Toll-like receptor 9 polymorphisms in brazilian patients with systemic lupus erythematosus: a pilot study

Toll-like receptor 9 (TLR9) is an important component of the innate immune system and have been associated with several autoimmune diseases, such as Systemic Lupus Erythematosus (SLE). The aim of this study was to investigate polymorphisms in TLR9 gene in a Brazilian SLE patients group and their association with clinical manifestation, particularly Jaccoud’s arthropathy (JA). We analyzed DNA samples from 204 SLE patients, having a subgroup of them presenting JA (n=24). A control group (n=133) from the same city was also included. TLR9 single nucleotide polymorphisms (SNPs) (−1237 C>T and +2848 G>A) were identified by sequencing analysis. The TLR9 gene genotype frequency was similar both in SLE patients and the control group. In the whole SLE population, an association between the homozygosis of allele C at position −1237 with psychosis and anemia (p < 0.01) was found. Likewise, the homozygosis of allele G at position +2848 was associated with a discoid rash (p < 0.05). There was no association between JA and TLR9 polymorphisms. These data show that TLR9 polymorphisms do not seem to be a predisposing factor for SLE in the Brazilian population, and that SNPs are not associated with JA.

Spatiotemporal Changes in Plasmodium vivax msp142 Haplotypes in Southern Mexico: From the Control to the Pre-Elimination Phase

For 20 years, Plasmodium vivax has been the only prevalent malaria species in Mexico, and cases have declined significantly and continuously. Spatiotemporal genetic studies can be helpful for understanding parasite dynamics and developing strategies to weaken malaria transmission, thus facilitating the elimination of the parasite. The aim of the current contribution was to analyze P. vivax-infected blood samples from patients in southern Mexico during the control (1993–2007) and pre-elimination phases (2008–2011). Nucleotide and haplotype changes in the pvmsp142 fragment were evaluated over time. The majority of multiple genotype infections occurred in the 1990s, when the 198 single nucleotide sequences exhibited 57 segregating sites, 64 mutations, and 17 haplotypes. Nucleotide and genetic diversity parameters showed subtle fluctuations from across time, in contrast to the reduced haplotype diversity and the increase in the R2 index and Tajima’s D value from 2008 to 2011. The haplotype network consisted of four haplogroups, the geographical distribution of which varied slightly over time. Haplogroup-specific B-cell epitopes were predicted. Since only high-frequency and divergent haplotypes persisted, there was a contraction of the parasite population. Given that 84% of haplotypes were exclusive to Mesoamerica, P. vivax flow is likely circumscribed to this region, representing important information for parasite surveillance.

An Updated Review on the Role of Single Nucleotide Polymorphisms in COVID-19 Disease Severity: A Global Aspect

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and recently has become a serious global pandemic. Age, gender, and comorbidities are known to be common risk factors for severe COVID-19 but are not enough to fully explain the magnitude of their effect on the risk of severity of the disease. Single nucleotide polymorphisms (SNPs) in several genes have been reported as a genetic factor contributing to COVID-19 severity. This comprehensive review focuses on the association between SNPs in four important genes and COVID-19 severity in a global aspect. We discuss a total of 39 SNPs in this review: five SNPs in the ABO gene, nine SNPs in the angiotensin-converting enzyme 2 (ACE2) gene, 19 SNPs in the transmembrane protease serine 2 (TMPRSS2) gene, and six SNPs in the toll-like receptor 7 (TLR7) gene. These SNPs data could assist in monitoring an individual's risk of severe COVID-19 disease, and therefore personalized management and pharmaceutical treatment could be planned in COVID-19 patients.

Functionally Antagonistic Transcription Factors IRF1 and IRF2 Regulate the Transcription of the Dopamine Receptor D2 Gene Associated with Aggressive Behavior of Weaned Pigs

Aggressive behavior has negative effects on animal welfare and growth performance in pigs. The dopamine receptor D2 (DRD2) has a critical neuromodulator role in the dopamine signal pathway within the brain to control behavior. A functional single-nucleotide polymorphism (SNP), rs1110730503, in the promoter region of the porcine DRD2 gene was identified, which affects aggressive behavior in pigs. A chromatin immunoprecipitation (ChIP) assay was used to identify the interactions between interferon regulatory factor 1 (IRF1) and IRF2 with the DRD2 gene. The overexpression or knockdown of these two transcription factors in porcine kidney-15 (PK15) and porcine neuronal cells (PNCs) indicate that the binding of IRF1 to DRD2 promotes the transcription of the DRD2 gene, but the binding of IRF2 to the DRD2 gene inhibits its transcription. Furthermore, IRF1 and IRF2 are functionally antagonistic to each other. The downregulation of DRD2 or upregulation of IRF2 increased the apoptosis rate of porcine neuroglial cells. Taken together, we found that transcriptional factors IRF1 and IRF2 have vital roles in regulating the transcription of the DRD2 gene, and rs1110730503 (−915A/T) is a functional SNP that influences IRF2 binding to the promoter of the DRD2 gene. These findings will provide further insight towards controlling aggressive behavior in pigs.

Association Study of the M132L Single Nucleotide Polymorphism With Susceptibility to Chronic Wasting Disease in Korean Elk: A Meta-Analysis

Chronic wasting disease (CWD) is a deleterious brain proteinopathy caused by a pathogenic form of prion protein (PrPSc), which is converted from a benign form of prion protein (PrPC) encoded by the prion protein gene (PRNP). In elk, the M132L single nucleotide polymorphism (SNP) of the PRNP gene likely plays a pivotal role in susceptibility to CWD. However, the association of the M132L SNP with susceptibility to CWD has not been evaluated in Korean elk to date. To estimate the association of the M132L SNP with susceptibility to CWD in Korean elk, we investigated the genotype and allele frequencies of the M132L SNP by amplicon sequencing and performed association analysis between CWD-positive and CWD-negative elk. In addition, we performed a meta-analysis to evaluate the association between the M132L SNP and susceptibility to CWD in quantitatively synthesized elk populations. Furthermore, we estimated the effect of the M132L SNP on elk PrP using in silico programs, including PolyPhen-2, PROVEAN, AMYCO and Swiss-PdbViewer. We did not identify a significant association between the M132L SNP of PRNP and susceptibility to CWD in Korean elk. The meta-analysis also did not identify a strong association between the M132L SNP of PRNP and susceptibility to CWD in quantitatively synthesized elk populations. Furthermore, we did not observe significant changes in structure, amyloid propensity or electrostatic potential based on the M132L SNP in elk PrP. To the best of our knowledge, this was the first report of an association analysis and meta-analysis in Korean elk and quantitatively synthesized elk populations, respectively.

Comprehensive patient-level classification and quantification of driver events in TCGA PanCanAtlas cohorts

There is a growing need to develop novel therapeutics for targeted treatment of cancer. The prerequisite to success is the knowledge about which types of molecular alterations are predominantly driving tumorigenesis. To shed light onto this subject, we have utilized the largest database of human cancer mutations–TCGA PanCanAtlas, multiple established algorithms for cancer driver prediction (2020plus, CHASMplus, CompositeDriver, dNdScv, DriverNet, HotMAPS, OncodriveCLUSTL, OncodriveFML) and developed four novel computational pipelines: SNADRIF (Single Nucleotide Alteration DRIver Finder), GECNAV (Gene Expression-based Copy Number Alteration Validator), ANDRIF (ANeuploidy DRIver Finder) and PALDRIC (PAtient-Level DRIver Classifier). A unified workflow integrating all these pipelines, algorithms and datasets at cohort and patient levels was created. We have found that there are on average 12 driver events per tumour, of which 0.6 are single nucleotide alterations (SNAs) in oncogenes, 1.5 are amplifications of oncogenes, 1.2 are SNAs in tumour suppressors, 2.1 are deletions of tumour suppressors, 1.5 are driver chromosome losses, 1 is a driver chromosome gain, 2 are driver chromosome arm losses, and 1.5 are driver chromosome arm gains. The average number of driver events per tumour increases with age (from 7 to 15) and cancer stage (from 10 to 15) and varies strongly between cancer types (from 1 to 24). Patients with 1 and 7 driver events per tumour are the most frequent, and there are very few patients with more than 40 events. In tumours having only one driver event, this event is most often an SNA in an oncogene. However, with increasing number of driver events per tumour, the contribution of SNAs decreases, whereas the contribution of copy-number alterations and aneuploidy events increases.

Rapid detection of single nucleotide polymorphisms using the MinION nanopore sequencer: a feasibility study for perioperative precision medicine

Introduction: Precision medicine is a phrase used to describe personalized medical care tailored to specific patients based on their clinical presentation and genetic makeup. However, despite the fact that several single nucleotide polymorphisms (SNPs) have been reported to be associated with increased susceptibility to particular anesthetic agents and the occurrence of perioperative complications, genomic profiling and thus precision medicine has not been widely applied in perioperative management. Methods: We validated six SNP loci known to affect perioperative outcomes in Japanese patients using genomic DNA from saliva specimens and nanopore sequencing of each SNP loci to facilitate allele frequency calculations and then compared the nanopore results to those produced using the conventional dideoxy sequencing method. Results: Nanopore sequencing reads clustered into the expected genotypes in both homozygous and heterozygous cases. In addition, the nanopore sequencing results were consistent with those obtained using conventional dideoxy sequencing and the workflow provided reliable allele frequency estimation, with a total analysis time of less than 4 h. Conclusion: Thus, our results suggest that nanopore sequencing may be a promising and versatile tool for SNP genotyping, allowing for rapid and feasible risk prediction of perioperative outcomes.