Genomics and metagenomics of microbes
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Genomics and metagenomics of microbes
Research related to fungal pathogen biology.
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Nature News: Devastating wheat fungus appears in Asia for first time (2016)

Nature News: Devastating wheat fungus appears in Asia for first time (2016) | Genomics and metagenomics of microbes | Scoop.it

Fields are ablaze in Bangladesh, as farmers struggle to contain Asia’s first outbreak of a fungal disease that periodically devastates crops in South America. Plant pathologists warn that wheat blast could spread to other parts of south and southeast Asia, and are hurrying to trace its origins.

 

Efforts are also under way to find wheat genes that confer resistance to the disease.

 

First detected in February and confirmed with genome sequencing by Kamoun’s lab this month, the wheat-blast outbreak has already caused the loss of more than 15,000 hectares of crops in Bangladesh. “It’s really an explosive, devastating disease,” says plant pathologist Barbara Valent of Kansas State University in Manhattan, Kansas. “It’s really critical that it be controlled in Bangladesh.”

 

After rice, wheat is the second most cultivated grain in Bangladesh, which has a population of 156 million people. More broadly, inhabitants of south Asia grow 135 million tonnes of wheat each year.

 

Wheat blast is caused by the fungus Magnaporthe oryzae. Since 1985, when scientists discovered it in Brazil’s Paraná state, the disease has raced across South America.

 

The fungus is better known as a pathogen of rice. But unlike in rice, where M. oryzae attacks the leaves, the fungus strikes the heads of wheat, which are difficult for fungicides to reach. A 2009 outbreak in wheat cost Brazil one-third of that year’s crop. “There are regions in South America where they don’t grow wheat because of the disease,” Valent says. Wheat blast was spotted in Kentucky in 2011, but vigorous surveillance helped to stop it spreading in the United States.

 

In South America, the disease tends to take hold in hot and humid spells. Such conditions are present in Bangladesh, and the disease could migrate across south and southeast Asia, say plant pathologists. In particular, itcould spread over the Indo-Gangetic Plain through Bangladesh, northern India and eastern Pakistan, warn scientists at the Bangladesh Agricultural Research Institute (BARI) in Nashipur.

 

Bangladeshi officials are burning government-owned wheat fields to contain the fungus, and telling farmers not to sow seeds from infected plots. The BARI hopes to identify wheat varieties that are more tolerant of the fungus and agricultural practices that can keep it at bay, such as crop rotation and seed treatment.

 

It is unknown how wheat blast got to Bangladesh. One possibility is that a wheat-infecting strain was brought in from South America, says Nick Talbot, a plant pathologist at the University of Exeter, UK. Another is that an M. oryzae strain that infects south Asian grasses somehow jumped to wheat, perhaps triggered by an environmental shift: that is what happened in Kentucky, when a rye-grass strain infected wheat.

 

To tackle the question, this month Kamoun’s lab sequenced a fungus sample from Bangladesh. The strain seems to be related to those that infect wheat in South America, says Kamoun, but data from other wheat-infecting strains and strains that plague other grasses are needed to pinpoint the outbreak’s origins conclusively.

 

The Open Wheat Blast website might help. Kamoun has uploaded the Bangladeshi data, and Talbot has deposited M. oryzae sequences from wheat in Brazil. Talbot hopes that widely accessible genome data could help to combat the outbreak. Researchers could use them to screen seeds for infection or identify wild grasses that can transmit the fungus to wheat fields.

 

Rapid data sharing is becoming more common in health emergencies, such as the outbreak of Zika virus in the Americas. Kamoun and Talbot say that their field should follow suit. “The plant-pathology community has a responsibility to allow data to be used to combat diseases that are happening now, and not worry too much about whether they may or may not get a Nature paper out of it,” says Talbot.

 

Last month, Valent’s team reported the first gene variant known to confer wheat-blast resistance (C. D. Cruz et al. Crop Sci. http://doi.org/bfk7; 2016), and field trials of crops that bear the resistance gene variant have begun in South America. But plant pathologists say that finding one variant is not enough: wheat strains must be bred with multiple genes for resistance, to stop M. oryzae quickly overcoming their defences.

 

The work could help in the Asian crisis, says Talbot. “What I would hope for out of this sorry situation,” he says, “is that there will be a bigger international effort to identify resistance genes.”


Via Kamoun Lab @ TSL
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A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling

A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling | Genomics and metagenomics of microbes | Scoop.it
A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling
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The invisible dimension of fungal diversity

The invisible dimension of fungal diversity | Genomics and metagenomics of microbes | Scoop.it
Taxonomy plays a central role in understanding the diversity of life, translating the products of biological exploration and discovery—specimens and observations—into systems of names that capture the relationships between species. Taxonomic names facilitate communication among scientists and the public and provide conceptual handles for complex phylogenetic hypotheses. However, taxonomy can be challenging, particularly for fungi and other microorganisms, which are morphologically simple and extremely diverse (1). Molecular environmental surveys have revealed previously unknown branches of the fungal tree of life (2–5) and illuminated biogeographic patterns across all groups of fungi (6, 7). Yet the products of this research are not being translated into formal species names, in part because of the very rules designed to facilitate taxonomy.

Via Steve Marek
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Comparative genome analysis and genome evolution of members of the magnaporthaceae family of fungi

Comparative genome analysis and genome evolution of members of the magnaporthaceae family of fungi | Genomics and metagenomics of microbes | Scoop.it
 A genome-scale comparative study was conducted across 74 fungal genomes to identify clusters of orthologous genes unique to the three Magnaporthaceae species as well as species specific genes. We found 1149 clusters that were unique to the Magnaporthaceae family of fungi with 295 of those containing genes from all three species. Gene clusters involved in metabolic and enzymatic activities were highly represented in the Magnaporthaceae specific clusters. Also highly represented in the Magnaporthaceae specific clusters as well as in the species specific genes were transcriptional regulators. In addition, we examined the relationship between gene evolution and distance to repetitive elements found in the genome. No correlations between diversifying or purifying selection and distance to repetitive elements or an increased rate of evolution in secreted and small secreted proteins were observed.
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On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-binary Gene Trees

On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-binary Gene Trees | Genomics and metagenomics of microbes | Scoop.it

Duplication-Transfer-Loss (DTL) reconciliation has emerged as a powerful technique for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation takes as input a gene family phylogeny and the corresponding species phylogeny, and reconciles the two by postulating speciation, gene duplication, horizontal gene transfer, and gene loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. However, gene trees are frequently non-binary. With such non-binary gene trees, the reconciliation problem seeks to find a binary resolution of the gene tree that minimizes the reconciliation cost. Given the prevalence of non-binary gene trees, many efficient algorithms have been developed for this problem in the context of the simpler Duplication-Loss (DL) reconciliation model. Yet, no efficient algorithms exist for DTL reconciliation with non-binary gene trees and the complexity of the problem remains unknown. In this work, we resolve this open question by showing that the problem is, in fact, NP-hard. Our reduction applies to both the dated and undated formulations of DTL reconciliation. By resolving this long-standing open problem, this work will spur the development of both exact and heuristic algorithms for this important problem.

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Impact of grassland management regimes on bacterial endophyte diversity differs with grass species

Impact of grassland management regimes on bacterial endophyte diversity differs with grass species | Genomics and metagenomics of microbes | Scoop.it

Most plant species are colonized by endophytic bacteria. Despite their importance for plant health and growth, the response of these bacteria to grassland management regimes is still not understood. Hence, we investigated the bacterial community structure in three agricultural important grass species Dactylis glomerata L., Festuca rubra L. and Lolium perenne L. with regard to fertilizer application and different mowing frequencies. For this purpose, above-ground plant material was collected from the Grassland Management Experiment (GrassMan) in Germany in September 2010 and 2011. DNA was extracted from surface-sterilized plant tissue and subjected to 16S rRNA gene PCRs. Endophytic community structures were assessed by denaturing gradient gel electrophoresis (DGGE) based analysis of obtained PCR products. DGGE fingerprints revealed that fertilizer application significantly altered the endophytic communities in L. perenne and F. rubra but not in D. glomerata. Although no direct effect of mowing was observed, mowing frequencies in combination with fertilizer application had a significant impact on endophyte bacterial community structures. However, this effect was not observed for all three grass species in both years. Therefore, our results showed that management regimes changed the bacterial endophyte communities but this effect was plant-specific and varied over time.

 
 
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NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes

NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes | Genomics and metagenomics of microbes | Scoop.it

The analysis of the microbial communities in and around us is a growing field of study, partly because of its major implications for human health, and partly because high-throughput DNA sequencing technology has only recently emerged to enable us to quantitatively study them. One of the most fundamental steps in analyzing these microbial communities is matching the microbial marker genes in environmental samples with existing databases to determine which microbes are present. The current techniques for doing this analysis are either slow or closed-source. We present an alternative technique that takes advantage of a high-speed Burrows-Wheeler alignment procedure combined with rapid filtering and parsing of the data to remove bottlenecks in the pipeline. We achieve an order-of-magnitude speedup over conventional techniques without sacrificing accuracy or memory use, and in some cases improving both significantly. Thus our method allows more biologists to process their own sequencing data without specialized computing resources, and it obtains more accurate and even optimal taxonomic annotation for their marker gene sequencing data.

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ISME J: Tree diversity and species identity effects on soil fungi, protists and animals are context dependent

ISME J: Tree diversity and species identity effects on soil fungi, protists and animals are context dependent | Genomics and metagenomics of microbes | Scoop.it

Plant species richness and the presence of certain influential species (sampling effect) drive the stability and functionality of ecosystems as well as primary production and biomass of consumers. However, little is known about these floristic effects on richness and community composition of soil biota in forest habitats owing to methodological constraints. We developed a DNA metabarcoding approach to identify the major eukaryote groups directly from soil with roughly species-level resolution. Using this method, we examined the effects of tree diversity and individual tree species on soil microbial biomass and taxonomic richness of soil biota in two experimental study systems in Finland and Estonia and accounted for edaphic variables and spatial autocorrelation. Our analyses revealed that the effects of tree diversity and individual species on soil biota are largely context dependent. Multiple regression and structural equation modelling suggested that biomass, soil pH, nutrients and tree species directly affect richness of different taxonomic groups. The community composition of most soil organisms was strongly correlated due to similar response to environmental predictors rather than causal relationships. On a local scale, soil resources and tree species have stronger effect on diversity of soil biota than tree species richness per se.


Via Stéphane Hacquard
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Hybridization of powdery mildew strains gives rise to pathogens on novel agricultural crop species : Nature Genetics

Hybridization of powdery mildew strains gives rise to pathogens on novel agricultural crop species : Nature Genetics | Genomics and metagenomics of microbes | Scoop.it
Throughout the history of agriculture, many new crop species (polyploids or artificial hybrids) have been introduced to diversify products or to increase yield. However, little is known about how these new crops influence the evolution of new pathogens and diseases. Triticale is an artificial hybrid of wheat and rye, and it was resistant to the fungal pathogen powdery mildew (Blumeria graminis) until 2001 (refs. 1,2,3). We sequenced and compared the genomes of 46 powdery mildew isolates covering several formae speciales. We found that B. graminis f. sp. triticale, which grows on triticale and wheat, is a hybrid between wheat powdery mildew (B. graminis f. sp. tritici) and mildew specialized on rye (B. graminis f. sp. secalis). Our data show that the hybrid of the two mildews specialized on two different hosts can infect the hybrid plant species originating from those two hosts. We conclude that hybridization between mildews specialized on different species is a mechanism of adaptation to new crops introduced by agriculture.

Via Francis Martin
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Functional overlap of the Arabidopsis leaf and root microbiota : Nature

Functional overlap of the Arabidopsis leaf and root microbiota : Nature | Genomics and metagenomics of microbes | Scoop.it
Roots and leaves of healthy plants host taxonomically structured bacterial assemblies, and members of these communities contribute to plant growth and health. We established Arabidopsis leaf- and root-derived microbiota culture collections representing the majority of bacterial species that are reproducibly detectable by culture-independent community sequencing. We found an extensive taxonomic overlap between the leaf and root microbiota. Genome drafts of 400 isolates revealed a large overlap of genome-encoded functional capabilities between leaf- and root-derived bacteria with few significant differences at the level of individual functional categories. Using defined bacterial communities and a gnotobiotic Arabidopsis plant system we show that the isolates form assemblies resembling natural microbiota on their cognate host organs, but are also capable of ectopic leaf or root colonization. While this raises the possibility of reciprocal relocation between root and leaf microbiota members, genome information and recolonization experiments also provide evidence for microbiota specialization to their respective niche.

Via Francis Martin
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Low multifunctional redundancy of soil fungal diversity at multiple scales

Low multifunctional redundancy of soil fungal diversity at multiple scales | Genomics and metagenomics of microbes | Scoop.it

Theory suggests that biodiversity might help sustain multiple ecosystem functions. To evaluate possible biodiversity–multifunctionality relationships in a natural setting, we considered different spatial scales of diversity metrics for soil fungi in the northern forests of Japan. We found that multifunctionality increased with increasing local species richness, suggesting a limited degree of multifunctional redundancy. This diversity–multifunctionality relationship was independent of the compositional uniqueness of each community. However, we still found the importance of community composition, because there was a positive correlation between community dissimilarity and multifunctional dissimilarity across the landscape. This result suggests that functional redundancy can further decrease when spatial variations in identities of both species and functions are simultaneously considered at larger spatial scales. We speculate that different scales of diversity could provide multiple levels of insurance against the loss of functioning if high-levels of local species diversity and compositional variation across locations are both maintained. Alternatively, making species assemblages depauperate may result in the loss of multifunctionality.

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Worse Comes to Worst: Bananas and Panama Disease—When Plant and Pathogen Clones Meet

Worse Comes to Worst: Bananas and Panama Disease—When Plant and Pathogen Clones Meet | Genomics and metagenomics of microbes | Scoop.it

The cultivated banana going extinct: it's just been a question of "when" for quite some time.

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The two-speed genomes of filamentous pathogens: waltz with plants

The two-speed genomes of filamentous pathogens: waltz with plants | Genomics and metagenomics of microbes | Scoop.it

Abstract: Fungi and oomycetes include deep and diverse lineages of eukaryotic plant pathogens. The last 10 years have seen the sequencing of the genomes of a multitude of species of these so-called filamentous plant pathogens. Already, fundamental concepts have emerged. Filamentous plant pathogen genomes tend to harbor large repertoires of genes encoding virulence effectors that modulate host plant processes. Effector genes are not randomly distributed across the genomes but tend to be associated with compartments enriched in repetitive sequences and transposable elements. These findings have led to the ‘two-speed genome’ model in which filamentous pathogen genomes have a bipartite architecture with gene sparse, repeat rich compartments serving as a cradle for adaptive evolution. Here, we review this concept and discuss how plant pathogens are great model systems to study evolutionary adaptations at multiple time scales. 

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Divergent and convergent evolution of fungal pathogenicity

Divergent and convergent evolution of fungal pathogenicity | Genomics and metagenomics of microbes | Scoop.it
Abstract:
Fungal pathogens of plants and animals have multifarious effects; they cause devastating damages to agricultures, lead to life-threatening diseases in humans, or induce beneficial effects by reducing insect pest populations. Many virulence factors have been determined in different fungal pathogens, however, the molecular determinants contributing to fungal host selection and adaptation are largely unknown. In this study, we sequenced the genomes of seven ascomycete insect pathogens and performed the genome-wide analyses of 33 species of filamentous ascomycete pathogenic fungi that infect insects (12 species), plants (12), and humans (9). Our results revealed that the genomes of plant pathogens encode more proteins and protein families than the insect and human pathogens. Unexpectedly, more common orthologous protein groups are shared between the insect and plant pathogens than between the two animal group pathogens. We also found that the pathogenicity of host-adapted fungi evolved multiple times, and that both divergent and convergent evolutions occurred during pathogen-host co-speciation thus resulting in protein families with similar features in each fungal group. However, the role of phylogenetic relatedness on the evolution of protein families and therefore pathotype formation could not be ruled out due to the effect of common ancestry. The evolutionary correlation analyses led to the identification of different protein families that correlated with alternate pathotypes. Particularly, the effector-like proteins identified in plant and animal pathogens were strongly linked to fungal host adaptation, suggesting the existence of similar gene-for-gene relationships in fungus-animal interactions that has not been established before. These results well advance our understanding of the evolution of fungal pathogenicity and the factors that contribute to fungal pathotype formation.
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Determining threshold values for barcoding fungi: lessons from Cortinarius (Basidiomycota), a highly diverse and widespread ectomycorrhizal genus

Determining threshold values for barcoding fungi: lessons from Cortinarius (Basidiomycota), a highly diverse and widespread ectomycorrhizal genus | Genomics and metagenomics of microbes | Scoop.it
Abstract Different distance-based threshold selection approaches were used to assess and compare use of the internal transcribed spacer (ITS) region to distinguish among 901 Cortinarius species represented by> 3000 collections. Sources of error...
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Deep Sequencing of Subseafloor Eukaryotic rRNA Reveals Active Fungi across Marine Subsurface Provinces

Deep Sequencing of Subseafloor Eukaryotic rRNA Reveals Active Fungi across Marine Subsurface Provinces | Genomics and metagenomics of microbes | Scoop.it
The deep marine subsurface is a vast habitat for microbial life where cells may live on geologic timescales. Because DNA in sediments may be preserved on long timescales, ribosomal RNA (rRNA) is suggested to be a proxy for the active fraction of a microbial community in the subsurface. During an investigation of eukaryotic 18S rRNA by amplicon pyrosequencing, unique profiles of Fungi were found across a range of marine subsurface provinces including ridge flanks, continental margins, and abyssal plains. Subseafloor fungal populations exhibit statistically significant correlations with total organic carbon (TOC), nitrate, sulfide, and dissolved inorganic carbon (DIC). These correlations are supported by terminal restriction length polymorphism (TRFLP) analyses of fungal rRNA. Geochemical correlations with fungal pyrosequencing and TRFLP data from this geographically broad sample set suggests environmental selection of active Fungi in the marine subsurface. Within the same dataset, ancient rRNA signatures were recovered from plants and diatoms in marine sediments ranging from 0.03 to 2.7 million years old, suggesting that rRNA from some eukaryotic taxa may be much more stable than previously considered in the marine subsurface.
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Dead fungal mycelium in forest soil represents a decomposition hotspot and a habitat for a specific microbial community

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BMC Bioinformatics

BMC Bioinformatics | Genomics and metagenomics of microbes | Scoop.it

The Ruby programming language has a lot to offer to any scientist with electronic data to process. Not only is the initial learning curve very shallow, but its reflection and meta-programming capabilities allow for the rapid creation of relatively complex applications while still keeping the code short and readable. This paper provides a gentle introduction to this scripting language for researchers without formal informatics training such as many wet-lab scientists. We hope this will provide such researchers an idea of how powerful a tool Ruby can be for their data management tasks and encourage them to learn more about it.

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PLOS Computational Biology: Ten Simple Rules for a Bioinformatics Journal Club

PLOS Computational Biology: Ten Simple Rules for a Bioinformatics Journal Club | Genomics and metagenomics of microbes | Scoop.it

Some structure for paper discussions.

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Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors

Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors | Genomics and metagenomics of microbes | Scoop.it
The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen’s advantage. Proteinaceous effectors are synthesised intracellularly and must be externalised to interact with host cells. Computational prediction of secreted proteins from genomic sequences is an important technique to narrow down the candidate effector repertoire for subsequent experimental validation. In this study, we benchmark secretion prediction tools on experimentally validated fungal and oomycete effectors. We observe that for a set of fungal SwissProt protein sequences, SignalP 4 and the neural network predictors of SignalP 3 (D-score) and SignalP 2 perform best. For effector prediction in particular, the use of a sensitive method can be desirable to obtain the most complete candidate effector set. We show that the neural network predictors of SignalP 2 and 3, as well as TargetP were the most sensitive tools for fungal effector secretion prediction, whereas the hidden Markov model predictors of SignalP 2 and 3 were the most sensitive tools for oomycete effectors. Thus, previous versions of SignalP retain value for oomycete effector prediction, as the current version, SignalP 4, was unable to reliably predict the signal peptide of the oomycete Crinkler effectors in the test set. Our assessment of subcellular localisation predictors shows that cytoplasmic effectors are often predicted as not extracellular. This limits the reliability of secretion predictions that depend on these tools. We present our assessment with a view to informing future pathogenomics studies and suggest revised pipelines for secretion prediction to obtain optimal effector predictions in fungi and oomycetes.
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Toward QIIME 2

Toward QIIME 2 | Genomics and metagenomics of microbes | Scoop.it
As some of our users may be aware, we’re starting to think about our transition from QIIME 1 to QIIME 2. We want to briefly share our thoughts about this transition so the QIIME user community has an idea of what to expect as we start this process. First, QIIME 1.9.x is a long-term support…
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BMC Bioinformatics

BMC Bioinformatics | Genomics and metagenomics of microbes | Scoop.it
Background

The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support.

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EffectorP: predicting fungal effector proteins from secretomes using machine learning

EffectorP: predicting fungal effector proteins from secretomes using machine learning | Genomics and metagenomics of microbes | Scoop.it

Effector prediction is tricky and essential.  This should be a great resource for mycologists!

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Metagenomics: Tools and Insights for Analyzing Next-Generation Sequencing Data Derived from Biodiversity Studies

Metagenomics: Tools and Insights for Analyzing Next-Generation Sequencing Data Derived from Biodiversity Studies | Genomics and metagenomics of microbes | Scoop.it

Broad review of metagenomic analysis tools.

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