Genome-wide identification and characterization of long non-coding RNAs related to grain yield in foxtail millet [Setaria italica (L.) P. Beauv.]
Long noncoding RNAs (lncRNAs) have been reported to play critical roles in diverse growth and development processes in plants. However, the systematic identification and characterization of lncRNAs in foxtail millet is nearly blank. In this study, we performed high-throughput sequencing of young spi...
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Published in | BMC genomics Vol. 21; no. 1; p. 853 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
BioMed Central Ltd
01.12.2020
BioMed Central BMC |
Subjects | |
Online Access | Get full text |
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Summary: | Long noncoding RNAs (lncRNAs) have been reported to play critical roles in diverse growth and development processes in plants. However, the systematic identification and characterization of lncRNAs in foxtail millet is nearly blank.
In this study, we performed high-throughput sequencing of young spikelets from four foxtail millet varieties in different yield levels at booting stage. As a result, a total of 12,378 novel lncRNAs were identified, and 70 were commonly significantly differentially expressed in comparisons between high-yield varieties and conventional varieties, suggesting that they involved in yield formation and regulation in foxtail millet. Functional analysis revealed that among the 70 significantly differentially expressed lncRNAs, 67 could transcriptionally modulate target genes in cis and in trans. Moreover, 18 lncRNAs related to grain yield in foxtail millet were predicted to function as miRNA target mimics and regulate gene expression by competing for the interaction between miRNAs and their target mRNAs.
Our results will provide materials for elucidation of the molecular mechanisms of lncRNAs participate in yield regulation, and will contribute to high yield foxtail millet breeding. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1471-2164 1471-2164 |
DOI: | 10.1186/s12864-020-07272-9 |