Abstract
Kiwifruit plants are particularly sensitive to soil waterlogging. Enhancement of waterlogging tolerance in kiwifruit can potentially considerably increase its fruit production and extend the shelf life of the fruit. We generated 95,945,496 bases of high-quality sequence from kiwifruit roots after 4-day waterlogging treatment using Illumina sequencing technology, and demonstrated de novo assembly and annotation of genes. These reads were assembled into 140,187 unigenes (mean length 556 bp). Based on a similarity search with known proteins in the non-redundant (nr) protein database, 56,912 unigenes (40.60 %) were functionally annotated with a cutoff E-value of 10−5. Using the RPKM method, we investigated differentially expressed genes by applying the Benjamini and Hochberg correction. Overall, 14,843 transcripts were identified as differentially expressed unigenes (DEG) in two samples. Among these unigenes, 5697 DEGs (about 38.5 %) were found to be induced by waterlogging, and 9146 DEGs (about 61.5 %) decreased in abundance. To identify the most important pathways represented by DEGs, we compared these genes to those in the KEGG database. The categories “ribosome,” “plant hormone signal transduction,” and “starch and sucrose metabolism” pathways contained the three highest numbers of differentially expressed unigenes and, thus, appear to play important roles in waterlogging perception. We identified many transcription factors, belonging to AP2/ERF, WRKY, TGA, MYB, bZIP families, implicating a potential function for them in waterlogging responses in kiwifruit. Our results provide a transcriptome profile that is associated with waterlogging stress induction in kiwifruit plants. The potential waterlogging stress-related transcripts identified in this study represent candidate genes and molecular resources to further understand the molecular mechanisms of the waterlogging response in kiwifruit.
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Abbreviations
- ADH:
-
Alcohol dehydrogenase
- KEGG:
-
Kyoto encyclopedia of genes and genomes
- COG:
-
Clusters of orthologous groups
- GO:
-
Gene ontology
- RPKM:
-
Reads per kilobase of exon region in a given gene per million mapped fragments
- DEGs:
-
Differential expression genes
- FDR:
-
False discovery rate
- PDC:
-
Pyruvate decarboxylase
- SK1:
-
SNORKEL1
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Acknowledgments
This study was supported by grants from the Natural Science Foundation of Jiangsu Province (Grant No. BK20140760) and the National Natural Science Foundation of China (NSFC) (31401854).
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Ji-Yu Zhang and Sheng-Nan Huang have contributed equally to this work.
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Supplemental Fig. 1
Length frequency distribution of unigenes (TIFF 168 kb)
Supplemental Fig. 2
Expression analysis of 10 DEGs by qRT-PCR performed on 10 members randomly selected from among the regulated genes (TIFF 10514 kb)
Supplemental Tab. 1
Primers for RT-qPCR in this study (DOCX 16 kb)
Supplemental Tab. 2
Length distribution of assembled contigs and unigenes (DOCX 17 kb)
Supplemental Tab. 3
Differentially expressed genes between two samples (p < 0.05) (XLS 8413 kb)
Supplemental Tab. 4
Most highly significantly regulated differentially expressed 200 genes between the two samples (q < 0.001) (XLS 53 kb)
Supplemental Tab. 5
Over-representative GO terms of DEGs in waterlogging-stressed kiwifruit (q < 0.05) (XLS 49 kb)
Supplemental Tab. 6
Pathway enrichment analyses for DEGs (q < 0.05) (XLS 31 kb)
Supplemental Tab. 7
Expression of the ADH and PDC gene families between two samples (q < 0.05) (XLS 27 kb)
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Zhang, JY., Huang, SN., Mo, ZH. et al. De novo transcriptome sequencing and comparative analysis of differentially expressed genes in kiwifruit under waterlogging stress. Mol Breeding 35, 208 (2015). https://doi.org/10.1007/s11032-015-0408-0
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DOI: https://doi.org/10.1007/s11032-015-0408-0