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Auto Tag: Population genomics

July 7, 2019  |  

The draft genome of the lichen-forming fungus Lasallia hispanica (Frey) Sancho & A. Crespo

Lasallia hispanica (Frey) Sancho & A. Crespo is one of three Lasallia species occurring in central-western Europe. It is an orophytic, photophilous Mediterranean endemic which is sympatric with the closely related, widely distributed, highly clonal sister taxon L. pustulata in the supra- and oro-Mediterranean belts. We sequenced the genome of L. hispanica from a multispore isolate. The total genome length is 41·2 Mb, including 8488 gene models. We present the annotation of a variety of genes that are involved in protein secretion, mating processes and secondary metabolism, and we report transposable elements. Additionally, we compared the genome of L. hispanica to the closely related, yet ecologically distant, L. pustulata and found high synteny in gene content and order. The newly assembled and annotated L. hispanica genome represents a useful resource for future investigations into niche differentiation, speciation and microevolution in L. hispanica and other members of the genus.

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July 7, 2019  |  

Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak.

Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions. Copyright © 2018. Published by Elsevier B.V.

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July 7, 2019  |  

Tracing the de novo origin of protein-coding genes in yeast.

De novo genes are very important for evolutionary innovation. However, how these genes originate and spread remains largely unknown. To better understand this, we rigorously searched for de novo genes in Saccharomyces cerevisiae S288C and examined their spread and fixation in the population. Here, we identified 84 de novo genes in S. cerevisiae S288C since the divergence with their sister groups. Transcriptome and ribosome profiling data revealed at least 8 (10%) and 28 (33%) de novo genes being expressed and translated only under specific conditions, respectively. DNA microarray data, based on 2-fold change, showed that 87% of the de novo genes are regulated during various biological processes, such as nutrient utilization and sporulation. Our comparative and evolutionary analyses further revealed that some factors, including single nucleotide polymorphism (SNP)/indel mutation, high GC content, and DNA shuffling, contribute to the birth of de novo genes, while domestication and natural selection drive the spread and fixation of these genes. Finally, we also provide evidence suggesting the possible parallel origin of a de novo gene between S. cerevisiae and Saccharomyces paradoxus Together, our study provides several new insights into the origin and spread of de novo genes.IMPORTANCE Emergence of de novo genes has occurred in many lineages during evolution, but the birth, spread, and function of these genes remain unresolved. Here we have searched for de novo genes from Saccharomyces cerevisiae S288C using rigorous methods, which reduced the effects of bad annotation and genomic gaps on the identification of de novo genes. Through this analysis, we have found 84 new genes originating de novo from previously noncoding regions, 87% of which are very likely involved in various biological processes. We noticed that 10% and 33% of de novo genes were only expressed and translated under specific conditions, therefore, verification of de novo genes through transcriptome and ribosome profiling, especially from limited expression data, may underestimate the number of bona fide new genes. We further show that SNP/indel mutation, high GC content, and DNA shuffling could be involved in the birth of de novo genes, while domestication and natural selection drive the spread and fixation of these genes. Finally, we provide evidence suggesting the possible parallel origin of a new gene. Copyright © 2018 Wu and Knudson.

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July 7, 2019  |  

sppIDer: a species identification tool to investigate hybrid genomes with high-throughput sequencing.

The genomics era has expanded our knowledge about the diversity of the living world, yet harnessing high-throughput sequencing data to investigate alternative evolutionary trajectories, such as hybridization, is still challenging. Here we present sppIDer, a pipeline for the characterization of interspecies hybrids and pure species, that illuminates the complete composition of genomes. sppIDer maps short-read sequencing data to a combination genome built from reference genomes of several species of interest and assesses the genomic contribution and relative ploidy of each parental species, producing a series of colorful graphical outputs ready for publication. As a proof-of-concept, we use the genus Saccharomyces to detect and visualize both interspecies hybrids and pure strains, even with missing parental reference genomes. Through simulation, we show that sppIDer is robust to variable reference genome qualities and performs well with low-coverage data. We further demonstrate the power of this approach in plants, animals, and other fungi. sppIDer is robust to many different inputs and provides visually intuitive insight into genome composition that enables the rapid identification of species and their interspecies hybrids. sppIDer exists as a Docker image, which is a reusable, reproducible, transparent, and simple-to-run package that automates the pipeline and installation of the required dependencies (https://github.com/GLBRC/sppIDer; last accessed September 6, 2018).

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July 7, 2019  |  

MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies.

Large-scale bacterial population genetics studies are now routine due to cost-effective Illumina short-read sequencing. However, analysing plasmid content remains difficult due to incomplete assembly of plasmids. Bacterial isolates can contain any number of plasmids and assembly remains complicated due to the presence of repetitive elements. Numerous tools have been developed to analyse plasmids but the performance and functionality of the tools are variable. The MOB-suite was developed as a set of modular tools for reconstruction and typing of plasmids from draft assembly data to facilitate characterization of plasmids. Using a set of closed genomes with publicly available Illumina data, the MOB-suite identified contigs of plasmid origin with both high sensitivity and specificity (95 and 88?%, respectively). In comparison, plasmidfinder demonstrated high specificity (99?%) but limited sensitivity (50?%). Using the same dataset of 377 known plasmids, MOB-recon accurately reconstructed 207 plasmids so that they were assigned to a single grouping without other plasmid or chromosomal sequences, whereas plasmidSPAdes was only able to accurately reconstruct 102 plasmids. In general, plasmidSPAdes has a tendency to merge different plasmids together, with 208 plasmids undergoing merge events. The MOB-suite reduces the number of errors but produces more hybrid plasmids, with 84 plasmids undergoing both splits and merges. The MOB-suite also provides replicon typing similar to plasmidfinder but with the inclusion of relaxase typing and prediction of conjugation potential. The MOB-suite is written in Python 3 and is available from https://github.com/phac-nml/mob-suite.

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July 7, 2019  |  

Evolutionary emergence of drug resistance in Candida opportunistic pathogens.

Fungal infections, such as candidiasis caused by Candida, pose a problem of growing medical concern. In developed countries, the incidence of Candida infections is increasing due to the higher survival of susceptible populations, such as immunocompromised patients or the elderly. Existing treatment options are limited to few antifungal drug families with efficacies that vary depending on the infecting species. In this context, the emergence and spread of resistant Candida isolates are being increasingly reported. Understanding how resistance can evolve within naturally susceptible species is key to developing novel, more effective treatment strategies. However, in contrast to the situation of antibiotic resistance in bacteria, few studies have focused on the evolutionary mechanisms leading to drug resistance in fungal species. In this review, we will survey and discuss current knowledge on the genetic bases of resistance to antifungal drugs in Candida opportunistic pathogens. We will do so from an evolutionary genomics perspective, focusing on the possible evolutionary paths that may lead to the emergence and selection of the resistant phenotype. Finally, we will discuss the potential of future studies enabled by current developments in sequencing technologies, in vitro evolution approaches, and the analysis of serial clinical isolates.

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July 7, 2019  |  

Traditional Norwegian kveik are a genetically distinct group of domesticated Saccharomyces cerevisiae brewing yeasts.

The widespread production of fermented food and beverages has resulted in the domestication of Saccharomyces cerevisiae yeasts specifically adapted to beer production. While there is evidence beer yeast domestication was accelerated by industrialization of beer, there also exists a farmhouse brewing culture in western Norway which has passed down yeasts referred to as kveik for generations. This practice has resulted in ale yeasts which are typically highly flocculant, phenolic off flavor negative (POF-), and exhibit a high rate of fermentation, similar to previously characterized lineages of domesticated yeast. Additionally, kveik yeasts are reportedly high-temperature tolerant, likely due to the traditional practice of pitching yeast into warm (>28°C) wort. Here, we characterize kveik yeasts from 9 different Norwegian sources via PCR fingerprinting, whole genome sequencing of selected strains, phenotypic screens, and lab-scale fermentations. Phylogenetic analysis suggests that kveik yeasts form a distinct group among beer yeasts. Additionally, we identify a novel POF- loss-of-function mutation, as well as SNPs and CNVs potentially relevant to the thermotolerance, high ethanol tolerance, and high fermentation rate phenotypes of kveik strains. We also identify domestication markers related to flocculation in kveik. Taken together, the results suggest that Norwegian kveik yeasts are a genetically distinct group of domesticated beer yeasts with properties highly relevant to the brewing sector.

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July 7, 2019  |  

Omics in weed science: A perspective from genomics, transcriptomics, and metabolomics approaches

Modern high-throughput molecular and analytical tools offer exciting opportunities to gain a mechanistic understanding of unique traits of weeds. During the past decade, tremendous progress has been made within the weed science discipline using genomic techniques to gain deeper insights into weedy traits such as invasiveness, hybridization, and herbicide resistance. Though the adoption of newer “omics” techniques such as proteomics, metabolomics, and physionomics has been slow, applications of these omics platforms to study plants, especially agriculturally important crops and weeds, have been increasing over the years. In weed science, these platforms are now used more frequently to understand mechanisms of herbicide resistance, weed resistance evolution, and crop–weed interactions. Use of these techniques could help weed scientists to further reduce the knowledge gaps in understanding weedy traits. Although these techniques can provide robust insights about the molecular functioning of plants, employing a single omics platform can rarely elucidate the gene-level regulation and the associated real-time expression of weedy traits due to the complex and overlapping nature of biological interactions. Therefore, it is desirable to integrate the different omics technologies to give a better understanding of molecular functioning of biological systems. This multidimensional integrated approach can therefore offer new avenues for better understanding of questions of interest to weed scientists. This review offers a retrospective and prospective examination of omics platforms employed to investigate weed physiology and novel approaches and new technologies that can provide holistic and knowledge-based weed management strategies for future.

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July 7, 2019  |  

Genomic insights into date palm origins.

With the development of next-generation sequencing technology, the amount of date palm (Phoenix dactylifera L.) genomic data has grown rapidly and yielded new insights into this species and its origins. Here, we review advances in understanding of the evolutionary history of the date palm, with a particular emphasis on what has been learned from the analysis of genomic data. We first record current genomic resources available for date palm including genome assemblies and resequencing data. We discuss new insights into its domestication and diversification history based on these improved genomic resources. We further report recent discoveries such as the existence of wild ancestral populations in remote locations of Oman and high differentiation between African and Middle Eastern populations. While genomic data are consistent with the view that domestication took place in the Gulf region, they suggest that the process was more complex involving multiple gene pools and possibly a secondary domestication. Many questions remain unanswered, especially regarding the genetic architecture of domestication and diversification. We provide a road map to future studies that will further clarify the domestication history of this iconic crop.

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July 7, 2019  |  

Hardwood tree genomics: Unlocking woody plant biology.

Woody perennial angiosperms (i.e., hardwood trees) are polyphyletic in origin and occur in most angiosperm orders. Despite their independent origins, hardwoods have shared physiological, anatomical, and life history traits distinct from their herbaceous relatives. New high-throughput DNA sequencing platforms have provided access to numerous woody plant genomes beyond the early reference genomes of Populus and Eucalyptus, references that now include willow and oak, with pecan and chestnut soon to follow. Genomic studies within these diverse and undomesticated species have successfully linked genes to ecological, physiological, and developmental traits directly. Moreover, comparative genomic approaches are providing insights into speciation events while large-scale DNA resequencing of native collections is identifying population-level genetic diversity responsible for variation in key woody plant biology across and within species. Current research is focused on developing genomic prediction models for breeding, defining speciation and local adaptation, detecting and characterizing somatic mutations, revealing the mechanisms of gender determination and flowering, and application of systems biology approaches to model complex regulatory networks underlying quantitative traits. Emerging technologies such as single-molecule, long-read sequencing is being employed as additional woody plant species, and genotypes within species, are sequenced, thus enabling a comparative (“evo-devo”) approach to understanding the unique biology of large woody plants. Resource availability, current genomic and genetic applications, new discoveries and predicted future developments are illustrated and discussed for poplar, eucalyptus, willow, oak, chestnut, and pecan.

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