BioProject

Maize is a globally important food and feed crop, and a low-phosphate (Pi) supply in the soil frequently limits maize yield in many areas. More...

Maize is a globally important food and feed crop, and a low-phosphate (Pi) supply in the soil frequently limits maize yield in many areas. MicroRNAs (miRNAs) play important roles in the development and adaptation of plants to the environment. In this study, the spatio-temporal miRNA transcript profiling of the maize inbred line Q319 root and leaf in response to low Pi was analyzed with high-throughput sequencing technologies, and the expression patterns of certain target genes were detected by real-time RT-PCR. Complex small RNA populations were detected after low-Pi culture and displayed different patterns in the root and leaf. miRNAs identified as responding to Pi deficiency can be grouped into ‘early’ miRNAs that respond rapidly, and often non-specifically, to Pi deficiency, and ‘late’ miRNAs that alter the morphology, physiology or metabolism of plants upon prolonged Pi deficiency. The miR827-Nitrogen limitation adaptation (NLA)-mediated post-transcriptional pathway was conserved in response to Pi availability of maize, but the miR399-mediated post-transcriptional pathway was different from Arabidopsis. Abiotic stress-related miRNAs engaged in interactions of different signaling and/or metabolic pathways. Auxin-related miRNAs (zma-miR393, zma-miR160a/b/c, zma-miR160d/e/g, zma-miR167a/b/c/d and zma-miR164a/b/c/d/g) and their targets play important roles in promoting primary root growth, inhibiting lateral root development and retarding upland growth of maize when subjected to low Pi. The changes in expression of miRNAs and their target genes suggest that the miRNA regulation/alterations compose an important mechanism in the adaptation of maize to a low-Pi environment; certain miRNAs participate in root architecture modification via the regulation of auxin signaling. A complex regulatory mechanism of miRNAs in response to a low-Pi environment exists in maize, revealing obvious differences from that in Arabidopsis. Overall design: Maize (Zea mays L.) inbred line Q319 was used in this study. Seeds of the maize inbred line Q319 were surface sterilized and held at 28°C in darkness. Seedlings (4 days old) were transferred to a sufficient phosphate (SP, 1,000 μM KH2PO4) solution (Ca(NO3)2.4H2O 2 mM, NH4NO3 1.25 mM, KCl 0.1 mM, K2SO4 0.65 mM, MgSO4 0.65 mM, H3BO3 10.0 mM, (NH4)6Mo7O24 0.5 mM, MnSO4 1.0 mM, CuSO4.5H2O 0.1 mM, ZnSO4.7H2O 1.0 mM, Fe-EDTA 0.1 mM), allowed to grow for 4 days (plants with 2–3 leaves). After 2-3 days of re-culturing in SP nutrient solutions, half of the seedlings were transplanted into a low phosphate (LP, same composition as the SP solution, except that 5 μM KH2PO4 and 1 mM KH2PO4 were replaced with 1 mM KCl) nutrient solution. The plants were grown under a 32°C/25°C (day/night) temperature regime at a photon flux density (PFD) of 700 μmol m-2 s-1 with a 14 h/10 h light/dark cycle in a greenhouse with approximately 65% relative humidity. The roots and leaves were then harvested at 0, 1, 2, 4, 8 days and 8 days and cultured in SP solution (as a normal growth control) for small RNA analysis. The samples were frozen in liquid nitrogen immediately and stored at -80℃ for further analysis. Each biological repeat contains segments from 15~20 plants. Total RNA was extracted as previously described in Molecular Cloning (Sambrook and Russell David, 1989) and was then subjected to two additional chloroform washes prior to nucleic acid precipitation. The small RNA digitalization analysis based on HiSeq high-throughput sequencing takes the SBS-sequencing by synthesis. Then the 50nt sequence tags from HiSeq sequencing will go through the data cleaning first, which includes getting rid of the low quality tags and several kinds of contaminants from the 50nt tags. Length distribution of clean tags are then summarized. Afterwards, the standard bioinformatics analysis will annotate the clean tags into different categories and take those which can not be annotated to any category to predict the novel miRNA and base edit of potential known miRNA. Compare the known miRNA expression between two samples to find out the differentially expressed miRNA. The procedures are shown as below: (1)Normalize the expression of miRNA in two samples (control and treatment) to get the expression of transcript per million (TPM). Normalization formula: Normalized expression = Actual miRNA count/Total count of clean reads*1000000 (2)Calculate fold-change and P-value from the normalized expression. Then generate the log2ratio plot and scatter plot. Less...