Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinsons disease

Background Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinsons disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD. Results Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered. Conclusions Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.This work has been supported by Macrogen Inc. (Grant No. MGR20-01)

Mobile-Oriented Future Internet: Implementation and Experimentations over EU–Korea Testbed

Today’s mobility management (MM) architectures, such as Mobile Internet Protocol (IP) and Proxy Mobile IP, feature integration of data and control planes, as well as centralized mobility control. In the existing architecture, however, the tight integration of the data and control planes can induce a non-optimal routing path, because data packets are delivered via a central mobility agent, such as Home Agent and Local Mobility Anchor. Furthermore, the centralized mobility control mechanism tends to increase traffic overhead due to the processing of both data and control packets at a central agent. To address these problems, a new Internet architecture for the future mobile network was proposed, named Mobile-Oriented Future Internet (MOFI). The MOFI architecture was mainly designed as follows: (1) separation of data and control planes for getting an optimal data path; (2) distributed identifier–locator mapping control for alleviating traffic overhead at a central agent. In this article, we investigate the validity of the MOFI architecture through implementation and experimentations over the European Union (EU)–Korea testbed network. For this purpose, the MOFI architecture is implemented using OpenFlow and Click Modular Router over a Linux platform, and then it is evaluated over the locally and internationally configured EU–Korea testbed network. In particular, we operate two realistic communication scenarios over the EU–Korea testbed network. From the experimentation results, we can see that the proposed MOFI architecture can not only provide the mobility management efficiently, but also support the backward compatibility for the current IP version 6 (IPv6) applications and an Internet Protocol network

ClinPharmSeq: A targeted sequencing panel for clinical pharmacogenetics implementation

© 2022 Lee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The accurate identification of genetic variants contributing to therapeutic drug response or adverse effects is the first step in implementation of precision drug therapy. Targeted sequencing has recently become a common methodology for large-scale studies of genetic variation thanks to its favorable balance between low cost, high throughput, and deep coverage. Here, we present ClinPharmSeq, a targeted sequencing panel of 59 genes with associations to pharmacogenetic (PGx) phenotypes, as a platform to explore the relationship between drug response and genetic variation, both common and rare. For validation, we sequenced DNA from 64 ethnically diverse Coriell samples with ClinPharmSeq to call star alleles (haplotype patterns) in 27 genes using the bioinformatics tool PyPGx. These reference samples were extensively characterized by multiple laboratories using PGx testing assays and, more recently, whole genome sequencing. We found that ClinPharmSeq can consistently generate deep-coverage data (mean = 274x) with high uniformity (30x or above = 94.8%). Our genotype analysis identified a total of 185 unique star alleles from sequencing data, and showed that diplotype calls from ClinPharmSeq are highly concordant with that from previous publications (97.6%) and whole genome sequencing (97.9%). Notably, all 19 star alleles with complex structural variation including gene deletions, duplications, and hybrids were recalled with 100% accuracy. Altogether, these results demonstrate that the ClinPharmSeq platform offers a feasible path for broad implementation of PGx testing and optimization of individual drug treatments.N

Gβ-like CpcB plays a crucial role for growth and development of Aspergillus nidulans and Aspergillus fumigatus.

Growth, development, virulence and secondary metabolism in fungi are governed by heterotrimeric G proteins (G proteins). A Gβ-like protein called Gib2 has been shown to function as an atypical Gβ in Gpa1-cAMP signaling in Cryptococcus neoformans. We found that the previously reported CpcB (cross pathway control B) protein is the ortholog of Gib2 in Aspergillus nidulans and Aspergillus fumigatus. In this report, we further characterize the roles of CpcB in governing growth, development and toxigenesis in the two aspergilli. The deletion of cpcB results in severely impaired cellular growth, delayed spore germination, and defective asexual sporulation (conidiation) in both aspergilli. Moreover, CpcB is necessary for proper expression of the key developmental activator brlA during initiation and progression of conidiation in A. nidulans and A. fumigatus. Somewhat in accordance with the previous study, the absence of cpcB results in the formation of fewer, but not micro-, cleistothecia in A. nidulans in the presence of wild type veA, an essential activator of sexual development. However, the cpcB deletion mutant cleistothecia contain no ascospores, validating that CpcB is required for progression and completion of sexual fruiting including ascosporogenesis. Furthermore, unlike the canonical GβSfaD, CpcB is not needed for the biosynthesis of the mycotoxin sterigmatocystin (ST) as the cpcB null mutant produced reduced amount of ST with unaltered STC gene expression. However, in A. fumigatus, the deletion of cpcB results in the blockage of gliotoxin (GT) production. Further genetic analyses in A. nidulans indicate that CpcB may play a central role in vegetative growth, which might be independent of FadA- and GanB-mediated signaling. A speculative model summarizing the roles of CpcB in conjunction with SfaD in A. nidulans is presented

The complete mitochondrial genome of Nilaparvata lugens (stål, 1854) captured in Korea (Hemiptera: Delphacidae)

Nilaparvata lugens is one of important pests of rice causing severe damagein early September in Korea after migrating from China. We completed mitogenome of N. lugens captured in Korea. The circular mitogenome of N. lugens is 17,610 bp including 13 protein-coding genes, 2 rRNAs, 22 tRNAs, and a 2424-bp--non-coding region. The base composition was AT-biased (89.5%). 112 single nucleotide polymorphisms (SNPs) and 59 insertions and deletions are identified by comparing with Chinese N. lugens. Phylogenetic trees presented an incongruence of topology in N. lugens clade, suggesting a need for further analyses to classify biotypes based on complete mitochondrial genomes

Multiplex analysis for the identification of plasma protein biomarkers for predicting lung cancer immunotherapy response

Background: Programmed death-ligand (PD-L1) expression serves as a predictive biomarker for immune checkpoint inhibitor (ICI) sensitivity in non-small cell lung cancer (NSCLC). Nevertheless, the development of biomarkers that reliably predict ICI response remains an ongoing endeavor due to imperfections in existing methodologies. Objectives: ICIs have led to a new paradigm in the treatment of NSCLC. The current companion PD-L1 diagnostics are insufficient in predicting ICI response. Therefore, we sought whether the Olink platform could be applied to predict response to ICIs in NSCLC. Design: We collected blood samples from patients with NSCLC before ICI treatment and retrospectively analyzed proteomes based on their response to ICI. Methods: Overall, 76 NSCLC patients’ samples were analyzed. Proteomic plasma analysis was performed using the Olink platform. Intraplate reproducibility, validation, and statistical analyses using elastic net regression and generalized linear models with clinical parameters were evaluated. Results: Intraplate coefficient of variation (CV) assays ranged from 3% to 6%, and the interplate CV was 14%. In addition, the Pearson correlation coefficient of the Olink Normalized Protein eXpression data was validated. No statistical differences were observed in the analyses of progressive disease and response to ICIs. Furthermore, no single proteome showed prognostic value in terms of progression-free survival. Conclusion: In this study, the proximity extension assay-based approach of the Olink panel could not predict the patient’s response to ICIs. Our proteomic analysis failed to achieve predictive value in both response or progression to ICIs and progression-free survival (PFS)

[Gamma]-Glutamyl transpeptidase (GgtA) of Aspergillus nidulans is not necessary for bulk degradation of glutathione

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