Selection of optimal computational strategies for analyzing metagenomics data is a decisive step in determining the microbial composition of a sample, and this procedure is complex because of the ...numerous tools currently available. The aim of this research was to summarize the results of crowdsourced sbv IMPROVER Microbiomics Challenge designed to evaluate the performance of off-the-shelf metagenomics software as well as to investigate the robustness of these results by the extended post-challenge analysis. In total 21 off-the-shelf taxonomic metagenome profiling pipelines were benchmarked for their capacity to identify the microbiome composition at various taxon levels across 104 shotgun metagenomics datasets of bacterial genomes (representative of various microbiome samples) from public databases. Performance was determined by comparing predicted taxonomy profiles with the gold standard. Most taxonomic profilers performed homogeneously well at the phylum level but generated intermediate and heterogeneous scores at the genus and species levels, respectively. kmer-based pipelines using Kraken with and without Bracken or using CLARK-S performed best overall, but they exhibited lower precision than the two marker-gene-based methods MetaPhlAn and mOTU. Filtering out the 1% least abundance species--which were not reliably predicted--helped increase the performance of most profilers by increasing precision but at the cost of recall. However, the use of adaptive filtering thresholds determined from the sample's Shannon index increased the performance of most kmer-based profilers while mitigating the tradeoff between precision and recall. kmer-based metagenomic pipelines using Kraken/Bracken or CLARK-S performed most robustly across a large variety of microbiome datasets. Removing non-reliably predicted low-abundance species by using diversity-dependent adaptive filtering thresholds further enhanced the performance of these tools. This work demonstrates the applicability of computational pipelines for accurately determining taxonomic profiles in clinical and environmental contexts and exemplifies the power of crowdsourcing for unbiased evaluation.
Abstract
Ensembl (https://www.ensembl.org) is unique in its flexible infrastructure for access to genomic data and annotation. It has been designed to efficiently deliver annotation at scale for all ...eukaryotic life, and it also provides deep comprehensive annotation for key species. Genomes representing a greater diversity of species are increasingly being sequenced. In response, we have focussed our recent efforts on expediting the annotation of new assemblies. Here, we report the release of the greatest annual number of newly annotated genomes in the history of Ensembl via our dedicated Ensembl Rapid Release platform (http://rapid.ensembl.org). We have also developed a new method to generate comparative analyses at scale for these assemblies and, for the first time, we have annotated non-vertebrate eukaryotes. Meanwhile, we continually improve, extend and update the annotation for our high-value reference vertebrate genomes and report the details here. We have a range of specific software tools for specific tasks, such as the Ensembl Variant Effect Predictor (VEP) and the newly developed interface for the Variant Recoder. All Ensembl data, software and tools are freely available for download and are accessible programmatically.
Abstract
Ensembl Genomes (https://www.ensemblgenomes.org) provides access to non-vertebrate genomes and analysis complementing vertebrate resources developed by the Ensembl project ...(https://www.ensembl.org). The two resources collectively present genome annotation through a consistent set of interfaces spanning the tree of life presenting genome sequence, annotation, variation, transcriptomic data and comparative analysis. Here, we present our largest increase in plant, metazoan and fungal genomes since the project's inception creating one of the world's most comprehensive genomic resources and describe our efforts to reduce genome redundancy in our Bacteria portal. We detail our new efforts in gene annotation, our emerging support for pangenome analysis, our efforts to accelerate data dissemination through the Ensembl Rapid Release resource and our new AlphaFold visualization. Finally, we present details of our future plans including updates on our integration with Ensembl, and how we plan to improve our support for the microbial research community. Software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license). Data updates are synchronised with Ensembl's release cycle.
Genome-wide single-nucleotide polymorphisms (SNPs) are highly useful in unraveling genetic insights and are essential to accelerate selections for genetic improvement in tobacco. The discovery of ...genome-wide SNPs in tobacco is very complex due to its high level of repetitive genome and polyploidy. At present, publicly available genomic data on SNPs are very limited, which warrants the need for high-throughput SNPs for application in tobacco breeding. In this research paper, we describe our efforts on SNP discovery by whole genome resequencing of 18 flue-cured Virginia (FCV) tobacco genotypes and annotation of SNPs in the tobacco genome. A large amount of data of about 225 GB per genotype was generated, with an average read depth of 50× using paired-end next-generation sequencing (NGS) with the HiSeq 2500 platform. The discovery of a large number of SNPs and indels was attempted to assist mapping and, thus, the selection processes to develop superior tobacco breeding lines. Discovered SNPs, their functional annotation, mapping to the reference genome, and their relative positioning in the linkage group are discussed in this paper.
The present work investigated a comprehensive genome-wide landscape of DNA methylome and its relationship with transcriptome upon gibberellin A
3
(GA
3
) foliar application under practical field ...conditions in solanaceae model,
Nicotiana tabacum
L. Methylated DNA Immunoprecipitation-Sequencing (MeDIP-Seq) analysis uncovered over 82% (18,456) of differential methylated regions (DMRs) in intergenic-region. Within protein-coding region, 2339 and 1685 of identified DMRs were observed in genebody- and promoter-region, respectively. Microarray study revealed 7032 differential expressed genes (DEGs) with 3507 and 3525 genes displaying up- and down-regulation, respectively. Integration analysis revealed 520 unique non-redundant annotated DMRs overlapping with DEGs. Our results indicated that GA
3
induced DNA hypo- as well as hyper-methylation were associated with both gene-silencing and -activation. No complete biasness or correlation was observed in either of the promoter- or genebody-regions, which otherwise showed an overall trend towards GA
3
induced global DNA hypo-methylation. Taken together, our results suggested that differential DNA methylation mediated by GA
3
may only play a permissive role in regulating the gene expression.
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