In planta Identification of Putative Pathogenicity Factors from the Chickpea Pathogen Ascochyta rabiei by De novo Transcriptome Sequencing Using RNA-Seq and Massive Analysis of cDNA Ends

Fondevilla, Sara; Krezdorn, Nicolas; Rotter, Björn; Kahl, G.; Winter, Peter

doi:10.3389/fmicb.2015.01329

Cited by 21 publications

(20 citation statements)

References 51 publications

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“…AUGUSTUS (v 3.3) (Stanke et al 2004(Stanke et al , 2006König et al 2016) and expressed gene sequence data from a published A. rabiei (isolate P4) transcriptome project (Fondevilla et al 2015) were used to annotate transcribed gene features of the ArME14 genome assembly. Figure 1 shows GC-balanced, gene-rich regions as thick black bars interspersed between AT-rich, gene-sparse regions.…”

Section: Resultsmentioning

confidence: 99%

“…Gene prediction for the reference A. rabiei ArME14 assembly was performed using the annotation program, AUGUSTUS v 3.3 (Stanke et al 2004(Stanke et al , 2006König et al 2016), based on sequence homology of in vitro and in planta RNASeq and Massive Analysis of cDNA Ends (MACE) libraries from the A. rabiei BioProject, PRJNA288273 (Fondevilla et al 2015). We used BUSCO version 3.0 (Simão et al 2015) to assess assembly and annotation completeness by running protein fasta files with benchmarking against the Ascomycota_odb9 single-copy orthologs file downloaded from the BUSCO website September 2019 (https://busco.ezlab.org/).…”

Section: Genome Annotation and Analysismentioning

confidence: 99%

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Reference Genome Assembly for AustralianAscochyta rabieiIsolate ArME14

Shah

Williams

Hane

et al. 2020

G3 Genes|Genomes|Genetics

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Ascochyta rabiei is the causal organism of ascochyta blight of chickpea and is present in chickpea crops worldwide. Here we report the release of a high-quality PacBio genome assembly for the Australian A. rabiei isolate ArME14. We compare the ArME14 genome assembly with an Illumina assembly for Indian A. rabiei isolate, ArD2. The ArME14 assembly has gapless sequences for nine chromosomes with telomere sequences at both ends and 13 large contig sequences that extend to one telomere. The total length of the ArME14 assembly was 40,927,385 bp, which was 6.26 Mb longer than the ArD2 assembly. Division of the genome by OcculterCut into GC-balanced and AT-dominant segments reveals 21% of the genome contains gene-sparse, AT-rich isochores. Transposable elements and repetitive DNA sequences in the ArME14 assembly made up 15% of the genome. A total of 11,257 protein-coding genes were predicted compared with 10,596 for ArD2. Many of the predicted genes missing from the ArD2 assembly were in genomic regions adjacent to AT-rich sequence. We compared the complement of predicted transcription factors and secreted proteins for the two A. rabiei genome assemblies and found that the isolates contain almost the same set of proteins. The small number of differences could represent real differences in the gene complement between isolates or possibly result from the different sequencing methods used. Prediction pipelines were applied for carbohydrate-active enzymes, secondary metabolite clusters and putative protein effectors. We predict that ArME14 contains between 450 and 650 CAZymes, 39 putative protein effectors and 26 secondary metabolite clusters.

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Section: Resultsmentioning

confidence: 99%

Section: Genome Annotation and Analysismentioning

confidence: 99%

Reference Genome Assembly for AustralianAscochyta rabieiIsolate ArME14

Shah

Williams

Hane

et al. 2020

G3 Genes|Genomes|Genetics

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“…Further, very little information about A. rabiei is available at the genomic level. Recently, Fondevilla et al [42] reported a comprehensive A. rabiei transcriptome and identified several putative pathogenicity factors specifically induced during infection.…”

Section: Pathogen Variabilitymentioning

confidence: 99%

An Update on Genetic Resistance of Chickpea to Ascochyta Blight

Sharma

Ghosh

2016

Agronomy

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Ascochyta blight (AB) caused by Ascochyta rabiei (Pass.) Labr. is an important and widespread disease of chickpea (Cicer arietinum L.) worldwide. The disease is particularly severe under cool and humid weather conditions. Breeding for host resistance is an efficient means to combat this disease. In this paper, attempts have been made to summarize the progress made in identifying resistance sources, genetics and breeding for resistance, and genetic variation among the pathogen population. The search for resistance to AB in chickpea germplasm, breeding lines and land races using various screening methods has been updated. Importance of the genotypeˆenvironment (GE) interaction in elucidating the aggressiveness among isolates from different locations and the identification of pathotypes and stable sources of resistance have also been discussed. Current and modern breeding programs for AB resistance based on crossing resistant/multiple resistant and high-yielding cultivars, stability of the breeding lines through multi-location testing and molecular marker-assisted selection method have been discussed. Gene pyramiding and the use of resistant genes present in wild relatives can be useful methods in the future. Identification of additional sources of resistance genes, good characterization of the host-pathogen system, and identification of molecular markers linked to resistance genes are suggested as the key areas for future study.

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“…Moreover, suitable RNA sequencing methods, such as the massive analysis of cDNA ends (MACE) (Fondevilla et al 2015;Zajac et al 2015;Zawada et al 2014), contributed higher-level resolution in transcriptome analyses and alternative transcript identification, in comparison with conventional RNA-seq approaches. In Bokszczanin et al (2015), novel small nuclear RNAs (sncRNAs) from tomato tetrads, post-meiotic and mature pollen, expressed under control or heat stress conditions were detected.…”

Section: Next Generation Sequencing (Ngs) Datamentioning

confidence: 99%

Bioinformatics resources for pollen

et al. 2016

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Bioinformatics for Pollen. Pollen plays a key role in crop production, and its development is the most delicate phase in reproduction. Different metabolic pathways are involved in pollen development, and changes in the level of some metabolites, as well as responses to stress, are correlated with the reduction in pollen viability, leading consequently to a decrease in the fruit production. However, studies on pollen may be hard because gamete development and fertilization are complex processes that occur during a short window of time. The rise of the so-called -omics sciences provided key strategies to promote molecular research in pollen tissues, starting from model organisms and moving to increasing number of species. An integrated multi-level approach based on investigations from genomics, transcriptomics, proteomics and metabolomics appears now feasible to clarify key molecular processes in pollen development and viability. To this aim, bioinformatics has a fundamental role for data production and analysis, contributing varied and ad hoc methodologies, endowed with different sensitivity and specificity, necessary for extracting added-value information from the large amount of molecular data achievable. Bioinformatics is also essential for data management, organization, distribution and integration in suitable resources. This is necessary to catch the biological features of the pollen tissues and to design effective approaches to identifying structural or functional properties, enabling the modeling of the major involved processes in normal or in stress conditions. In this review, we provide an overview of the available bioinformatics resources for pollen, ranging from raw data collections to complete databases or platforms, when available, which include data and/or results from -omics efforts on the male gametophyte. Perspectives in the fields will also be described.

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In planta Identification of Putative Pathogenicity Factors from the Chickpea Pathogen Ascochyta rabiei by De novo Transcriptome Sequencing Using RNA-Seq and Massive Analysis of cDNA Ends

Cited by 21 publications

References 51 publications

Reference Genome Assembly for AustralianAscochyta rabieiIsolate ArME14

Reference Genome Assembly for AustralianAscochyta rabieiIsolate ArME14

An Update on Genetic Resistance of Chickpea to Ascochyta Blight

Bioinformatics resources for pollen

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