Literature DB >> 30533460

Differential gene expression analysis and SNP/InDel marker discovery in resistant wild Asparagus kiusianus and susceptible A. officinalis in response to Phomopsis asparagi infection.

Mostafa Abdelrahman1,2, Mai Mitoma1, Takao Ikeuchi3, Mitsutaka Mori3, Kyoko Murakami3, Yukio Ozaki4, Masaru Matsumoto5, Atsuko Uragami6, Akira Kanno1.   

Abstract

This data article reports de novo transcriptome analysis of resistant wild Asparagus kiusianus and susceptible A. officinalis plants 24 and 48 h post-inoculation (24 and 48 hpi) with Phomopsis asparagi. Differential gene expression (DGE) analysis demonstrated that several genes involved in secondary metabolites and plant-pathogen interactions are up-regulated in resistant wild A. kiusianus relative to susceptible A. officinalis. The assembled contig sequences generated in this study were used to search single nucleotide polymorphism (SNP) and insertion/deletion (InDel) distribution in A. kiusianus and A. officinalis plants. SNP and InDel data developed from this transcriptome analysis will be used to generate a high-density linkage map to facilitate further development of molecular marker-assisted selection in A. officinalis.

Entities:  

Keywords:  Asparagus; Insertion/deletion; RNA-Seq; Single nucleotide polymorphism; Transcriptome

Year:  2018        PMID: 30533460      PMCID: PMC6262200          DOI: 10.1016/j.dib.2018.11.034

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications table Value of the data This is the first report about transcriptome dynamics and SNP/InDel variants associated with Phomopsis disease resistance in resistant wild Asparagus kiusianus and susceptible A. officinalis plants. DEG analysis provides a valuable information about defense responsive genes in Asparagus species against Phomopsis disease. SNP and InDel variants provided in this study will be useful for researchers involved in the future development of high-density linkage maps associated with Phomopsis disease resistance. SNP and Indel data can be further used for phylogenetic analysis of different Asparagus populations.

Data

In this study, the plant defense response in resistant wild A. kiusianus and susceptible A. officinalis was investigated 24 and 48 hpi with P. asparagi in comparison with non-inoculated control plants. Our recent study [1] showed that A. kiusianus, a wild relative of cultivated A. officinalis, displayed significantly reduced disease symptoms compared with susceptible A. officinalis upon artificial inoculation with P. asparagi [1]. In this study, we conducted de novo transcriptome analysis of resistant wild A. kiusianus and susceptible A. officinalis 24 and 48 hpi with P. asparagi. In total, 390,811,866 and 432,232,432 read counts with 100 bp read length were generated from 18 cDNA libraries. After removing adaptors and low-quality reads, more than 98% of the raw reads were clean reads. The high-quality reads were de novo assembled using Trinity software, and more than 95.68% and 95.74% were successfully mapped for the A. officinalis and A. kiusianus samples, respectively. In total, 206,164 and 213,950 contigs (average length, 973 bp) were obtained from A. officinalis and A. kiusianus, respectively. The quality of transcriptome assemblies was assessed, and the length distribution of the contigs in both A. officinalis and A. kiusianus is shown in Fig. 1A and B. Principal component analysis (PCA) of the transcriptome data (two Asparagus species × three biological replicates × three treatments (control, 24 and 48 hpi)) demonstrated a significant segregation in the wild resistant A. kiusianus (accumulation of variance 54,3%) and A. officinalis (accumulation of variance 58.3%) 24 and 48 hpi with P. asparagi relative to untreated control plants (Fig. 1C and D). The DEG analyses revealed that the total number of up-regulated transcripts in resistant wild A. kiusianus (7728) was relatively higher than that (7499) in susceptible A. officinalis (Fig. 1E and F). However, down-regulated transcripts (10,713) in susceptible A. officinalis was relatively higher than that (6789) in resistant wild A. kiusianus (Fig. 1G and H), suggesting that gene expression responses to P. asparagi infection differed between susceptible A. officinalis and resistant wild A. kiusianus. Further, we conducted SNP and InDel distribution in the resistant wild A. kiusianus and susceptible A. officinalis transcriptome using the recently released A. officinalis reference genome in NCBI (Tables S1–S4).
Fig. 1

Principal component analysis (PCA) and MA scatter plot of Asparagus kiusianus and A. officinalis 24 and 48 h post-inoculation (AKI_24hpi, AKI_48hpi, AOI_24hpi, and AOI_48hpi, respectively) with Phomopsis asparagi in comparison with non-inoculated control plants (AKC and AOC, respectively). (A and B) Length distribution of assembled transcriptome fragments in A. kiusianus and A. officinalis. (C and D) PCA analysis of AKI_24hpi, AKI_48hpi, AOI_24hpi, and AOI_48hpi relative to non-inoculated control plants (AKC and AOC, respectively). (E and F) MA scatter plots of differential gene expression in AKI_24hpi and AKI_48hpi in comparison with AKC control plants. (G and H) MA scatter plots of differential gene expression in AOI_24hpi and AOI_48hpi in comparison with AOC control plants. Log2 fold change on the y-axis and average count of RPKM (Reads Per Kilobase of exon per Million mapped reads) values on the x-axis. Significantly up-regulated genes (red, fold change > 2 and FDR < 0.05), down-regulated genes (green, fold change < 0.5 and FDR < 0.05).

Principal component analysis (PCA) and MA scatter plot of Asparagus kiusianus and A. officinalis 24 and 48 h post-inoculation (AKI_24hpi, AKI_48hpi, AOI_24hpi, and AOI_48hpi, respectively) with Phomopsis asparagi in comparison with non-inoculated control plants (AKC and AOC, respectively). (A and B) Length distribution of assembled transcriptome fragments in A. kiusianus and A. officinalis. (C and D) PCA analysis of AKI_24hpi, AKI_48hpi, AOI_24hpi, and AOI_48hpi relative to non-inoculated control plants (AKC and AOC, respectively). (E and F) MA scatter plots of differential gene expression in AKI_24hpi and AKI_48hpi in comparison with AKC control plants. (G and H) MA scatter plots of differential gene expression in AOI_24hpi and AOI_48hpi in comparison with AOC control plants. Log2 fold change on the y-axis and average count of RPKM (Reads Per Kilobase of exon per Million mapped reads) values on the x-axis. Significantly up-regulated genes (red, fold change > 2 and FDR < 0.05), down-regulated genes (green, fold change < 0.5 and FDR < 0.05).

Experimental designs, materials and methods

Male wild A. kiusianus (AK0501 strain) and female A. officinalis ‘Mary Washington 500W’ were cultivated under greenhouse conditions at Kagawa Prefectural Agricultural Experiment Station, Kagawa, Japan. Total RNA was extracted from 5-year-old A. officinalis and wild A. kiusianus 24 and 48 hpi with P. asparagi and from non-inoculated Asparagus plants grown under the same conditions (two Asparagus species × three biological replicates × three treatments (control, 24 and 48 hpi)). RNA concentration and quality were assessed using gel electrophoresis and UV/VIS Beckman DU 730 spectrophotometer (Beckman Coulter Inc., San Diego, CA, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies Inc., USA) instruments. Paired-end reads were generated by TaKaRa Bio (TaKaRa Bio, Kusatsu, Japan) using an Illumina HiSeq. 2500 instrument (Illumina Inc., USA). The raw reads were trimmed using Cutadapt v.1.339 and Sickle v.1.200. After trimming, 26.5 Gb of data were used for de novo transcriptome assembly using Trinity package v.2.0.6 [2], [3]. After assembly, 213,950 and 206,164 contigs were obtained from A. officinalis and A. kiusianus, respectively. These contigs were further used for DEG analysis. Sequencing read counts were calculated using RSEM v1.2.15 [4]. Gene expression from different samples was normalized by the TMM method [5]. DEGs were determined using the edgeR program. Genes with false discovery rate (FDR) < 0.05 and fold change > 2 were considered to be differentially expressed. PCA analysis was carried out by R statistics v3.4 (https://www.r-project.org/) using PCA-based unsupervised gene expression of A. officinalis and A. kiusianus. SNPs and InDels between A. officinalis, wild A. kiusianus, and the recently released A. officinalis reference genome were precisely pinpointed using a variant calling process. RNA-Seq reads were aligned to the reference genome using TopHat v. The output BAM files were subjected to SNP/InDel calling using PICARD and GATK (http://www.broadinstitute.org/gatk/) using the default parameters. In each condition, SNPs with reading depth > 5 and quality > 20 were identified as putative homozygous SNPs. The read depth at each locus was calculated using BED tools.
Subject areaBiology
More specific subject areaPlant molecular biology
Type of dataExcel file and figure
How data were acquiredNext-generation sequencing using Illumine HiSeq. 2500 platform
Data formatRaw, analyzed
Experimental factorsResistant A. kiusianus and susceptible A. officinalis plants were inoculated with P. asparagi and samples were collected 24 and 48 h post-inoculation.
Experimental featuresTranscriptome analysis was performed using cDNA libraries of A. officinalis and A. kiusianus 24 and 48 hpi with P. asparagi. The assembled contigs were further used for DEG analysis and SNP and InDel discovery.
Data source locationSendai, Japan
Data accessibilitySNP and InDel data are included in this article
  5 in total

1.  A scaling normalization method for differential expression analysis of RNA-seq data.

Authors:  Mark D Robinson; Alicia Oshlack
Journal:  Genome Biol       Date:  2010-03-02       Impact factor: 13.583

2.  De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis.

Authors:  Brian J Haas; Alexie Papanicolaou; Moran Yassour; Manfred Grabherr; Philip D Blood; Joshua Bowden; Matthew Brian Couger; David Eccles; Bo Li; Matthias Lieber; Matthew D MacManes; Michael Ott; Joshua Orvis; Nathalie Pochet; Francesco Strozzi; Nathan Weeks; Rick Westerman; Thomas William; Colin N Dewey; Robert Henschel; Richard D LeDuc; Nir Friedman; Aviv Regev
Journal:  Nat Protoc       Date:  2013-07-11       Impact factor: 13.491

3.  RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.

Authors:  Bo Li; Colin N Dewey
Journal:  BMC Bioinformatics       Date:  2011-08-04       Impact factor: 3.307

4.  Comparative de novo transcriptome profiles in Asparagus officinalis and A. kiusianus during the early stage of Phomopsis asparagi infection.

Authors:  Mostafa Abdelrahman; Naoyuki Suzumura; Mai Mitoma; Satoshi Matsuo; Takao Ikeuchi; Mitsutaka Mori; Kyoko Murakami; Yukio Ozaki; Masaru Matsumoto; Atsuko Uragami; Akira Kanno
Journal:  Sci Rep       Date:  2017-06-01       Impact factor: 4.379

5.  Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Authors:  Manfred G Grabherr; Brian J Haas; Moran Yassour; Joshua Z Levin; Dawn A Thompson; Ido Amit; Xian Adiconis; Lin Fan; Raktima Raychowdhury; Qiandong Zeng; Zehua Chen; Evan Mauceli; Nir Hacohen; Andreas Gnirke; Nicholas Rhind; Federica di Palma; Bruce W Birren; Chad Nusbaum; Kerstin Lindblad-Toh; Nir Friedman; Aviv Regev
Journal:  Nat Biotechnol       Date:  2011-05-15       Impact factor: 54.908

  5 in total
  1 in total

1.  MicroRNAs in Vitis vinifera cv. Chardonnay Are Differentially Expressed in Response to Diaporthe Species.

Authors:  Ales Eichmeier; Tomas Kiss; Eliska Penazova; Jakub Pecenka; Akila Berraf-Tebbal; Miroslav Baranek; Robert Pokluda; Jana Cechova; David Gramaje; Dariusz Grzebelus
Journal:  Genes (Basel)       Date:  2019-11-07       Impact factor: 4.096

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.