Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline ATM sequence variants.

The ClinGen Hereditary Breast, Ovarian and Pancreatic Cancer (HBOP) Variant Curation Expert Panel (VCEP) is composed of internationally recognized experts in clinical genetics, molecular biology and variant interpretation. This VCEP made specifications for ACMG/AMP guidelines for the ataxia telangiectasia mutated (ATM) gene according to the Food and Drug Administration (FDA)-approved ClinGen protocol. These gene-specific rules for ATM were modified from the American College of Medical Genetics and Association for Molecular Pathology (ACMG/AMP) guidelines and were tested against 33 ATM variants of various types and classifications in a pilot curation phase. The pilot revealed a majority agreement between the HBOP VCEP classifications and the ClinVar-deposited classifications. Six pilot variants had conflicting interpretations in ClinVar and reevaluation with the VCEP's ATM-specific rules resulted in four that were classified as benign, one as likely pathogenic and one as a variant of uncertain significance (VUS) by the VCEP, improving the certainty of interpretations in the public domain. Overall, 28 the 33 pilot variants were not VUS leading to an 85% classification rate. The ClinGen-approved, modified rules demonstrated value for improved interpretation of variants in ATM.

Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup.

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP.

The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.

A Comparison of Lossless Compression Methods in Microscopy Data Storage Applications.

Modern high-throughput microscopy methods such as light-sheet imaging and electron microscopy are capable of producing petabytes of data inside of a single experiment. Storage of these large images, however, is challenging because of the difficulty of moving, storing, and analyzing such vast amounts of data, which is often collected at very high data rates (>1GBps). In this report, we provide a comparison of the performance of several compression algorithms using a collection of published and unpublished datasets including confocal, fMOST, and pathology images. We also use simulated data to demonstrate the efficiency of each algorithm as image content or entropy increases. As a result of this work, we recommend the use of the BLOSC algorithm combined with ZSTD for various microscopy applications, as it produces the best compression ratio over a collection of conditions.

Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology.

Objective.Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Approach.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.8µm diameter) carbon fiber electrodes and the positions of surrounding neurons. We implanted male rats with carbon fiber electrode arrays for 6 or 12+ weeks targeting layer V motor cortex. After explanting the arrays, we immunostained the implant site and localized putative recording site tips with subcellular-cellular resolution. We then 3D segmented neuron somata within a 50µm radius from implanted tips to measure neuron positions and health and compare to healthy cortex with symmetric stereotaxic coordinates.Main results.Immunostaining of astrocyte, microglia, and neuron markers confirmed that overall tissue health was indicative of high biocompatibility near the tips. While neurons near implanted carbon fibers were stretched, their number and distribution were similar to hypothetical fibers placed in healthy contralateral brain. Such similar neuron distributions suggest that these minimally invasive electrodes demonstrate the potential to sample naturalistic neural populations. This motivated the prediction of spikes produced by nearby neurons using a simple point source model fit using recorded electrophysiology and the mean positions of the nearest neurons observed in histology. Comparing spike amplitudes suggests that the radius at which single units can be distinguished from others is near the fourth closest neuron (30.7 ± 4.6µm,X-± S) in layer V motor cortex.Significance.Collectively, these data and simulations provide the first direct evidence that neuron placement in the immediate vicinity of the recording site influences how many spike clusters can be reliably identified by spike sorting.

Analysis of BRCA1 and BRCA2 alternative splicing in predisposition to ovarian cancer.

BACKGROUND: The mRNA splicing is regulated on multiple levels, resulting in the proper distribution of genes' transcripts in each cell and maintaining cell homeostasis. At the same time, the expression of alternative transcripts can change in response to underlying genetic variants, often missed during routine diagnostics. AIM: The main aim of this study was to define the frequency of aberrant splicing in BRCA1 and BRCA2 genes in blood RNA extracted from ovarian cancer patients who were previously found negative for the presence of pathogenic alterations in the 25 most commonly analysed ovarian cancer genes, including BRCA1 and BRCA2. MATERIAL AND METHODS: Frequency and spectrum of splicing alterations in BRCA1 and BRCA2 genes were analysed in blood RNA from 101 ovarian cancer patients and healthy controls (80 healthy women) using PCR followed by gel electrophoresis and Sanger sequencing. The expression of splicing events was examined using RT-qPCR. RESULTS: We did not identify any novel, potentially pathogenic splicing alterations. Nevertheless, we detected six naturally occurring transcripts, named BRCA1ΔE9-10, BRCA1ΔE11, BRCA1ΔE11q, and BRCA2ΔE3, BRCA2ΔE12 and BRCA2ΔE17-18 of which three (BRCA1ΔE11q, BRCA1ΔE11 and BRCA2ΔE3) were significantly higher expressed in the ovarian cancer cohort than in healthy controls (p ≤ 0.0001). CONCLUSIONS: This observation indicates that the upregulation of selected naturally occurring transcripts can be stimulated by non-genetic mechanisms and be a potential systemic response to disease progression and/or treatment. However, this hypothesis requires further examination.

Clinical, splicing, and functional analysis to classify BRCA2 exon 3 variants: Application of a points-based ACMG/AMP approach.

Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.

Leukemia-initiating HSCs in chronic lymphocytic leukemia reveal clonal leukemogenesis and differential drug sensitivity.

The existence of "leukemia-initiating cells" (LICs) in chronic lymphocytic leukemia (CLL) remains controversial due to the difficulty in isolating and identifying the tumor-initiating cells. Here, we demonstrate a microchannel electroporation (MEP) microarray that injects RNA-detecting probes into single live cells, allowing the imaging and characterization of heterogeneous LICs by intracellular RNA expression. Using limited-cell FACS sequencing (LC-FACSeq), we can detect and monitor rare live LICs during leukemogenesis and characterize their differential drug sensitivity. Disease-associated mutation accumulation in developing B lymphoid but not myeloid lineage in CLL patient hematopoietic stem cells (CLL-HSCs), and development of independent clonal CLL-like cells in murine patient-derived xenograft models, suggests the existence of CLL LICs. Furthermore, we identify differential protein ubiquitination and unfolding response signatures in GATA2high CLL-HSCs that exhibit increased sensitivity to lenalidomide and resistance to fludarabine compared to GATA2lowCLL-HSCs. These results highlight the existence of therapeutically targetable disease precursors in CLL.

Genome-wide DNA hypermethylation opposes healing in patients with chronic wounds by impairing epithelial-mesenchymal transition.

An extreme chronic wound tissue microenvironment causes epigenetic gene silencing. An unbiased whole-genome methylome was studied in the wound-edge tissue of patients with chronic wounds. A total of 4,689 differentially methylated regions (DMRs) were identified in chronic wound-edge skin compared with unwounded human skin. Hypermethylation was more frequently observed (3,661 DMRs) in the chronic wound-edge tissue compared with hypomethylation (1,028 DMRs). Twenty-six hypermethylated DMRs were involved in epithelial-mesenchymal transition (EMT). Bisulfite sequencing validated hypermethylation of a predicted specific upstream regulator TP53. RNA-Seq analysis was performed to qualify findings from methylome analysis. Analysis of the downregulated genes identified the TP53 signaling pathway as being significantly silenced. Direct comparison of hypermethylation and downregulated genes identified 4 genes, ADAM17, NOTCH, TWIST1, and SMURF1, that functionally represent the EMT pathway. Single-cell RNA-Seq studies revealed that these effects on gene expression were limited to the keratinocyte cell compartment. Experimental murine studies established that tissue ischemia potently induces wound-edge gene methylation and that 5'-azacytidine, inhibitor of methylation, improved wound closure. To specifically address the significance of TP53 methylation, keratinocyte-specific editing of TP53 methylation at the wound edge was achieved by a tissue nanotransfection-based CRISPR/dCas9 approach. This work identified that reversal of methylation-dependent keratinocyte gene silencing represents a productive therapeutic strategy to improve wound closure.

Characterization of an alloherpesvirus from wild lake sturgeon Acipenser fulvescens in Wisconsin (USA).

In the spring of 2017, 2 adult lake sturgeon (LS) Acipenser fulvescens captured from the Wolf River, Wisconsin (USA), presented with multiple cutaneous plaques that, upon microscopic examination, indicated proliferative epidermitis. Ultrastructural examination of affected keratinocytes revealed particles in the nucleus having a morphology typical of herpesviruses. A degenerate PCR assay targeting the DNA polymerase catalytic subunit (pol) gene of large double-stranded DNA viruses generated amplicons of the anticipated size from skin samples, and sequences of amplicons confirmed the presence of a novel alloherpesvirus (lake sturgeon herpesvirus, LSHV) related to acipenserid herpesvirus 1 (AciHV1). The complete genome (202660 bp) of this virus was sequenced using a MiSeq System, and phylogenetic analyses substantiated the close relationship to AciHV1. A PCR assay targeting the LSHV DNA packaging terminase subunit 1 (ter1) gene demonstrated the presence of the virus in 39/42 skin lesion samples collected from wild LS captured in 2017-2019 and 2021 in 4/4 rivers in Wisconsin. Future efforts to isolate LSHV in cell culture would facilitate challenge studies to determine the disease potential of the virus.

nGauge: Integrated and Extensible Neuron Morphology Analysis in Python.

The study of neuron morphology requires robust and comprehensive methods to quantify the differences between neurons of different subtypes and animal species. Several software packages have been developed for the analysis of neuron tracing results stored in the standard SWC format. The packages, however, provide relatively simple quantifications and their non-extendable architecture prohibit their use for advanced data analysis and visualization. We developed nGauge, a Python toolkit to support the parsing and analysis of neuron morphology data. As an application programming interface (API), nGauge can be referenced by other popular open-source software to create custom informatics analysis pipelines and advanced visualizations. nGauge defines an extendable data structure that handles volumetric constructions (e.g. soma), in addition to the SWC linear reconstructions, while remaining lightweight. This greatly extends nGauge's data compatibility.

Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations.

Multipotent neural stem cells (NSCs) are found in several isolated niches of the adult mammalian brain where they have unique potential to assist in tissue repair. Modern transcriptomics offer high-throughput methods for identifying disease or injury associated gene expression signatures in endogenous adult NSCs, but they require adaptation to accommodate the rarity of NSCs. Bulk RNA sequencing (RNAseq) of NSCs requires pooling several mice, which impedes application to labor-intensive injury models. Alternatively, single cell RNAseq can profile hundreds to thousands of cells from a single mouse and is increasingly used to study NSCs. The consequences of the low RNA input from a single NSC on downstream identification of differentially expressed genes (DEGs) remains insufficiently explored. Here, to clarify the role that low RNA input plays in NSC DEG identification, we directly compared DEGs in an oxidative stress model of cultured NSCs by bulk and single cell sequencing. While both methods yielded DEGs that were replicable, single cell sequencing using the 10X Chromium platform yielded DEGs derived from genes with higher relative transcript counts compared to non-DEGs and exhibited smaller fold changes than DEGs identified by bulk RNAseq. The loss of high fold-change DEGs in the single cell platform presents an important limitation for identifying disease-relevant genes. To facilitate identification of such genes, we determined an RNA-input threshold that enables transcriptional profiling of NSCs comparable to standard bulk sequencing and used it to establish a workflow for in vivo profiling of endogenous NSCs. We then applied this workflow to identify DEGs after lateral fluid percussion injury, a labor-intensive animal model of traumatic brain injury. Our work joins an emerging body of evidence suggesting that single cell RNA sequencing may underestimate the diversity of pathologic DEGs. However, our data also suggest that population level transcriptomic analysis can be adapted to capture more of these DEGs with similar efficacy and diversity as standard bulk sequencing. Together, our data and workflow will be useful for investigators interested in understanding and manipulating adult hippocampal NSC responses to various stimuli.

Rare germline copy number variants (CNVs) and breast cancer risk.

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

PP2A is a therapeutically targetable driver of cell fate decisions via a c-Myc/p21 axis in human and murine acute myeloid leukemia.

Dysregulated cellular differentiation is a hallmark of acute leukemogenesis. Phosphatases are widely suppressed in cancers but have not been traditionally associated with differentiation. In this study, we found that the silencing of protein phosphatase 2A (PP2A) directly blocks differentiation in acute myeloid leukemia (AML). Gene expression and mass cytometric profiling revealed that PP2A activation modulates cell cycle and transcriptional regulators that program terminal myeloid differentiation. Using a novel pharmacological agent, OSU-2S, in parallel with genetic approaches, we discovered that PP2A enforced c-Myc and p21 dependent terminal differentiation, proliferation arrest, and apoptosis in AML. Finally, we demonstrated that PP2A activation decreased leukemia-initiating stem cells, increased leukemic blast maturation, and improved overall survival in murine Tet2-/-Flt3ITD/WT and human cell-line derived xenograft AML models in vivo. Our findings identify the PP2A/c-Myc/p21 axis as a critical regulator of the differentiation/proliferation switch in AML that can be therapeutically targeted in malignancies with dysregulated maturation fate.

Bitbow Enables Highly Efficient Neuronal Lineage Tracing and Morphology Reconstruction in Single Drosophila Brains.

Identifying the cellular origins and mapping the dendritic and axonal arbors of neurons have been century old quests to understand the heterogeneity among these brain cells. Current Brainbow based transgenic animals take the advantage of multispectral labeling to differentiate neighboring cells or lineages, however, their applications are limited by the color capacity. To improve the analysis throughput, we designed Bitbow, a digital format of Brainbow which exponentially expands the color palette to provide tens of thousands of spectrally resolved unique labels. We generated transgenic Bitbow Drosophila lines, established statistical tools, and streamlined sample preparation, image processing, and data analysis pipelines to conveniently mapping neural lineages, studying neuronal morphology and revealing neural network patterns with unprecedented speed, scale, and resolution.

RNAscope compatibility with image analysis platforms for the quantification of tissue-based colorectal cancer biomarkers in archival formalin-fixed paraffin-embedded tissue.

RNAscope®, has emerged as an important in-situ hybridisation method to validate mRNA expression within single cells whilst preserving tissue morphology in histological samples. The aim of this research was to compare the utility of various open-source and commercial image analysis methods, to quantify mRNA transcripts identified by RNAscope within formalin fixed paraffin embedded (FFPE) histological samples and cell monolayer preparations. Examination of MLH1 expression from 10 histological FFPE colorectal cancer specimens using four image analysis tools (Colour Deconvolution, SpotStudio, WEKA and the LEICA RNA-ISH algorithm) showed the WEKA tool as having the greatest level of agreement with manual quantification. Comparing image analysis methods to qRT-PCR for quantifying MLH1, GFI1 and TNFRSF11A expression within two colorectal cell lines results suggest that these image analysis methods perform at a similar level to qRT-PCR. Furthermore, we describe the strengths and limitations for each image analysis method when used in combination with RNAscope assays. Our study concludes that there are several freely available and commercial image analysis tools that enable reliable RNA in situ expression analysis, however operators need to consider factors, such as expected expression levels of target genes, software usability and functionality.

Increased gene expression variability in BRCA1-associated and basal-like breast tumours.

PURPOSE: Inherited variants in the cancer susceptibility genes, BRCA1 and BRCA2 account for up to 5% of breast cancers. Multiple gene expression studies have analysed gene expression patterns that maybe associated with BRCA12 pathogenic variant status; however, results from these studies lack consensus. These studies have focused on the differences in population means to identified genes associated with BRCA1/2-carriers with little consideration for gene expression variability, which is also under genetic control and is a feature of cellular function. METHODS: We measured differential gene expression variability in three of the largest familial breast cancer datasets and a 2116 breast cancer meta-cohort. Additionally, we used RNA in situ hybridisation to confirm expression variability of EN1 in an independent cohort of more than 500 breast tumours. RESULTS: BRCA1-associated breast tumours exhibited a 22.8% (95% CI 22.3-23.2) increase in transcriptome-wide gene expression variability compared to BRCAx tumours. Additionally, 40 genes were associated with BRCA1-related breast cancers that had ChIP-seq data suggestive of enriched EZH2 binding. Of these, two genes (EN1 and IGF2BP3) were significantly variable in both BRCA1-associated and basal-like breast tumours. RNA in situ analysis of EN1 supported a significant (p = 6.3 × 10-04) increase in expression variability in BRCA1-associated breast tumours. CONCLUSION: Our novel results describe a state of increased gene expression variability in BRCA1-related and basal-like breast tumours. Furthermore, genes with increased variability may be driven by changes in DNA occupancy of epigenetic effectors. The variation in gene expression is replicable and led to the identification of novel associations between genes and disease phenotypes.

The molecular landscape of neural differentiation in the developing Drosophila brain revealed by targeted scRNA-seq and multi-informatic analysis.

The Drosophila type II neuroblast lineages present an attractive model to investigate the neurogenesis and differentiation process as they adapt to a process similar to that in the human outer subventricular zone. We perform targeted single-cell mRNA sequencing in third instar larval brains to study this process of the type II NB lineage. Combining prior knowledge, in silico analyses, and in situ validation, our multi-informatic investigation describes the molecular landscape from a single developmental snapshot. 17 markers are identified to differentiate distinct maturation stages. 30 markers are identified to specify the stem cell origin and/or cell division numbers of INPs, and at least 12 neuronal subtypes are identified. To foster future discoveries, we provide annotated tables of pairwise gene-gene correlation in single cells and MiCV, a web tool for interactively analyzing scRNA-seq datasets. Taken together, these resources advance our understanding of the neural differentiation process at the molecular level.

Variable expression quantitative trait loci analysis of breast cancer risk variants.

Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations (p < 5 × 10-8) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes (CYP11B1, CYP17A1 HSD3B2 and STAR) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO, suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.

Differential Expression of BARD1 Isoforms in Melanoma.

Melanoma comprises <5% of cutaneous malignancies, yet it causes a significant proportion of skin cancer-related deaths worldwide. While new therapies for melanoma have been developed, not all patients respond well. Thus, further research is required to better predict patient outcomes. Using long-range nanopore sequencing, RT-qPCR, and RNA sequencing analyses, we examined the transcription of BARD1 splice isoforms in melanoma cell lines and patient tissue samples. Seventy-six BARD1 mRNA variants were identified in total, with several previously characterised isoforms (γ, φ, δ, ε, and η) contributing to a large proportion of the expressed transcripts. In addition, we identified four novel splice events, namely, Δ(E3_E9), ▼(i8), IVS10+131▼46, and IVS10▼176, occurring in various combinations in multiple transcripts. We found that short-read RNA-Seq analyses were limited in their ability to predict isoforms containing multiple non-contiguous splicing events, as compared to long-range nanopore sequencing. These studies suggest that further investigations into the functional significance of the identified BARD1 splice variants in melanoma are warranted.