The Rhinella arenarum transcriptome: de novo assembly, annotation and gene prediction

Chaga (Inonotus obliquus) is a medicinal fungus used in traditional medicine of Native American and North Eurasian cultures. Several studies have demonstrated the medicinal properties of chaga’s bioactive molecules. For example, several terpenoids (e.g., betulin, betulinic acid and inotodiol) isolated from I. obliquus cells have proven effectiveness in treating different types of tumor cells. However, the molecular mechanisms and regulation underlying the biosynthesis of chaga terpenoids remain unknown. In this study, we report on the optimization of growing conditions for cultured I. obliquus in presence of different betulin sources (e.g., betulin or white birch bark). It was found that better results were obtained for a liquid culture pH 6.2 at 28 °C. In addition, a de novo assembly and characterization of I. obliquus transcriptome in these growth conditions using Illumina technology was performed. A total of 219,288,500 clean reads were generated, allowing for the identification of 20,072 transcripts of I. obliquus including transcripts involved in terpenoid biosynthesis. The differential expression of these genes was confirmed by quantitative-PCR. This study provides new insights on the molecular mechanisms and regulation of I. obliquus terpenoid production. It also contributes useful molecular resources for gene prediction or the development of biotechnologies for the alternative production of terpenoids.

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Telomere length de novo assembly of all 7 chromosomes and mitogenome sequencing of the model entomopathogenic fungus, Metarhizium brunneum, by means of a novel assembly pipeline

BMC Genomics ◽

10.1186/s12864-021-07390-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Zack Saud ◽

Alexandra M. Kortsinoglou ◽

Vassili N. Kouvelis ◽

Tariq M. Butt

Keyword(s):

De Novo Assembly ◽

De Novo ◽

Gene Prediction ◽

Fungal Species ◽

Orthologous Protein ◽

Metarhizium Brunneum ◽

Sequencing Technologies ◽

Protein Clusters ◽

Assembly Pipeline ◽

Generation Sequencing

Abstract Background More accurate and complete reference genomes have improved understanding of gene function, biology, and evolutionary mechanisms. Hybrid genome assembly approaches leverage benefits of both long, relatively error-prone reads from third-generation sequencing technologies and short, accurate reads from second-generation sequencing technologies, to produce more accurate and contiguous de novo genome assemblies in comparison to using either technology independently. In this study, we present a novel hybrid assembly pipeline that allowed for both mitogenome de novo assembly and telomere length de novo assembly of all 7 chromosomes of the model entomopathogenic fungus, Metarhizium brunneum. Results The improved assembly allowed for better ab initio gene prediction and a more BUSCO complete proteome set has been generated in comparison to the eight current NCBI reference Metarhizium spp. genomes. Remarkably, we note that including the mitogenome in ab initio gene prediction training improved overall gene prediction. The assembly was further validated by comparing contig assembly agreement across various assemblers, assessing the assembly performance of each tool. Genomic synteny and orthologous protein clusters were compared between Metarhizium brunneum and three other Hypocreales species with complete genomes, identifying core proteins, and listing orthologous protein clusters shared uniquely between the two entomopathogenic fungal species, so as to further facilitate the understanding of molecular mechanisms underpinning fungal-insect pathogenesis. Conclusions The novel assembly pipeline may be used for other haploid fungal species, facilitating the need to produce high-quality reference fungal genomes, leading to better understanding of fungal genomic evolution, chromosome structuring and gene regulation.

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Telomere length de novo assembly of all 7 chromosomes and mitogenome sequencing of the model entomopathogenic fungus, Metarhizium brunneum, by means of a novel assembly pipeline

10.21203/rs.3.rs-60098/v3 ◽

2020 ◽

Author(s):

Zack Saud ◽

Alexandra M. Kortsinoglou ◽

Vassili N. Kouvelis ◽

Tariq M. Butt

Keyword(s):

De Novo Assembly ◽

De Novo ◽

Gene Prediction ◽

Fungal Species ◽

Orthologous Protein ◽

Metarhizium Brunneum ◽

Sequencing Technologies ◽

Protein Clusters ◽

Assembly Pipeline ◽

Generation Sequencing

Abstract Background More accurate and complete reference genomes have improved understanding of gene function, biology, and evolutionary mechanisms. Hybrid genome assembly approaches leverage benefits of both long, relatively error-prone reads from third-generation sequencing technologies and short, accurate reads from second-generation sequencing technologies, to produce more accurate and contiguous de novo genome assemblies in comparison to using either technology independently. In this study, we present a novel hybrid assembly pipeline that allowed for both mitogenome de novo assembly and telomere length de novo assembly of all 7 chromosomes of the model entomopathogenic fungus, Metarhizium brunneum . Results The improved assembly allowed for better ab initio gene prediction and a more BUSCO complete proteome set has been generated in comparison to the eight current NCBI reference Metarhizium spp. genomes. Remarkably, we note that including the mitogenome in ab initio gene prediction training improved overall gene prediction. The assembly was further validated by comparing contig assembly agreement across various assemblers, assessing the assembly performance of each tool. Genomic synteny and orthologous protein clusters were compared between Metarhizium brunneum and three other Hypocreales species with complete genomes, identifying core proteins, and listing orthologous protein clusters shared uniquely between the two entomopathogenic fungal species, so as to further facilitate the understanding of molecular mechanisms underpinning fungal-insect pathogenesis. Conclusions The novel assembly pipeline may be used for other haploid fungal species, facilitating the need to produce high-quality reference fungal genomes, leading to better understanding of fungal genomic evolution, chromosome structuring and gene regulation.

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DATMA: Distributed AuTomatic Metagenomic Assembly and annotation framework

PeerJ ◽

10.7717/peerj.9762 ◽

2020 ◽

Vol 8 ◽

pp. e9762

Author(s):

Andres Benavides ◽

Friman Sanchez ◽

Juan F. Alzate ◽

Felipe Cabarcas

Keyword(s):

Quality Control ◽

De Novo Assembly ◽

De Novo ◽

Gene Prediction ◽

Draft Genome ◽

Computing Model ◽

Sequencing Quality ◽

Prime Objective ◽

Metagenomic Assembly ◽

Taxonomic Annotation

Background A prime objective in metagenomics is to classify DNA sequence fragments into taxonomic units. It usually requires several stages: read’s quality control, de novo assembly, contig annotation, gene prediction, etc. These stages need very efficient programs because of the number of reads from the projects. Furthermore, the complexity of metagenomes requires efficient and automatic tools that orchestrate the different stages. Method DATMA is a pipeline for fast metagenomic analysis that orchestrates the following: sequencing quality control, 16S rRNA-identification, reads binning, de novo assembly and evaluation, gene prediction, and taxonomic annotation. Its distributed computing model can use multiple computing resources to reduce the analysis time. Results We used a controlled experiment to show DATMA functionality. Two pre-annotated metagenomes to compare its accuracy and speed against other metagenomic frameworks. Then, with DATMA we recovered a draft genome of a novel Anaerolineaceae from a biosolid metagenome. Conclusions DATMA is a bioinformatics tool that automatically analyzes complex metagenomes. It is faster than similar tools and, in some cases, it can extract genomes that the other tools do not. DATMA is freely available at https://github.com/andvides/DATMA.

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Telomere length de novo assembly of all 7 chromosomes and mitogenome sequencing of the model entomopathogenic fungus, Metarhizium brunneum, by means of a novel assembly pipeline

10.21203/rs.3.rs-60098/v4 ◽

2021 ◽

Author(s):

Zack Saud ◽

Alexandra M. Kortsinoglou ◽

Vassili N. Kouvelis ◽

Tariq M. Butt

Keyword(s):

De Novo Assembly ◽

De Novo ◽

Gene Prediction ◽

Fungal Species ◽

Orthologous Protein ◽

Metarhizium Brunneum ◽

Sequencing Technologies ◽

Protein Clusters ◽

Assembly Pipeline ◽

Generation Sequencing

Abstract Background More accurate and complete reference genomes have improved understanding of gene function, biology, and evolutionary mechanisms. Hybrid genome assembly approaches leverage benefits of both long, relatively error-prone reads from third-generation sequencing technologies and short, accurate reads from second-generation sequencing technologies, to produce more accurate and contiguous de novo genome assemblies in comparison to using either technology independently. In this study, we present a novel hybrid assembly pipeline that allowed for both mitogenome de novo assembly and telomere length de novo assembly of all 7 chromosomes of the model entomopathogenic fungus, Metarhizium brunneum . Results The improved assembly allowed for better ab initio gene prediction and a more BUSCO complete proteome set has been generated in comparison to the eight current NCBI reference Metarhizium spp. genomes. Remarkably, we note that including the mitogenome in ab initio gene prediction training improved overall gene prediction. The assembly was further validated by comparing contig assembly agreement across various assemblers, assessing the assembly performance of each tool. Genomic synteny and orthologous protein clusters were compared between Metarhizium brunneum and three other Hypocreales species with complete genomes, identifying core proteins, and listing orthologous protein clusters shared uniquely between the two entomopathogenic fungal species, so as to further facilitate the understanding of molecular mechanisms underpinning fungal-insect pathogenesis. Conclusions The novel assembly pipeline may be used for other haploid fungal species, facilitating the need to produce high-quality reference fungal genomes, leading to better understanding of fungal genomic evolution, chromosome structuring and gene regulation.

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