Dataset Information

Identification and Temporal Expression Analysis of Conserved and Novel MicroRNAs in the Leaves of Winter Wheat Grown in the Field.

ABSTRACT: Cold acclimation and vegetative/reproductive transition are two important evolutionary adaptive mechanisms for winter wheat surviving the freezing temperature in winter and successful seeds setting in the next year. MicroRNA (miRNA) is a class of regulatory small RNAs (sRNAs), which plays critical roles in the growth and development of plants. However, the regulation mechanism of miRNAs during cold acclimation and vegetative/reproductive transition of winter wheat is not much understood. In this study, four sRNA libraries from leaves of winter wheat grown in the field at the three-leaf stage, winter dormancy stage, spring green-up stage, and jointing stage were analyzed to identify known and novel miRNAs and to understand their potential roles in the growth and development of winter wheat. We examined miRNA expression using a high-throughput sequencing technique. A total of 373 known, 55 novel, and 27 putative novel miRNAs were identified. Ninety-one miRNAs were found to be differentially expressed at the four stages. Among them, the expression of six known and eight novel miRNAs was significantly suppressed at the winter dormancy stage, whereas the expression levels of seven known and eight novel miRNAs were induced at this stage; three known miRNAs and three novel miRNAs were significantly induced at the spring green-up stage; six known miRNAs were induced at the spring green-up stage and reached the highest expression level at the jointing stage; and 20 known miRNAs and 10 novel miRNAs were significantly induced at the jointing stage. Expression of a number of representative differentially expressed miRNAs was verified using quantitative real-time polymerase chain reaction (qRT-PCR). Potential target genes for known and novel miRNAs were predicted. Moreover, six novel target genes for four Pooideae species-specific miRNAs and two novel miRNAs were verified using the RNA ligase-mediated 5'-rapid amplification of cDNA ends (RLM-5'RACE) technique. These results indicate that miRNAs are key non-coding regulatory factors modulating the growth and development of wheat. Our study provides valuable information for in-depth understanding of the regulatory mechanism of miRNAs in cold acclimation and vegetative/reproductive transition of winter wheat grown in the field.

SUBMITTER: Li YF

PROVIDER: S-EPMC6737308 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification and Temporal Expression Analysis of Conserved and Novel MicroRNAs in the Leaves of Winter Wheat Grown in the Field.

Li Yong-Fang YF Wei Kangning K Wang Menglei M Wang Li L Cui Junxia J Zhang Daijing D Guo Junqiang J Zhao Miao M Zheng Yun Y

Frontiers in genetics 20190904

Cold acclimation and vegetative/reproductive transition are two important evolutionary adaptive mechanisms for winter wheat surviving the freezing temperature in winter and successful seeds setting in the next year. MicroRNA (miRNA) is a class of regulatory small RNAs (sRNAs), which plays critical roles in the growth and development of plants. However, the regulation mechanism of miRNAs during cold acclimation and vegetative/reproductive transition of winter wheat is not much understood. In this ...[more]

PMID: 31552091

Similar Datasets

Project description:Low temperatures represent a crucial environmental factor determining winter survival (WS) of barley and wheat winter-type varieties. In laboratory experiments, low temperatures induce an active plant acclimation response, which is associated with an enhanced accumulation of several stress-inducible proteins including dehydrins. Here, dehydrin accumulations in sampled wheat (WCS120 protein family, or WCS120 and WDHN13 transcripts) and barley (DHN5 protein) varieties grown in two locations for two winters were compared with the variety WS evaluated by a provocation wooden-box test. A high correlation between dehydrin transcripts or protein relative accumulation and variety WS score was found only in samples taken prior vernalization fulfillment, when high tolerant varieties accumulated dehydrins earlier and to higher level than less tolerant varieties, and the plants have not yet been vernalized. After vernalization fulfillment, the correlation was weak, and the apical development indicated that plants reached double ridge (DR) in barley or stayed before DR in wheat. Dehydrin proteins and transcripts can be thus used as reliable markers of wheat or barley variety winter hardiness in the field conditions; however, only at the beginning of winter, when the plants have not yet finished vernalization. In wheat, a higher correlation was obtained for the total amount of dehydrins than for the individual dehydrin proteins.Highlights-More tolerant winter-type wheat and barley plants reveal higher threshold induction temperatures for dehydrin accumulation in comparison to less tolerant varieties. Thus, more tolerant winter cereals have higher dehydrin levels than the less tolerant ones upon the same ambient temperature in November samplings.-A significant correlation between dehydrin transcript/protein accumulation and winter survival was found in both winter wheat and winter barley plants in the field conditions, but only prior to vernalization fulfillment.

Project description:BackgroundWinter wheat requires prolonged exposure to low temperature to initiate flowering (vernalization). Shoot apical meristem of the crown is the site of cold perception, which produces leaf primordia during vegetative growth before developing into floral primordia at the initiation of the reproductive phase. Although many essential genes for winter wheat cold acclimation and floral initiation have been revealed, the importance of microRNA (miRNA) meditated post-transcriptional regulation in crowns is not well understood. To understand the potential roles of miRNAs in crown tissues, we performed a temporal expression study of miRNAs in crown tissues at the three-leaf stage, winter dormancy stage, spring green-up stage, and jointing stage of winter wheat grown under natural growth conditions.ResultsIn total, 348 miRNAs belonging to 298 miRNA families, were identified in wheat crown tissues. Among them, 92 differentially expressed miRNAs (DEMs) were found to be significantly regulated from the three-leaf stage to the jointing stage. Most of these DEMs were highly expressed at the three-leaf stage and winter dormancy stage, and then declined in later stages. Six DEMs, including miR156a-5p were markedly induced during the winter dormancy stage. Eleven DEMs, including miR159a.1, miR390a-5p, miR393-5p, miR160a-5p, and miR1436, were highly expressed at the green-up stage. Twelve DEMs, such as miR172a-5p, miR394a, miR319b-3p, and miR9676-5p were highly induced at the jointing stage. Moreover, 14 novel target genes of nine wheat or Pooideae-specific miRNAs were verified using RLM-5' RACE assay. Notably, six mTERFs and two Rf1 genes, which are associated with mitochondrial gene expression, were confirmed as targets of three wheat-specific miRNAs.ConclusionsThe present study not only confirmed the known miRNAs associated with phase transition and floral development, but also identified a number of wheat or Pooideae-specific miRNAs critical for winter wheat cold acclimation and floral development. Most importantly, this study provided experimental evidence that miRNA could regulate mitochondrial gene expression by targeting mTERF and Rf1 genes. Our study provides valuable information for further exploration of the mechanism of miRNA mediated post-transcriptional regulation during winter wheat vernalization and inflorescent initiation.

Project description:Remote sensing has been used as an important means of modern crop production monitoring, especially for wheat quality prediction in the middle and late growth period. In order to further improve the accuracy of estimating grain protein content (GPC) through remote sensing, this study analyzed the quantitative relationship between 14 remote sensing variables obtained from images of environment and disaster monitoring and forecasting small satellite constellation system equipped with wide-band CCD sensors (abbreviated as HJ-CCD) and field-grown winter wheat GPC. The 14 remote sensing variables were normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), optimized soil-adjusted vegetation index (OSAVI), nitrogen reflectance index (NRI), green normalized difference vegetation index (GNDVI), structure intensive pigment index (SIPI), plant senescence reflectance index (PSRI), enhanced vegetation index (EVI), difference vegetation index (DVI), ratio vegetation index (RVI), Rblue (reflectance at blue band), Rgreen (reflectance at green band), Rred (reflectance at red band) and Rnir (reflectance at near infrared band). The partial least square (PLS) algorithm was used to construct and validate the multivariate remote sensing model of predicting wheat GPC. The research showed a close relationship between wheat GPC and 12 remote sensing variables other than Rblue and Rgreen of the spectral reflectance bands. Among them, except PSRI and Rblue, Rgreen and Rred, other remote sensing vegetation indexes had significant multiple correlations. The optimal principal components of PLS model used to predict wheat GPC were: NDVI, SIPI, PSRI and EVI. All these were sensitive variables to predict wheat GPC. Through modeling set and verification set evaluation, GPC prediction models' coefficients of determination (R2) were 0.84 and 0.8, respectively. The root mean square errors (RMSE) were 0.43% and 0.54%, respectively. It indicated that the PLS algorithm model predicted wheat GPC better than models for linear regression (LR) and principal components analysis (PCA) algorithms. The PLS algorithm model's prediction accuracies were above 90%. The improvement was by more than 20% than the model for LR algorithm and more than 15% higher than the model for PCA algorithm. The results could provide an effective way to improve the accuracy of remotely predicting winter wheat GPC through satellite images, and was conducive to large-area application and promotion.

Dataset Information

Identification and Temporal Expression Analysis of Conserved and Novel MicroRNAs in the Leaves of Winter Wheat Grown in the Field.

Publications

Identification and Temporal Expression Analysis of Conserved and Novel MicroRNAs in the Leaves of Winter Wheat Grown in the Field.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets