Cytological observation and RNA-seq analysis reveal novel miRNAs high expression associated with the pollen fertility of neo-tetraploid rice.

BACKGROUND: Neo-tetraploid rice lines exhibit high fertility and strong heterosis and harbor novel specific alleles, which are useful germplasm for polyploid rice breeding. However, the mechanism of the fertility associated with miRNAs remains unknown. In this study, a neo-tetraploid rice line, termed Huaduo21 (H21), was used. Cytological observation and RNA-sequencing were employed to identify the fertility-related miRNAs in neo-tetraploid rice. RESULTS: H21 showed high pollen fertility (88.08%), a lower percentage of the pollen mother cell (PMC) abnormalities, and lower abnormalities during double fertilization and embryogenesis compared with autotetraploid rice. A total of 166 non-additive miRNAs and 3108 non-additive genes were detected between H21 and its parents. GO and KEGG analysis of non-additive genes revealed significant enrichments in the DNA replication, Chromosome and associated proteins, and Replication and repair pathways. Comprehensive multi-omics analysis identified 32 pairs of miRNA/target that were associated with the fertility in H21. Of these, osa-miR408-3p and osa-miR528-5p displayed high expression patterns, targeted the phytocyanin genes, and were associated with high pollen fertility. Suppression of osa-miR528-5p in Huaduo1 resulted in a low seed set and a decrease in the number of grains. Moreover, transgenic analysis implied that osa-MIR397b-p3, osa-miR5492, and osa-MIR5495-p5 might participate in the fertility of H21. CONCLUSION: Taken together, the regulation network of fertility-related miRNAs-targets pairs might contribute to the high seed setting in neo-tetraploid rice. These findings enhance our understanding of the regulatory mechanisms of pollen fertility associated with miRNAs in neo-tetraploid rice.

Comparative Cytological and Transcriptome Analysis Revealed the Normal Pollen Development Process and Up-Regulation of Fertility-Related Genes in Newly Developed Tetraploid Rice.

Autotetraploid rice is a useful germplasm for polyploid rice breeding; however, low seed setting is a major hindrance for its utilization. Here, we reported the development of a new tetraploid rice, Huoduo1 (H1), which has the characteristic of high fertility, from crossing generations of autotetraploid rice. Cytological observations displayed the high fertility of the pollen (95.62%) in H1, a lower percentage of pollen mother cell (PMC) abnormalities, and stable chromosome configurations during the pollen development process compared with its parents. Using RNA-seq analysis, we detected 440 differentially expressed genes (DEGs) in H1 compared with its parents. Of these DEGs, 193 were annotated as pollen fertility-related genes, and 129 (~66.8%) exhibited significant up-regulation in H1 compared with the parents, including three environmentally sensitive genic male sterility genes (TMS9-1, TMS5, and CSA), one meiosis gene (RAD51D), and three tapetal-related genes (MIL2, OsAP25, and OsAP37), which were validated by qRT-PCR in this study. Two genes, TMS9-1 and TMS5, were knocked out using CRISPR/Cas9 technology, and their mutants displayed low fertility and the abnormal development of pollen. Our findings provide evidence for the regulatory mechanisms of fertility in tetraploid rice and indicated that the up-regulation of pollen fertility-related genes may contribute to the high fertility in new tetraploid rice.

Research on evaluation index method of cloud-network convergence capability.

There is no measurable and evaluable index system for cloud-network convergence that provides guidance and reference for the subsequent construction and development of cloud-network convergence. It is a big project to select and evaluate the indexes of cloud-network convergence, which requires suitable index selection and index evaluation schemes. Based on analytic hierarchy process (AHP) and entropy weight method, this paper proposes an improved AHP (i-AHP) index selection scheme and index evaluation scheme leveraging the years of experts' experience, the geometric mean and the least square method. The improved weighted least square method (WLSM) is finally proved to be more stable for index evaluation scheme by adding abnormal data. In addition, the index weight obtained by the index evaluation scheme with WLSM are provided as a reference for the future development of cloud-network convergence. The simulation results show that the proposed scheme is superior to the existing index evaluation scheme and can avoid the weight deviation caused by the disturbance and fluctuation of abnormal data.