round of DNA replication. Depletion of mH3.3 can lead to a loss of H3K27ac, resulting in minor ZGA failure and early embryonic arrest. Mechanistically, mH3.3 deposition on the sperm genome removes repressive histone modifications, promotes the establishment of active histone modifications, and in turn enables the initiation of minor ZGA from the paternal genome. Our study highlights the pivotal role of mH3.3 in paternal genome reprogramming and minor ZGA initiation.

genetics↗

bioRxiv2024

Self-Authenticating Genomic Materials with Advanced Genome Signatures

The authenticity and integrity of synthetic genomic materials containing valuable intellectual property are essential for advancing scientific knowledge and enhancing biosafety. Existing DNA tags and watermarks, however, have limited efficacy due to low mutation tolerance and inadequate digital encoding capacity. Here, we present "Genome Signature", a biochemically stable and tamper-resistant DNA labeling system that enables the creation of self-authenticating genomes. Central to this system is a novel Golomb-ruler-derived Genome-Comb, which efficiently maps extensive nucleotide sequences onto limited codons within endogenous genes, significantly improving error correction and data encoding across millions of nucleotides. Our method successfully recorded a 4.5 million-nucleotide genome in living E. coli. The Genome Signature autonomously identifies and corrects mutations and effectively encodes data within codon orders, ensuring genome integrity and authenticity. Furthermore, it allows precise tracking of sequences across different cells, potentially revolutionizing the development of reliable genomic materials in synthetic biology.

synthetic biology↗

bioRxiv2024

Genome-wide mapping of EBV-induced genomic variationsidentifies the role of MUC19 in EBV latency

Epstein-Barr virus (EBV) infects over 95% of the worlds population and is tightly associated with multiple human malignant diseases. As the first discovered human oncovirus, EBV is known to induce genomic instability by promoting various types of genomic modifications in host chromosomes. However, the mechanisms through which EBV interacts with the host genome and regulates cellular gene expression in genomic modifications are not yet fully elucidated. In this study, we conducted primary EBV infection in B cells and performed the analyses of copy number variants using whole genome sequencing. After comparing to other distinct B cells with varying EBV infection backgrounds, we identified susceptible regions and unveiled critical host factors induced by EBV infection on chromosomes. Combined with the genome-wide transcriptomic analyses, we found that the mucin gene MUC19 is distinctively activated by EBV infection and MUC19 promotes oncogenesis through the activation of mTOR signaling in lymphoblastoid cell lines (LCLs). Further results indicate that EBV nuclear antigen 1 (EBNA1) binds to multiple regions within MUC19 and enhances the expression of MUC19. Moreover, sequence alignment has shown intriguing motif homology between the basic repeat unit of MUC19 and EBV genome, suggesting the potential of EBV-specific integration. To conclude, our study maps the genomic perturbations induced by EBV primary infection and offers new insights into the oncogenic roles of MUC19 during EBV latency.

microbiology↗

bioRxiv2025

Genomic Language Model for Predicting Enhancers and Their Allele-Specific Activity in the Human Genome

Predicting and deciphering the regulatory logic of enhancers is a challenging problem, due to the intricate sequence features and lack of consistent genetic or epigenetic signatures that can accurately discriminate enhancers from other genomic regions. Recent machine-learning based methods have spotlighted the importance of extracting nucleotide composition of enhancers but failed to learn the sequence context and perform suboptimally. Motivated by advances in genomic language models, we developed DNABERT-Enhancer, a novel enhancer prediction method, by applying DNABERT pre-trained language model on the human genome. We trained two different models, using large collection of enhancers curated from the ENCODE registry of candidate cis-Regulatory Elements. The best fine-tuned model achieved 88.05% accuracy with Matthews correlation coefficient of 76% on independent set aside data. Further, we present the analysis of the predicted enhancers for all chromosomes of the human genome by comparing with the enhancer regions reported in publicly available databases. Finally, we applied DNABERT-Enhancer along with other DNABERT based regulatory genomic region prediction models to predict candidate SNPs with allele-specific enhancer and transcription factor binding activity. The genome-wide enhancer annotations and candidate loss-of-function genetic variants predicted by DNABERT-Enhancer provide valuable resources for genome interpretation in functional and clinical genomics studies.

bioinformatics↗

bioRxiv2025

Genomic prediction of stalk lodging resistance and the associated intermediate phenotypes in maize using whole-genome resequence and multi-environmental data

Breeding for stalk lodging resistance is of paramount importance to maintain and improve maize yield and quality and meet increasing food demand. The integration of environmental, phenotypic, and genotypic information offers the opportunity to develop genomic prediction strategies that can improve the genetic gain for complex traits such as stalk lodging. However, implementation of genomic predictions for stalk lodging resistance has been sparse primarily due to the lack of reliable and reproducible phenotyping strategies. In this study, we measured 10 traits related to stalk lodging resistance obtained from a novel phenotyping platform on approximately 31,000 individual stalks. These traits were combined with environmental information and whole-genome resequence data to investigate the predictive ability of different single and multi-environment genomic prediction models. In total, 555 maize inbred lines from the Wisconsin diversity panel were evaluated in four environments. The multi-environment models more than doubled the prediction accuracy compared to the single-environment model for most traits, particularly when predicting lines in a sparse testing design. Predictive correlations for stalk bending strength and stalk flexural stiffness, a non-destructive method for assessment of stalk lodging resistance, were moderately high and ranged between 0.32 to 0.89 and 0.26 to 0.88, respectively. In contrast, rind thickness was the most difficult trait to predict. Our results show that the use of multi-environmental data could improve genomic prediction accuracy for stalk lodging resistance and its intermediate phenotypes. This study will serve as a first step toward genetic improvement and the development of maize varieties resistant to stalk lodging. Core IdeasO_LIThe DARLING platform was successfully used to collect lodging resistance-related phenotypes C_LIO_LIProportion of variation explained by genotype by environment interaction was not negligible C_LIO_LIGenomic predictions for lodging resistance phenotypes ranged from moderate to high C_LIO_LIAccounting for genotype by environment interaction was found to be important for improved predictive performance C_LI Plain language summaryStalk lodging - when maize stalks break or fall over before harvest - can seriously reduce crop yields. Breeding maize that resists lodging is important to ensure reliable food production. We tested about 31,000 individual stalks for 10 traits related to lodging resistance using a new phenotyping system. These traits were combined with environmental information and whole-genome resequence data to investigate the predictive ability of single and multi-environment genomic prediction models. By analyzing 555 maize lines, we found that using data from multiple environments improved genomic prediction accuracy by more than twice as much as using data from a single environment. Traits such as bending strength and flexural stiffness were easier to predict, while rind thickness was more difficult. These results show that combining genetic, environmental, and phenotypic data can help breeders more accurately select maize plants with stronger stalks, leading to better, more resilient crops.

genetics↗

bioRxiv2025

Horizontal transfer of a 180-kbp genomic fraction among the largest viral genomes

Viruses are generally considered tiny biological entities with small genomes; however, some dsDNA viruses, known as giant viruses, have large genomes that are comparable to those of small bacteria. Previous studies indicated that the genomes of giant viruses expanded from a small ancestor by a combination of gene duplication, de novo gene creation, and horizontal gene transfer (HGT). Among them, virus-to-virus HGTs are recently recognized as an important mechanism for disseminating functional genes between giant viruses. In this study, we isolated a giant virus of a member of pandoraviruses, which have the largest genome sizes reaching 2.5 Mbp. Based on the average nucleotide identity of known pandoraviruses, this new pandoravirus belongs to an existing viral species. However, its genome was approximately 200 kbp larger than those of the other strains from the same species. A genome-wide comparison identified a 180-kbp region with 168 genes missing from the other strains but found in phylogenetically distant pandoraviruses. The GC ratio and homology of the deduced amino acid sequences in this 180-kbp region suggest that the new virus horizontally acquired this region from a distantly related pandoravirus. The gene composition in the 180-kbp region further indicates that this region was already large at the time of the horizontal transfer. Our findings suggest that pandoraviruses can horizontally exchange a large portion of their genomes. This event presumably represents one mechanism for accelerating genomic evolution and gigantism in giant viruses.

microbiology↗

bioRxiv2025

A genome-scale CRISPR deletion screen in Chinese Hamster Ovary cells reveals essential regions of the coding and non-coding genome

The biopharmaceutical sector relies on CHO cells to investigate biological processes and as the preferred host for production of biotherapeutics. Simultaneously, advancements in CHO cell genome assembly have provided insights for developing sophisticated genetic engineering strategies. While the majority of these efforts have focused on coding genes, with some interest in transcribed non-coding RNAs (e.g., microRNAs and lncRNAs), there remains a lack of genome-wide systematic studies that precisely examine the remaining 90% of the genome. This unannotated "dark matter" includes regulatory elements and other, poorly understood or characterized functionality of the genome that may be potentially critical for cell survival. In this study, we deployed a genome-scale CRISPR screening platform with 112,272 paired guide RNAs targeting 14,034 genomic regions for complete deletion of 150 kb long sections. This platform enabled the execution of a negative screen that selectively identified dying cells to determine regions essential for cell survival. By using paired gRNAs, we overcame the intrinsic limitations of traditional frameshift strategies, which will likely have little or no effect on the non-coding genome. This study revealed 427 regions essential for CHO survival, many of which currently lack gene annotation or known function. For these regions we present annotation status, transcriptional activity as well as annotated chromatin states such as enhancers. Selected regions, specifically those that were negative for all the above, were individually deleted for confirmation. This work sheds a novel light on a substantial part of the mammalian genome which is traditionally difficult to investigate and therefore, neglected.

cell biology↗

bioRxiv2025

Genomic Touchstone: Benchmarking Genomic Language Models in the Context of the Central Dogma

The emergence of genomic language models (gLMs) has revolutionized the analysis of genomic sequences, enabling robust capture of biologically meaningful patterns from DNA sequences for an improved understanding of human genome-wide regulatory programs, variant pathogenicity and therapeutic discovery. Given that DNA serves as the foundational blueprint within the central dogma, the ultimate evaluation of a gLM is its ability to generalize across this entire biological cascade. However, existing evaluations lack this holistic and consistent framework, leaving researchers uncertain about which model best translates sequence understanding into downstream biological prediction. Here we present Genomic Touchstone, a comprehensive benchmark designed to evaluate gLMs across 36 diverse tasks and 88 datasets structured along the central dogmas modalities of DNA, RNA, and protein, encompassing 5.34 billion base pairs of genomic sequences. We evaluate 34 representative models encompassing transformers and convolutional neural networks, as well as emerging efficient architectures such as Hyena and Mamba. Our analysis yield four key insights. First, gLMs achieve comparable or superior performance on RNA and protein tasks compared to models pretrained on these molecules. Second, transformer-based models continue to lead in overall performance, yet efficient sequence models show promising task-specific capabilities and deserve further exploration. Third, the scaling behavior of gLMs remains incompletely understood. While longer input sequences and more diverse pretraining data consistently improve performance, increases in model size do not always translate into better results. Fourth, pretraining strategies, including the choice of training objectives and the composition of pretraining corpora, exert substantial influence on downstream generalization across different genomic contexts. Genomic Touchstone establishes a unified evaluation framework tailored to human genomics. By spanning multiple molecular modalities and biological tasks, it offers a valuable foundation for guiding future gLM design and understanding model generalizability in complex biological contexts.

bioinformatics↗

bioRxiv2018

A European whitefish linkage map and its implications for understanding genome-wide synteny between salmonids following whole genome duplication

Genomic datasets continue to increase in size and ease of production for a wider selection of species including non-model organisms. For many of these species highly contiguous and well-annotated genomes are unavailable due to their prohibitive complexity and cost. As a result, a common starting point for genomic work in non-model species is the production of a linkage map, which involves the grouping and relative ordering of genetic markers along the genome. Dense linkage maps facilitate the analysis of genomic data in a variety of ways, from broad scale observations regarding genome structure e.g. chromosome number and type or sex-related structural differences, to fine scale patterns e.g. recombination rate variation and co-localisation of differentiated regions. Here we present both a sex-averaged and sex-specific linkage maps for Coregonus sp. \"Albock\" containing 5395 single nucleotide polymorphism (SNP) loci across 40 linkage groups to facilitate future investigation into the genomic basis of whitefish adaptation and speciation. The map was produced using restriction-site associated digestion (RAD) sequencing data from two wild-caught parents and 156 F1 offspring in Lep-MAP3. We discuss the differences between our sex-avagerated and sex-specific maps and identify synteny between C. sp. \"Albock\" linkage groups and the Atlantic salmon (Salmo salar) genome. Our synteny analysis confirms that many patterns of homology observed between Atlantic salmon and Oncorhynchus and Salvelinus species are also shared by members of the Coregoninae subfamily.

evolutionary biology↗

bioRxiv2019

The soursop genome and comparative genomics of basalangiosperms provide new insights on evolutionaryincongruence

Deep relationships and the sequence of divergence among major lineages of angiosperms (magnoliids, monocots and eudicots) remain ambiguous and differ depending on analytical approaches and datasets used. Complete genomes potentially provide opportunities to resolve these uncertainties, but two recently published magnoliid genomes instead deliver further conflicting signals. To disentangle key angiosperm relationships, we report a high-quality draft genome for the soursop (Annona muricata, Annonaceae). We reconstructed phylogenomic trees and show that the soursop represents a genomic mosaic supporting different histories, with scaffolds almost exclusively supporting single topologies. However, coalescent methods and a majority of genes support magnoliids as sister to monocots and eudicots, where previous whole genome-based studies remained inconclusive. This result is clear and consistent with recent studies using plastomes. The soursop genome highlights the need for more early diverging angiosperm genomes and critical assessment of the suitability of such genomes for inferring evolutionary history.

evolutionary biology↗