View source for IC4R004-miRNA-2013-23469249

== Project Title ==
''' Identification and Expression Analysis of microRNAs at the Grain Filling Stage in Rice( Oryza sativa L.)via Deep Sequencing  '''

==The Background of This Project==
[[File:IC4R004-miRNA-2013-23469249-1.PNG|700px|thumb|right|'''Figure 1.''' '' GWA Analysis of Al Tolerance within and across Rice Subpopulations.'']]
* Rice (Oryza sativa L.) grain filling is a highly coordinated developmental process. During this period, large amounts of storage compounds are synthesized and transported into the rice endosperm, which are major determinants of the economic value of rice grain and provide nutrients and calories for humans and many other animals. Extensive studies on the mechanisms underlying this process have been carried out in the past two decades. It has been documented that transcription control is a primary mechanism for determining endosperm development. Several enzymes interact with certain key transcription factors to regulate the transcription of nutrient partitioning genes during grain filling, at each developmental stage. Both the participating enzymes and reserve compounds are expressed in appropriate amounts and are tightly regulated both spatially and temporally. Phytohormones are also considered to play important roles in plant development. It has been reported that appropriate concentrations of ethylene, IAA and abscisic acid (ABA) can increase the rate of reserve compound synthesis, leading to higher grain yields. Proteomic and cDNA microarray analyses revealed that the products of grain filling-related genes are associated with several important processes, including biosynthesis, metabolism, transportation, the response to stimuli and signal transduction. These findings, together with observations of the morphological changes that occur rice grain during the filling process, suggest that the accumulation of reserves involves multiple metabolic and regulatory pathways, and the expression of the genes in different pathways is coordinately regulated in a timely manner between different developmental stages during grain filling. In spite of this, the genes and underlying molecular mechanisms controlling rice grain filling remain elusive.

==Plant Culture & Treatment==
* Rice (Oryza sativa L. cv Nipponbare) was grown in soil in an experimental field at the Wuhan University Institute of Genetics (Wuhan, China) (latitude 30u340N; longitude 114u170E). Rice grains at different developmental stages, including: 5 DAF, 7 DAF, 12 DAF and 17 DAF, were collected, frozen in liquid nitrogen and stored at 280uC for further use.

==Research Findings==
* Total RNA was isolated from developing rice grains collected at 5 DAF, 7 DAF, 12 DAF and 17 DAF to construct four libraries and then subjected to Solexa (now Illumina Inc.) high-throughput RNA-sequencing to determine the expression profiles of miRNAs among the different libraries. The total numbers of clean reads, ranging from 18 to 30 nucleotides in length, were yielded from each of four libraries after precluding the low quality reads, 39 adaptor and 59 contaminant sequences were as follows: 17029030 (5 DAF), 15582300 (7 DAF), 15860692(12 DAF) and 15174972(17 DAF). These reads corresponded to 4707574, 5109716, 6367974 and 6302095 unique sRNA sequences in the 5 DAF, 7 DAF, 12 DAF and 17 DAF libraries, respectively (Table 1). Of the millions of high-quality sRNAs obtained, 92.71% (5 DAF), 89.25% (7 DAF), 91.37% (12 DAF) and 91.27% (17 DAF) were 20–24 nt in length with 24 and 21 nt representing the major size classes, consistent with the size of products trimmed by Dicer-like(DCL) [27] ('''Figure. 1A'''). Using SOAP software, 91.38%, 91.91%, 91.13% and 90.33% of the total sRNA sequences, corresponding to representing 77.98%, 83.46%, 85.91% and 85.97% of the unique sRNAs from 5 DAF, 7 DAF, 12 DAF and 17 DAF libraries, were mapped onto the rice genome (MSU6.1), respectively ('''Table 1''''). Almost every category of RNA, including miRNA, siRNA, rRNA, snoRNA, snRNA, tRNA, repeat-associated sRNA, and degraded fragments of mRNA introns or exons, was detected in this study. Known rice miRNAs accounted for 3.82%, 8.82%, 15.45% and 11.36% of the sequence reads in the 5 DAF, 7 DAF, 12 DAF and 17 DAF libraries, respectively, indicating that mature miRNAs were relatively enriched in the 12 DAF library. Overall, regarding the common and specific reads of sRNAs between two adjacent libraries, greater than 60% of the total sRNAs were common to two different libraries, which represented only a relatively small fraction (14%–15%) of the unique sequence reads, suggesting that there was a less abundant but much more diverse pool of small RNAs that could be assumed to represent stage-specific small RNAs ('''Figure. 1B, C, D, E, F, G'''). These data highlight the differences and complexities in the miRNA reservoir between the different developmental stages.
* One of the most important advantages of high-throughput sequencing technology is that it can produce a large volume of data up to the gigabase level during small RNA sequencing, which is helpful for detecting novel miRNAs with extremely low expression levels. In this study, a total of 60 predicted novel miRNAs were obtained, fifty-six of which have not been deposited in miRBase (v18.0) and have never been detected in Oryza sativa or Arabidopsis thaliana, while 4 of these miRNAs were reported during preparation of this draft. The structures of the precursors of all of the novel miRNAs were predicted using MFOLD (http://mfold.rna.albany.edu/) and checked manually. Four of these structures are presented ('''Figure. 2A'''). The novel miRNAs were temporarily named following the Osa number format, e.g., Osa-1, before being submitted to obtain an official designation.Of the 60 predicted novel miRNAs, 11 miRNAs were expressed in all four libraries, while 30 were detected in 5 DAF, 44 in the 7 DAF, 47 in the 12 DAF and 36 in the 17 DAF libraries. Comparing the number of known miRNAs expressed in four libraries, the 5 DAF library exhibited the lowest abundance of both novel miRNAs and known miRNAs (30 and 380, re-spectively), which implied that more miRNAs remain to be revealed in the 5 DAF stage. As previously reported, the most important rule of novel miRNA annotation is to detect miRNA* sequences corresponding to mature miRNAs; alternatively, in miRNA*-deficient cases, miRNAs should be detected from multiple, independent libraries. In the present study, each of the novel miRNAs could be sequenced in two or more libraries, while only 12 miRNA* sequences were detected. This finding could be due to the rapid degradation rate of miRNA*. Interestingly, Osa-44 showed similar abundance in terms of both miRNA and miRNA*(read number of 22 vs. 20 in 7 DAF library), suggesting that both the miRNA and miRNA* might be functional in regulating gene expression. To validate the predicted novel miRNAs, the expression of five novel miRNAs whose sequencing counts exceeded 100 in at least one library were selected to be further confirmed using stem-loop RT-PCR. As a result, all five selected novel miRNAs were found to be expressed in rice grains, suggesting that the computational filters used here were sufficiently strict for predicting novel miRNAs ('''Figure. 2B''').
[[File:IC4R004-miRNA-2013-23469249-2.PNG|700px|thumb|center|'''Figure 2.''' ''Predicted novel miRNAs identified in this study.'']]

== Labs working on this Project ==
* State Key Laboratory of Hybrid Rice, Department of Genetics, College of Life Sciences, Wuhan University, Wuhan, People’s Republic of China

==Corresponding Author==
* '''Yi Ding'''(yiding@whu.edu.cn)