Optimizing ddRAD sequencing for population genomic studies with ddgRADer

Double-digest Restriction-site Associated DNA sequencing (ddRADseq) is widely used to generate genomic data for non-model organisms in evolutionary and ecological studies. Along with affordable paired-end sequencing, this method makes population genomic analyses more accessible. However, multiple factors should be considered when designing a ddRADseq experiment, which can be challenging for new users. The generated data often suffer from substantial read overlaps and adaptor contamination, severely reducing sequencing efficiency and affecting data quality. Here, we analyse diverse datasets from the literature and carry out controlled experiments to understand the effects of enzyme choice and size selection on sequencing efficiency. The empirical data reveal that size selection is imprecise and has limited efficacy. In certain scenarios, a substantial proportion of short fragments pass below the lower size-selection cut-off resulting in low sequencing efficiency. However, enzyme choice can considerably mitigate inadvertent inclusion of these shorter fragments. A simple model based on these experiments is implemented to predict the number of genomic fragments generated after digestion and size selection, number of SNPs genotyped, number of samples that can be multiplexed and the expected sequencing efficiency. We developed ddgRADer - http://ddgrader.haifa.ac.il/ - a user-friendly webtool and incorporated these calculations to aid in ddRADseq experimental design while optimizing sequencing efficiency. This tool can also be used for single enzyme protocols such as Genotyping-by-Sequencing. Given user-defined study goals, ddgRADer recommends enzyme pairs and allows users to compare and choose enzymes and size-selection criteria. ddgRADer improves the accessibility and ease of designing ddRADseq experiments and increases the probability of success of the first population genomic study conducted in labs with no prior experience in genomics.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes

The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.

PlotXpress, a webtool for normalization and visualization of reporter expression data

In molecular cell biology, reporter assays are frequently used to investigate gene expression levels. Reporter assays employ a gene that encodes a light-emitting protein, of which the luminescence is quantified as a proxy of gene expression. Commercial parties provide reporter assay kits that include protocols and specialized detection machinery. However, downstream analysis of the output data and their presentation are not standardized. We have developed plotXpress to fill this gap, providing a free, open-source platform for the semi-automated analysis and standardized visualisation of experimental gene reporter data. Users can upload raw luminescence data acquired from a reporter gene assay with an internal control. In plotXpress, the data is corrected for sample variation with the internal control and the average for each condition is calculated. When a reference condition is selected the fold change is calculated for all other conditions, based on the selected reference. The results are shown as dot plots with a statistical summary, which can be adjusted to create publication-grade plots without requiring coding skills. Altogether, plotXpress is an open-source, low-threshold, web-based tool, that promotes a standardized and reproducible analysis while providing an appealing visualization of reporter data. The webtool can be accessed at: https://huygens.science.uva.nl/PlotXpress/

Whole-Genome-Based Helicobacter pylori Geographic Surveillance: A Visualized and Expandable Webtool

Helicobacter pylori exhibit specific geographic distributions that are related to clinical outcomes. Despite the high infection rate of H. pylori throughout the world, the genetic epidemiology surveillance of H. pylori still needs to be improved. This study used the single nucleotide polymorphisms (SNPs) profiling approach based on whole genome sequencing (WGS) to facilitate genomic population analyses of H. pylori and encourage the dissemination of microbial genotyping strategies worldwide. A total number of 1,211 public H. pylori genomes were downloaded and used to construct the typing tool, named HpTT (H. pylori Typing Tool). Combined with the metadata, we developed two levels of genomic typing, including a continent-scale and a country scale that nested in the continent scale. Results showed that Asia was the largest isolate source in our dataset, while isolates from Europe and Oceania were comparatively more widespread. More specifically, Switzerland and Australia are the main sources of widespread isolates in their corresponding continents. To integrate all the typing information and enable researchers to compare their dataset against the existing global database easily and rapidly, a user-friendly website (https://db.cngb.org/HPTT/) was developed with both genomic typing tools and visualization tools. To further confirm the validity of the website, ten newly assembled genomes were downloaded and tested precisely located on the branch as we expected. In summary, the H. pylori typing tool (HpTT) is a novel genomic epidemiological tool that can achieve high-resolution analysis of genomic typing and visualizing simultaneously, providing insights into the genetic population structure, evolution analysis, and epidemiological surveillance of H. pylori.

A protocol for introduction of multiple genetic modifications in Saccharomyces cerevisiae using CRISPR/Cas9

Here, two methods are described for efficient genetic modification of Saccharomyces cerevisiae using CRISPR/Cas9. The first method enables the modification of a single genetic locus using in vivo assembly of a guide RNA (gRNA) expression plasmid without the need for prior cloning. A second method using in vitro assembled plasmids that could contain up to two gRNAs was used to simultaneously introduce up to six genetic modifications (e.g. six gene deletions) in a single transformation step by transforming up to three gRNA expression plasmids simultaneously. The method is not only suitable for gene deletion but is also applicable for in vivo site-directed mutagenesis and integration of multiple DNA fragments in a single locus. In all cases, the strain transformed with the gRNA expression plasmids was equipped with a genomic integration of Spcas9, leading to strong and constitutive expression of SpCas9. The protocols detailed here have been streamlined to be executed by virtually any yeast molecular geneticist.

MultiSyn: A Webtool for Multiple Synteny Detection and Visualization of User's Sequence of Interest Compared to Public Plant Species

Information on multiple synteny between plants and/or within a plant is key information to understand genome evolution. In addition, visualization of multiple synteny is helpful in interpreting evolution. So far, some web applications have been developed to determine and visualize multiple homology regions at once. However, the applications are not fully convenient for biologists because some of them do not include the function of synteny determination but visualize the multiple synteny plots by allowing users to upload their synteny data by determining the synteny based only on BLAST similarity information, with some algorithms not designed for synteny determination. Here, we introduce a web application that determines and visualizes multiple synteny from two types of files, simplified browser extensible data and protein sequence file by MCScanX algorithm, which have been used in many synteny studies.

CRISPR/Cas9: a molecular Swiss army knife for simultaneous introduction of multiple genetic modifications in Saccharomyces cerevisiae

A variety of techniques for strain engineering in Saccharomyces cerevisiae have recently been developed. However, especially when multiple genetic manipulations are required, strain construction is still a time-consuming process. This study describes new CRISPR/Cas9-based approaches for easy, fast strain construction in yeast and explores their potential for simultaneous introduction of multiple genetic modifications. An open-source tool (http://yeastriction.tnw.tudelft.nl) is presented for identification of suitable Cas9 target sites in S. cerevisiae strains. A transformation strategy, using in vivo assembly of a guideRNA plasmid and subsequent genetic modification, was successfully implemented with high accuracies. An alternative strategy, using in vitro assembled plasmids containing two gRNAs, was used to simultaneously introduce up to six genetic modifications in a single transformation step with high efficiencies. Where previous studies mainly focused on the use of CRISPR/Cas9 for gene inactivation, we demonstrate the versatility of CRISPR/Cas9-based engineering of yeast by achieving simultaneous integration of a multigene construct combined with gene deletion and the simultaneous introduction of two single-nucleotide mutations at different loci. Sets of standardized plasmids, as well as the web-based Yeastriction target-sequence identifier and primer-design tool, are made available to the yeast research community to facilitate fast, standardized and efficient application of the CRISPR/Cas9 system.

CRISPR/Cas9 like a Swiss army knife enables molecular biologists to quickly introduce simultaneous multiple and diverse genetic modifications in baker's yeast Saccharomyces cerevisiae.