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How Have Massively Parallel Sequencing Technologies Furthered Our Understanding of Oncogenesis and Cancer Progression?

Massively parallel sequencing technologies have been a boon to many fields of biological science, including oncology. Cancer is an umbrella term for many diseases featuring abnormal cellular growth due to genetic and epigenetic aberrations. Advances in sequencing technology allow for interrogation of the DNA and RNA of cancer cells and other cells in the tumor microenvironment down to a single-base resolution. However, these strides come after a rich history of ground-breaking biological assays, like the discovery of the Philadelphia chromosome in the context of leukemia. Many specific genetic and epigenetic modifications have been implicated in oncogenesis, cancer progression, and response to treatment. Sequencing technologies have also helped to associate populations of bacteria in the microbiome to cancer development and prognosis. However, all this new information, especially when procured via high-throughput methods, comes at the cost of being more computationally and staff-resource intensive. There is also more risk to the privacy of the individuals with sequenced genomes. Notwithstanding, the overall benefit of sequencing technologies can greatly outweigh the risks with careful advancements and continued focus on the goal: helping those affected by cancer via precision medicine. Cancer biology has been and will continue to be elucidated by sequencing innovations in ways unimaginable without it.

Humans

Decipher RNA isoform combinations from minigene splicing assays and massive parallel sequencing with MAGIC.

SUMMARY: Functional testing of RNA using minigene splicing assays is increasingly being realized to demonstrate the effects of variants on splicing. In complex cases, variant pathogenicity is assessed by Sanger sequencing, which can be time consuming and may be replaced by short read sequencing. Moreover, strategies based on long read sequencing of the amplified minigene construct are promising and allow the isoforms to be fully characterized. We introduce MAGIC, a user-friendly tool that first generates the artificial construction genome files required to then perform alignment, assembly and annotation of the isoforms obtained by either short or long read minigene splicing assay sequencing. AVAILABILITY AND IMPLEMENTATION: MAGIC is available at https://github.com/LBGC-CFB/MAGIC. Zenodo DOI: 10.5281/zenodo.17052752.

High-Throughput Nucleotide Sequencing

Molecular diagnostic yield and barriers in inherited retinal diseases: a retrospective cohort study.

OBJECTIVE: To evaluate the diagnostic yield of panel-based genetic testing for inherited retinal diseases (IRDs) and identify barriers to molecular resolution. DESIGN: Retrospective cohort. PARTICIPANTS: A total of 404 patients with clinically confirmed IRDs who were evaluated at the Adult Inherited Retinal Dystrophy Service, Ontario, Canada (October 2021-September 2024). METHODS: Patients underwent targeted massive parallel sequencing panel testing. Diagnostic yield was calculated, and unresolved cases were reviewed. Associations between yield, phenotype, ethnicity, and sex were assessed using χ² analysis. RESULTS: Of 685 referrals, 570 had confirmed IRDs. After we excluded 140 pending results and 26 patients who declined testing, 404 patients were analyzed. At referral, 94 patients (23.2%) had a previous molecular diagnosis, and 138 (34.0%) were diagnosed through clinic-initiated testing, giving an overall yield of 57.4%. Yield varied significantly by phenotype (χ², P = 1.4 × 10⁻⁶), from 94.4% in vitelliform macular dystrophies to 25.0% in vitreoretinopathies, with no sex association (P = 1.0). Disease-causing variants were identified in 83 IRD-associated genes, most frequently ABCA4, USH2A, and BEST1. Of 172 unresolved cases, 62 (36.0%) had negative panels, and 110 (63.9%) were inconclusive, including 30 with unphased pathogenic variants in recessive genes and 10 with high-suspicion variants of uncertain significance. Key barriers included limited family availability for phasing, restricted access to functional assays, and lack of public coverage for whole-exome or whole-genome sequencing. CONCLUSIONS: Massive parallel sequencing-based panel testing achieved a 57% diagnostic yield in this IRD population. Success was strongly phenotype-dependent with substantial heterogeneity. Whole-exome sequencing, whole-genome sequencing, family segregation, and functional genomics could improve diagnostic outcomes and management.

Humans

Genetic Identification of Burned Human Remains: A Systematic Review.

Background/Objectives: DNA-based identification of degraded human remains represents a major challenge in forensic science, particularly in cases involving burned, fragmented, or commingled bodies. Advances in forensic genetics have expanded the analytical capabilities for such samples; however, the effectiveness of different approaches and their integration within Disaster Victim Identification (DVI) workflows remain heterogeneous. This systematic review aims to critically evaluate current evidence on DNA-based identification of degraded remains, focusing on methodological strategies, emerging genomic technologies, and DVI applications, while integrating laboratory evidence and operational forensic practice into a structured analytical framework. Methods: A systematic literature search was conducted in Scopus and Web of Science from database inception to 5 June 2026, following PRISMA 2020 guidelines. Eligible studies included original research addressing DNA analysis of degraded, thermally altered, or highly compromised human remains in forensic or DVI contexts. After a multistep screening process involving title/abstract and full-text evaluation, 37 studies were included. Data were extracted and organized into three thematic categories: (i) core DNA analysis, (ii) advanced molecular technologies, and (iii) DVI case applications. Results: The findings demonstrate that DNA recovery from degraded remains is influenced by thermal exposure, tissue type, and sampling strategy. Teeth and dense cortical bone consistently provide higher DNA yield. While autosomal STR profiling remains the primary analytical approach, its limitations in highly degraded samples are mitigated through the complementary use of mitochondrial DNA (mtDNA), Y-chromosome STRs (Y-STRs), and SNP markers, together with advanced sequencing technologies such as massively parallel sequencing (MPS). Emerging technologies, including rapid DNA systems and predictive models based on macroscopic indicators, significantly enhance efficiency and success rates. DVI studies report identification rates exceeding 90-95% when multidisciplinary and structured workflows are applied. The evidence further supports a flexible triage-based analytical strategy, in which marker selection is guided by tissue preservation and degradation level. Conclusions: DNA-based identification of degraded human remains has evolved into an adaptive, multi-level forensic process. Successful outcomes rely on the integration of optimized sampling, hierarchical genetic analysis, and coordinated DVI strategies. The findings support a triage-based framework that links tissue selection, degradation assessment, and analytical methodology to maximize identification success. Future developments should focus on predictive models, advanced genomic tools, and standardized workflows to further improve identification in challenging forensic scenarios.

Humans

Probability of Mitochondrial DNA heteroplasmy in different tissues from European populations.

Mitochondrial DNA (mtDNA) heteroplasmy complicates genetic analyses due to its variability across individuals and tissues. We analyzed over 400 Spanish blood samples and integrated published Massively Parallel Sequencing (MPS) data from ten additional European tissues. Heteroplasmy was tissue-specific, with skeletal muscle, kidney, and liver showing the highest levels, while the intestines, skin, and cerebellum had the lowest. Blood uniquely displayed more heteroplasmies in coding than non-coding regions. Several conserved positions not previously described as hotspots showed high frequencies. These results establish the first comprehensive tissue-specific heteroplasmic profile of the complete mitochondrial genome in a European population, improving the interpretation of mtDNA variation in forensic and biomedical contexts.

Humans

Sequencing the orthologs of human autosomal forensic short tandem repeats provides individual- and species-level identification in African great apes.

BACKGROUND: Great apes are a global conservation concern, with anthropogenic pressures threatening their survival. Genetic analysis can be used to assess the effects of reduced population sizes and the effectiveness of conservation measures. In humans, autosomal short tandem repeats (aSTRs) are widely used in population genetics and for forensic individual identification and kinship testing. Traditionally, genotyping is length-based via capillary electrophoresis (CE), but there is an increasing move to direct analysis by massively parallel sequencing (MPS). An example is the ForenSeq DNA Signature Prep Kit, which amplifies multiple loci including 27 aSTRs, prior to sequencing via Illumina technology. Here we assess the applicability of this human-based kit in African great apes. We ask whether cross-species genotyping of the orthologs of these loci can provide both individual and (sub)species identification. RESULTS: The ForenSeq kit was used to amplify and sequence aSTRs in 52 individuals (14 chimpanzees; 4 bonobos; 16 western lowland, 6 eastern lowland, and 12 mountain gorillas). The orthologs of 24/27 human aSTRs amplified across species, and a core set of thirteen loci could be genotyped in all individuals. Genotypes were individually and (sub)species identifying. Both allelic diversity and the power to discriminate (sub)species were greater when considering STR sequences rather than allele lengths. Comparing human and African great-ape STR sequences with an orangutan outgroup showed general conservation of repeat types and allele size ranges. Variation in repeat array structures and a weak relationship with the known phylogeny suggests stochastic origins of mutations giving rise to diverse imperfect repeat arrays. Interruptions within long repeat arrays in African great apes do not appear to reduce allelic diversity. CONCLUSIONS: Orthologs of most human aSTRs in the ForenSeq DNA Signature Prep Kit can be analysed in African great apes. Primer redesign would reduce observed variability in amplification across some loci. MPS of the orthologs of human loci provides better resolution for both individual and (sub)species identification in great apes than standard CE-based approaches, and has the further advantage that there is no need to limit the number and size ranges of analysed loci.

Animals

Zfp423 binds autoregulatory sites in p19 cell culture model.

Zfp423 is a 30 zinc finger transcription factor that forms regulatory complexes with EBF family members and factors targeted by canonical signaling pathways. Zfp423 mutations produce a range of developmental abnormalities in mice and humans related to the ciliopathies. Surprisingly, computational analysis of clustered Zfp423 and partner motifs in conserved genomic sequences predicts enrichment in Zfp423 and Ebf genes. In cell culture models selected for Zfp423 and EBF expression, we identify strong and reproducible occupancy of two Zfp423 intronic sites using chromatin immunoprecipitation with multiple independent antibodies. Both sites are significantly enriched in either quantitative PCR or massively parallel sequencing assays. A site in intron 5 acts as a classical enhancer in transient assays, but does not require the consensus motif for activity, suggesting a redundant or modulatory role for Zfp423 binding in this context. We speculate that Zfp423 may repress this enhancer as part of a developmental ratchet.

Animals

The Use of Next-Generation Sequencing in Personalized Medicine.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Humans

Molecular analysis of individuals with suspected 46,XY differences of sex development in a homogenous and understudied population.

Differences of sex development (DSD) are a group of rare congenital conditions defined by atypical chromosomal, gonadal, and/or hormonal sex. Despite advances in massively parallel sequencing (MPS), more than half of DSD cases have an unknown genetic aetiology. We recruited and analysed 21 individuals with 46,XY DSD from the Greater Middle East population using chromosomal microarray and whole exome sequencing. Participants had DSD ranging from micropenis to anorchia (absence of testes) with extra-genital features reported in four individuals (19%). Using a combination of microarray and WES, a genetic diagnosis (variants curated as likely pathogenic or pathogenic) was identified in 12/21 (57%) individuals. Microarray analysis showed two DSD participants with extra genital features had chromosomal abnormalities (48,XXXY and mosaic Y chromosomal rearrangement). Microarray also indicated a high degree of consanguinity, with extensive long contiguous stretches of homozygosity (LCSH) (>3% of the genome) in 6/21 (28.6%) individuals, all of whom received a genetic diagnosis. WES analysis revealed variants in the NR5A1 (three individuals), SRD5A2 (three individuals), TALDO1 (one individual) and AR (two individuals) genes. This includes the novel frameshift variant, c.1309del (p.Leu437Cysfs*59), in NR5A1. This study contributes to the characterisation of clinical features and molecular findings in individuals with DSD in this understudied and homogenous population and highlights the challenges with DSD diagnosis in the region. The genetic diagnoses identified may contribute to improved patient care and management.

Humans

Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): a cloud-based platform for curating and classifying germline variants.

Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

Child

The use of next-generation sequencing in personalized medicine.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

High-throughput sequencing

Long-range mRNA folding shapes expression and sequence of bacterial genes.

Bacterial gene expression is strongly influenced by local mRNA secondary structure, yet the impact of long-range folding remains poorly understood. Here, we show that sequences hundreds of nucleotides from the mRNA 5' end can act as potent repressors of gene expression through long-range base pairing to the ribosome binding site (RBS), subjecting anti-RBS sequences to negative selection. Using massively parallel reporter assays in Bacillus subtilis, we identify anti-RBS sequences as among the strongest determinants of reduced mRNA abundance across the transcript body. We demonstrate that distal anti-RBS elements engage in long-range folding with the Shine-Dalgarno sequence, blocking ribosome entry and promoting mRNA decay. Consistent with these repressive effects, anti-RBS-like sequences are depleted throughout diverse bacterial coding sequences but not from leaderless transcripts, and introducing distal anti-RBS to native genes reduces expression. Our findings establish that long-range mRNA folding is a conserved force shaping gene expression and constrains coding sequence evolution.

Bacillus subtilis

Allele Level Sequencing of Killer Cell Immunoglobulin-Like Receptor Genes Using Oxford Nanopore Long Read Sequencing.

The human Killer cell Immunoglobulin-like Receptor (KIR) genes, found on chromosome 19, encode for cell surface protein receptors that, through interaction with their ligand, modulate the action of Natural Killer (NK) cells and some subsets of T lymphocytes. KIR genes exhibit extensive variation through variable gene content, copy number, and allele polymorphism. The combination of KIR genes and their ligands is implicated in various clinical settings including haematopoietic stem cell and solid organ transplant, and infectious disease progression. KIR gene content has been used in the selection of optimal stem cell donors with haplotype variations in recipient and donor giving differential clinical outcomes. With the introduction of massively parallel clonal next generation sequencing and single molecule long read third generation sequencing, allele level determination of KIR genotypes has become feasible. We describe a method for amplicon-based long read sequencing on the Oxford Nanopore Technologies platform that provides largely unambiguous allele level typing of KIR genes. The method was validated using DNA extracted from 48 10th International Histocompatibility Workshop (IHWS) cell lines with previously published allele level KIR genotypes and 176 Western Australian samples previously tested for the presence or absence of KIR genes. Our long-read sequencing method was able to accurately determine KIR alleles with an overall concordance of 97%-99% with the published data. Importantly, phasing ambiguity caused by the inability to phase heterozygous base positions over long stretches of gene sequence was resolved in several samples. Thus, our long read PCR sequencing strategy can be used to determine KIR genotypes at allele resolution level.

Humans

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type and sex specificity of gene expression with novel genetic risk for MERTK in female.

Alzheimer's disease, the most common age-related neurodegenerative disease, is closely associated with both amyloid-ß plaque and neuroinflammation. Two thirds of Alzheimer's disease patients are females and they have a higher disease risk. Moreover, women with Alzheimer's disease have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration. To identify how sex difference induces structural brain changes, we performed unbiased massively parallel single nucleus RNA sequencing on Alzheimer's disease and control brains focusing on the middle temporal gyrus, a brain region strongly affected by the disease but not previously studied with these methods. We identified a subpopulation of selectively vulnerable layer 2/3 excitatory neurons that that were RORB-negative and CDH9-expressing. This vulnerability differs from that reported for other brain regions, but there was no detectable difference between male and female patterns in middle temporal gyrus samples. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of diseased brains differed between males and females. Combining single cell transcriptomic data with results from genome-wide association studies (GWAS), we identified MERTK genetic variation as a risk factor for Alzheimer's disease selectively in females. Taken together, our single cell dataset revealed a unique cellular-level view of sex-specific transcriptional changes in Alzheimer's disease, illuminating GWAS identification of sex-specific Alzheimer's risk genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of Alzheimer's disease.

Journal Article

Massively parallel approaches for characterizing noncoding functional variation in human evolution.

The genetic differences underlying unique phenotypes in humans compared to our closest primate relatives have long remained a mystery. Similarly, the genetic basis of adaptations between human groups during our expansion across the globe is poorly characterized. Uncovering the downstream phenotypic consequences of these genetic variants has been difficult, as a substantial portion lies in noncoding regions, such as cis-regulatory elements (CREs). Here, we review recent high-throughput approaches to measure the functions of CREs and the impact of variation within them. CRISPR screens can directly perturb CREs in the genome to understand downstream impacts on gene expression and phenotypes, while massively parallel reporter assays can decipher the regulatory impact of sequence variants. Machine learning has begun to be able to predict regulatory function from sequence alone, further scaling our ability to characterize genome function. Applying these tools across diverse phenotypes, model systems, and ancestries is beginning to revolutionize our understanding of noncoding variation underlying human evolution.

Humans

Predicting dynamic expression patterns in budding yeast with a fungal DNA language model.

Predicting gene expression from DNA sequence remains challenging due to complex regulatory codes. We introduce a masked DNA language model pretrained on 165 fungal genomes closely related to budding yeast that captures conserved regulatory grammar. Fine-tuning the LM on yeast RNA-seq data-including high-resolution transcriptional regulator induction time courses generated in this study-yielded Shorkie, a model that substantially improves gene expression prediction compared to baselines trained without self-supervision. Shorkie identified canonical transcription factor (TF) binding motifs and tracked their usage across induction experiments. Furthermore, Shorkie accurately predicted variant effects, outperforming leading sequence-to-expression models in cis-eQTL classification and achieving high concordance with massively parallel reporter assays. Interpretability analyses revealed Shorkie's ability to resolve promoter dynamics, splicing signals, and temporal changes in regulatory motif usage. This framework demonstrates that evolutionary-scale pretraining combined with transfer learning substantially improves our ability to decode gene regulation from sequence, providing insights into noncoding variants and regulatory networks.

Journal Article

Active learning of enhancers and silencers in the developing neural retina.

Deep learning is a promising strategy for modeling cis-regulatory elements. However, models trained on genomic sequences often fail to explain why the same transcription factor can activate or repress transcription in different contexts. To address this limitation, we developed an active learning approach to train models that distinguish between enhancers and silencers composed of binding sites for the photoreceptor transcription factor cone-rod homeobox (CRX). After training the model on nearly all bound CRX sites from the genome, we coupled synthetic biology with uncertainty sampling to generate additional rounds of informative training data. This allowed us to iteratively train models on data from multiple rounds of massively parallel reporter assays. The ability of the resulting models to discriminate between CRX sites with identical sequence but opposite functions establishes active learning as an effective strategy to train models of regulatory DNA. A record of this paper's transparent peer review process is included in the supplemental information.

Retina