Tracing human genetic histories and natural selection with precise local ancestry inference.

Local ancestry inference is crucial for unraveling demographic histories, discovering selection signals, and including admixed individuals in genomic studies for improved equity and portability. To date, the precision and resolution of local ancestry inference were limited by technical and dataset issues. To address them, we present Orchestra, a model we train on over 10,000 single-origin individuals from 35 worldwide populations that demonstrates superior accuracy in benchmarking analyzes.

: Unsupervised Classification of Electroencephalographic Data.

Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel. Moreover, the low rate of capturing abnormal events during the procedure makes interpretation time-consuming, resource-hungry, and overall an expensive process.

SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration.

Background: Generating polygenic risk scores for diseases and complex traits requires high quality GWAS summary statistic files. Often, these files can be difficult to acquire either as a result of unshared or incomplete data. To date, bioinformatics tools which focus on restoring missing columns containing identification and association data are limited, which has the potential to increase the number of usable GWAS summary statistics files.

Flexible Machine Learning Algorithms for Clinical Gait Assessment Tools.

The current gold standard of gait diagnostics is dependent on large, expensive motion-capture laboratories and highly trained clinical and technical staff. Wearable sensor systems combined with machine learning may help to improve the accessibility of objective gait assessments in a broad clinical context. However, current algorithms lack flexibility and require large training datasets with tedious manual labelling of data.

Metatranscriptomics captures dynamic shifts in mycorrhizal coordination in boreal forests.

Carbon storage and cycling in boreal forests-the largest terrestrial carbon store-is moderated by complex interactions between trees and soil microorganisms. However, existing methods limit our ability to predict how changes in environmental conditions will alter these associations and the essential ecosystem services they provide. To address this, we developed a metatranscriptomic approach to analyze the impact of nutrient enrichment on Norway spruce fine roots and the community structure, function, and tree-microbe coordination of over 350 root-associated fungal species.

EZTraits: A programmable tool to evaluate multi-site deterministic traits.

The vast majority of human traits, including many disease phenotypes, are affected by alleles at numerous genomic loci. With a continually increasing set of variants with published clinical disease or biomarker associations, an easy-to-use tool for non-programmers to rapidly screen VCF files for risk alleles is needed. We have developed EZTraits as a tool to quickly evaluate genotype data against a set of rules defined by the user.

Comparative Fungal Community Analyses Using Metatranscriptomics and Internal Transcribed Spacer Amplicon Sequencing from Norway Spruce.

The health, growth, and fitness of boreal forest trees are impacted and improved by their associated microbiomes. Microbial gene expression and functional activity can be assayed with RNA sequencing (RNA-Seq) data from host samples. In contrast, phylogenetic marker gene amplicon sequencing data are used to assess taxonomic composition and community structure of the microbiome.

Building de novo reference genome assemblies of complex eukaryotic microorganisms from single nuclei.

The advent of novel sequencing techniques has unraveled a tremendous diversity on Earth. Genomic data allow us to understand ecology and function of organisms that we would not otherwise know existed. However, major methodological challenges remain, in particular for multicellular organisms with large genomes.

Investigation of the host transcriptional response to intracellular bacterial infection using Dictyostelium discoideum as a host model.

Background: During infection by intracellular pathogens, a highly complex interplay occurs between the infected cell trying to degrade the invader and the pathogen which actively manipulates the host cell to enable survival and proliferation. Many intracellular pathogens pose important threats to human health and major efforts have been undertaken to better understand the host-pathogen interactions that eventually determine the outcome of the infection. Over the last decades, the unicellular eukaryote Dictyostelium discoideum has become an established infection model, serving as a surrogate macrophage that can be infected with a wide range of intracellular pathogens.

Author Correction: Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes.

Type 2 diabetes (T2D) mellitus is a complex metabolic disease commonly caused by insulin resistance in several tissues. We performed a matched two-dimensional metabolic screening in tissue samples from 43 multi-organ donors. The intra-individual analysis was assessed across five key metabolic tissues (serum, visceral adipose tissue, liver, pancreatic islets and skeletal muscle), and the inter-individual across three different groups reflecting T2D progression.

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigenetic analyses have yielded ambiguous and sometimes conflicting results.

ACES: a machine learning toolbox for clustering analysis and visualization.

Background: Studies that aim at explaining phenotypes or disease susceptibility by genetic or epigenetic variants often rely on clustering methods to stratify individuals or samples. While statistical associations may point at increased risk for certain parts of the population, the ultimate goal is to make precise predictions for each individual. This necessitates tools that allow for the rapid inspection of each data point, in particular to find explanations for outliers.

Functional and evolutionary genomic inferences in through genome and population sequencing of American and European aspen.

The genus is one of the major plant model systems, but genomic resources have thus far primarily been available for poplar species, and primarily (Torr. & Gray), which was the first tree with a whole-genome assembly. To further advance evolutionary and functional genomic analyses in , we produced genome assemblies and population genetics resources of two aspen species, L.

Special Issue Introduction: The Wonders and Mysteries Next Generation Sequencing Technologies Help Reveal.

The massive increase in computational power over the recent years and wider applicationsof machine learning methods, coincidental or not, were paralleled by remarkable advances inhigh-throughput DNA sequencing technologies.[..

Global characterization of the Dicer-like protein DrnB roles in miRNA biogenesis in the social amoeba Dictyostelium discoideum.

Micro (mi)RNAs regulate gene expression in many eukaryotic organisms where they control diverse biological processes. Their biogenesis, from primary transcripts to mature miRNAs, have been extensively characterized in animals and plants, showing distinct differences between these phylogenetically distant groups of organisms. However, comparably little is known about miRNA biogenesis in organisms whose evolutionary position is placed in between plants and animals and/or in unicellular organisms.

Comparative omics and feeding manipulations in chicken indicate a shift of the endocrine role of visceral fat towards reproduction.

Background: The mammalian adipose tissue plays a central role in energy-balance control, whereas the avian visceral fat hardly expresses leptin, the key adipokine in mammals. Therefore, to assess the endocrine role of adipose tissue in birds, we compared the transcriptome and proteome between two metabolically different types of chickens, broilers and layers, bred towards efficient meat and egg production, respectively.

Results: Broilers and layer hens, grown up to sexual maturation under free-feeding conditions, differed 4.

Reading and editing the Pleurodeles waltl genome reveals novel features of tetrapod regeneration.

Salamanders exhibit an extraordinary ability among vertebrates to regenerate complex body parts. However, scarce genomic resources have limited our understanding of regeneration in adult salamanders. Here, we present the ~20 Gb genome and transcriptome of the Iberian ribbed newt Pleurodeles waltl, a tractable species suitable for laboratory research.

Characterization of the Giardia intestinalis secretome during interaction with human intestinal epithelial cells: The impact on host cells.

Background: Giardia intestinalis is a non-invasive protozoan parasite that causes giardiasis in humans, the most common form of parasite-induced diarrhea. Disease mechanisms are not completely defined and very few virulence factors are known.

Methodology: To identify putative virulence factors and elucidate mechanistic pathways leading to disease, we have used proteomics to identify the major excretory-secretory products (ESPs) when Giardia trophozoites of WB and GS isolates (assemblages A and B, respectively) interact with intestinal epithelial cells (IECs) in vitro.

A practical guide to build assemblies for single tissues of non-model organisms: the example of a Neotropical frog.

Whole genome sequencing (WGS) is a very valuable resource to understand the evolutionary history of poorly known species. However, in organisms with large genomes, as most amphibians, WGS is still excessively challenging and transcriptome sequencing (RNA-seq) represents a cost-effective tool to explore genome-wide variability. Non-model organisms do not usually have a reference genome and the transcriptome must be assembled .

RNA-sequence data normalization through in silico prediction of reference genes: the bacterial response to DNA damage as case study.

Background: Measuring how gene expression changes in the course of an experiment assesses how an organism responds on a molecular level. Sequencing of RNA molecules, and their subsequent quantification, aims to assess global gene expression changes on the RNA level (transcriptome). While advances in high-throughput RNA-sequencing (RNA-seq) technologies allow for inexpensive data generation, accurate post-processing and normalization across samples is required to eliminate any systematic noise introduced by the biochemical and/or technical processes.

Evolution of the p53-MDM2 pathway.

Background: The p53 signalling pathway, which controls cell fate, has been extensively studied due to its prominent role in tumor development. The pathway includes the tumor supressor protein p53, its vertebrate paralogs p63 and p73, and their negative regulators MDM2 and MDM4. The p53/p63/p73-MDM system is ancient and can be traced in all extant animal phyla.

PiiL: visualization of DNA methylation and gene expression data in gene pathways.

Background: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date.

Correspondence on Lovell et al.: identification of chicken genes previously assumed to be evolutionarily lost.

Through RNA-Seq analyses, we identified 137 genes that are missing in chicken, including the long-sought-after nephrin and tumor necrosis factor genes. These genes tended to cluster in GC-rich regions that have poor coverage in genome sequence databases. Hence, the occurrence of syntenic groups of vertebrate genes that have not been observed in Aves does not prove the evolutionary loss of such genes.

microTaboo: a general and practical solution to the k-disjoint problem.

Background: A common challenge in bioinformatics is to identify short sub-sequences that are unique in a set of genomes or reference sequences, which can efficiently be achieved by k-mer (k consecutive nucleotides) counting. However, there are several areas that would benefit from a more stringent definition of "unique", requiring that these sub-sequences of length W differ by more than k mismatches (i.e.