Transcriptome dataset of gall-rust infected Sengon (Falcataria falcata) seedlings using long-read PCR-cDNA sequencing

Sengon (Falcataria falcata) is an economically important legume tree widely cultivated in community forests, especially in Java Island. However, attacks of gall rust disease by Uromycladium falcatariae is difficult to manage. Understanding sengon genes expressions when artificially infected with gall rust fungi can help unravel its resistance mechanisms. Total RNA was extracted from sengon seedlings samples inoculated with U. falcatariae fungi at 7, 21, and 35 days after inoculation (DAI) and from the control group. Total RNA sequencing was performed using the PCR-cDNA Sequencing protocol (SQK-PCB109) from Oxford Nanopore Technologies. The RNA-Seq obtained varies from 1.3 million to 1.9 million total reads. The assembled full-length transcript was constructed using the RATTLE program, resulting in 21,819 transcripts. The TransDecoder program used to define open reading frames (ORFs) generated 2,342 transcripts, of which 34.15% were 5′prime_partial, 8.15% were 3′prime_partial, 8.5% were internal, and 49.14% were complete. Analysis of differentially expressed genes (DEGs) between resistant and susceptible seedlings, found that 1,013 genes that were up-regulated and 1,130 genes that were down-regulated in the resistant lines. The transcriptome data discussed in this article have been deposited in the DDBJ with accession number DRA015681.

a b s t r a c t Sengon ( Falcataria falcata ) is an economically important legume tree widely cultivated in community forests, especially in Java Island.However, attacks of gall rust disease by Uromycladium falcatariae is difficult to manage.Understanding sengon genes expressions when artificially infected with gall rust fungi can help unravel its resistance mechanisms.Total RNA was extracted from sengon seedlings samples inoculated with U. falcatariae fungi at 7, 21, and 35 days after inoculation (DAI) and from the control group.Total RNA sequencing was performed using the PCR-cDNA Sequencing protocol (SQK-PCB109) from Oxford Nanopore Technologies.The RNA-Seq obtained varies from 1.3 million to 1.9 million total reads.The assembled full-length transcript was constructed using the RATTLE program, resulting in 21,819 transcripts.The TransDecoder program used to define open reading frames (ORFs) generated 2,342 transcripts, of which 34.15% were 5 prime_partial, 8.15% were 3 prime_partial, 8.5% were internal, and 49.14% were complete.Analysis of differentially expressed genes (DEGs) between resistant and susceptible seedlings, found that 1,013 genes that were upregulated and 1,130 genes that were down-regulated in the resistant lines.

Value of the Data
• The data provide F. falcata seedling transcriptome reference using Oxford Nanopore Technologies of PCR-cDNA long-read sequencing after gall rust artificial inoculation • The presented dataset could help to explain the mechanisms of F. falcata resistance to gall rust disease • The data is beneficial to researchers involved in identifying genes that show differential expression during gall rust infection process and can be used to create genetic markers that will serve as a valuable tool for improvement of gall rust-resistant F. falcata trees.

Data Description
A total of eight RNA libraries consisted of resistant control, resistant 7 DAI (Day After Inoculation), resistant 21 DAI, resistant 35 DAI, susceptible control, as well as susceptible 7 DAI, susceptible 21 DAI, and susceptible 35 DAI were prepared and sequenced by PCR-cDNA long-read sequencing using MinION apparatus from Oxford Nanopore Technologies.Total RNA was extracted from each seedling leaves using Plant Total RNA Mini Kit (Geneaid) according to the manufacturer protocol.The raw data generated during sequencing were then preprocessed using Phychopper [1] and Cutadapt [2] to remove SSP (strand-switching primer), VNP (oligo-dT 30 VN), and polyA tails present in the reads.The raw and preprocessed data are shown in Table 1 .De novo assembly was then performed on the clean reads data using RATTLE [3][4][5] , which resulted in 21,819 transcripts ( Table 2 ).The assembled data transcripts were then annotated using BLAST + v.2.7.1 [6] .With a filtered-UNIPROT database and processed with Blast2go 6.0 software [7] .The TransDecoder program v.5.5.0 with default parameters [ 8 , 9 ] was then used to define open reading frames (ORFs) and generated 2,342 transcripts, of which 34.15% were 5 prime_partial, 8.15% were 3 prime_partial, 8.5% were internal, and 49.14% were complete ( Table 2 ).An overview of the Gene Ontology (GO) classification generated from F. falcata is shown in Fig. 1 .Gene Ontology is divided into three classifications, namely biological process, molecular function, and cellular component.The gene ontology that has the highest -log(10) value in each classification is transport for biological process, chaperone for molecular component, and chloroplast for cellular component.Fig. 2 shows the 17 KEGG pathways identified in F. falcata .Differentially Expressed Genes (DEGs) analysis on resistant vs susceptible seedlings using R v.4.1.0software with edgeR v.3.34.0 package showed that there were 1,013 up-regulated genes and 1,130 down-regulated genes in the resistant lines ( Fig. 3 ).The top ten up-regulated and down-regulated genes associated with defense responses to biotic stress in resistant vs susceptible F. falcata seedlings is shown in Table 3 .

Plant Materials
Two groups of two-month-old sengon seedlings, i.e resistant and susceptible lines ( Fig. 4 ) were used for artificial inoculation with U. falcatariae fungi [10] with control (non-inoculated ones) from each group.All seedlings were grown in the greenhouse of the Faculty of Forestry and Environment, IPB University, Indonesia (6 °33 ' 24.23 S 106 °43 ' 33.4 E).The leaf samples were collected from seedlings on 7, 21, and 35 days after inoculation (DAI) and from the control group ( Fig. 4 ).Three seedlings were used as biological replicates.

Total RNA Extraction and Sequencing
The RNA was extracted from leaves using the Plant Total RNA Mini Kit (Geneaid) according to the manufacturer protocol.The total RNA was extracted from three biological replicate and pooled based on DAI groups ( Fig. 4 ).The quality and quantity of the RNA were checked using the Nanophotometer NP-80 (Implen) and the Qubit TM RNA Broad Range (BR) assay on the Qubit® Fluorometer (Invitrogen).The extracted RNA was then used for RNA sequencing using PCR-cDNA Barcoding-SQK-PCB109 (PCB_9092_v109_revB_10Oct2019).The sequencing process was performed on a Flow Cell R9.4.1 (FLO-MIN106D) using the MinION Mk1B.

Functional Annotation
The assembled transcripts were annotated with the BLAST + v.2.7.1 [6] using a filtered UNIPROT database (Viridiplantae TaxID: 2759, downloaded October 19, 2021) with a cut-off threshold of 10 −5 .The resulting blast output was then processed using Blast2Go v.6.0 software to obtain functional annotations for Gene Ontology and KEGG pathways.DEGs analysis was performed using R v.4.1.0software with edgeR v.3.34.0 package to estimate the expression levels of all transcripts [14] .The results of the DEGs analysis are visualized with volcano plot using the tools available in the usegalaxy ( https://usegalaxy.eu/ ) web interface with logFC ≥ 2. Gene ontology and KEGG pathways of DEGs from resistant and susceptible seedlings were performed using the DAVID 2021 beta ( https://david.ncifcrf.gov/tools.jsp ) web interface [ 15 , 16 ].

Limitations
This study used seedlings derived from the seeds of resistant and susceptible parent trees that cross-pollinate in nature.In addition, due to limitations in obtaining good quality total RNA without degradation and fragmentation during library construction, sample pooling was carried out.

Ethics Statement
No human subjects, animal experiments, or any data collected from social media platforms were performed to obtain the data
The transcriptome data discussed in this article have been deposited in the DDBJ with accession number DRA015681.© 2023 The Authors.Published by Elsevier Inc.This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Table 2
Summary of de novo transcriptome assembly and open reading frames (ORFs) prediction characteristics.

Table 3
Top six each of up-regulated and down-regulated genes associated with defense responses to biotic stress in resistant vs susceptible Falcataria falcata seedlings.