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The water gas shift (WGS) is an equilibrium exothermic reaction, whose corresponding industrial process is normally carried out in two adiabatic stages, to overcome the thermodynamic and kinetic limitations. The high temperature stage makes use of iron/chromium-based catalysts, while the low temperature stage employs copper/zinc-based catalysts. Nevertheless, both these systems have several problems, mainly dealing with safety issues and process efficiency. Accordingly, in the last decade abundant researches have been focused on the study of alternative catalytic systems. The best performances have been obtained with noble metal-based catalysts, among which, platinum-based formulations showed a good compromise between performance and ease of preparation. These catalytic systems are extremely attractive, as they have numerous advantages, including the feasibility of intermediate temperature (250–400 °C) applications, the absence of pyrophoricity, and the high activity even at low loadings. The particle size plays a crucial role in determining their catalytic activity, enhancing the performance of the nanometric catalytic systems: the best activity and stability was reported for particle sizes < 1.7 nm. Moreover the optimal Pt loading seems to be located near 1 wt%, as well as the optimal Pt coverage was identified in 0.25 ML. Kinetics and mechanisms studies highlighted the low energy activation of Pt/Mo2C-based catalytic systems (Ea of 38 kJ·mol−1), the associative mechanism is the most encountered on the investigated studies. This review focuses on a selection of recent published articles, related to the preparation and use of unstructured platinum-based catalysts in water gas shift reaction, and is organized in five main sections: comparative studies, kinetics, reaction mechanisms, sour WGS and electrochemical promotion. Each section is divided in paragraphs, at the end of the section a summary and a summary table are provided.

Background The availability of the peach genome sequence has fostered relevant research in peach and related Prunus species enabling the identification of genes underlying important horticultural traits as well as the development of advanced tools for genetic and genomic analyses. The first release of the peach genome (Peach v1.0) represented a high-quality WGS (Whole Genome Shotgun) chromosome-scale assembly with high contiguity (contig L50 214.2 kb), large portions of mapped sequences (96%) and high base accuracy (99.96%). The aim of this work was to improve the quality of the first assembly by increasing the portion of mapped and oriented sequences, correcting misassemblies and improving the contiguity and base accuracy using high-throughput linkage mapping and deep resequencing approaches. Results Four linkage maps with 3,576 molecular markers were used to improve the portion of mapped and oriented sequences (from 96.0% and 85.6% of Peach v1.0 to 99.2% and 98.2% of v2.0, respectively) and enabled a more detailed identification of discernible misassemblies (10.4 Mb in total). The deep resequencing approach fixed 859 homozygous SNPs (Single Nucleotide Polymorphisms) and 1347 homozygous indels. Moreover, the assembled NGS contigs enabled the closing of 212 gaps with an improvement in the contig L50 of 19.2%. Conclusions The improved high quality peach genome assembly (Peach v2.0) represents a valuable tool for the analysis of the genetic diversity, domestication, and as a vehicle for genetic improvement of peach and related Prunus species. Moreover, the important phylogenetic position of peach and the absence of recent whole genome duplication (WGD) events make peach a pivotal species for comparative genomics studies aiming at elucidating plant speciation and diversification processes.

Background Structural variations (SVs) or copy number variations (CNVs) greatly impact the functions of the genes encoded in the genome and are responsible for diverse human diseases. Although a number of existing SV detection algorithms can detect many types of SVs using whole genome sequencing (WGS) data, no single algorithm can call every type of SVs with high precision and high recall. Results We comprehensively evaluate the performance of 69 existing SV detection algorithms using multiple simulated and real WGS datasets. The results highlight a subset of algorithms that accurately call SVs depending on specific types and size ranges of the SVs and that accurately determine breakpoints, sizes, and genotypes of the SVs. We enumerate potential good algorithms for each SV category, among which GRIDSS, Lumpy, SVseq2, SoftSV, Manta, and Wham are better algorithms in deletion or duplication categories. To improve the accuracy of SV calling, we systematically evaluate the accuracy of overlapping calls between possible combinations of algorithms for every type and size range of SVs. The results demonstrate that both the precision and recall for overlapping calls vary depending on the combinations of specific algorithms rather than the combinations of methods used in the algorithms. Conclusion These results suggest that careful selection of the algorithms for each type and size range of SVs is required for accurate calling of SVs. The selection of specific pairs of algorithms for overlapping calls promises to effectively improve the SV detection accuracy.

Copy number variations (CNVs) play a crucial role in cancer diagnostics and prognostics, potentially impacting treatment decisions. Ultra‐low‐pass whole‐genome sequencing (ULP‐WGS) has emerged as a promising alternative to array‐based methods for CNV detection, especially in formalin‐fixed paraffin‐embedded (FFPE) samples. However, sequencing biases and sample heterogeneity necessitate the optimization of CNV detection tools for FFPE sample‐derived data. This study evaluates three open‐source CNV callers (CNVpytor, ichorCNA, and WisecondorX) using ULP‐WGS and compares their performance against a single nucleotide polymorphism (SNP) array. Our results demonstrate that under optimal experimental conditions, ichorCNA and WisecondorX achieved equal detection of true positive results, with reduced false positive results compared to the SNP array. The SNP array detection pattern differed somewhat from that of the CNV callers, while ichorCNA and WisecondorX had the most comparable detection pattern. We highlight the importance of (pre‐)analytical parameters such as neoplastic cell content, sequencing coverage, and bin size selection on CNV detection accuracy. Our findings support the adoption of ULP‐WGS‐based CNV detection as a robust alternative to SNP arrays, with WisecondorX emerging as the most suitable tool for clinical implementation. This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized. Two CNV callers matched or exceeded the performance of a standard array method, demonstrating the potential for utilizing FFPE samples in genomic studies and cancer diagnostics.

Thoracic aortic aneurysm and dissection (TAAD) can affect individuals across all age groups. A family history is present in as many as 20% of individuals with thoracic aortic disease. The genetic basis of TAAD remains poorly understood; many different genes have been identified which cause TAAD either as part of a syndrome (e.g. Marfan, Loeys-Dietz syndromes) or as non-syndromic isolated cases (e.g. ACTA2, MYLK), however, the majority of cases remain unsolved. The 100,000 Genomes Project conducted whole genome sequencing for patients with rare diseases and cancers, including those recruited for TAAD, and screened them against virtual gene panels to identify pathogenic variants. Here, we analysed clinical, phenotypic, and genetic data from the 100,000 Genomes Project to identify potentially pathogenic variants in 833 participants recruited for TAAD, including both isolated and syndromic cases. TAAD has one of the lowest diagnostic yields in the 100,000 Genomes Project, with a pathogenic variant being identified in only 3% of cases.We screened known TAAD genes in this cohort and identified potentially pathogenic variants in a further 14% of the unsolved cases, giving a maximum diagnostic yield of 17%. The majority of these variants are classified as variants of uncertain significance (VUS), and additional work is needed to confirm the functional impact of these variants. Copy number variants (CNVs) are known to play an important role in TAAD, so to gain further insight into our unsolved cases, we explored specific genes from the virtual gene panels and the literature in which CNVs are detected. Wider screening of TAAD genes could increase the diagnostic yield of the 100,000 Genomes Project for participants with TAAD. Exploring rare variants within this group will reveal new genes and genomic regions associated with TAAD, contributing to a better understanding of the genetic underpinnings of TAAD. The ability to conduct this research was facilitated by accessing the data derived from the 100,000 Genomes Project.Conflict of InterestNONE

Background The microbiome of the oral cavity is the second-largest and diverse microbiota after the gut, harboring over 700 species of bacteria and including also fungi, viruses, and protozoa. With its diverse niches, the oral cavity is a very complex environment, where different microbes preferentially colonize different habitats. Recent data indicate that the oral microbiome has essential functions in maintaining oral and systemic health, and the emergence of 16S rRNA gene next-generation sequencing (NGS) has greatly contributed to revealing the complexity of its bacterial component. However, a detailed site-specific map of oral microorganisms (including also eukaryotes and viruses) and their relative abundance is still missing. Here, we aimed to obtain a comprehensive view of the healthy oral microbiome (HOM), including its drug-resistance features. Results The oral microbiome of twenty healthy subjects was analyzed by whole-genome sequencing (WGS) and real-time quantitative PCR microarray. Sampled oral micro-habitat included tongue dorsum, hard palate, buccal mucosa, keratinized gingiva, supragingival and subgingival plaque, and saliva with or without rinsing. Each sampled oral niche evidenced a different microbial community, including bacteria, fungi, and viruses. Alpha-diversity evidenced significant differences among the different sampled sites ( p  < 0.0001) but not among the enrolled subjects ( p  = 0.876), strengthening the notion of a recognizable HOM. Of note, oral rinse microbiome was more representative of the whole site-specific microbiomes, compared with that of saliva. Interestingly, HOM resistome included highly prevalent genes conferring resistance to macrolide, lincosamides, streptogramin, and tetracycline. Conclusions The data obtained in 20 subjects by WGS and microarray analysis provide for the first time a comprehensive view of HOM and its resistome, contributing to a deeper understanding of the composition of oral microbiome in the healthy subject, and providing an important reference for future studies, allowing to identify microbial signatures related to functional and metabolic alterations associated with diseases, potentially useful for targeted therapies and precision medicine.

Genetic characterization of strains recovered from cystic fibrosis patients. The whole-genome sequence of 12 strains was determined using Illumina technology. The position of the strains within the genus was analyzed using selected partial gene sequences, core genome multi-locus sequence typing and average nucleotide identity analysis. Furthermore, the sequences were annotated. The results show that some strains previously identified as , ,  and belong to novel species. The strains did not harbor acquired antibiotic resistance genes but encoded an OXA-type ß-lactamase. The taxonomy of the genus needs to be revised.

Genome-wide association studies (GWAS) have become indispensable in human medicine and genomics, but very few have been carried out on bacteria. Here we introduce Scoary, an ultra-fast, easy-to-use, and widely applicable software tool that scores the components of the pan-genome for associations to observed phenotypic traits while accounting for population stratification, with minimal assumptions about evolutionary processes. We call our approach pan-GWAS to distinguish it from traditional, single nucleotide polymorphism (SNP)-based GWAS. Scoary is implemented in Python and is available under an open source GPLv3 license at https://github.com/AdmiralenOla/Scoary .

Background The study of microbiomes using whole-metagenome shotgun sequencing enables the analysis of uncultivated microbial populations that may have important roles in their environments. Extracting individual draft genomes (bins) facilitates metagenomic analysis at the single genome level. Software and pipelines for such analysis have become diverse and sophisticated, resulting in a significant burden for biologists to access and use them. Furthermore, while bin extraction algorithms are rapidly improving, there is still a lack of tools for their evaluation and visualization. Results To address these challenges, we present metaWRAP, a modular pipeline software for shotgun metagenomic data analysis. MetaWRAP deploys state-of-the-art software to handle metagenomic data processing starting from raw sequencing reads and ending in metagenomic bins and their analysis. MetaWRAP is flexible enough to give investigators control over the analysis, while still being easy-to-install and easy-to-use. It includes hybrid algorithms that leverage the strengths of a variety of software to extract and refine high-quality bins from metagenomic data through bin consolidation and reassembly. MetaWRAP’s hybrid bin extraction algorithm outperforms individual binning approaches and other bin consolidation programs in both synthetic and real data sets. Finally, metaWRAP comes with numerous modules for the analysis of metagenomic bins, including taxonomy assignment, abundance estimation, functional annotation, and visualization. Conclusions MetaWRAP is an easy-to-use modular pipeline that automates the core tasks in metagenomic analysis, while contributing significant improvements to the extraction and interpretation of high-quality metagenomic bins. The bin refinement and reassembly modules of metaWRAP consistently outperform other binning approaches. Each module of metaWRAP is also a standalone component, making it a flexible and versatile tool for tackling metagenomic shotgun sequencing data. MetaWRAP is open-source software available at https://github.com/bxlab/metaWRAP .

Brycon nattereri is a Brazilian fish species of the order Characiformes (Bryconidae). Like others in the genus, B. nattereri is classified as \"vulnerable\" on the red list of endangered species. For this work, we collected a sample of B. nattereri from the Upper Paraná and São Francisco river basins, identified it and registered in an ichthyology collection. Whole genome sequencing was performed by Illumina. The raw reads were assembled with Novoplasty and the sequence annotated with MitoAnnotator. This is the third complete mitochondrial genome described for the genus and is available on GenBank: MT428073.1 and MT428074.1.