Illumina MiSeq sequencing of fungal functional genes
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR922328_1.fastq.gz | Fastqsanger.gz | |||
| ERR922328_2.fastq.gz | Fastqsanger.gz | |||
| ERR922329_1.fastq.gz | Fastqsanger.gz | |||
| ERR922329_2.fastq.gz | Fastqsanger.gz | |||
| ERR922330_1.fastq.gz | Fastqsanger.gz |
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Project description:PCR primers to study the diversity of expressed fungal genes encoding lignocellulolytic enzymes in soils using high-throughput sequencing
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Project description:A study was conducted to analyze fungal diversity in the roots of acid lime (Citrus aurantifolia) collected from Oman, a semi-arid country located in the South Eastern part of the Arabian Peninsula. MiSeq analysis showed the Ascomycota and Sordariomycetes were the most abundant phylum and class in acid lime roots, respectively. Glomeromycota, Basidiomycota and Microsporidia were the other fungal phyla, while Glomeromycetes and some other classes belonging to Ascomycota and Basidiomycota were detected at lower frequencies. The genus Fusarium was the most abundant in all samples, making up 46 to 95% of the total reads. Some fungal genera of Arbuscular mycorrhizae and nematophagous fungi were detected in some of the acid lime roots. Analysis of the level of fungal diversity showed that no significant differences exist among groups of root samples (from different locations) in their Chao richness and Shannon diversity levels (P < 0.05). Principle component analysis of fungal communities significantly separated samples according to their locations. This is the first study to evaluate fungal diversity in acid lime roots using high throughput sequencing analysis. The study reveals the presence of various fungal taxa in the roots, dominated by Fusarium species and including some mycorrhizae and nematophagous fungi.
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Project description:Deadwood plays a crucial role in forest ecosystems, but we have limited information about the specific fungal taxa and extracellular lignocellulolytic enzymes that are actively involved in the decomposition process in situ. To investigate this, we studied the fungal metaproteome of twelve deadwood tree species in a replicated, eight-year experiment. Key fungi observed included genera of white-rot fungi (Basidiomycota, e.g. Armillaria, Hypholoma, Mycena, Ischnoderma, Resinicium), brown-rot fungi (Basidiomycota, e.g. Fomitopsis, Antrodia), diverse Ascomycota including xylariacous soft-rot fungi (e.g. Xylaria, Annulohypoxylon, Nemania) and various wood-associated endophytes and saprotrophs (Ascocoryne, Trichoderma, Talaromyces). These fungi used a whole range of extracellular lignocellulolytic enzymes, such as peroxidases, peroxide-producing enzymes, laccases, cellulases, glucosidases, hemicellulases (xylanases) and lytic polysaccharide monooxygenases (LPMOs). Both the fungi and enzymes were tree-specific, with specialists and generalists being distinguished by network analysis. The extracellular enzymatic system was highly redundant, with many enzyme classes of different origins present simultaneously in all decaying logs. Strong correlations were found between peroxide-producing enzymes (oxidases) and peroxidases as well as LPMOs, and between ligninolytic, cellulolytic and hemicellulolytic enzymes. The overall protein abundance of lignocellulolytic enzymes was reduced by up to -30% in gymnosperm logs compared to angiosperm logs, and gymnosperms lacked ascomycetous enzymes, which may have contributed to the lower decomposition of gymnosperm wood. In summary, we have obtained a comprehensive and detailed insight into the enzymatic machinery of wood-inhabiting fungi in several temperate forest tree species, which can help to improve our understanding of the complex ecological processes in forest ecosystems.
2024-04-22 | PXD041962 | Pride
Project description:Thermothelomyces thermophilus, formerly known as Myceliophthora thermophila, is used in industry to produce lignocellulolytic enzymes and heterologous proteins. However, the transcriptional network driving the expression of these proteins remains elusive. As a first step to systematically uncover this network, we investigated growth, protein secretion, and transcriptomic fingerprints of strains deficient in the cellulolytic transcriptional regulators Clr1, Clr2, and Clr4, respectively. The genes encoding Clr1, Clr2, and Clr4 were individually deleted using split marker or the CRISPR/Cas12a technology and the resulting strains as well as the parental strain were cultivated in bioreactors under chemostat conditions using glucose as carbon source. During steady state conditions, cellulose was added instead of glucose to study the genetic and cellular responses in all four strains to the shift in carbon source availability. Notably, the clr1 and clr2 deletion strains were unable to continue to grow on cellulose, demonstrating a key role of both regulators in cellulose catabolism. Their transcriptomic fingerprints uncovered not only a lack of cellulase gene expression but also reduced expression of genes predicted to encode hemicellulases, pectinases, and esterases. In contrast, the growth of the clr4 deletion strain was very similar compared to the parental strain. However, a much stronger expression of cellulases, hemicellulases, pectinases, and esterases was observed. The data gained in this study suggest that both transcriptional regulators Clr1 and Clr2 activate the expression of genes predicted to encode cellulases as well as hemicellulases, pectinases, and esterases. They further suggest that Clr1 controls the basal expression of cellulases and initiates the main lignocellulolytic response to cellulose via induction of clr2 expression. In contrast, Clr4 seems to act as a repressor of the lignocellulolytic response presumably via controlling clr2 expression. Comparative transcriptomics in all four strains revealed potentially new regulators in carbohydrate catabolism and lignocellulolytic enzyme expression that define a candidate gene list for future analyses.
2021-12-15 | GSE183387 | GEO
Project description:Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered, the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.
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Project description:Green fluorescent protein (GFP) is one of the most used reporter genes. We have used next-generation sequencing (NGS) to analyse the genetic diversity of a recombinant influenza A virus that expresses GFP and found a remarkable coverage dip in the GFP coding sequence. This coverage dip was present when virus-derived RT-PCR product or the parental plasmid DNA was used as starting material for NGS and regardless of whether Nextera XT transposase or Covaris shearing was used for DNA fragmentation. Therefore, the sequence coverage dip in the GFP coding sequence was not the result of emerging GFP mutant viruses or a bias introduced by Nextera XT fragmentation. Instead, we found that the Illumina MiSeq sequencing method disfavours the 'CCCGCC' motif in the GFP coding sequence.
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Project description:This study aimed to evaluate the difference in gut microbiomes between preterm and term infants using third-generation long-read sequencing (Oxford Nanopore Technologies, ONT) compared with an established gold standard, Illumina (second-generation short-read sequencing). A total of 69 fecal samples from 51 term (T) and preterm (P) infants were collected at 7 and 28 days of life. Gut colonization profiling was performed by 16S rRNA gene sequencing using ONT. We used Illumina to validate and compare the patterns in 13 neonates. Using bioinformatic analysis, we identified features that differed between P and T. Both T1 and P1 microbiomes were dominated by Firmicutes (Staphylococcus and Enterococcus), whereas sequentially showed dominant transitions to Lactobacillus (p < 0.001) and Streptococcus in T2 (p = 0.001), and pathogenic bacteria (Klebsiella) in P2 (p = 0.001). The abundance of beneficial bacteria (Bifidobacterium and Lactobacillus) increased in T2 (p = 0.026 and p < 0.001, respectively). These assignments were correlated with the abundance at the species-level. Bacterial α-diversity increased in T (p = 0.005) but not in P (p = 0.156), and P2 showed distinct β-diversity clustering than T2 (p = 0.001). The ONT reliably identified pathogenic bacteria at the genus level, and taxonomic profiles were comparable to those identified by Illumina at the genus level. This study shows that ONT and Illumina are highly correlated. P and T had different microbiome profiles, and the α- and β-diversity varied. ONT sequencing has potential for pathogen detection in neonates in clinical settings.
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Project description:Human immunodeficiency virus type-1 (HIV-1) exhibits high between-host genetic diversity and within-host heterogeneity, recognized as quasispecies. Because HIV-1 quasispecies fluctuate in terms of multiple factors, such as antiretroviral exposure and host immunity, analyzing the HIV-1 genome is critical for selecting effective antiretroviral therapy and understanding within-host viral coevolution mechanisms. Here, to obtain HIV-1 genome sequence information that includes minority variants, we sought to develop a method for evaluating quasispecies throughout the HIV-1 near-full-length genome using the Illumina MiSeq benchtop deep sequencer. To ensure the reliability of minority mutation detection, we applied an analysis method of sequence read mapping onto a consensus sequence derived from de novo assembly followed by iterative mapping and subsequent unique error correction. Deep sequencing analyses of aHIV-1 clone showed that the analysis method reduced erroneous base prevalence below 1% in each sequence position and discarded only < 1% of all collected nucleotides, maximizing the usage of the collected genome sequences. Further, we designed primer sets to amplify the HIV-1 near-full-length genome from clinical plasma samples. Deep sequencing of 92 samples in combination with the primer sets and our analysis method provided sufficient coverage to identify >1%-frequency sequences throughout the genome. When we evaluated sequences of pol genes from 18 treatment-naïve patients' samples, the deep sequencing results were in agreement with Sanger sequencing and identified numerous additional minority mutations. The results suggest that our deep sequencing method would be suitable for identifying within-host viral population dynamics throughout the genome.
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