Biology subjects

Buena-Atienza, E.

Publications and source records attributed to Buena-Atienza, E..

5 recordsLinked to original sources

bioRxiv2026

MethylBench: A comprehensive benchmark of DNA methylation profiling methods across diverse sequencing platforms

BackgroundDNA methylation can be profiled using multiple technologies that vary in resolution, coverage and cost. Prior benchmarking efforts have laid important groundwork, yet critical gaps remain. The SEQC2 EpiQC study[14] provided a multi-platform QC framework across whole-genome bisulfite sequencing (WGBS), oxidative bisulfite sequencing, enzymatic deamination, ONT and Illumina 850k arrays, showing high overall concordance but limited replication and no coverage of current enzymatic conversion, hybridization-based panels or modern long-read chemistries. More recently, Sigurpalsdottir et al.[40] systematically compared methylation detection tools within the long-read domain, demonstrating high ONT accuracy relative to oxidative bisulfite sequencing, but restricted their analysis to ONT and PacBio, excluding short-read, targeted-panel and array-based platforms as well as the biological interpretability of differential methylation across platform classes. A comprehensive cross-platform benchmark addressing coverage heterogeneity and annotation redundancy in the interpretation of differentially methylated cytosines thus remains absent. MethodsWe compared six widely used technologies - Illumina EPIC array, TWIST, Whole-Genome Enzymatic Conversion (WGEC), Reduced Representation Bisulfite Sequencing (RRBS), Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) - using GIAB reference samples and ten blood/fibroblast samples from 5 individuals. We assessed CpG coverage, consistency of differentially methylated cytosine (DMC) detection, and genomic annotation, with particular attention to overlapping signals across assays. ResultsDespite major assay differences, all technologies consistently identified DMCs enriched in promoter and intronic regions, marking these as robust hotspots of epigenetic variability. Annotation redundancy strongly shaped initial interpretations, with CpG island-related categories largely disappearing once annotations were collapsed to unique features. Sequencing-based methods (WGEC, TWIST, ONT) achieved the most comprehensive coverage, while EPIC arrays reliably captured promoter-associated differences despite limited scope. ONT showed strong concordance with short-read methods after coverage filtering, but required higher, more uniform coverage for reproducible CpG-level agreement. PacBio showed a coverage-independent discrepancy, with concordance plateauing regardless of mean coverage - pointing to residual technology-specific bias rather than a simple coverage effect. ConclusionsCross-platform benchmarking yields coherent biological insights once coverage and annotation redundancies are addressed. EPIC arrays remain valuable for promoter-focused cohort studies, WGEC and TWIST enable genome-wide discovery and ONT offers unique phasing and multimodal potential - together guiding method selection and more robust interpretation of DNA methylation data.

genomics↗

bioRxiv2025

Ultra-deep long-read metagenomics captures diverse taxonomic and biosynthetic potential of soil microbes

BackgroundSoil ecosystems have long been recognised as hotspots of microbial diversity, but most estimates of their microbial and functional complexity remain speculative despite decades of study, in part because conventional sequencing campaigns lack the depth and contiguity required to recover low-abundance and repetitive genomes. Here, we revisit this question using one of the deepest metagenomic sequencing efforts to date, applying 148 billion base pairs of Nanopore long-read and 122 billion base pairs of Illumina short-read data to a single forest soil sample. ResultsOur hybrid assembly reconstructed 837 metagenome-assembled genomes, including 466 that meet high- and medium-quality standards, nearly all lacking close relatives among cultivated taxa. Rarefaction and k-mer analyses reveal that, even at this depth, we capture only a fraction of the extant diversity: non-parametric models project that more than ten trillion base pairs of sequencing data would be required to approach saturation. These findings offer a quantitative, technology-enabled update to long-standing diversity estimates and demonstrate that conventional metagenomic sequencing efforts likely miss the majority of microbial and biosynthetic potential in soil. We further identify more than 11 000 biosynthetic gene clusters, over 99% of which have no match in current databases, underscoring the breadth of unexplored metabolic capacity. ConclusionsTaken together, our results emphasise both the power and the present limitations of metagenomics in resolving natural microbial complexity, and they provide a new baseline for evaluating future advances in microbial genome recovery, taxonomic classification, and natural product discovery. Data DescriptionIn order to quantify how much taxonomic and biosynthetic novelty present-day sequencing can recover from soil, we extracted high-molecular-weight DNA from a single Cambisol forest soil sample (Schonbuch, Germany) and generated an ultra-deep 270 Gbp dataset - 148 Gbp of Oxford Nanopore PromethION long reads (read-length N50 = 12.2 kb) plus 122 Gbp of Illumina NovaSeq reads. The hybrid metagenome assembly we conducted produced a 10.5 Gbp assembly, from which multi-tool binning and subsequent refinement recovered 837 MAGs, and antiSMASH/BiG-SCAPE annotation revealed more than 11 000 largely novel biosynthetic gene clusters, creating a resource for benchmarking assembly or binning pipelines, modelling diversity-coverage relationships and mining natural products; all raw reads are archived under ENA BioProject PRJEB89893 [1], and the polished assembly, MAG set and BGC catalogue are available via Zenodo for unrestricted reuse [2, 3]. Key PointsO_LIUltra-deep hybrid sequencing (148 Gbp Nanopore + 122 Gbp Illumina) of a single forest soil sample yielded 837 metagenome-assembled genomes, all lacking cultured counterparts. C_LIO_LIDespite this unprecedented 270 Gbp depth, rarefaction and coverage modelling indicate that more than 10 Tbp of data would still be needed to reach saturation in soil. C_LIO_LIOnly 0.7% and 16.7% of all assembled contigs can be assigned to a species and genus, respectively, with at least one cultured representative, highlighting an unprecedented level of novelty in soil. C_LIO_LIThe assembly uncovers 11 381 biosynthetic gene clusters forming over 10 000 mostly novel families, spotlighting an immense, untapped reservoir of microbial natural-product potential. C_LI

microbiology↗

bioRxiv2023

Reference genome of the ant Lasius platythorax

Ants are a highly diversified insect family of the order Hymenoptera, with many fascinating characteristics such as eusociality, chemical communication, farming, or social parasitism. Moreover, ants frequent a wide variety of habitats from dry deserts, grasslands, and savannas to cold temperate forests. The ability of ants to inhabit such diverse habitat ranges demonstrates their adaptability and ecological resilience. However, little is known about the genetic underpinnings of this vast array of traits and their adaptive potential. Here, we generated a high-quality genome assembly for the ant species Lasius platythorax using long-read PacBio HiFi in combination with chromatin conformation capture (Hi-C) sequencing. We successfully assembled the genome into 15 chromosome-level scaffolds ranging from 7.9 to 19.2 Mb and encompassing 204.6 Mb out of 235.3 Mb (total assembly), and a BUSCO score of 86% (Hymenoptera_odb10). Comparative genomics between the two sister species will provide insights into the genomic basis of trait differentiation.

genomics↗

bioRxiv2022

Comparative multi-OMICS single-cell atlas of five COVID-19 (rAdVV and mRNA) vaccines describe unique and distinct mechanisms of action

COVID-19 vaccines based on a range of expression platforms have shown considerable protective efficacy, generating antibody and T cell immune responses. However, molecular pathways underpinning COVID-19 vaccine priming of immunity against the SARS-CoV-2 virus have not yet been explored extensively. This analysis is critical to optimization of future vaccination strategies, schedules, and combinations. Thus, we investigated a cohort of individuals pre- and post-vaccination to understand the humoral and cellular immune response against different COVID-19 vaccines, including recombinant adenoviral vector (rAdVV) and mRNA-based vaccines. Single-cell RNA sequencing allowed characterization of monocytes, T, NK and B cell activation at the transcriptomics/proteomic level, in response to different COVID-19 vaccines. Our data revealed that different COVID-19 vaccines elicit a unique and distinct mechanism of action. Specifically, we revealed that rAdVV vaccines negatively regulate CD4+ T cell activation, leukocytes chemotaxis, IL-18 signalling and antigen presentation by monocytes whilst mRNA vaccines positively regulate NKT cell activation, platelets activation and chemokine signalling pathways. An antigen-specific T cell response was already observed following the 1st vaccine dose and was not further augmented after the subsequent 2nd dose of the same vaccine and it was dependent on the type of vaccination used. Our integrated three layered-analyses highlights that COVID-19 vaccines evoke a strong but divergent immune response at the RNA, protein, and cellular levels. Our approach is able to pinpoint efficacy and mechanisms controlling immunity to vaccination and open the door for better vaccination which could induce innate and adaptive immunity equally in the long term. Key findingsO_LIDecrease in major three cell types classical and non-classical monocytes and NK type III cells after COVID-19 vaccination C_LIO_LIIndividual vaccination (AZ, JJ, MD, PB) has differential effect on various immune cell subsets and regulates unique cell populations, whilst no change was observed for CV vaccination C_LIO_LIrAdVV and mRNA vaccines have different mechanism of action for activation of lymphocytes and monocytes, respectively C_LIO_LIrAdVV vaccines negatively regulates CD4+ T cell activation, leukocytes chemotaxis, IL-18 signalling and antigen presentation whilst mRNA vaccines positively regulate NKT cell activation, platelets activation and chemokine signalling pathways. C_LIO_LIAn antigen-specific T cell response was prompted after the 1st vaccine dose and not augmented after the subsequent 2nd dose of the same vaccine. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/507666v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@11fd7eborg.highwire.dtl.DTLVardef@198a9c7org.highwire.dtl.DTLVardef@1b28735org.highwire.dtl.DTLVardef@1cadbb5_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2019

Wengan: Efficient and high quality hybrid de novo assembly of human genomes

The continuous improvement of long-read sequencing technologies along with the development of ad-doc algorithms has launched a new de novo assembly era that promises high-quality genomes. However, it has proven difficult to use only long reads to generate accurate genome assemblies of large, repeat-rich human genomes. To date, most of the human genomes assembled from long error-prone reads add accurate short reads to further polish the consensus quality. Here, we report the development of a novel algorithm for hybrid assembly, WO_SCPCAPENGANC_SCPCAP, and the de novo assembly of four human genomes using a combination of sequencing data generated on ONT PromethION, PacBio Sequel, Illumina and MGI technology. WO_SCPCAPENGANC_SCPCAP implements efficient algorithms that exploit the sequence information of short and long reads to tackle assembly contiguity as well as consensus quality. The resulting genome assemblies have high contiguity (contig NG50:16.67-62.06 Mb), few assembly errors (contig NGA50:10.9-45.91 Mb), good consensus quality (QV:27.79-33.61), and high gene completeness (BO_SCPCAPUSCOC_SCPCAP complete: 94.6-95.1%), while consuming low computational resources (CPU hours:153-1027). In particular, the WO_SCPCAPENGANC_SCPCAP assembly of the haploid CHM13 sample achieved a contig NG50 of 62.06 Mb (NGA50:45.91 Mb), which surpasses the contiguity of the current human reference genome (GRCh38 contig NG50:57.88 Mb). Providing highest quality at low computational cost, WO_SCPCAPENGANC_SCPCAP is an important step towards the democratization of the de novo assembly of human genomes. The WO_SCPCAPENGANC_SCPCAP assembler is available at https://github.com/adigenova/wengan

bioinformatics↗