Variations on a theme: cataloging human DNA sequence variation

Association between programmed death protein 1-related single-nucleotide polymorphisms and immune-related adverse events induced by programmed death protein 1 inhibitors-a pilot study

Programmed death protein 1 (PD-1) inhibitors have potent anti-tumor activities. However, they often result in immune-related adverse events (irAEs) of varying severity. Therefore, the factors affecting the incidence of irAEs warrant urgent investigation. This study aimed to identify specific and sensitive predictors of irAEs in a Chinese population. We conducted a genome-wide association study (GWAS) comprising 80 patients with malignant tumors to evaluate single-nucleotide polymorphism (SNP) loci associated with the incidence of irAEs. The SNP rs2157775 on the LOC339166 gene had the lowest P value but did not reach the significance threshold after Bonferroni correction. Therefore, potentially associated SNPs were further investigated through the mechanism-related PD-1 pathway using the ImmPort and PathCards Human Gene Databases. A binary logistic regression model revealed that CD3E (rs3782040) A/A was associated with a lower incidence of irAEs in patients with malignant tumors who received PD-1 inhibitors. In contrast, PTPN11 (rs143894582) C/CA was associated with a higher incidence of irAEs. These findings provide a basis for the verification and identification of new loci to provide insight into the etiology of irAEs.

Association between BCL2 interacting protein 3 like (BNIP3L) genetic polymorphisms and the risk of multiple myeloma in China

BACKGROUND

The BCL2 interacting protein 3-like (BNIP3L) protein is involved in multiple myeloma (MM) development and progression. This study aims to explore the connection between BNIP3L single-nucleotide polymorphisms (SNPs) and MM.

METHODS

SNaPshot was used to examine six SNP loci of the BNIP3L gene in enrolled subjects. The relationship between these loci and MM susceptibility and prognosis was explored. Survival analysis was used to evaluate the impact of different factors on patient survival.

RESULTS

The rs2874670 AA genotype and A allele were associated with increased MM risk (P < 0.05). The CCACAC haplotype had a higher frequency in MM, while CCGCAC had a higher frequency in normal patients (all P < 0.05). Patients with R-ISS stage I and II had higher survival rates than those with stage III (P < 0.05). Patients, who received chemotherapy followed by autologous stem cell transplantation, had longer survival time than those who only received chemotherapy (P < 0.05). Low levels of LDH and β2-MG were associated with better survival rates (P < 0.05). Cox regression identified that LDH levels, β2-MG levels, and R-ISS staging were the risk factors for the death of MM. Mann-Whitney U test found a significant difference in survival time between MM patients with different BNIP3L rs2874670 genotypes after BD chemotherapy (P < 0.05).

CONCLUSION

To our knowledge, this is the first study to find that BNIP3L rs2874670 could increase MM susceptibility in China. Different BNIP3L rs2874670 genotypes may affect the prognosis of MM patients receiving BD chemotherapy.

Models for depression recognition and efficacy assessment based on clinical and sequencing data

Major depression is a complex psychiatric disorder that includes genetic, neurological, and cognitive factors. Early detection and intervention can prevent progression, and help select the best treatment. Traditional clinical diagnosis tends to be subjective and misdiagnosed. Based on this, this study leverages clinical scale assessments and sequencing data to construct disease prediction models. Firstly, data undergoes preprocessing involving normalization and other requisite procedures. Feature engineering is then applied to curate subsets of features, culminating in the construction of a model through the implementation of machine learning and deep learning algorithms. In this study, 18 features with significant differences between patients and healthy controls were selected. The depression recognition model was constructed by deep learning with an accuracy of 87.26 % and an AUC of 91.56 %, which can effectively distinguish patients with depression from healthy controls. In addition, 33 features selected by recursive feature elimination method were used to construct a prognostic effect model of patients after 2 weeks of treatment, with an accuracy of 75.94 % and an AUC of 83.33 %. The results show that the deep learning algorithm based on clinical and sequencing data has good accuracy and provides an objective and accurate method for the diagnosis and pharmacodynamic prediction of depression. Furthermore, the selected differential features can serve as candidate biomarkers to provide valuable clues for diagnosis and efficacy prediction.

Prediction of Deleterious Single Amino Acid Polymorphisms with a Consensus Holdout Sampler

Background

Single Amino Acid Polymorphisms (SAPs) or nonsynonymous Single Nucleotide Variants (nsSNVs) are the most common genetic variations. They result from missense mutations where a single base pair substitution changes the genetic code in such a way that the triplet of bases (codon) at a given position is coding a different amino acid. Since genetic mutations sometimes cause genetic diseases, it is important to comprehend and foresee which variations are harmful and which ones are neutral (not causing changes in the phenotype). This can be posed as a classification problem.

Methods

Computational methods using machine intelligence are gradually replacing repetitive and exceedingly overpriced mutagenic tests. By and large, uneven quality, deficiencies, and irregularities of nsSNVs datasets debase the convenience of artificial intelligence-based methods. Subsequently, strong and more exact approaches are needed to address these problems. In the present work paper, we show a consensus classifier built on the holdout sampler, which appears strong and precise and outflanks all other popular methods.

Results

We produced 100 holdouts to test the structures and diverse classification variables of diverse classifiers during the training phase. The finest performing holdouts were chosen to develop a consensus classifier and tested using a k-fold (1 ≤ k ≤5) cross-validation method. We also examined which protein properties have the biggest impact on the precise prediction of the effects of nsSNVs.

Conclusion

Our Consensus Holdout Sampler outflanks other popular algorithms, and gives excellent results, highly accurate with low standard deviation. The advantage of our method emerges from using a tree of holdouts, where diverse LM/AI-based programs are sampled in diverse ways.

Identification of novel genetic variations in ABCB6 and GRN genes associated with HIV-associated lipodystrophy

Protease inhibitors (PIs) are associated with an incidence of lipodystrophy among people living with HIV(PLHIV). Lipodystrophiesare characterised by the loss of adipose tissue. Evidence suggests that a patient's lipodystrophy phenotype is influenced by genetic mutation, age, gender, and environmental and genetic factors, such as single-nucleotide variants (SNVs). Pathogenic variants are considered to cause a more significant loss of adipose tissue compared to non-pathogenic. Lipid metabolising enzymes and transporter genes have a role in regulating lipoprotein metabolism and have been associated with lipodystrophy in HIV-infected patients (LDHIV). The long-term effect of the lipodystrophy syndrome is related to cardiovascular diseases (CVDs). Hence, we determined the SNVs of lipid metabolising enzymes and transporter genes in a total of 48 patient samples, of which 24 were with and 24 were without HIV-associated lipodystrophy (HIVLD) using next-generation sequencing. A panel of lipid metabolism, transport and elimination genes were sequenced. Three novel heterozygous non-synonymous variants at exon 8 (c.C1400A:p.S467Y, c.G1385A:p.G462E, and c.T1339C:p.S447P) in the ABCB6 gene were identified in patients with lipodystrophy. One homozygous non-synonymous SNV (exon5:c.T358C:p.S120P) in the GRN gene was identified in patients with lipodystrophy. One novelstop-gain SNV (exon5:c.C373T:p.Q125X) was found in the GRN gene among patients without lipodystrophy. Patients without lipodystrophy had one homozygous non-synonymous SNV (exon9:c.G1462T:p.G488C) in the ABCB6 gene. Our findings suggest that novel heterozygous non-synonymous variants in the ABCB6 gene may contribute to defective protein production, potentially intensifying the severity of lipodystrophy. Additionally, identifying a stop-gain SNV in the GRN gene among patients without lipodystrophy implies a potential role in the development of HIVLD.

Breaking genetic shackles: The advance of base editing in genetic disorder treatment

The rapid evolution of gene editing technology has markedly improved the outlook for treating genetic diseases. Base editing, recognized as an exceptionally precise genetic modification tool, is emerging as a focus in the realm of genetic disease therapy. We provide a comprehensive overview of the fundamental principles and delivery methods of cytosine base editors (CBE), adenine base editors (ABE), and RNA base editors, with a particular focus on their applications and recent research advances in the treatment of genetic diseases. We have also explored the potential challenges faced by base editing technology in treatment, including aspects such as targeting specificity, safety, and efficacy, and have enumerated a series of possible solutions to propel the clinical translation of base editing technology. In conclusion, this article not only underscores the present state of base editing technology but also envisions its tremendous potential in the future, providing a novel perspective on the treatment of genetic diseases. It underscores the vast potential of base editing technology in the realm of genetic medicine, providing support for the progression of gene medicine and the development of innovative approaches to genetic disease therapy.

C and G are frequently mutated into T and A in coding regions of human genes

Nucleotide mutations in human genes have long been a hot subject for study because some of them may lead to severe human diseases. Understanding the general mutational process and evolutionary trend of human genes could help answer such questions as why certain diseases occur and what challenges we face in protecting human health. In this study, we conducted statistics on 89,895 single-nucleotide variations identified in coding regions of 18,339 human genes. The results show that C and G are frequently mutated into T and A in human genes. C/G (C or G)-to-T/A mutations lead to reduction of hydrogen bonds in double-stranded DNA because C-G and T-A base pairs are maintained by three and two hydrogen bonds respectively. C-to-T and G-to-A mutations occur predominantly in human genes because they not only reduce hydrogen bonds but also belong to transition mutation. Reduction of hydrogen bonds could reduce energy consumption not only in separating double strands of mutated DNA for transcription and replication but also in disrupting stem-loop structure of mutated mRNA for translation. It is thus considered that to reduce hydrogen bonds (and thus to reduce energy consumption in gene expression) is one of the driving forces for nucleotide mutation. Moreover, codon mutation is positively correlated to its content, suggesting that most mutations are not targeted on changing any specific codons (amino acids) but are merely for reducing hydrogen bonds. Our study provides an example of utilizing single-nucleotide variation data to infer evolutionary trend of human genes, which can be referenced to conduct similar studies in other organisms.

The Emerging Role of Toll-Like Receptor-Mediated Neuroinflammatory Signals in Psychiatric Disorders and Acquired Epilepsy

The new and evolving paradigms of psychiatric disorders pathogenesis are deeply inclined toward chronic inflammation that leads to disturbances in the neuronal networks of patients. A strong association has been established between the inflammation and neurobiology of depression which is mediated by different toll-like receptors (TLRs). TLRs and associated signalling pathways are identified as key immune regulators to stress and infections in neurobiology. They are a special class of transmembrane proteins, which are one of the broadly studied members of the Pattern Recognition Patterns family. This review focuses on summarizing the important findings on the role of TLRs associated with psychotic disorders and acquired epilepsy. This review also shows the promising potential of TLRs in immune response mediated through antidepressant therapies and TLRs polymorphism associated with various psychotic disorders. Moreover, this also sheds light on future directions to further target TLRs as a therapeutic approach for psychiatric disorders.

Fluid protein fold space and its implications

Fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli, suggest a new view of protein fold space. For decades, experimental evidence has indicated that protein fold space is discrete: dissimilar folds are encoded by dissimilar amino acid sequences. Challenging this assumption, fold-switching proteins interconnect discrete groups of dissimilar protein folds, making protein fold space fluid. Three recent observations support the concept of fluid fold space: (1) some amino acid sequences interconvert between folds with distinct secondary structures, (2) some naturally occurring sequences have switched folds by stepwise mutation, and (3) fold switching is evolutionarily selected and likely confers advantage. These observations indicate that minor amino acid sequence modifications can transform protein structure and function. Consequently, proteomic structural and functional diversity may be expanded by alternative splicing, small nucleotide polymorphisms, post-translational modifications, and modified translation rates.

Role of CD93 in Health and Disease

CD93 (also known as complement protein 1 q subcomponent receptor C1qR1 or C1qRp), is a transmembrane glycoprotein encoded by a gene located on 20p11.21 and composed of 652 amino acids. CD93 can be present in two forms: soluble (sCD93) and membrane-bound (CD93). CD93 is mainly expressed on endothelial cells, where it plays a key role in promoting angiogenesis both in physiology and disease, such as age-related macular degeneration and tumor angiogenesis. In fact, CD93 is highly expressed in tumor-associated vessels and its presence correlates with a poor prognosis, poor immunotherapy response, immune cell infiltration and high tumor, node and metastasis (TNM) stage in many cancer types. CD93 is also expressed in hematopoietic stem cells, cytotrophoblast cells, platelets and many immune cells, i.e., monocytes, neutrophils, B cells and natural killer (NK) cells. Accordingly, CD93 is involved in modulating important inflammatory-associated diseases including systemic sclerosis and neuroinflammation. Finally, CD93 plays a role in cardiovascular disease development and progression. In this article, we reviewed the current literature regarding the role of CD93 in modulating angiogenesis, inflammation and tumor growth in order to understand where this glycoprotein could be a potential therapeutic target and could modify the outcome of the abovementioned pathologies.

The Role of NQO1 in Ovarian Cancer

Ovarian cancer is one of the most dangerous gynecologic malignancies showing a high fatality rate because of late diagnosis and relapse occurrence due to chemoresistance onset. Several researchers reported that oxidative stress plays a key role in ovarian cancer occurrence, growth and development. The NAD(P)H:quinone oxidoreductase 1 (NQO1) is an antioxidant enzyme that, using NADH or NADPH as substrates to reduce quinones to hydroquinones, avoids the formation of the highly reactive semiquinones, then protecting cells against oxidative stress. In this review, we report evidence from the literature describing the effect of NQO1 on ovarian cancer onset and progression.

Celebrating a Century of Research in Behavioral Genetics

A century after the first twin and adoption studies of behavior in the 1920s, this review looks back on the journey and celebrates milestones in behavioral genetic research. After a whistle-stop tour of early quantitative genetic research and the parallel journey of molecular genetics, the travelogue focuses on the last fifty years. Just as quantitative genetic discoveries were beginning to slow down in the 1990s, molecular genetics made it possible to assess DNA variation directly. From a rocky start with candidate gene association research, by 2005 the technological advance of DNA microarrays enabled genome-wide association studies, which have successfully identified some of the DNA variants that contribute to the ubiquitous heritability of behavioral traits. The ability to aggregate the effects of thousands of DNA variants in polygenic scores has created a DNA revolution in the behavioral sciences by making it possible to use DNA to predict individual differences in behavior from early in life.

Transcriptomic Approach for Global Distribution of SNP/Indel and Plant Genotyping

Single Nucleotide Polymorphisms (SNPs) are the most common structural variants found in any genome. They have been used for different genetic studies, from the understanding of genetic structure of populations to the development of breeding selection markers. In this chapter we present the use of transcriptomic data obtained from contrasting phenotypes for a target trait, in searching of SNPs and insertions/deletions (InDels). This approach has the advantage that the identified markers are in or close to differentially expressed genes, and so they have higher chances to tag the genes underlying the phenotypic expression of a particular trait.

Characterization of the MMP9 Gene and Its Association with Cryptocaryon irritans Resistance Traits in Trachinotus ovatus (Linnaeus, 1758)

The MMPs are endogenous proteolytic enzymes that require zinc and calcium as cofactors. MMP9 is one of the most complex matrix metalloproteinases in the gelatinase family and has many biological functions. In mammals, mmp9 is thought to be closely associated with cancer. However, studies in fish have rarely been reported. In this study, to understand the expression pattern of the ToMMP9 gene and its association with the resistance of Trachinotus ovatus to Cryptocaryon irritans, the sequence of the MMP9 gene was obtained from the genome database. The expression profiles were measured by qRT-PCR, the SNPs were screened by direct sequencing, and genotyping was performed. The ToMMP9 gene contained a 2058 bp ORF encoding a putative amino acid sequence of 685 residues. The homology of the ToMMP9 in teleosts was more than 85%, and the genome structure of ToMMP9 was conserved in chordates. The ToMMP9 gene was expressed in different tissues of healthy individuals and was highly expressed in the fin, the gill, the liver and the skin tissues. The ToMMP9 expression in the skin of the infected site and its adjacent sites increased significantly after C. irritans infection. Two SNPs were identified in the ToMMP9 gene, and the SNP (+400A/G) located in the first intron was found to be significantly associated with the susceptibility/resistance to C. irritans. These findings suggest that ToMMP9 may play an important role in the immune response of T. ovatus against C. irritans.

Successful therapeutic intervention in new mouse models of frizzled 2-associated congenital malformations

Frizzled 2 (FZD2) is a transmembrane Wnt receptor. We previously identified a pathogenic human FZD2 variant in individuals with FZD2-associated autosomal dominant Robinow syndrome. The variant encoded a protein with a premature stop and loss of 17 amino acids, including a region of the consensus dishevelled-binding sequence. To model this variant, we used zygote microinjection and i-GONAD-based CRISPR/Cas9-mediated genome editing to generate a mouse allelic series. Embryos mosaic for humanized Fzd2W553* knock-in exhibited cleft palate and shortened limbs, consistent with patient phenotypes. We also generated two germline mouse alleles with small deletions: Fzd2D3 and Fzd2D4. Homozygotes for each allele exhibit a highly penetrant cleft palate phenotype, shortened limbs compared with wild type and perinatal lethality. Fzd2D4 craniofacial tissues indicated decreased canonical Wnt signaling. In utero treatment with IIIC3a (a DKK inhibitor) normalized the limb lengths in Fzd2D4 homozygotes. The in vivo replication represents an approach for further investigating the mechanism of FZD2 phenotypes and demonstrates the utility of CRISPR knock-in mice as a tool for investigating the pathogenicity of human genetic variants. We also present evidence for a potential therapeutic intervention.

Rs205764 and rs547311 in linc00513 may influence treatment responses in multiple sclerosis patients: A pharmacogenomics Egyptian study

Background

Multiple sclerosis (MS) is characterized by a complex etiology that is reflected in the lack of consistently predictable treatment responses across patients of seemingly similar characteristics. Approaches to demystify the underlying predictors of aberrant treatment responses have made use of genome-wide association studies (GWAS), with imminent progress made in identifying single nucleotide polymorphisms (SNPs) associated with MS risk, disease progression, and treatment response. Ultimately, such pharmacogenomic studies aim to utilize the approach of personalized medicine to maximize patient benefit and minimize rate of disease progression.

Objective

Very limited research is available around the long intergenic non-coding RNA (linc)00513, recently being reported as a novel positive regulator of the type-1 interferon (IFN) pathway, following its overexpression in the presence of two polymorphisms: rs205764 and rs547311 in the promoter region of this gene. We attempt to provide data on the prevalence of genetic variations at rs205764 and rs547311 in Egyptian MS patients, and correlate these polymorphisms with the patients' responses to disease-modifying treatments.

Methods

Genomic DNA from 144 RRMS patients was isolated and analyzed for genotypes at the positions of interest on linc00513 using RT-qPCR. Genotype groups were compared with regards to their response to treatment; additional secondary clinical parameters including the estimated disability status score (EDSS), and onset of the disease were examined in relation to these polymorphisms.

Results

Polymorphisms at rs205764 were associated with a significantly higher response to fingolimod and a significantly lower response to dimethylfumarate. Moreover, the average EDSS of patients carrying polymorphisms at rs547311 was significantly higher, whereas no correlation appeared to exist with the onset of MS.

Conclusion

Understanding the complex interplay of factors influencing treatment response is pivotal in MS. One of the factors contributing to a patient's response to treatment, as well as disease disability, may be polymorphisms on non-coding genetic material, such as rs205764 and rs547311 on linc00513. Through this work, we propose that genetic polymorphisms may partially drive disease disability and inconsistent responses to treatment in MS; we also aim to draw attention towards genetic approaches, such as screening for specific polymorphisms, to possibly direct treatment choices in such a complex disease.

Insilico prediction and functional analysis of nonsynonymous SNPs in human CTLA4 gene

The CTLA4 receptor is an immune checkpoint involved in the downregulation of T cells. Polymorphisms in this gene have been found to be associated with different diseases like rheumatoid arthritis, autosomal dominant immune dysregulation syndrome, juvenile idiopathic arthritis and autoimmune Addison's disease. Therefore, the identification of polymorphisms that have an effect on the structure and function of CTLA4 gene is important. Here we identified the most damaging missense or non-synonymous SNPs (nsSNPs) that might be crucial for the structure and function of CTLA4 using different bioinformatics tools. These in silico tools included SIFT, PROVEAN, PhD-SNP, PolyPhen-2 followed by MutPred2, I-Mutant 2.0 and ConSurf. The protein structures were predicted using Phyre2 and I-TASSER, while the gene-gene interactions were predicted by GeneMANIA and STRING. Our study identified three damaging missense SNPs rs1553657429, rs1559591863 and rs778534474 in coding region of CTLA4 gene. Among these SNPs the rs1553657429 showed a loss of potential phosphorylation site and was found to be highly conserved. The prediction of gene-gene interaction showed the interaction of CTlA4 with other genes and its importance in different pathways. This investigation of damaging nsSNPs can be considered in future while studying CTLA4 related diseases and can be of great importance in precision medicine.

From oncoproteins to spike proteins: the evaluation of intramolecular stability using hydropathic force field

Evaluation of the intramolecular stability of proteins plays a key role in the comprehension of their biological behavior and mechanism of action. Small structural alterations such as mutations induced by single nucleotide polymorphism can impact biological activity and pharmacological modulation. Covid-19 mutations, that affect viral replication and the susceptibility to antibody neutralization, and the action of antiviral drugs, are just one example. In this work, the intramolecular stability of mutated proteins, like Spike glycoprotein and its complexes with the human target, is evaluated through hydropathic intramolecular energy scoring originally conceived by Abraham and Kellogg based on the “Extension of the fragment method to calculate amino acid zwitterion and side-chain partition coefficients” by Abraham and Leo in Proteins: Struct. Funct. Genet. 1987, 2:130 − 52. HINT is proposed as a fast and reliable tool for the stability evaluation of any mutated system. This work has been written in honor of Prof. Donald J. Abraham (1936–2021).

Digital Droplet Loop-Mediated Isothermal Amplification Featuring a Molecular Beacon Assay, 3D Printed Droplet Generation, and Smartphone Imaging for Sequence-Specific DNA Detection

Nucleic acid detection is widely used in the amplification and quantitation of nucleic acids from biological samples. While polymerase chain reaction (PCR) enjoys great popularity, expensive thermal cyclers are required for precise temperature control. Loop-mediated isothermal amplification (LAMP) enables highly sensitive, rapid, and low-cost amplification of nucleic acids at constant temperatures. LAMP detection often relies on double-stranded DNA-binding dyes or metal indicators that lack sequence selectivity. Molecular beacons (MBs) are hairpin-shaped oligonucleotide probes whose sequence specificity in LAMP provides the capability of differentiating between single-nucleotide polymorphisms (SNPs). Digital droplet LAMP (ddLAMP) enables a large number of independent LAMP reactions to be performed and provides quantification of target DNA sequences. However, a major challenge with ddLAMP is the requirement of expensive droplet generators to form homogeneous microdroplets. In this study, we demonstrate for the first time that a three-dimensional (3D) printed droplet generation platform can be coupled to a LAMP assay featuring MBs as sequence-specific probes. The low-cost 3D printed droplet generator system was designed, and its customizability was demonstrated in the formation of monodisperse ddLAMP assay-in-oil microdroplets. Additionally, a smartphone-based imaging system is demonstrated to increase accessibility for point-of-care applications. The MB-ddLAMP assay is shown to discriminate between two SNPs at various amplification temperatures to afford a useful platform for sequence-specific, sensitive, and accurate DNA quantification. This work expands the utility of MBs to ddLAMP for quantitative studies in the detection of SNPs and exploits the customizability of 3D printing technologies to optimize the homogeneity, size, and volume of oil-in-water microdroplets.

ZIP11 Regulates Nuclear Zinc Homeostasis in HeLa Cells and Is Required for Proliferation and Establishment of the Carcinogenic Phenotype

Zinc (Zn) is an essential trace element that plays a key role in several biological processes, including transcription, signaling, and catalysis. A subcellular network of transporters ensures adequate distribution of Zn to facilitate homeostasis. Among these are a family of importers, the Zrt/Irt-like proteins (ZIP), which consists of 14 members (ZIP1-ZIP14) that mobilize Zn from the extracellular domain and organelles into the cytosol. Expression of these transporters varies among tissues and during developmental stages, and their distribution at various cellular locations is essential for defining the net cellular Zn transport. Normally, the ion is bound to proteins or sequestered in organelles and vesicles. However, though research has focused on Zn internalization in mammalian cells, little is known about Zn mobilization within organelles, including within the nuclei under both normal and pathological conditions. Analyses from stomach and colon tissues isolated from mouse suggested that ZIP11 is the only ZIP transporter localized to the nucleus of mammalian cells, yet no clear cellular role has been attributed to this protein. We hypothesized that ZIP11 is essential to maintaining nuclear Zn homeostasis in mammalian cells. To test this, we utilized HeLa cells, as research in humans correlated elevated expression of ZIP11 with poor prognosis in cervical cancer patients. We stably knocked down ZIP11 in HeLa cancer cells and investigated the effect of Zn dysregulation in vitro. Our data show that ZIP11 knockdown (KD) reduced HeLa cells proliferation due to nuclear accumulation of Zn. RNA-seq analyses revealed that genes related to angiogenesis, apoptosis, mRNA metabolism, and signaling pathways are dysregulated. Although the KD cells undergoing nuclear Zn stress can activate the homeostasis response by MTF1 and MT1, the RNA-seq analyses showed that only ZIP14 (an importer expressed on the plasma membrane and endocytic vesicles) is mildly induced, which may explain the sensitivity to elevated levels of extracellular Zn. Consequently, ZIP11 KD HeLa cells have impaired migration, invasive properties and decreased mitochondrial potential. Furthermore, KD of ZIP11 delayed cell cycle progression and rendered an enhanced senescent state in HeLa cells, pointing to a novel mechanism whereby maintenance of nuclear Zn homeostasis is essential for cancer progression.

Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease

Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.

Polygenic risk, population structure and ongoing difficulties with race in human genetics

‘The Apportionment of Human Diversity’ stands as a noteworthy intervention, both for the field of human population genetics as well as in the annals of public communication of science. Despite the widespread uptake of Lewontin's conclusion that racial classification is of ‘virtually no genetic or taxonomic significance’, the biomedical research community continues to grapple with whether and how best to account for race in its work. Nowhere is this struggle more apparent than in the latest attempts to translate genetic associations with complex disease risk to clinical use in the form of polygenic risk scores, or PRS. In this perspective piece, we trace current challenges surrounding the appropriate development and clinical application of PRS in diverse patient cohorts to ongoing difficulties deciding which facets of population structure matter, and for what reasons, to human health. Despite numerous analytical innovations, there are reasons that emerge from Lewontin's work to remain sceptical that accounting for population structure in the context of polygenic risk estimation will allow us to more effectively identify and intervene on the significant health disparities which plague marginalized populations around the world.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Optimized electroporation of CRISPR-Cas9/gRNA ribonucleoprotein complex for selection-free homologous recombination in human pluripotent stem cells

Selection-free, scarless genome editing in human pluripotent stem cells (PSCs) by utilizing ribonucleoprotein (RNP) of CRISPR-Cas9 is a useful tool for a variety of applications. However, the process can be hampered by time-consuming subcloning steps and inefficient delivery of the RNP complex and ssDNA template. Here, we describe the optimized protocol to introduce a single nucleotide change or a loxP site insertion in feeder-free, xeno-free iPSCs by utilizing MaxCyte and 4D-Nucleofector electroporators. For complete details on the use and execution of this protocol, please refer to Kagita et al. (2021) and Xu et al. (2019).

Label-free bioassay with graphene oxide-based fluorescent aptasensors: A review

Bioassays using a fluorophore and DNA aptamer have been extensively developed due to the ultrasensitivity of fluorophores and recognition ability of DNA aptamers. Conventional fluorescent aptamer-based sensors (aptasensors) require chemical labeling between the fluorophore and aptamer and is technologically impracical for various sensing and assay applications. A simple "mix and go" strategy has been introduced that uses label-free technology as a platform for sensor development. The biosensors comprise a fluorophore, a ssDNA aptamer, and eco-friendly graphene oxide (GO). In the absence of the sensor target, GO quenches the fluorescence of the fluorophore and single-strand DNA aptamer complex. When the target is added, the DNA aptamer conformationally turns into a duplex, G-quadruplexe, or other secondary structure. This structure change leads to release of GO by the fluorophore-aptamer-target complex, generating dramatic fluorescence recovery and amplification. With this sensing method, the DNA aptamer does not need to be chemically labeled. Therefore, flexible fluorophore indicators and ssDNA aptamers can be used in this label-free aptasensing strategy. In this review, we discuss various unlabeled fluorophores, including synthetic small molecular fluorophores and genetically encoded fluorescent proteins, as indicators for generating GO-based fluorescent DNA aptasensors for label-free bioassay.

Knowledge discovery in genetics of diabetes in Iran, a roadmap for future researches

Purpose

The pathogenesis of diabetes is considered polygenic as a result of complex interactions between genetic/epigenetic and environmental factors. This review intended to evaluate the scientometric and knowledge gap of diabetes genetics researches conducted in Iran as a case of developing countries, and drawn up a roadmap for future studies.

Methods

We searched Scopus and PubMed databases from January 2015 until December 2019 using the keywords: (diabetes OR diabetic) AND (Iran). All publications were reviewed by two experts and after choosing relevant articles, they were categorized based on the subject, level of evidence, study design, publication year, and type of genetic studies.

Results

Of 10,540 records, 428 articles were met the inclusion criteria. Generally, the number of researches about diabetes genetics rose since 2015. Case-control/cross-sectional and animal studies were the common types of study design and based on the subject, the most frequent researches were about genetic factors involved in diabetes development (38%). Briefly, the top seven genes that were evaluated for T2DM were TCF7L2, APOAII, FTO, PON1, ADIPOQ, MTHFR, and PPARG respectively, and also, CTL4 for T1DM. miR-21, miR-155, and miR-375 respectively were the most micro-RNAs that were evaluated. Furthermore, there were six studies about lncRNAs.

Discussion and Conclusion

Investigation about the genetic of diabetes is progressed although there are some limitations like non-homogenous data from Iran, heterogeneity of ethnicity, and rationale of studies. Compared to the previous analysis in Iran, still, GWAS and large-scale studies are required to achieve better policies for manage and control of diabetes disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-021-00838-8.

Deciphering genes associated with diffuse large B-cell lymphoma with lymphomatous effusions: A mutational accumulation scoring approach

Introduction

Earlier studies have shown that lymphomatous effusions in patients with diffuse large B-cell lymphoma (DLBCL) are associated with a very poor prognosis, even worse than for non-effusion-associated patients with stage IV disease. We hypothesized that certain genetic abnormalities were associated with lymphomatous effusions, which would help to identify related pathways, oncogenic mechanisms, and therapeutic targets.

Methods

We compared whole-exome sequencing on DLBCL samples involving solid organs (n = 22) and involving effusions (n = 9). We designed a mutational accumulation-based approach to score each gene and used mutation interpreters to identify candidate pathogenic genes associated with lymphomatous effusions. Moreover, we performed gene-set enrichment analysis from a microarray comparison of effusion-associated versus non-effusion-associated DLBCL cases to extract the related pathways.

Results

We found that genes involved in identified pathways or with high accumulation scores in the effusion-based DLBCL cases were associated with migration/invasion. We validated expression of 8 selected genes in DLBCL cell lines and clinical samples: MUC4, SLC35G6, TP53BP2, ARAP3, IL13RA1, PDIA4, HDAC1 and MDM2, and validated expression of 3 proteins (MUC4, HDAC1 and MDM2) in an independent cohort of DLBCL cases with (n = 31) and without (n = 20) lymphomatous effusions. We found that overexpression of HDAC1 and MDM2 correlated with the presence of lymphomatous effusions, and HDAC1 overexpression was associated with the poorest prognosis. 

Conclusion

Our findings suggest that DLBCL associated with lymphomatous effusions may be associated mechanistically with TP53-MDM2 pathway and HDAC-related chromatin remodeling mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40364-021-00330-8.

Study on the concordance between different SNP-genotyping platforms in sheep

Different SNP genotyping technologies are commonly used in multiple studies to perform QTL detection, genotype imputation, and genomic predictions. Therefore, genotyping errors cannot be ignored, as they can reduce the accuracy of different procedures applied in genomic selection, such as genomic imputation, genomic predictions, and false-positive results in genome-wide association studies. Currently, whole-genome resequencing (WGR) also offers the potential for variant calling analysis and high-throughput genotyping. WGR might overshadow array-based genotyping technologies due to the larger amount and precision of the genomic information provided; however, its comparatively higher price per individual still limits its use in larger populations. Thus, the objective of this work was to evaluate the accuracy of the two most popular SNP-chip technologies, namely, Affymetrix and Illumina, for high-throughput genotyping in sheep considering high-coverage WGR datasets as references. Analyses were performed using two reference sheep genome assemblies, the popular Oar_v3.1 reference genome and the latest available version Oar_rambouillet_v1.0. Our results demonstrate that the genotypes from both platforms are suggested to have high concordance rates with the genotypes determined from reference WGR datasets (96.59% and 99.51% for Affymetrix and Illumina technologies, respectively). The concordance results provided in the current study can pinpoint low reproducible markers across multiple platforms used for sheep genotyping data. Comparing results using two reference genome assemblies also informs how genome assembly quality can influence genotype concordance rates among different genotyping platforms. Moreover, we describe an efficient pipeline to test the reliability of markers included in sheep SNP-chip panels against WGR datasets available on public databases. This pipeline may be helpful for discarding low-reliability markers before exploiting genomic information for gene mapping analyses or genomic prediction.

Varicella-Zoster Virus-Genetics, Molecular Evolution and Recombination

This chapter first details the structure, organization and coding content of the VZV genome to provide a foundation on which the molecular evolution of the virus can be projected. We subsequently describe the evolution of molecular profiling approaches from restriction fragment length polymorphisms to single nucleotide polymorphism profiling to modern day high-throughput sequencing approaches. We describe how the application of these methodologies led to our current model of VZV phylogeograpy including the number and structure of geographic clades and the role of recombination in reshaping these.

Analysis and Interpretation of the Impact of Missense Variants in Cancer

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

RMVar: an updated database of functional variants involved in RNA modifications

Distinguishing the few disease-related variants from a massive number of passenger variants is a major challenge. Variants affecting RNA modifications that play critical roles in many aspects of RNA metabolism have recently been linked to many human diseases, such as cancers. Evaluating the effect of genetic variants on RNA modifications will provide a new perspective for understanding the pathogenic mechanism of human diseases. Previously, we developed a database called 'm6AVar' to host variants associated with m6A, one of the most prevalent RNA modifications in eukaryotes. To host all RNA modification (RM)-associated variants, here we present an updated version of m6AVar renamed RMVar (http://rmvar.renlab.org). In this update, RMVar contains 1 678 126 RM-associated variants for 9 kinds of RNA modifications, namely m6A, m6Am, m1A, pseudouridine, m5C, m5U, 2'-O-Me, A-to-I and m7G, at three confidence levels. Moreover, RBP binding regions, miRNA targets, splicing events and circRNAs were integrated to assist investigations of the effects of RM-associated variants on posttranscriptional regulation. In addition, disease-related information was integrated from ClinVar and other genome-wide association studies (GWAS) to investigate the relationship between RM-associated variants and diseases. We expect that RMVar may boost further functional studies on genetic variants affecting RNA modifications.

Current insights into the genetics of food allergy

Food allergy (FA), a growing public health burden in the United States, and familial aggregation studies support strong roles for both genes and environment in FA risk. Deepening our understanding of the molecular and cellular mechanisms driving FAs is paramount to improving its prevention, diagnosis, and clinical management. In this review, we document lessons learned from the genetics of FA that have aided our understanding of these mechanisms. Although current genetic association studies suffer from low power, heterogeneity in definition of FA, and difficulty in our ability to truly disentangle FA from food sensitization (FS) and general atopy genetics, they reveal a set of genetic loci, genes, and variants that continue to implicate the importance of barrier and immune function genes across the atopic march, and FA in particular. The largest reported effects on FA are from MALT1 (odds ratio, 10.99), FLG (average odds ratio, ∼2.9), and HLA (average odds ratio, ∼2.03). The biggest challenge in the field of FA genetics is to elucidate the specific mechanism of action on FA risk and pathogenesis for these loci, and integrative approaches including genetics/genomics with transcriptomics, proteomics, and metabolomics will be critical next steps to translating these genetic insights into practice.

The emergent phenomenon of aspirin resistance: insights from genetic association studies

Despite the clinical benefits of aspirin, the interindividual variation in response to this antiplatelet drug is considerable. The manifestation of aspirin resistance (AR) is frequently observed, although this complex process remains poorly understood. While AR etiology is likely to be multifactorial, genetic factors appear to be preponderant. According to several genetic association studies, both genome-wide and candidate gene studies, numerous SNPs in cyclooxygenase, thromboxane and platelet receptors-related genes have been identified as capable of negatively affecting aspirin action. Thus, it is essential to understand the clinical relevance of AR-related SNPs as potential predictive and prognostic biomarkers as they may be essential to defining the AR phenotype.

In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review

Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.

Evaluation of beta-thalassemia in the fetus through cffDNA with multiple polymorphisms as a haplotype in the beta-globin gene

OBJECTIVE

Invasive biopsy during the pregnancy is associated with an abortion risk of approximately 1% for the fetus. Free fetal DNA in maternal plasma is an excellent source of genetic material for prenatal molecular diagnoses. This study was conducted to investigate beta-thalassemia mutation in the fetus through maternal blood with multiple polymorphisms as haplotypes in the beta-globin gene.

METHODS

In this study, a total of 33 beta-thalassemia carrier (minor) couples were genotyped by ARMS-PCR for IVSII-IG>A mutation. During pregnancy, 10mL of blood was collected from pregnant women, and DNA was extracted by the magnetic bead-based extraction, and fetal DNA was enriched with AMPure XP kit. Five polymorphisms in 4 haplotype groups were evaluated by the Sanger Sequencing method. Finally, results were compared with those of the invasion method.

RESULTS

Participants in study were 33 couples, mean age of the men was 26±5 years, and mean age of women was 23±4 years, and mean MCV, MCH, HbA2 blood parameters were 62.4±5.3, 19.6±3.1, 4.2±2.1 respectively. A total of 33 fetuses were genotyped for IVSII-IG>A mutation. Nine fetuses were affected, 10 fetuses were normal and 14 fetuses were carrier of beta-thalassemia. Sensitivity and specificity of Sanger Sequencing were equal to 88.8% and 91.6% respectively. Positive and negative predictive values were obtained as 80% and 95.6%, respectively.

CONCLUSION

Mutational status of the fetus can be assessed by determining inheritance of paternally-derived alleles based on detection of haplotype-associated SNP in maternal plasma. Magnetic-based DNA extraction and fetal DNA enrichment are very simple and easy to perform and have satisfactory accuracy.

Vitamin D Receptor Gene Polymorphisms and the Risk of Metabolic Syndrome (MetS): A Meta-Analysis

BACKGROUND

Several studies have assessed the association between the vitamin D receptor (VDR) polymorphism and the risk of metabolic syndrome (MetS). However, the results were inconsistent and inconclusive. Therefore, we conducted a meta-analysis to clarify the exact association between the vitamin D receptor (VDR) polymorphisms and the risk of MetS.

METHODS

All accessible studies reporting the association between the FokI (rs2228570) or/and TaqI (rs731236) or/and BsmI (rs1544410) or/and ApaI (rs7975232 polymorphisms of the Vitamin D Receptor and susceptibility to MetS published prior to February 2019 were systematically searched in Web of Science, Scopus, and PubMed. After that, Odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were estimated to evaluate the strength of the association in five genetic models.

RESULTS

A total of 9 articles based on four gene variations, and comprising 3348 participants with 1779 metabolic syndrome patients were included. The overall results suggested a significant association between BsmI (rs1544410) polymorphism and MetS susceptibility in recessive model (OR, 0.72, 95% CI, 0.55-0.95, fixed effect model), allelic model (OR, 0.83, 95% CI, 0.72-0.95, fixed effect model), and bb vs BB (OR, 0.65, 95% CI, 0.46-0.93, fixed effect). However, no significant association was identified between TaqI (rs731236) polymorphism, ApaI (rs7975232) polymorphism, and FokI (rs2228570) polymorphism and MetS.

CONCLUSION

This meta-analysis suggested an association between the BsmI (rs1544410) polymorphism and MetS. Indeed, BsmI (rs1544410) acts as a protective factor in the MetS. As a result, the VDR gene could be regarded as a promising pharmacological and physiological target in the prevention or treatment of the MetS.

Allele-specific PCR with a novel data processing method based on difference value for single nucleotide polymorphism genotyping of ALDH2 gene

Single nucleotide polymorphism (SNP) analysis based on allele-specific polymerase chain reaction (AS-PCR) is a relatively effective and economical method compared with other genotyping technologies such as DNA sequencing, DNA hybridization and isothermal amplification strategies. But AS-PCR is limited by its labor-intensive optimization of reaction parameters and time-consuming result assessment. In this study, we put forward a novel idea of data processing to address this problem. SNP analysis was accomplished by AS-PCR with endpoint electrochemical detection. For each sample, two separate reactions were run simultaneously with two sets of allele-specific primers (wild-type primers for W system and mutant primers for M system). We measured their redox current signals on screen-printed electrodes once AS-PCR finished and calculated the difference value of current signals between two systems to determine the genotyping result. Based on the difference value of fluorescent signals, real-time fluorescent PCR was used to study reaction parameters in AS-PCR. With screened parameters, we obtained the genotyping results within 50 min. 36 hair-root samples from volunteers were analyzed by our method and their genotypes of ALDH2 gene (encoding aldehyde dehydrogenase 2) were totally identical with data from commercialized sequencing. Our work first employed difference value between two reaction systems to differentiate allele and provided a novel idea of data processing in AS-PCR method. It is able to promote the quick analysis of SNP in the fields of health monitor, disease precaution, and personalized diagnosis and treatment.

In silico analysis on the functional and structural impact of Rad50 mutations involved in DNA strand break repair

BACKGROUND

DNA double strand break repair is important to preserve the fidelity of our genetic makeup after DNA damage. Rad50 is one of the components in MRN complex important for DNA repair mechanism. Rad50 mutations can lead to microcephaly, mental retardation and growth retardation in human. However, Rad50 mutations in human and other organisms have never been gathered and heuristically compared for their deleterious effects. It is important to assess the conserved region in Rad50 and its homolog to identify vital mutations that can affect functions of the protein.

METHOD

In this study, Rad50 mutations were retrieved from SNPeffect 4.0 database and literature. Each of the mutations was analyzed using various bioinformatic analyses such as PredictSNP, MutPred, SNPeffect 4.0, I-Mutant and MuPro to identify its impact on molecular mechanism, biological function and protein stability, respectively.

RESULTS

We identified 103 mostly occurred mutations in the Rad50 protein domains and motifs, which only 42 mutations were classified as most deleterious. These mutations are mainly situated at the specific motifs such as Walker A, Q-loop, Walker B, D-loop and signature motif of the Rad50 protein. Some of these mutations were predicted to negatively affect several important functional sites that play important roles in DNA repair mechanism and cell cycle signaling pathway, highlighting Rad50 crucial role in this process. Interestingly, mutations located at non-conserved regions were predicted to have neutral/non-damaging effects, in contrast with previous experimental studies that showed deleterious effects. This suggests that software used in this study may have limitations in predicting mutations in non-conserved regions, implying further improvement in their algorithm is needed. In conclusion, this study reveals the priority of acid substitution associated with the genetic disorders. This finding highlights the vital roles of certain residues such as K42E, C681A/S, CC684R/S, S1202R, E1232Q and D1238N/A located in Rad50 conserved regions, which can be considered for a more targeted future studies.

Genomic Medicine-Progress, Pitfalls, and Promise

In the wake of the Human Genome Project (HGP), strong expectations were set for the timeline and impact of genomics on medicine-an anticipated transformation in the diagnosis, treatment, and prevention of disease. In this Perspective, we take stock of the nascent field of genomic medicine. In what areas, if any, is genomics delivering on this promise, or is the path to success clear? Where are we falling short, and why? What have been the unanticipated developments? Overall, we argue that the optimism surrounding the transformational potential of genomics on medicine remains justified, albeit with a considerably different form and timescale than originally projected. We also argue that the field needs to pivot back to basics, as understanding the entirety of the genotype-to-phenotype equation is a likely prerequisite for delivering on the full potential of the human genome to advance the human condition.

Computational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene

Single Nucleotide Polymorphisms (SNPs) are the most common candidate mutations in human beings that play a vital role in the genetic basis of certain diseases. Previous studies revealed that Solute Carrier Family 26 Member 4 (SLC26A4) being an essential gene of the multi-faceted transporter family SLC26 facilitates reflexive movement of Iodide into follicular lumen through apical membrane of thyrocyte. SLC26A4 gene encodes Pendred protein, a membrane glycoprotein, highly hydrophobic in nature, present at the apical membrane of thyrocyte functioning as transporter of iodide for thyroid cells. A minor genetic variation in SLC26A4 can cause Pendred syndrome, a syndrome associated with thyroid glands and deafness. In this study, we performed in-silico analysis of 674 missense SNPs of SLC26A4 using different computational platforms. The bunch of tools including SNPNEXUS, SNAP-2, PhD-SNP, SNPs&GO, I-Mutant, ConSurf, and ModPred were used to predict 23 highly confident damaging and disease causing nsSNPs (G209V, G197R, L458P, S427P, Q101P, W472R, N392Y, V359E, R409C, Q235R, R409P, G139V, G497S, H723R, D87G, Y127H, F667C, G334A, G95R, S427C, R291W, Q383H and E384G) that could potentially alter the SLC26A4 gene. Moreover, protein structure prediction, protein-ligand docking and Molecular Dynamics simulation were performed to confirm the impact of two evident alterations (Y127H and G334A) on the protein structure and function.

Using gold nanoparticles to detect single-nucleotide polymorphisms: toward liquid biopsy

The possibility of detecting genetic mutations rapidly in physiological media through liquid biopsy has attracted the attention within the materials science community. The physical properties of nanoparticles combined with robust transduction methods ensure an improved sensitivity and specificity of a given assay and its implementation into point-of-care devices for common use. Covering the last twenty years, this review gives an overview of the state-of-the-art of the research on the use of gold nanoparticles in the development of colorimetric biosensors for the detection of single-nucleotide polymorphism as cancer biomarker. We discuss the main mechanisms of the assays that either are assisted by DNA-based molecular machines or by enzymatic reactions, summarize their performance and provide an outlook towards future developments.

Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis

Rheumatoid arthritis (RA) risk has a large genetic component (~60%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.

The genetic side of type 2 diabetes - A review

AIM

Type 2 diabetes (T2DM) is a complex disease. Interactions between genetic susceptible variants and environmental cues results in the development of this heterogenous disease. Having an understanding of the genetics of T2DM may lead to a better perspective and management of the pathogenesis contributing to T2DM.

MATERIALS AND METHODS

Published primary and secondary sources were reviewed covering the keywords "genetics + type 2 diabetes" using PubMed and Google Scholar as the main databases. Full articles were considered when the title and the abstract was found to be sufficiently related to the review's aim.

RESULTS

Various genetic aspects of T2DM were summarised including a general understanding of the heritability and heterogeneity of T2DM. Furthermore, an explanation of the different genetic modalities that can be used to identify T2DM susceptible genes was provided.

CONCLUSION

In this day and era, researchers and healthcare professionals working in the field of metabolic disorders should have an understanding of T2DM genetics. The future lies in preventive and management action plans targeting the combination of genetics and environmental risk factors for a better health outcome.

[Exploring the association between SPRY gene family and non-syndromic oral clefts among Chinese populations using data of a next-generation sequencing study]

OBJECTIVE

To explore the association between SPRY gene family and the risk of non-syndromic oral clefts among Chinese populations, in respect of single nucleotide polymorphisms (SNPs) association and parent-of-origin effects.

METHODS

Based on case-parent design, this study used the data of SPRY gene family in a next generation sequencing study of 183 non-syndromic cleft lip with or without cleft palate (NSCL/P) case-parent trios (549 participants) recruited from 2016 to 2018, to analyze the effects of SNP association and parent-of-origin. The sequencing study adopted a two-stage design. In the first stage, whole exome sequencing was conducted among 24 NSCL/P trios with family history to explore potential signals. Then in the second stage, another 159 NSCL/P trios were used as validation samples to verify the signals found in the first stage. The data of general information, disease features and parental environmental exposures for participants were collected through questionnaires. Blood samples were collected from each participant for DNA extraction and sequencing. Transmission disequilibrium tests (TDT) were conducted to test for the association between SNPs and NSCL/P, while Z score tests were applied to analyze parent-of-origin effects. The analyses were performed using Plink (v1.07). TRIO package in R (v3.5.1). Besides, famSKAT analyses were conducted in the first stage to combine the effect of SNPs located on the same gene, using famSKAT package in R(V3.5.1). Bonferroni method was adopted to correct multiple tests in the second stage.

RESULTS

Twenty-two SNPs in SPRY gene family were included for analyses after the quality control process in the first stage. Based on the variants annotation, functional prediction and statistical analysis, rs1298215244 (SPRY1) and rs504122 (SPRY2) were included in the second verification stage. TDTs in the verification stage revealed that rs1298215244: T>C, rs504122: G>C and rs504122: G>T were associated with the risk of NSCL/P after Bonferroni corrections, where rs504122: G>T was a rare variation. Although the test for parent-of-origin effect of rs1298215244: T>C reached nominal significance level, no SNP showed significant association with NSCL/P through parent-of-origin effect after Bonferroni corrections.

CONCLUSION

This study found that SNPs (including both common and rare variants) among the SPRY gene family were associated with the risk of NSCL/P among Chinese populations. This study failed to detect parent-of-origin effects among the SPRY gene family.

What Have We Learned from Studies of IFN-λ Variants and Hepatitis C Virus Infection?

Chronic infection with the hepatitis C virus (HCV) is a major cause of cirrhosis and hepatocellular carcinoma. In 2009, genome-wide association studies (GWAS) strongly linked genetic variants in the interferon lambda (IFN-λ) chromosomal region to HCV clearance. In 2013, discovery of the IFNL4 gene provided a functional explanation for those GWAS findings. The IFNL4-ΔG/TT (rs368234815) variant controls generation of the IFN-λ4 protein. Paradoxically, the IFNL4-TT allele, which abrogates IFN-λ4, associates with higher rates of spontaneous HCV clearance and better response to treatments for HCV infection. The finding that a "knock-out" allele for IFN-λ4 enhances HCV clearance challenges the paradigm of IFNs as antiviral cytokines. Genetic variants in the IFN-λ region have also been associated with hepatic inflammation and fibrosis from various etiologies, however, alleles that are linked with improved HCV clearance associates with worse inflammation and fibrosis. These studies demonstrate that GWAS of infectious diseases may yield important and unexpected biological insights.

New insights into the pathogenicity of non-synonymous variants through multi-level analysis

Precise classification of non-synonymous single nucleotide variants (SNVs) is a fundamental goal of clinical genetics. Next-generation sequencing technology is effective for establishing the basis of genetic diseases. However, identification of variants that are causal for genetic diseases remains a challenge. We analyzed human non-synonymous SNVs from a multilevel perspective to characterize pathogenicity. We showed that computational tools, though each having its own strength and weakness, tend to be overly dependent on the degree of conservation. For the mutations at non-degenerate sites, the amino acid sites of pathogenic substitutions show a distinct distribution in the classes of protein domains compared with the sites of benign substitutions. Overlooked disease susceptibility of genes explains in part the failures of computational tools. The more pathogenic sites observed, the more likely the gene is expressed in a high abundance or in a high tissue-specific manner, and have a high node degree of protein-protein interaction. The destroyed functions due to some false-negative mutations may arise because of a reprieve from the epigenetic repressed state which shouldn't happen in multiple biological conditions, instead of the defective protein. Our work adds more to our knowledge of non-synonymous SNVs' pathogenicity, thus will benefit the field of clinical genetics.

Genetic Factors That Affect Spontaneous Clearance of Hepatitis C or B Virus, Response to Treatment, and Disease Progression

Hepatitis C virus (HCV) and hepatitis B virus (HBV) infections can lead to cirrhosis, end-stage liver disease, and hepatocellular carcinoma. Over the past decade, studies of individuals infected with these viruses have established genetic associations with the probability of developing a chronic infection, risk of disease progression, and likelihood of treatment response. We review genetic and genomic methods that have been used to study risk of HBV and HCV infection and patient outcomes. For example, genome-wide association studies have linked a region containing the interferon lambda genes to spontaneous and treatment-induced clearance of HCV. We review the genetic variants associated with HCV and HBV infection, and how these variants affect specific expression or activities of their products. Further studies of these variants could provide insights into risk factors for and mechanisms of chronic infection and disease progression, as well as new strategies for treatment.

Variations on a Chip: Technologies of Difference in Human Genetics Research

In this article we examine the history of the production of microarray technologies and their role in constructing and operationalizing views of human genetic difference in contemporary genomics. Rather than the "turn to difference" emerging as a post-Human Genome Project (HGP) phenomenon, interest in individual and group differences was a central, motivating concept in human genetics throughout the twentieth century. This interest was entwined with efforts to develop polymorphic "genetic markers" for studying human traits and diseases. We trace the technological, methodological and conceptual strategies in the late twentieth century that established single nucleotide polymorphisms (SNPs) as key focal points for locating difference in the genome. By embedding SNPs in microarrays, researchers created a technology that they used to catalog and assess human genetic variation. In the process of making genetic markers and array-based technologies to track variation, scientists also made commitments to ways of describing, cataloging and "knowing" human genetic differences that refracted difference through a continental geographic lens. We show how difference came to matter in both senses of the term: difference was made salient to, and inscribed on, genetic matter(s), as a result of the decisions, assessments and choices of collaborative and hybrid research collectives in medical genomics research.

Guidance Molecules in Vascular Smooth Muscle

Several highly conserved families of guidance molecules, including ephrins, Semaphorins, Netrins, and Slits, play conserved and distinct roles in tissue remodeling during tissue patterning and disease pathogenesis. Primarily, these guidance molecules function as either secreted or surface-bound ligands that interact with their receptors to activate a variety of downstream effects, including cell contractility, migration, adhesion, proliferation, and inflammation. Vascular smooth muscle cells, contractile cells comprising the medial layer of the vessel wall and deriving from the mural population, regulate vascular tone and blood pressure. While capillaries lack a medial layer of vascular smooth muscle, mural-derived pericytes contribute similarly to capillary tone to regulate blood flow in various tissues. Furthermore, pericyte coverage is critical in vascular development, as perturbations disrupt vascular permeability and viability. During cardiovascular disease, smooth muscle cells play a more dynamic role in which suppression of contractile markers, enhanced proliferation, and migration lead to the progression of aberrant vascular remodeling. Since many types of guidance molecules are expressed in vascular smooth muscle and pericytes, these may contribute to blood vessel formation and aberrant remodeling during vascular disease. While vascular development is a large focus of the existing literature, studies emerged to address post-developmental roles for guidance molecules in pathology and are of interest as novel therapeutic targets. In this review, we will discuss the roles of guidance molecules in vascular smooth muscle and pericyte function in development and disease.