News Release

Wheat's long non-coding RNAs unveiled: A leap in understanding grain development

Peer-Reviewed Publication

Maximum Academic Press

Figure 1.

image: Comparison of protein-coding genes and lncRNAs in wheat. view more 

Credit: Seed Biology

Wheat is a global staple food and plays a pivotal role in the livelihoods of billions of people. Although long non-coding RNAs (lncRNAs) have been recognized as crucial regulators of numerous biological processes, our knowledge of lncRNAs associated with wheat (Triticum aestivum) grain development remains minimal.

Seed Biology published an online paper entitled “A comprehensive atlas of long non-coding RNAs provides insight into grain development in wheat” on 04 September 2023.

To elucidate the landscape of lncRNAs in wheat, this study conducted genome-wide strand-specific RNA sequencing (ssRNA-seq) on grain endosperm at 10 and 15 days after pollination (DAP) and integrated 545 publicly available transcriptome datasets from various developmental stages and tissues. The analysis pipeline  was adapted from a previous study with modifications, processed RNA-seq data in three primary steps: mapping, assembly, and filtering. The results identified 20,893 lncRNAs in wheat. The characterization of these lncRNAs indicated an average transcript length of 900 bp, and were predominantly single exon structure (48%), with significant overlap with long terminal repeat retrotransposons (LTRs, 41.40%). Compared with protein-coding genes (PCGs), wheat lncRNAs exhibit shorter transcript lengths, fewer exons, and higher tissue-specific expression than PCGs, and their expression patterns were positively correlated with adjacent PCGs. Furthermore, analyzing the distribution of lncRNAs across the three wheat subgenomes (A, B, and D) revealed that 90.7% of the lncRNAs were exclusive to a single subgenome, suggesting that lncRNAs have different evolutionary trajectories compared with PCGs. To ensure efficient access to this wealth data, this study developed the comprehensive database wLNCdb (http://wheat.cau.edu.cn/wLNCdb) , which provides various tools to explore wheat lncRNA profiles, including expression patterns, co-expression networks, functional annotations, and single nucleotide polymorphisms among wheat accessions. Notably, using wLNCdb, the authors identified the lncRNA TraesLNC1D26001.1, which negatively regulates seed germination as its overexpression delayed wheat seed germination by upregulating Abscisic acid-insensitive 5 (TaABI5). Moreover, this lncRNA appears to co-express with genes associated with starch and protein biosynthesis in wheat, emphasizing its potential regulatory role in grain development and end-use quality.

In summation, this pioneering study provides a comprehensive map of wheat lncRNAs. The wLNCdb, with its plethora of information and advanced toolset, lays the groundwork for future exploration and analysis of the functions of lncRNAs. This research not only deepens our understanding of wheat lncRNAs' roles, especially during seed development, but also paves the way for leveraging this knowledge to boost wheat yields and quality in the future.

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References

Authors

Zhaoheng Zhang1,#, Ruijie Zhang1,#, Fengfan Meng1, Yongming Chen1, Wenxi Wang1, Kai Yang1, Yujiao Gao2, Mingming Xin1, Jinkun Du1, Zhaorong Hu1, Zhongfu Ni1, Qixin Sun1, Weilong Guo1,* ,  & Yingyin Yao1,*

# These authors contributed equally: Zhaoheng Zhang, Ruijie Zhang

Affiliations

1. Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China

2. Jiangsu Co-innovation Center for Modern Production Technology of Grain Crops/Jiangsu Key Lab of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou 225009, China

About Weilong Guo & Yingyin Yao

Weilong Guo: An associate professor at the College of Agriculture, China Agricultural University. He is currently taking wheat as his research object, combining bioinformatics, genomics, artificial intelligence and other means to focus on the integration and mining of multi-omics big data of crops, analysis of wheat genome variation and evolutionary laws, composition of wheat germplasm resources and utilization of excellent genes, and other issues.

Yingyin Yao: A professor at the College of Agriculture, China Agricultural University. She is mainly engaged in research of genetic improvement of wheat processing quality traits.


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