Systematic Characterization of Long Non-Coding RNAs and Their Responses to Drought Stress in Dongxiang Wild Rice

doi:10.1016/j.rsci.2019.12.003

Abstract

Abstract:

Long non-coding RNAs (lncRNAs) play important roles in response to various biotic and abiotic stresses. So far, systematic identification and characterization of lncRNAs have been reported in a few model plant species and major crops, but their roles in abiotic stress response have not yet been reported in common wild rice (Oryza rufipogon). Dongxiang wild rice (DXWR) possesses a high degree of drought resistance and has been well recognized as a precious genetic resource for drought resistant rice breeding. We presented the reference catalog of 1 655 novel lncRNA transcripts in DXWR using strand-specific RNA sequencing and bioinformatics approaches. Meanwhile, a total of 1 092 lncRNAs were determined as differentially expressed lncRNAs under drought stress. Quantitative real-time PCR results exhibited a high concordance with RNA sequencing data, which conﬁrmed that the expression patterns of lncRNAs based on RNA sequencing were highly reliable. Furthermore, 8 711 transcripts were predicted as target genes of the differentially expressed lncRNAs. Functional annotation analysis based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases showed that the target genes were signiﬁcantly enriched in cellular and metabolic processes, cell part, binding and plant hormone signal transduction, as well as many other terms related to abiotic stress resistance. These results expanded our understanding of lncRNA biology and provided candidate regulators for genetic improvement of drought resistance in rice cultivars.

Key words: Dongxiang wild rice, drought stress, long non-coding RNA, systematic characterization

Weidong Qi, Hongping Chen, Zuozhen Yang, Biaolin Hu, Xiangdong Luo, Bing Ai, Yuan Luo, Yu Huang, Jiankun Xie, Fantao Zhang. Systematic Characterization of Long Non-Coding RNAs and Their Responses to Drought Stress in Dongxiang Wild Rice[J]. Rice Science, 2020, 27(1): 21-31.

Figures/Tables 5

Table 1 RNA sequencing data for two samples.

Parameter	Control (DY-CK)	Drought stress (DY-D)
Raw base number	17 474 692 200	15 504 071 700
Clean base number	13 883 436 900	12 486 326 400
Raw read number	116 497 948	103 360 478
Low-quality read number ^a	9 723 402 (8.35%)	8 005 290 (7.75%)
Adapter polluted read number ^a	10 420 480 (8.95%)	8 331 824 (8.06%)
Clean read number ^a	92 556 246 (79.45%)	83 242 176 (80.54%)
Unmapped reads ^b	4 598 146 (4.97%)	4 835 398 (5.81%)
Total mapped reads ^b	87 958 100 (95.03%)	78 406 778 (94.19%)
Multiple mapped reads ^b	31 889 847 (34.45%)	21 343 543 (25.64%)
Unique mapped reads ^b	56 068 253 (60.58%)	57 063 235 (68.55%)
Reads map to exonic region (%)	66.01	71.79
Reads map to intronic region (%)	6.58	6.05
Reads map to intergenic region (%)	27.41	22.16

Fig. 1. Venn diagram of non-coding transcripts from the Coding-Non-Coding Index (CNCI), the Coding Potential Calculator (CPC), the Protein Families Database (PFAM), and the Coding-Potential Assessment Tool (CPAT).

Fig. 2. Comparison of expression levels of 15 randomly selected drought responsive lncRNAs using RNA sequencing and qRT-PCR methods. ===Seven down-regulated (MSTRG25356, MSTRG29971, MSTRG42925, MSTRG45354, MSTRG54123, MSTRG55730 and MSTRG69646) and eight up-regulated (MSTRG5459, MSTRG14660, MSTRG21367, MSTRG22525, MSTRG31874, MSTRG43289, MSTRG46940 and MSTRG62647) lncRNAs were used.

Fig. 3. Gene ontology (GO) classification for the predicted target genes of drought-responsive lncRNAs.

Fig. 4. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway assignments for predicted target genes of drought-responsive lncRNAs.

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