Missense RHD single nucleotide variants induce weakened D antigen expression by altering splicing and/or protein expression

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

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Unsuspected somatic mosaicism for FBN1 gene contributes to Marfan syndrome

Genetics in Medicine ◽

10.1038/s41436-020-01078-6 ◽

2021 ◽

Author(s):

Pauline Arnaud ◽

Hélène Morel ◽

Olivier Milleron ◽

Laurent Gouya ◽

Christine Francannet ◽

...

Keyword(s):

Marfan Syndrome ◽

Somatic Mosaicism ◽

Variant Calling ◽

Copy Number Variations ◽

Pathogenic Variant ◽

Single Nucleotide Variants ◽

Bioinformatics Analyses ◽

Single Nucleotide ◽

Fbn1 Gene ◽

Pathogenic Variants

Abstract Purpose Individuals with mosaic pathogenic variants in the FBN1 gene are mainly described in the course of familial screening. In the literature, almost all these mosaic individuals are asymptomatic. In this study, we report the experience of our team on more than 5,000 Marfan syndrome (MFS) probands. Methods Next-generation sequencing (NGS) capture technology allowed us to identify five cases of MFS probands who harbored a mosaic pathogenic variant in the FBN1 gene. Results These five sporadic mosaic probands displayed classical features usually seen in Marfan syndrome. Combined with the results of the literature, these rare findings concerned both single-nucleotide variants and copy-number variations. Conclusion This underestimated finding should not be overlooked in the molecular diagnosis of MFS patients and warrants an adaptation of the parameters used in bioinformatics analyses. The five present cases of symptomatic MFS probands harboring a mosaic FBN1 pathogenic variant reinforce the fact that apparently asymptomatic mosaic parents should have a complete clinical examination and a regular cardiovascular follow-up. We advise that individuals with a typical MFS for whom no single-nucleotide pathogenic variant or exon deletion/duplication was identified should be tested by NGS capture panel with an adapted variant calling analysis.

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Whole-exome mutational landscape of neuroendocrine carcinomas of the gallbladder

Signal Transduction and Targeted Therapy ◽

10.1038/s41392-020-00412-3 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Fatao Liu ◽

Yongsheng Li ◽

Dongjian Ying ◽

Shimei Qiu ◽

Yong He ◽

...

Keyword(s):

Gene Mutations ◽

Large Cell ◽

Molecular Signatures ◽

Single Nucleotide Variants ◽

Oncogenic Signaling ◽

Single Nucleotide ◽

Whole Exome ◽

Deadly Disease ◽

Oncogenic Signaling Pathways ◽

Neuroendocrine Carcinomas

AbstractNeuroendocrine carcinoma (NEC) of the gallbladder (GB-NEC) is a rare but extremely malignant subtype of gallbladder cancer (GBC). The genetic and molecular signatures of GB-NEC are poorly understood; thus, molecular targeting is currently unavailable. In the present study, we applied whole-exome sequencing (WES) technology to detect gene mutations and predicted somatic single-nucleotide variants (SNVs) in 15 cases of GB-NEC and 22 cases of general GBC. In 15 GB-NECs, the C > T mutation was predominant among the 6 types of SNVs. TP53 showed the highest mutation frequency (73%, 11/15). Compared with neuroendocrine carcinomas of other organs, significantly mutated genes (SMGs) in GB-NECs were more similar to those in pulmonary large-cell neuroendocrine carcinomas (LCNECs), with driver roles for TP53 and RB1. In the COSMIC database of cancer-related genes, 211 genes were mutated. Strikingly, RB1 (4/15, 27%) and NAB2 (3/15, 20%) mutations were found specifically in GB-NECs; in contrast, mutations in 29 genes, including ERBB2 and ERBB3, were identified exclusively in GBC. Mutations in RB1 and NAB2 were significantly related to downregulation of the RB1 and NAB2 proteins, respectively, according to immunohistochemical (IHC) data (p values = 0.0453 and 0.0303). Clinically actionable genes indicated 23 mutated genes, including ALK, BRCA1, and BRCA2. In addition, potential somatic SNVs predicted by ISOWN and SomVarIUS constituted 6 primary COSMIC mutation signatures (1, 3, 30, 6, 7, and 13) in GB-NEC. Genes carrying somatic SNVs were enriched mainly in oncogenic signaling pathways involving the Notch, WNT, Hippo, and RTK-RAS pathways. In summary, we have systematically identified the mutation landscape of GB-NEC, and these findings may provide mechanistic insights into the specific pathogenesis of this deadly disease.

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scSNV: accurate dscRNA-seq SNV co-expression analysis using duplicate tag collapsing

Genome Biology ◽

10.1186/s13059-021-02364-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Gavin W. Wilson ◽

Mathieu Derouet ◽

Gail E. Darling ◽

Jonathan C. Yeung

Keyword(s):

Genetic Variants ◽

False Positive ◽

Variant Calling ◽

Call Rate ◽

Rna Seq ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Variant Call ◽

Two Samples ◽

Co Detection

AbstractIdentifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples.

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173 The role of an intronic single nucleotide polymorphism within the dopamine receptor type-2 gene on pituitary prolactin protein expression in bulls

Journal of Animal Science ◽

10.1093/jas/skz397.085 ◽

2020 ◽

Vol 98 (Supplement_2) ◽

pp. 37-37

Author(s):

Andrea N DeCarlo ◽

Keelee J McCarty ◽

Sarah K Richey ◽

Nathan Long ◽

Scott Pratt

Keyword(s):

Protein Expression ◽

Genotype Distribution ◽

Nucleotide Polymorphisms ◽

Genotypic Effect ◽

Single Nucleotide ◽

Detection Range ◽

Cull Cows ◽

Densitometry Analysis ◽

Pcr Products

Abstract Detrimental effects to male reproductive physiology have been observed due to changes in prolactin (PRL) serum concentration. Regulation of PRL by dopamine binding to the dopamine type-2 receptor (DRD2) is well defined and associations between male physiology and single nucleotide polymorphisms (SNPs) within the DRD2 gene have been observed. The objective of the study was to evaluate association of a DRD2 SNP to PRL protein expression in bulls. Testis and epididymis were collected from bulls grazing a forage containing or lacking a dopamine agonist at the end of a 126 d study (n = 14). Bovine pituitaries (n = 587) were collected randomly over 3 mo from a local abattoir which processes cull cows and bulls. Sex of pituitaries was verified (n = 259 males) by duplex PCR for amplification of SRY and b-actin followed by Southern blotting of PCR products for selection of male. Prolactin protein expression was assessed in testis, epididymis, and pituitary by western blotting. Expression of PRL protein was below detection range in reproductive tissues but was present in pituitary, therefore experiments continued in pituitary. Restriction fragment length polymorphism genotyping was performed on pituitaries by amplification of the DRD2 SNP region followed by digestion with a Tfil enzyme. Digested of products produced 3,2, or 1 band (AG, AA, GG, respectively). A subset of male pituitaries was blotted by slot blot manifold and PRL protein expression assessed by immunodetection and densitometry analysis normalized to GAPDH expression. Pituitary genotype distribution was 17.4% AA (n = 16), 63% AG (n = 58), and 19.6% GG (n = 18). Prolactin protein expression in the pituitary was similar across genotype (P = 0.23). These findings indicate that the DRD2 SNP has no genotypic effect on PRL protein expression in bovine pituitary.

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Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology

npj Precision Oncology ◽

10.1038/s41698-021-00155-6 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Ianthe A. E. M. van Belzen ◽

Alexander Schönhuth ◽

Patrick Kemmeren ◽

Jayne Y. Hehir-Kwa

Keyword(s):

Intratumor Heterogeneity ◽

Precision Oncology ◽

Single Nucleotide Variants ◽

Full Spectrum ◽

Single Nucleotide ◽

Sequencing Technologies ◽

Cancer Genomes ◽

Genomic Aberrations

AbstractCancer is generally characterized by acquired genomic aberrations in a broad spectrum of types and sizes, ranging from single nucleotide variants to structural variants (SVs). At least 30% of cancers have a known pathogenic SV used in diagnosis or treatment stratification. However, research into the role of SVs in cancer has been limited due to difficulties in detection. Biological and computational challenges confound SV detection in cancer samples, including intratumor heterogeneity, polyploidy, and distinguishing tumor-specific SVs from germline and somatic variants present in healthy cells. Classification of tumor-specific SVs is challenging due to inconsistencies in detected breakpoints, derived variant types and biological complexity of some rearrangements. Full-spectrum SV detection with high recall and precision requires integration of multiple algorithms and sequencing technologies to rescue variants that are difficult to resolve through individual methods. Here, we explore current strategies for integrating SV callsets and to enable the use of tumor-specific SVs in precision oncology.

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SARS-CoV-2 genomic analyses in cancer patients reveal elevated intrahost genetic diversity

Virus Evolution ◽

10.1093/ve/veab013 ◽

2021 ◽

Author(s):

Juliana D Siqueira ◽

Livia R Goes ◽

Brunna M Alves ◽

Pedro S de Carvalho ◽

Claudia Cicala ◽

...

Keyword(s):

Genetic Diversity ◽

Phylogenetic Analysis ◽

Cancer Patients ◽

Disease Severity ◽

Healthcare Workers ◽

Viral Population ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Consensus Sequences ◽

Vulnerable Patients

Abstract Numerous factors have been identified to influence susceptibility to SARS-CoV-2 infection and disease severity. Cancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. We have determined the full-length SARS-CoV-2 genomic sequences of cancer patients and healthcare workers (non-cancer controls) by deep sequencing and investigated the within-host viral population of each infection, quantifying intrahost genetic diversity. Naso- and oropharyngeal SARS-CoV-2+ swabs from 57 cancer patients and 14 healthcare workers from the Brazilian National Cancer Institute were collected in April–May 2020. Complete genome amplification using ARTIC network V3 multiplex primers was performed followed by next-generation sequencing. Assemblies were conducted in Geneious R11, where consensus sequences were extracted and intrahost single nucleotide variants were identified. Maximum likelihood phylogenetic analysis was performed using PhyMLv.3.0 and lineages were classified using Pangolin and CoV-GLUE. Phylogenetic analysis showed that all but one strain belonged to clade B1.1. Four genetically linked mutations known as the globally dominant SARS-CoV-2 haplotype (C241T, C3037T, C14408T and A23403G) were found in the majority of consensus sequences. SNV signatures of previously characterized Brazilian genomes were also observed in most samples. Another 85 SNVs were found at a lower frequency (1.4-19.7%) among the consensus sequences. Cancer patients displayed a significantly higher intrahost viral genetic diversity compared to healthcare workers. This difference was independent of SARS-CoV-2 Ct values obtained at the diagnostic tests, which did not differ between the two groups. The most common nucleotide changes of intrahost SNVs in both groups were consistent with APOBEC and ADAR activities. Intrahost genetic diversity in cancer patients was not associated with disease severity, use of corticosteroids, or use of antivirals, characteristics that could influence viral diversity. Moreover, the presence of metastasis, either in general or specifically in the lung, was not associated with intrahost diversity among cancer patients. Cancer patients carried significantly higher numbers of minor variants compared to non-cancer counterparts. Further studies on SARS-CoV-2 diversity in especially vulnerable patients will shed light onto the understanding of the basis of COVID-19 different outcomes in humans.

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Association between HOX Transcript Antisense RNA Single-Nucleotide Variants and Recurrent Implantation Failure

International Journal of Molecular Sciences ◽

10.3390/ijms22063021 ◽

2021 ◽

Vol 22 (6) ◽

pp. 3021

Author(s):

Jeong Yong Lee ◽

Eun Hee Ahn ◽

Hyeon Woo Park ◽

Ji Hyang Kim ◽

Young Ran Kim ◽

...

Keyword(s):

Antisense Rna ◽

Coagulation Factors ◽

Healthy Controls ◽

Implantation Failure ◽

Single Nucleotide Variants ◽

Recurrent Implantation Failure ◽

Single Nucleotide ◽

Vitro Fertilization ◽

And Control

Recurrent implantation failure (RIF) refers to the occurrence of more than two failed in vitro fertilization–embryo transfers (IVF-ETs) in the same individual. RIF can occur for many reasons, including embryo characteristics, immunological factors, and coagulation factors. Genetics can also contribute to RIF, with some single-nucleotide variants (SNVs) reported to be associated with RIF occurrence. We examined SNVs in a long non-coding RNA, homeobox (HOX) transcript antisense RNA (HOTAIR), which is known to affect cancer development. HOTAIR regulates epigenetic outcomes through histone modifications and chromatin remodeling. We recruited 155 female RIF patients and 330 healthy controls, and genotyped HOTAIR SNVs, including rs4759314, rs920778, rs7958904, and rs1899663, in all participants. Differences in these SNVs were compared between the patient and control groups. We identified significant differences in the occurrence of heterozygous genotypes and the dominant expression model for the rs1899663 and rs7958904 SNVs between RIF patients and control subjects. These HOTAIR variants were associated with serum hemoglobin (Hgb), luteinizing hormone (LH), total cholesterol (T. chol), and blood urea nitrogen (BUN) levels, as assessed by analysis of variance (ANOVA). We analyzed the four HOTAIR SNVs and found significant differences in haplotype patterns between RIF patients and healthy controls. The results of this study showed that HOTAIR is not only associated with the development of cancer but also with pregnancy-associated diseases. This study represents the first report showing that HOTAIR is correlated with RIF.

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