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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is worldwide the main cause of the COVID-19 pandemic. After infection of human pulmonary cells, intracellular viral replication take place in different cellular compartments resulting in the destruction of the host cells and causing severe respiratory diseases. Although cellular trafficking of SARS-CoV-2 have been explored, little is known about the role of the cytoskeleton during viral replication in pulmonary cells. Here we show that SARS-CoV-2 infection induces dramatic changes of F-actin nanostructures overtime. Ring-like actin nanostructures are surrounding viral intracellular organelles, suggesting a functional interplay between F-actin and viral M clusters during particle assembly. Filopodia-like structures loaded with viruses to neighbour cells suggest these structures as mechanism for cell-to-cell virus transmission. Strikingly, gene expression profile analysis and PKN inhibitor treatments of infected pulmonary cells reveal a major role of alpha-actinins superfamily proteins in SARS-CoV-2 replication. Overall, our results highlight cell actors required for SARS-CoV2 replication that are promises for antiviral targets.TeaserImpairing regulation of actin filaments inhibits SARS-CoV-2 particle production in human pulmonary cells.

There has been limited study of Native American whole genome diversity to date, which impairs effective implementation of personalized medicine and a detailed description of its demographic history. Here we report high coverage whole genome sequencing of 76 unrelated individuals, from 27 indigenous groups across Mexico, with more than 97% average Native American ancestry. On average, each individual has 3.26 million Single Nucleotide Variants and short indels, that together comprise a catalog of 9,737,152 variants, 44,118 of which are novel. We report 497 common Single Nucleotide Variants (with allele frequency > 5%) mapped to drug responses and 316,577 in enhancer or promoter elements; interestingly we found some of these enhancer variants in PPARG, a nuclear receptor involved in highly prevalent health problems in Mexican population, such as obesity, diabetes, and insulin resistance. By detecting signals of positive selection we report 24 enriched key pathways under selection, most of them related to immune mechanisms. No missense variants in ACE2, the receptor responsible for the entry of the SARS CoV-2 virus, were found in any individual. Population genomics and phylogenetic analyses demonstrated stratification in a Northern-Central-Southern axis, with major substructure in the Central region. The Seri, a northern group with the most genetic divergence in our study, showed a distinctive genomic context with the most novel variants, and the most population specific genotypes. Genome-wide analysis showed that the average haplotype blocks are longer in Native Mexicans than in other world populations. With this dataset we describe previously undetected population level variation in Native Mexicans, helping to reduce the gap in genomic data representation of such groups.

RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step-- such as alignment of reads to a reference genome-- of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses. In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided.

Nextflow pipeline that runs and plots admixture and smartpca from a compressed VCF.

Nextflow pipeline used to count variants for the 100GMX project 'nf-100GMX-variant-summarizer' is a pipeline tool that counts variants in a VEPextended annotated VCF file. This pipeline generates 3 outputs: 1) a TSV file with the total number of SNV and indels 2) a TSV file with per sample counts for variants of type SNV, indel, novel, worldwide singletons, clinvar, gwascat and pharmgkb 3) a PDF file with the number of discernible variants in sample groups of interest. Important note: input file must be previously annotated by https://github.com/Iaguilaror/nf-VEPextended

'nf-vcf-cataloguer' is a tool, implemented in Nextflow, that generates a general table description in TSV format of the description of each category and subgroup of a VCF with the extended annotation made by VEP. Furthermore, it plots each subset of the consequences of variants.

Nextflow pipeline used to build the novel variants dataset for the 100GMX project. 'nf-vcf-novel-dataset-builder' is a pipeline tool that builds a VCF file compiling only novel variants according to dbSNP and VEP, from a VEPextended annotated VCF file. This novel selection does not include singletons and private variants. The main output is in VCF format. Additional outputs include the dataset in TSV format, and a sequence coverage from gnomAD in these sites. Important note: input file must be previously annotated byhttps://github.com/Iaguilaror/nf-VEPextended All steps described are mk modules of code that will be done automatically through Nextflow pipeline.

In this work, we evaluated several tools used for the alignment of short sequences and found that most aligners execute reasonably well for identical sequences, whereas a variety of alignment errors emerge for dissimilar ones. Since alignments are essential in computational biology, we developed ExtendAlign, a post-analysis tool that corrects these errors and improves the alignment of dissimilar short sequences. We used simulated and biological data to show that ExtendAlign outperforms the other aligners in most metrics tested. ExtendAlign is useful for pinpointing the identity percentage for alignments of short sequences in the range of ∼35–50% similarity.