Small RNAs are widespread in plants and animals. They largely include microRNAs (miRNAs) and short interfering RNAs (siRNAs), and they play key roles in gene and chromatin regulations. Here we describe in detail the method for an effective construction of the recently developed short tandem target mimic (STTM) technology to block small RNA functions in plants and animals. STTM is a powerful technology complementing the previous target mimic (TM) in plants and the miRNA sponge, as well as the recently defined endogenous competing RNA (CeRNA) in animals. We expect STTM will not only be effective in blocking small RNA functions in plants but will also become a popular approach in animals.

BackgroundThe inferior spikelets are defined to be those at portions where the grains receive less photosynthetic products during the seed development. The typical inferior spikelets are physically located on the proximal secondary branches in a rice panicle and traditionally characterized by a later flowering time and a slower grain-filling rate, compared to those so-called superior spikelets. Grains produced on the inferior spikelets are consequently under-developed and lighter in weight than those formed on the superior spikelets. MicroRNAs (miRNAs) are recognized as key players in regulating plant development through post-transcriptional gene regulations. We previously presented the evidence that miRNAs may influence grain-filling rate and played a role in determining the grain weight and yield in rice.ResultsIn this study, further analyses of the expressed small RNAs in superior and inferior spikelets were conducted at five distinct developmental stages of grain development. Totally, 457 known miRNAs and 13 novel miRNAs were analyzed, showing a differential expression of 141 known miRNAs between superior and inferior spikelets with higher expression levels of most miRNAs associated with the superior than the inferior spikelets during the early stage of grain filling. Genes targeted by those differentially expressed miRNAs (i.e. miR156, miR164, miR167, miR397, miR1861, and miR1867) were recognized to play roles in multiple developmental and signaling pathways related to plant hormone homeostasis and starch accumulation.ConclusionsOur data established a complicated link between miRNA dynamics and the traditional role of hormones in grain filling and development, providing new insights into the widely accepted concepts of the so-called superior and inferior spikelets in rice production.

microRNAs (miRNAs) are endogenous small non-coding RNAs that bind to mRNAs and target them for cleavage and/or translational repression, leading to gene silencing. We previously developed short tandem target mimic (STTM) technology to deactivate endogenous miRNAs in Arabidopsis. Here, we created hundreds of STTMs that target both conserved and species-specific miRNAs in Arabidopsis, tomato, rice, and maize, providing a resource for the functional interrogation of miRNAs. We not only revealed the functions of several miRNAs in plant development, but also demonstrated that tissue-specific inactivation of a few miRNAs in rice leads to an increase in grain size without adversely affecting overall plant growth and development. RNA-seq and small RNA-seq analyses of STTM156/157 and STTM165/166 transgenic plants revealed the roles of these miRNAs in plant hormone biosynthesis and activation, secondary metabolism, and ion-channel activity-associated electrophysiology, demonstrating that STTM technology is an effective approach for studying miRNA functions. To facilitate the study and application of STTM transgenic plants and to provide a useful platform for storing and sharing of information about miRNA-regulated gene networks, we have established an online Genome Browser (https://blossom.ffr.mtu.edu/designindex2.php) to display the transcriptomic and miRNAomic changes in STTM-induced miRNA knockdown plants.

Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04–6.06, 7.02–7.03, and 10.06–10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%).