Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone.

Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer.

Single-cell RNA sequencing predominantly employs short-read sequencing to characterize cell types, states and dynamics; however, it is inadequate for comprehensive characterization of RNA isoforms. Long-read sequencing technologies enable single-cell RNA isoform detection but are hampered by lower throughput and unintended sequencing of artifacts. Here we develop Single-cell Targeted Isoform Long-Read Sequencing (scTaILoR-seq), a hybridization capture method which targets over a thousand genes of interest, improving the median number of on-target transcripts per cell by 29-fold. We use scTaILoR-seq to identify and quantify RNA isoforms from ovarian cancer cell lines and primary tumors, yielding 10,796 single-cell transcriptomes. Using long-read variant calling we reveal associations of expressed single nucleotide variants (SNVs) with alternative transcript structures. Phasing of SNVs across transcripts enables the measurement of allelic imbalance within distinct cell populations. Overall, scTaILoR-seq is a long-read targeted RNA sequencing method and analytical framework for exploring transcriptional variation at single-cell resolution.

Germline homozygosity and allelic imbalance of HLA-I are common in esophagogastric adenocarcinoma and impair the repertoire of immunogenic peptides.

BACKGROUND: The individual HLA-I genotype is associated with cancer, autoimmune diseases and infections. This study elucidates the role of germline homozygosity or allelic imbalance of HLA-I loci in esophago-gastric adenocarcinoma (EGA) and determines the resulting repertoires of potentially immunogenic peptides. METHODS: HLA genotypes and sequences of either (1) 10 relevant tumor-associated antigens (TAAs) or (2) patient-specific mutation-associated neoantigens (MANAs) were used to predict good-affinity binders using an in silico approach for MHC-binding (www.iedb.org). Imbalanced or lost expression of HLA-I-A/B/C alleles was analyzed by transcriptome sequencing. FluoroSpot assays and TCR sequencing were used to determine peptide-specific T-cell responses. RESULTS: We show that germline homozygosity of HLA-I genes is significantly enriched in EGA patients (n=80) compared with an HLA-matched reference cohort (n=7605). Whereas the overall mutational burden is similar, the repertoire of potentially immunogenic peptides derived from TAAs and MANAs was lower in homozygous patients. Promiscuity of peptides binding to different HLA-I molecules was low for most TAAs and MANAs and in silico modeling of the homozygous to a heterozygous HLA genotype revealed normalized peptide repertoires. Transcriptome sequencing showed imbalanced expression of HLA-I alleles in 75% of heterozygous patients. Out of these, 33% showed complete loss of heterozygosity, whereas 66% had altered expression of only one or two HLA-I molecules. In a FluoroSpot assay, we determined that peptide-specific T-cell responses against NY-ESO-1 are derived from multiple peptides, which often exclusively bind only one HLA-I allele. CONCLUSION: The high frequency of germline homozygosity in EGA patients suggests reduced cancer immunosurveillance leading to an increased cancer risk. Therapeutic targeting of allelic imbalance of HLA-I molecules should be considered in EGA.

A gastric invasive tubular adenocarcinomatous lesion arising from foveolar-type neoplasia: molecular histogenesis.

Here, we report a rare case of a depressed lesion exhibiting both tubular differentiated adenocarcinomatous (TDA) and intraepithelial foveolar neoplasia (IFN) components (with the histological appearance of foveolar hyperplasia due to low-grade atypia). Histologically, the TDA surrounded the IFN, suggesting that the TDA may have originated from the IFN. Therefore, we examined molecular alterations in the TDA and IFN components separately. MUC5AC and MUC6 expression was observed immunohistochemically in both components. p53 expression was wild type in both components, suggesting no mutation of TP53. We investigated allelic imbalances at multiple loci (1p, 3p, 4p, 5q, 8q, 9p, 13q, TP53, 18q, and 22q), mutations (KRAS, BRAF, and GNAS), and DNA methylation and microsatellite status in both components using PCR-based analyses. Although multiple allelic imbalances were common to both components, allelic imbalances at 3p and TP53 were found only in the TDA component. No mutations were found, and DNA methylation status was low epigenotype for both components. Ultimately, this tumor was considered microsatellite stable. Considering the origin of TDA, which is frequently encountered in routine practice, IFN may develop into TDA.

Leveraging Off-Target Reads in Panel Sequencing for Homologous Recombination Repair Deficiency Screening in Tumor.

Targeted tumor only sequencing has become a standard practice in cancer diagnostics. This study aims to develop an approach for robust copy number variant calling in tumor samples using only off-target region (OTR) reads. We also established a clinical use case for homologous recombination deficiency (HRD) score estimation (HRDest) using the sum of telomeric-allelic imbalance and large-scale state transition scores without the need for loss of heterozygosity information. A strong correlation was found between HRD score and the sum of telomeric-allelic imbalance + large-scale state transition in The Cancer Genome Atlas cohort (ρ = 0.99, P < 2.2 × 10-16) and in a clinical in-house cohort of 34 tumors (ρ = 0.9, P = 5.1 × 10-13) comparing whole-exome sequencing and targeted sequencing data. HRDest scores from 1086 clinical cases were compared with The Cancer Genome Atlas data set. There were no significant differences in HRD score distribution within the analyzed tumor types. As a control, commercially available HRD standards were also sequenced, and the HRDest scores obtained from the OTR reads were well within the HRD reference range provided by the manufacturer. In conclusion, OTR reads of tumor-only panel sequencing can be used to determine genome-wide copy number variant profiles and to approximate HRD scores.

Inter-subspecies mouse F1 hybrid embryonic stem cell lines newly established for studies of allelic imbalance in gene expression.

Allele-specific monoallelic gene expression is a unique phenomenon and a great resource for analyzing gene regulation. To study this phenomenon, we established new embryonic stem (ES) cell lines derived from F1 hybrid blastocysts from crosses between four mouse subspecies (Mus musculus domesticus, C57BL/6; M. musculus molossinus, MSM/Ms; M. musculus musculus, PWK; M. musculus castaneus, HMI/Ms) and analyzed the expression levels of undifferentiated pluripotent stem cell markers and karyotypes of each line. To demonstrate the utility of our cell lines, we analyzed the allele-specific expression pattern of the Inpp5d gene as an example. The allelic expression depended on the parental alleles; this dependence could be a consequence of differences in compatibility between cis- and trans-elements of the Inpp5d gene from different subspecies. The use of parental mice from four subspecies greatly enhanced genetic polymorphism. The F1 hybrid ES cells retained this polymorphism not only in the Inpp5d gene, but also at a genome-wide level. As we demonstrated for the Inpp5d gene, the established cell lines can contribute to the analysis of allelic expression imbalance based on the incompatibility between cis- and trans-elements and of phenotypes related to this incompatibility.

Prediction of homologous recombination deficiency from Oncomine Comprehensive Assay Plus correlating with SOPHiA DDM HRD Solution.

OBJECTIVE: Poly(ADP-ribose) polymerase (PARP) inhibitors are used for targeted therapy for ovarian cancer with homologous recombination deficiency (HRD). In this study, we aimed to develop a homologous recombination deficiency prediction model to predict the genomic integrity (GI) index of the SOPHiA DDM HRD Solution from the Oncomine Comprehensive Assay (OCA) Plus. We also tried to a find cut-off value of the genomic instability metric (GIM) of the OCA Plus that correlates with the GI index of the SOPHiA DDM HRD Solution. METHODS: We included 87 cases with high-grade ovarian serous carcinoma from five tertiary referral hospitals in Republic of Korea. We developed an HRD prediction model to predict the GI index of the SOPHiA DDM HRD Solution. As predictor variables in the model, we used the HRD score, which included percent loss of heterozygosity (%LOH), percent telomeric allelic imbalance (%TAI), percent large-scale state transitions (%LST), and the genomic instability metric (GIM). To build the model, we employed a penalized logistic regression technique. RESULTS: The final model equation is -21.77 + 0.200 × GIM + 0.102 × %LOH + 0.037 × %TAI + 0.261 × %LST. To improve the performance of the prediction model, we added a borderline result category to the GI results. The accuracy of our HRD status prediction model was 0.958 for the test set. The accuracy of HRD status using GIM with a cut-off value of 16 was 0.911. CONCLUSION: The Oncomine Comprehensive Assay Plus provides a reliable biomarker for homologous recombination deficiency.

KRAS allelic imbalance drives tumour initiation yet suppresses metastasis in colorectal cancer in vivo.

Oncogenic KRAS mutations are well-described functionally and are known to drive tumorigenesis. Recent reports describe a significant prevalence of KRAS allelic imbalances or gene dosage changes in human cancers, including loss of the wild-type allele in KRAS mutant cancers. However, the role of wild-type KRAS in tumorigenesis and therapeutic response remains elusive. We report an in vivo murine model of colorectal cancer featuring deletion of wild-type Kras in the context of oncogenic Kras. Deletion of wild-type Kras exacerbates oncogenic KRAS signalling through MAPK and thus drives tumour initiation. Absence of wild-type Kras potentiates the oncogenic effect of KRASG12D, while incidentally inducing sensitivity to inhibition of MEK1/2. Importantly, loss of the wild-type allele in aggressive models of KRASG12D-driven CRC significantly alters tumour progression, and suppresses metastasis through modulation of the immune microenvironment. This study highlights the critical role for wild-type Kras upon tumour initiation, progression and therapeutic response in Kras mutant CRC.

A pan-tissue survey of mosaic chromosomal alterations in 948 individuals.

Genetic mutations accumulate in an organism's body throughout its lifetime. While somatic single-nucleotide variants have been well characterized in the human body, the patterns and consequences of large chromosomal alterations in normal tissues remain largely unknown. Here, we present a pan-tissue survey of mosaic chromosomal alterations (mCAs) in 948 healthy individuals from the Genotype-Tissue Expression project, augmenting RNA-based allelic imbalance estimation with haplotype phasing. We found that approximately a quarter of the individuals carry a clonally-expanded mCA in at least one tissue, with incidence strongly correlated with age. The prevalence and genome-wide patterns of mCAs vary considerably across tissue types, suggesting tissue-specific mutagenic exposure and selection pressures. The mCA landscapes in normal adrenal and pituitary glands resemble those in tumors arising from these tissues, whereas the same is not true for the esophagus and skin. Together, our findings show a widespread age-dependent emergence of mCAs across normal human tissues with intricate connections to tumorigenesis.

Asimetrías en jugadores alevines de fútbol de una cantera de élite: diferencias entre sexos / Assymetries in junior football players from an elite youth academy: differences between sexes

El objetivo de este estudio fue detectar las asimetrías en jugadores/as de fútbol a través de una batería de test, analizar las asimetrías del lado dominante y no dominante, y comparar la correlación entre ambos sexos. 25 jugadores de fútbol del Real Racing Club de Santander, pertenecientes a la categoría Alevín, 13 jugadoras femeninas y 12 masculinos, fueron evaluados en diferentes test neuromusculares para detectar las asimetrías del miembro inferior: Single Hop Test (SHT), Triple Hop Test (THT), Salto de contramovimiento unilateral (SLCMJ), y test de cambio de dirección (505 COD). Con el fin de identificar el índice de asimetrías (ASI) neuromusculares entre los miembros inferiores se comparó la pierna dominante (PD) con la no dominante (PND) a través de la siguiente fórmula: ASI = ((PD-PND)/PD)x100. En los hallazgos se encontraron diferencias significativas (p <0.05) al comparar las asimetrías neuromusculares entre ambos sexos en los diferentes test. En cambio, no se encontraron diferencias entre pierna dominante y no dominante. Además, se observó que un 36% de la muestra de jugadores/as obtuvo un ASI >10%, considerado un factor de mayor probabilidad de sufrir una lesión en el miembro inferior. En conclusión, se ha podido comprobar a través de este estudio que se han encontrado diferencias significativas en las asimetrías del miembro inferior en función del sexo, pero no entre la pierna dominante y no dominante. En definitiva, son necesarios más estudios donde analicen las asimetrías en diferentes sexos con el fin de obtener un mayor análisis de los resultados. (AU)

The present study uses a cross-sectional design of independent and related samples whose objectives were: to detect asymmetries in football players through a battery of tests, to analyse the asymmetries of the dominant and non-dominant side, and to compare the correlation between both sexes. A total of 25 football players from Real Racing Club de Santander belonging to the Alevín category, 13 female players and 12 male players were evaluated in different neuromuscular tests to detect lower limb asymmetries: Single Hop Test (SHT), Triple Hop Test (THT), Unilateral Countermovement Jumping (SLCMJ), and Change of Direction Test (505 COD). In order to identify the neuromuscular asymmetry index (ASI) between the lower limbs, the dominant leg (PD) was compared to the non-dominant leg (PND) using the following formula: ASI = ((PD-PND)/PD)x100. Significant differences (p<0.05) were found in the findings when comparing the neuromuscular asymmetries between both sexes in the different tests. In contrast, there is no difference between dominant and non-dominant leg. In addition, it was observed that 36% of the sample of players had an ASI >10%, which is considered to be a factor of increased likelihood of lower limb injury. The highest asymmetry was detected at 20% in the SLCMJ test, which may be the most suitable jump test for identifying asymmetries. In conclusion, this study has shown that significant differences were found in lower limb asymmetries according to sex, but not between the dominant and non-dominant leg. (AU)

SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty.

Detecting allelic imbalance at the isoform level requires accounting for inferential uncertainty, caused by multi-mapping of RNA-seq reads. Our proposed method, SEESAW, uses Salmon and Swish to offer analysis at various levels of resolution, including gene, isoform, and aggregating isoforms to groups by transcription start site. The aggregation strategies strengthen the signal for transcripts with high uncertainty. The SEESAW suite of methods is shown to have higher power than other allelic imbalance methods when there is isoform-level allelic imbalance. We also introduce a new test for detecting imbalance that varies across a covariate, such as time.

Genetic analysis and allele-specific expression of SMAD7 3'UTR variants in human colorectal cancer reveal a novel somatic variant exhibiting allelic imbalance.

BACKGROUND: Considering the impact of SMAD7 deregulation in colorectal cancer (CRC) progression and the significance of single nucleotide variant (SNV)-mediated disruptions of microRNA (miRNA)-dependent regulation for cancer susceptibility, our study aimed to analyze genetic variation in the SMAD7 3' untranslated region ( 3'UTR) in CRC, measure differences in allelic mRNA expression, and evaluate its interference with miRNA-mediated post-transcriptional regulation. PATIENTS AND METHODS: This study included 80 patients with different CRC stages and six human colon cancer cell lines of various histological origins. SMAD7 3'UTR was analyzed by direct sequencing, followed by the relative quantification of differential allelic expression of detected variants by allele-specific qRT-PCR. In silico tools were employed for predictions of regulatory consequences of detected variants. RESULTS: A total of four different SNVs in one cell line and nine patients were found, among which were a novel somatic point variant and three already known germline variants (rs16950113, rs1050799536, and rs1043778717). All evaluated SNVs exhibited variable extents of allelic imbalance in expression. In silico analysis predicted significant effects of SNVs on miRNA binding efficiency, with each SNV disrupting existing and creating new target sites for one or more miRNAs. CONCLUSION: Imbalance observed in the expression of SNV alleles altering miRNA binding suggests that all investigated SNVs are potential contributing factors impacting SMAD7 expression regulation in CRC that further studies should investigate.

Diagnostic and therapeutic potential of RNASET2 in Crohn's disease: Disease-risk polymorphism modulates allelic-imbalance in expression and circulating protein levels and recombinant-RNASET2 attenuates pro-inflammatory cytokine secretion.

Ribonuclease T2 gene (RNASET2) variants are associated in genome wide association studies (GWAS) with risk for several autoimmune diseases, including Crohn's disease (CD). In T cells, a functional and biological relationship exists between TNFSF15-mediated enhancement of IFN-γ production, mucosal inflammation and RNASET2. Disease risk variants are associated with decreased mRNA expression and clinical characteristics of severe CD; however, functional classifications of variants and underlying molecular mechanisms contributing to pathogenesis remain largely unknown. In this study we demonstrate that allelic imbalance of RNASET2 disease risk variant rs2149092 is associated with transcriptional and post-transcriptional mechanisms regulating transcription factor binding, promoter-transactivation and allele-specific expression. RNASET2 mRNA expression decreases in response to multiple modes of T cell activation and recovers following elimination of activator. In CD patients with severe disease necessitating surgical intervention, preoperative circulating RNASET2 protein levels were decreased compared to non-IBD subjects and rebounded post-operatively following removal of the inflamed region, with levels associated with allelic carriage. Furthermore, overexpression or treatment with recombinant RNASET2 significantly reduced IFN-γ secretion. These findings reveal that RNASET2 cis- and trans-acting variation contributed regulatory complexity and determined expression and provide a basis for linking genetic variation with CD pathobiology. These data may ultimately identify RNASET2 as an effective therapeutic target in a subset of CD patients with severe disease.

Precise identification of cancer cells from allelic imbalances in single cell transcriptomes.

A fundamental step of tumour single cell mRNA analysis is separating cancer and non-cancer cells. We show that the common approach to separation, using shifts in average expression, can lead to erroneous biological conclusions. By contrast, allelic imbalances representing copy number changes directly detect the cancer genotype and accurately separate cancer from non-cancer cells. Our findings provide a definitive approach to identifying cancer cells from single cell mRNA sequencing data.

Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms.

While many germline cancer risk variants have been identified through genome-wide association studies (GWAS), the mechanisms by which these variants operate remain largely unknown. Here we used 406 cancer ATAC-Seq samples across 23 cancer types to identify 7,262 germline allele-specific accessibility QTLs (as-aQTLs). Cancer as-aQTLs had stronger enrichment for cancer risk heritability (up to 145 fold) than any other functional annotation across seven cancer GWAS. Most cancer as-aQTLs directly altered transcription factor (TF) motifs and exhibited differential TF binding and gene expression in functional screens. To connect as-aQTLs to putative risk mechanisms, we introduced the regulome-wide associations study (RWAS). RWAS identified genetically associated accessible peaks at >70% of known breast and prostate loci and discovered new risk loci in all examined cancer types. Integrating as-aQTL discovery, motif analysis and RWAS identified candidate causal regulatory elements and their probable upstream regulators. Our work establishes cancer as-aQTLs and RWAS analysis as powerful tools to study the genetic architecture of cancer risk.

Association between germline variants and somatic mutations in colorectal cancer.

Colorectal cancer (CRC) is a heterogeneous disease with evidence of distinct tumor types that develop through different somatically altered pathways. To better understand the impact of the host genome on somatically mutated genes and pathways, we assessed associations of germline variations with somatic events via two complementary approaches. We first analyzed the association between individual germline genetic variants and the presence of non-silent somatic mutations in genes in 1375 CRC cases with genome-wide SNPs data and a tumor sequencing panel targeting 205 genes. In the second analysis, we tested if germline variants located within previously identified regions of somatic allelic imbalance were associated with overall CRC risk using summary statistics from a recent large scale GWAS (n≃125 k CRC cases and controls). The first analysis revealed that a variant (rs78963230) located within a CNA region associated with TLR3 was also associated with a non-silent mutation within gene FBXW7. In the secondary analysis, the variant rs2302274 located in CDX1/PDGFRB frequently gained/lost in colorectal tumors was associated with overall CRC risk (OR = 0.96, p = 7.50e-7). In summary, we demonstrate that an integrative analysis of somatic and germline variation can lead to new insights about CRC.

Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets.

MOTIVATION: Allelic expression analysis aids in detection of cis-regulatory mechanisms of genetic variation, which produce allelic imbalance (AI) in heterozygotes. Measuring AI in bulk data lacking time or spatial resolution has the limitation that cell-type-specific (CTS), spatial- or time-dependent AI signals may be dampened or not detected. RESULTS: We introduce a statistical method airpart for identifying differential CTS AI from single-cell RNA-sequencing data, or dynamics AI from other spatially or time-resolved datasets. airpart outputs discrete partitions of data, pointing to groups of genes and cells under common mechanisms of cis-genetic regulation. In order to account for low counts in single-cell data, our method uses a Generalized Fused Lasso with Binomial likelihood for partitioning groups of cells by AI signal, and a hierarchical Bayesian model for AI statistical inference. In simulation, airpart accurately detected partitions of cell types by their AI and had lower Root Mean Square Error (RMSE) of allelic ratio estimates than existing methods. In real data, airpart identified differential allelic imbalance patterns across cell states and could be used to define trends of AI signal over spatial or time axes. AVAILABILITY AND IMPLEMENTATION: The airpart package is available as an R/Bioconductor package at https://bioconductor.org/packages/airpart. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Allelic imbalance of HLA-B expression in human lung cells infected with coronavirus and other respiratory viruses.

The human leucocyte antigen (HLA) loci have been widely characterized to be associated with viral infectious diseases using either HLA allele frequency-based association or in silico predicted studies. However, there is less experimental evidence to link the HLA alleles with COVID-19 and other respiratory infectious diseases, particularly in the lung cells. To examine the role of HLA alleles in response to coronavirus and other respiratory viral infections in disease-relevant cells, we designed a two-stage study by integrating publicly accessible RNA-seq data sets, and performed allelic expression (AE) analysis on heterozygous HLA genotypes. We discovered an increased AE pattern accompanied with overexpression of HLA-B gene in SARS-CoV-2-infected human lung epithelial cells. Analysis of independent data sets verified the respiratory virus-induced AE of HLA-B gene in lung cells and tissues. The results were further experimentally validated in cultured lung cells infected with SARS-CoV-2. We further uncovered that the antiviral cytokine IFNß contribute to AE of the HLA-B gene in lung cells. Our analyses provide a new insight into allelic influence on the HLA expression in association with SARS-CoV-2 and other common viral infectious diseases.

Interpreting coronary artery disease GWAS results: A functional genomics approach assessing biological significance.

Genome-wide association studies (GWAS) have implicated 58 loci in coronary artery disease (CAD). However, the biological basis for these associations, the relevant genes, and causative variants often remain uncertain. Since the vast majority of GWAS loci reside outside coding regions, most exert regulatory functions. Here we explore the complexity of each of these loci, using tissue specific RNA sequencing data from GTEx to identify genes that exhibit altered expression patterns in the context of GWAS-significant loci, expanding the list of candidate genes from the 75 currently annotated by GWAS to 245, with almost half of these transcripts being non-coding. Tissue specific allelic expression imbalance data, also from GTEx, allows us to uncover GWAS variants that mark functional variation in a locus, e.g., rs7528419 residing in the SORT1 locus, in liver specifically, and rs72689147 in the GUYC1A1 locus, across a variety of tissues. We consider the GWAS variant rs1412444 in the LIPA locus in more detail as an example, probing tissue and transcript specific effects of genetic variation in the region. By evaluating linkage disequilibrium (LD) between tissue specific eQTLs, we reveal evidence for multiple functional variants within loci. We identify 3 variants (rs1412444, rs1051338, rs2250781) that when considered together, each improve the ability to account for LIPA gene expression, suggesting multiple interacting factors. These results refine the assignment of 58 GWAS loci to likely causative variants in a handful of cases and for the remainder help to re-prioritize associated genes and RNA isoforms, suggesting that ncRNAs maybe a relevant transcript in almost half of CAD GWAS results. Our findings support a multi-factorial system where a single variant can influence multiple genes and each genes is regulated by multiple variants.