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At least 19 recordsLinked to original sources
PubMed2025

Quantifying prevalence and risk factors of HIV multiple infection in Uganda from population-based deep-sequence data.

People living with HIV can acquire secondary infections through a process called superinfection, giving rise to simultaneous infection with genetically distinct variants (multiple infection). Multiple infection provides the necessary conditions for the generation of novel recombinant forms of HIV and may worsen clinical outcomes and increase the rate of transmission to HIV seronegative sexual partners. To date, studies of HIV multiple infection have relied on insensitive bulk-sequencing, labor intensive single genome amplification protocols, or deep-sequencing of short genome regions. Here, we identified multiple infections in whole-genome or near whole-genome HIV RNA deep-sequence data generated from plasma samples of 2,029 people living with viremic HIV who participated in the population-based Rakai Community Cohort Study (RCCS). We estimated individual- and population-level probabilities of being multiply infected and assessed epidemiological risk factors using the novel Bayesian deep-phylogenetic multiple infection model (deep - phyloMI) which accounts for bias due to partial sequencing success and false-negative and false-positive detection rates. We estimated that between 2010 and 2020, 4.09% (95% highest posterior density interval (HPD) 2.95%-5.45%) of RCCS participants with viremic HIV multiple infection at time of sampling. Participants living in high-HIV prevalence communities along Lake Victoria were 2.33-fold (95% HPD 1.3-3.7) more likely to harbor a multiple infection compared to individuals in lower prevalence neighboring communities. This work introduces a high-throughput surveillance framework for identifying people with multiple HIV infections and quantifying population-level prevalence and risk factors of multiple infection for clinical and epidemiological investigations.

Humans↗
PubMed2026

Identification and masking of artifactual and misleading within-host variants in deep-sequencing SARS-CoV-2 data.

Deep-sequencing data are increasingly used to study within-host viral diversity and to inform evolutionary inference. For SARS-CoV-2, analyses based on intra-host single-nucleotide variants (iSNVs) have been widely applied to quantify within-host diversity and infer transmission dynamics. However, these applications critically depend on the reliable identification of low-frequency variants, which remain vulnerable to systematic and technical artifacts. In this study, we show that recurrent artifactual iSNVs are common in large-scale SARS-CoV-2 sequencing data and can persist even under conservative minor allele frequency thresholds. Using data from the UK's Office for National Statistics COVID-19 Infection Survey, we demonstrate that such artifacts are predominantly sequencing center-specific rather than primer-specific. Each center exhibits a modest, distinct set of recurrent artifactual variants showing little overlap with sites routinely masked at the consensus level. To address this, we developed a systematic, dataset-aware framework that uses recurrence within sequencing datasets to identify small, noise-adapted sets of artifactual iSNVs to mask. Applying this framework reduces spurious sharing of low-frequency variants between samples and qualitatively alters downstream inferences, including estimates of within-host diversity and transmission bottleneck sizes. Although this study focused on SARS-CoV-2, it is likely that recurrent artifactual iSNVs will be problematic for other viruses as mass-sequencing becomes increasingly routine. Together, these findings highlight the importance of explicit, dataset-aware artifact control for robust inference from within-host variation, particularly as genomic studies increasingly seek to exploit sub-consensus diversity in rapidly evolving pathogens.

Humans↗
PubMed2026

Metagenomic Deep Sequencing Identifies Gene Mutations Associated with Chemotherapeutic Resistance in Vitreoretinal Lymphoma.

PURPOSE: To identify gene mutations associated with chemotherapeutic resistance in patients with vitreoretinal lymphoma (VRL) using metagenomic deep sequencing (MDS) of intraocular specimens. METHODS: Patients with VRL confirmed by cytopathology and immunohistochemistry, flow cytometry, and/or polymerase chain reaction for MYD88, were included. Intraocular specimens underwent MDS of the host genome. Gene mutations were identified and cross-referenced with the Catalogue of Somatic Mutations in Cancer database to determine associations with chemotherapeutic resistance. RESULTS: Forty-nine patients with VRL underwent MDS, with six specimens from four patients revealing eight gene mutations associated with chemotherapeutic resistance. Four specimens from three patients harbored mutations associated with methotrexate resistance, the mainstay of VRL treatment. In one patient, serial sampling from the initial vitrectomy and two subsequent recurrences revealed distinct resistance-associated mutations at each time point. Despite multi-agent therapy including rituximab, consolidation regimens, and lenalidomide, this patient ultimately succumbed to the disease, whereas the other three patients remained in long-term remission. CONCLUSIONS: Our findings demonstrated that specific gene mutations associated with chemotherapeutic resistance may be harbored by VRL. The detection of different resistance mutations at sequential time points in one patient may reflect clonal selection, treatment pressure, or variable detection sensitivity. The ability to easily sample ocular fluid and detect different mutations associated with tumor recurrence or persistence may provide insights into tumor pathogenesis and could inform prognosis and influence treatment decisions. These findings establish a foundation for developing targeted PCR assays for identified resistance genes, which could transform clinical practice in VRL.

Chemotherapeutic resistance-associated mutations↗
PubMed2025

Deep Sequencing Reveals Dual Evolution of SARS-CoV-2: Insights Into Defective Genomes From Wuhan-Hu-1 Variants to Omicron Subvariants.

SARS-CoV-2 has evolved from early variants dominating the first (B.1.5, B.1.1) and second (B.1.177) pandemic waves, which exhibited a higher frequency of minority mutants with deletions leading to Defective Viral Genomes (DVGs) in the spike region near the S1/S2 cleavage site than the Alpha, Beta, and Delta variants. The emergence of Omicron has significantly altered the dominant variant profile, with Omicron subvariants now representing 100% of circulating viruses. To monitor the evolution and adaptation of Omicron in the human population, a deep-sequencing study was performed in RNA samples of BA.1, BA.1.1, BA.2, BA.5, BQ.1.1, XBB.1.5 and BA.2.86 Omicron subvariants. The findings reveal two occurrences of similar evolutionary patterns within SARS-CoV-2 characterized by a shift from a significant to a very low production of DVGs. This event suggests that DVGs might play a role in the virus's spread and adaptation for persistence in infected humans.

SARS-CoV-2↗
PubMed2025

HIV-phyloTSI: subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data.

BACKGROUND: Estimating the time since HIV infection (TSI) at population level is essential for tracking changes in the global HIV epidemic. Most methods for determining TSI give a binary classification of infections as recent or non-recent within a window of several months, and cannot assess the cumulative impact of an intervention. RESULTS: We developed a Random Forest Regression model, HIV-phyloTSI, which combines measures of within-host diversity and divergence to generate continuous TSI estimates directly from viral deep-sequencing data, with no need for additional variables. HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. It performs equally well for all major HIV subtypes based on data from African and European cohorts. CONCLUSIONS: We demonstrate how HIV-phyloTSI can be used for incidence estimates on a population level.

HIV Infections↗
PubMed2025

AmpSeqR: an R package for amplicon deep sequencing data analysis.

Amplicon sequencing (AmpSeq) is a methodology that targets specific genomic regions of interest for polymerase chain reaction (PCR) amplification so that they can be sequenced to a high depth of coverage. Amplicons are typically chosen to be highly polymorphic, usually with several highly informative, high frequency single nucleotide polymorphisms (SNPs) segregating in an amplicon of 100-200 base pair (bp). This allows high sensitivity detection and quantification of the frequency of each sequence within each sample making it suitable for applications such as low frequency somatic mosaicism detection or minor clone detection in mixed samples. AmpSeq is being increasingly applied to both biological and medical studies, in applications such as cancer, infectious diseases and brain mosaicism studies. Current bioinformatics pipelines for AmpSeq data processing lack downstream analysis, have difficulty distinguishing between true sequences and PCR sequencing errors and artifacts, and often require bioinformatic expertise. We present a new R package: AmpSeqR, designed for the processing of deep short-read amplicon sequencing data, with a focus on infectious diseases. The pipeline integrates several existing R packages combining them with newly developed functions to perform optimal filtering of reads to remove noise and improve the accuracy of the detected sequences data, permitting detection of very low frequency clones in mixed samples. The package provides useful functions including data pre-processing, amplicon sequence variants (ASVs) estimation, data post-processing, data visualization, and automatically generates a comprehensive Rmarkdown report that contains all essential results facilitating easy inclusion into reports and publications. AmpSeqR is publicly available at https://github.com/bahlolab/AmpSeqR.

High-Throughput Nucleotide Sequencing↗
PubMed2025

Using Chromosome Conformation Capture Combined with Deep Sequencing (Hi-C) to Study Genome Organization in Bacteria.

Genome organization is fundamental to all living organisms. Long DNA molecules are organized in hierarchical orders to be accommodated into eukaryotic nuclei or bacterial cells, which are thousands of folds shorter. Over the past two decades, chromosome conformation capture (3C) techniques substantially advanced our understanding of genome folding inside cells. 3C involves crosslinking and proximity ligation, and quantifies the physical contacts between two DNA regions within the genome. Coupled with high-throughput sequencing, 3C-seq and Hi-C techniques detect genome-wide DNA interactions, providing a comprehensive view of global genome organization. Here, we describe a detailed method to prepare Hi-C libraries using Bacillus subtilis, which includes procedures of crosslinking chromatin, digesting the crosslinked genome, labeling DNA ends with biotin, ligating DNA, and preparing the DNA library for sequencing using an Illumina platform.

High-Throughput Nucleotide Sequencing↗
PubMed2005

Coffee and tomato share common gene repertoires as revealed by deep sequencing of seed and cherry transcripts.

An EST database has been generated for coffee based on sequences from approximately 47,000 cDNA clones derived from five different stages/tissues, with a special focus on developing seeds. When computationally assembled, these sequences correspond to 13,175 unigenes, which were analyzed with respect to functional annotation, expression profile and evolution. Compared with Arabidopsis, the coffee unigenes encode a higher proportion of proteins related to protein modification/turnover and metabolism-an observation that may explain the high diversity of metabolites found in coffee and related species. Several gene families were found to be either expanded or unique to coffee when compared with Arabidopsis. A high proportion of these families encode proteins assigned to functions related to disease resistance. Such families may have expanded and evolved rapidly under the intense pathogen pressure experienced by a tropical, perennial species like coffee. Finally, the coffee gene repertoire was compared with that of Arabidopsis and Solanaceous species (e.g. tomato). Unlike Arabidopsis, tomato has a nearly perfect gene-for-gene match with coffee. These results are consistent with the facts that coffee and tomato have a similar genome size, chromosome karyotype (tomato, n=12; coffee n=11) and chromosome architecture. Moreover, both belong to the Asterid I clade of dicot plant families. Thus, the biology of coffee (family Rubiacaeae) and tomato (family Solanaceae) may be united into one common network of shared discoveries, resources and information.

Arabidopsis↗
PubMed2005

A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage.

BACKGROUND: The allele frequencies of single-nucleotide polymorphisms (SNPs) are needed to select an optimal subset of common SNPs for use in association studies. Sequence-based methods for finding SNPs with allele frequencies may need to handle thousands of sequences from the same genome location (sequences of deep coverage). RESULTS: We describe a computational method for finding common SNPs with allele frequencies in single-pass sequences of deep coverage. The method enhances a widely used program named PolyBayes in several aspects. We present results from our method and PolyBayes on eighteen data sets of human expressed sequence tags (ESTs) with deep coverage. The results indicate that our method used almost all single-pass sequences in computation of the allele frequencies of SNPs. CONCLUSION: The new method is able to handle single-pass sequences of deep coverage efficiently. Our work shows that it is possible to analyze sequences of deep coverage by using pairwise alignments of the sequences with the finished genome sequence, instead of multiple sequence alignments.

Computers, Molecular↗
PubMed2022

Pneumococcal within-host diversity during colonization, transmission and treatment.

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.

Child↗
PubMed2026

Whole metagenome sequencing: not deep enough for complete microbial function recovery.

BACKGROUND: Whole metagenome shotgun sequencing (WMS) is widely used to profile microbial function. However, technical variability in sequencing and analysis often obscures true biological patterns. Large-scale studies are particularly susceptible to batch effects, such as differences in sequencing depth and platform and annotation strategies, as well as sample-to-flow-cell assignments. However, the relative effects of these factors on functional inference in such studies have yet to be systematically evaluated. We analyzed oral-rinse WMS data from 671 Nigerian youths aged 9-18, sequenced on two Illumina platforms. Microbial molecular functionality encoded in these data was annotated using the mi-faser/Fusion pipeline, to capture the broad functional repertoire, and HUMAnN 3/EC numbers pipeline to characterize curated enzymatic activities. We then quantified how technical factors and batch effects shaped the recovery of microbial functionality. RESULTS: Three findings of our work were most salient. First, we observed that the choice of annotation strategy traded off between breadth and specificity of functional coverage. Second, we found that low-prevalence functions were disproportionately lost at shallow sequencing depths, indicating that in, e.g., case-control studies with few representatives of the minor class, sequencing depth could critically impact study resolution. Finally, using our newly developed model relating sequencing depth to functional recovery, we demonstrated that increasing sequencing depth does not directly or proportionally improve functional recall. That is, at as little as 10% of this study's sequencing depth, 30% of the estimated complete microbiome functional repertoire was detectable. However, even at the full depth used in this study, we were only able to recover an estimated 60% of that complete functional repertoire. We further showed that despite biomes differences in functional diversity and host contamination levels (e.g., soil, fecal), incomplete functional recovery at commonly used sequencing depths was consistently observed. CONCLUSIONS: Together, these findings and our depth-to-function mapping framework provide practical guidelines for the design and interpretation of WMS studies. Coordinating sequencing depth planning with annotation strategy, experimental design, and rigorous batch control is thus essential for robust detection of microbial functions and for ensuring reproducible microbiome insights. Video Abstract.

Humans↗
PubMed1997

[Preoperative evaluation for volume reduction surgery of pulmonary emphysema using MRI: usefulness of HASTE (half-Fourier single-shot turbo SE) sequence during deep respiration].

Volume reduction surgery has recently been an important surgical procedure for patients with severe pulmonary emphysema. We compared the sagittal and coronal images taken by the HASTE sequence with those obtained by turbo FLASH during deep breathing and with CT images obtained under deep inspiration. Clear images were obtained from both sequences, without cardiac or respiratory motion artifacts. The emphysematous areas were demonstrated as low signal intensity areas, as in CT images. The ratio of signal intensity in the expiratory phase to that in the inspiratory phase was lower than that of volunteers in the HASTE sequence. The HASTE sequence provides useful information about respiratory movement as well as about changes in the pulmonary parenchyma when used for preoperative examination.

Adult↗
PubMed2025

Integrating RNA sequencing with deep learning-based metabolic toxicity prediction: A new perspective on screening prioritized liquid crystal monomers.

Nearly 99 % of liquid crystal monomers (LCMs) toxicological data remains gaps, especially to aquatic organisms. Herein, this study proposes a rapid and high-throughput screening method for identifying priority LCMs in natural water. Using six fluorinated LCMs (LCMsF) with significant enrichment characteristics in zebrafish as examples, RNA sequencing revealed that LCMsF-induced metabolic disturbances are predominant, including 28 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway abnormalities attributed to 498 differentially expressed genes. Notably, the intricate sequencing process resulted in the inability to rapid identify additional 857 LCMsF that may induce metabolic disturbances. To address this, LCMsT-MTP, a predictive deep learning model based on RNA sequencing, was developed. This model integrates a comprehensive representation of LCMsF structures and metabolic toxicity target sequences. LCMsT-MTP improves upon traditional methods that are limited to single targets and mechanisms by facilitating the simultaneous identification of 21 metabolic toxicities induced by LCMsF. In addition, the LCMsT-MTP model was further applied to non-fluorinated LCMs (LCMsNone F) that satisfy the applicability domains test. Accordingly, a metabolic toxicity priority list of LCMs was proposed, with ∼95 % of LCMs classified as high or medium risk. Priority list validation by molecular dynamics confirmed that the interactions of LCMsF/LCMsNone F and metabolic toxicity targets in representative KEGG pathways were distinct.

Animals↗
PubMed2025

Experimental Evolution of Poxviruses.

Experimental evolution is the process of exposing virus populations to defined selective pressures in a laboratory setting to identify adaptive changes. Coupled with deep sequencing, this experimental approach allows for nucleotide-level resolution of poxvirus adaptive strategies over time. Here, we present a general method of poxvirus experimental evolution, Illumina-based deep sequencing, and bioinformatic analyses to identify structural changes (e.g., gene duplication) as well as local adaptive changes (e.g., small indels and single nucleotide polymorphisms).

Poxviridae↗
PubMed2026

Evaluation of germline transmission of electroporation-mediated double gene-edited cattle lines.

Gene editing in livestock using clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) offers a promising approach for genetic improvement in cattle. This study evaluated germline transmission and mutation stability of double-knockout cattle generated by zygote electroporation. Previously reported myostatin/beta-lactoglobulin (MSTN/BLG) and newly generated α-1,3-galactosyltransferase (GGTA1/BLG) double-knockout cattle were produced using CRISPR/Cas9-mediated genome editing. Targeted deep sequencing demonstrated extensive somatic mosaicism across multiple tissues. Computer-assisted sperm analysis (CASA) demonstrated normal sperm motility in MSTN/BLG double-knockout males. Fertilization of wild-type oocytes produced heterozygous embryos, with mutation frequencies of 37.76 ± 10.74% at the MSTN locus and 54.80 ± 7.73% at the BLG locus, as assessed by T7 endonuclease I (T7E1) assay. MSTN/BLG double-knockout sperm were subsequently used for embryo production and for artificial insemination of GGTA1/BLG double-knockout females. Healthy offspring were successfully obtained (n = 3), alongside one stillborn calf. Targeted deep sequencing of all four progenies revealed highly variable allele frequencies that deviated substantially from the approximately 50% expected for heterozygous germline transmission. In contrast, whole-genome sequencing (WGS) results were consistent with Mendelian expectations, underscoring the limitations of PCR-based targeted sequencing for assessing germline transmission in mosaic founders. These results show that CRISPR/Cas9-edited embryos generated by electroporation can develop into healthy, sexually mature cattle capable of germline transmission. While variable transmission rates were observed owing to founder mosaicism, non-mosaic F1 offspring were successfully generated. However, direct, embryo-mediated gene-editing strategies remain technically and economically challenging for large-scale commercial calf production, and reports in cattle are limited. This study provides a reference for future applications of gene-edited embryos and their germline propagation.

Animals↗
PubMed2026

Deep tissue sequencing improves genetic diagnostic yield in focal cortical dysplasia.

Focal cortical dysplasias (FCDs) are malformations of cortical development associated with drug-resistant focal epilepsy. We analyzed surgical tissue from 25 consecutive cases recruited from adult and pediatric epilepsy surgery programs. We performed high-depth sequencing of lesional tissue, validated somatic variants using droplet digital PCR or amplicon sequencing, and investigated genotype-phenotype correlations. A pathogenic or likely pathogenic variant was detected in 64% (n = 16/25) of cases. Of these, five cases with FCDIIa or FCDIIb had germline variants in NPRL3 (n = 3) or DEPDC5 (n = 2). Somatic variants were identified in 44% (n = 11/25) of cases. The genetic yield for FCDIIb was 77% of cases having a pathogenic mTOR pathway variant detected (n = 10/13), and for FCDIIa 66% (n = 6/9). High depth sequencing approaches allowed detection of somatic variants with very low (down to 0.4%) variant allele fractions (VAFs). No pathogenic variants were detected in 3 cases with FCDI. 62% (n = 15/24) of the cases with ≥12 months follow up experienced a favourable seizure outcome (Engel 1-2) following surgery. Of note, n = 9 patients required repeat surgery to resect residual dysplasia. Determining a genetic diagnosis reveals aetiology and paves the way to precision therapies that may benefit those with FCD who do not respond to current treatments.

Humans↗
PubMed2000

Common and rare ABCA1 variants affecting plasma HDL cholesterol.

Mutations in ABCA1, a member of the ATP-binding cassette family, have been shown to underlie Tangier disease (TD) and familial hypoalphalipoproteinemia (FHA), which are genetic disorders that are characterized by depressed concentrations of plasma high density lipoprotein (HDL) cholesterol. An important question is whether common variants within the coding sequence of ABCA1 can affect plasma HDL cholesterol in the general population. To address this issue, we developed a screening strategy to find common ABCA1 variants. This strategy involved long-range amplification of genomic DNA by using coding sequences only, followed by deep sequencing into the introns. This method helped us to characterize a new set of amplification primers, which permitted amplification of virtually all of the coding sequence of ABCA1 and its intron-exon boundaries with a single DNA amplification program. With these new sequencing primers, we found 3 novel ABCA1 mutations: a frameshift mutation (4570insA, A1484S-->X1492), a missense mutation (A986D) in a TD family, and a missense mutation (R170C) in aboriginal subjects with FHA. We also used these sequencing primers to characterize 4 novel common amino acid variants in ABCA1, in addition to 5 novel common silent variants. We tested for association of the ABCA1 I/M823 variant with plasma HDL cholesterol in Canadian Inuit and found that M823/M823 homozygotes had significantly higher plasma HDL cholesterol compared with subjects with the other genotypes. The results provide proof of principle of the effectiveness of this approach to identify both rare and common ABCA1 genomic variants and also suggest that common amino acid variation in ABCA1 is a determinant of plasma HDL cholesterol in the general population.

ATP Binding Cassette Transporter 1↗