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Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https//github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.

The clinical consequences of SARS-CoV-2 and DENGUE virus co-infection are not promising. However, their treatment options are currently unavailable. Current studies have shown that quercetin is both resistant to COVID-19 and DENGUE; this study aimed to evaluate the possible functional roles and underlying mechanisms of action of quercetin as a potential molecular candidate against COVID-19 and DENGUE co-infection.

We used a series of bioinformatics analyses to understand and characterize the biological functions, pharmacological targets and therapeutic mechanisms of quercetin in COVID-19 and DENGUE co-infection.

We revealed the clinical characteristics of COVID-19 and DENGUE, including pathological mechanisms, key inflammatory pathways and possible methods of intervention, 60 overlapping targets related to the co-infection and the drug were identified, the protein-protein interaction (PPI) was constructed and TNFα, CCL-2 and CXCL8 could become potential drug targets. Furthermore, we disclosed the signalssible evidence for quercetin as a potential molecule drug for the treatment of COVID-19 and DENGUE, but the findings have not been verified in actual patients, so further clinical drug trials are needed.

Genomic Islands (GIs) are clusters of genes that are mobilized through horizontal gene transfer. GIs play a pivotal role in bacterial evolution as a mechanism of diversification and adaptation to different niches. Therefore, identification and characterization of GIs in bacterial genomes is important for understanding bacterial evolution. However, quantifying GIs is inherently difficult, and the existing methods suffer from low prediction accuracy and precision-recall trade-off. OG-L002 Moreover, several of them are supervised in nature, and thus, their applications to newly sequenced genomes are riddled with their dependency on the functional annotation of existing genomes.

We present SSG-LUGIA, a completely automated and unsupervised approach for identifying GIs and horizontally transferred genes. SSG-LUGIA is a novel method based on unsupervised anomaly detection technique, accompanied by further refinement using cues from signal processing literature. SSG-LUGIA leverages the atypical compositional biases of tally transferred genes. SSG-LUGIA is available as an open source software at https//nibtehaz.github.io/SSG-LUGIA/.

Our results indicate that SSG-LUGIA achieved superior performance in comparison to frequently used existing methods. Importantly, it yielded a better trade-off between precision and recall than the existing methods. Its nondependency on the functional annotation of genomes makes it suitable for analyzing newly sequenced, yet uncharacterized genomes. Thus, our study is a significant advance in identification of GIs and horizontally transferred genes. SSG-LUGIA is available as an open source software at https//nibtehaz.github.io/SSG-LUGIA/.

The positive predictive value of newborn screening for CAH in New Zealand is approximately 10%. The use of a second tier liquid chromatography tandem mass spectrometry bloodspot steroid profile test with birthweight or gestational age adjusted screening cut-offs may result in further screening improvements.

Three years of newborn screening data with additional second tier steroid metabolites was evaluated (n=167672 births). Data from babies with a negative screening test and confirmed CAH cases were compared. First and second-tier steroid measurements were correlated with both birthweight and with gestational age. Analysis of variance was used to determine birthweight and gestational age groups. Screening cut-offs were determined and applied retrospectively to model screening performance.

First tier immunoassay data correlated better with gestational age than with birthweight but there was no difference with second tier steroid measurements. Four distinct birthweight and gestational age groups were established for 17-hydroxyprogesterone and a steroid ratio measurement. Application of 97.5 th percentile second tier birthweight or gestational age adjusted cut-offs would result in 10 positive tests over the period of the study with 8 true positive screens and 2 false positive tests. The positive predictive value of screening would be increased from 10.8% to 80%.

The use of either birthweight or gestational age adjusted cut-offs for second tier screening tests can significantly reduce the false positive rate of newborn screening for congenital adrenal hyperplasia in New Zealand without loss in screening sensitivity.

The use of either birthweight or gestational age adjusted cut-offs for second tier screening tests can significantly reduce the false positive rate of newborn screening for congenital adrenal hyperplasia in New Zealand without loss in screening sensitivity.