Generation of germ cells from pluripotent stem cells in vitro could have great application for treating infertility and provides an excellent model for uncovering molecular mechanisms controlling gametogenesis. In this study, we explored the differentiation potential of mouse induced pluripotent stem (iPS) cells towards male germ cells. Embryoid body formation and retinoic acid/testosterone induction were applied to promote differentiation of mouse iPS cells into male germ cells in vitro. Quantitative RT-PCR and immunoflourescence were performed to characterize the iPS cell differentiation process, and notably there were different temporal expression profiles of male germ cell-associated genes. The expression of proteins, including MVH, CDH1, and SCP3, was remarkably increased. mRNA expression of Stra8, Odf2, Act, and Prm1 was upregulated in iPS cells by retinoic acid or testosterone induction, whereas Oct-4 transcription was reduced in these cells compared to the controls. Hormones were also measured in the EB medium. DNA content analysis by flow cytometry revealed that iPS cells could differentiate into haploid cells through retinoic acid or testosterone treatment. Collectively, our results suggest that mouse iPS cells possess the potency to differentiate into male germ cells in vitro through embryoid body formation and retinoic acid or testosterone induction.

Background

The Barley stripe mosaic virus (BSMV)-based vector has been developed and used for gene silencing in barley and wheat seedlings to assess gene functions in pathogen- or insect-resistance, but conditions for gene silencing in spikes and grains have not been evaluated. In this study, we explored the feasibility of using BSMV for gene silencing in wheat spikes or grains.

Results

Apparent photobleaching on the spikes infected with BSMV:PDS at heading stage was observed after13 days post inoculation (dpi), and persisted until 30dpi, while the spikes inoculated with BSMV:00 remained green during the same period. Grains of BSMV:PDS infected spikes also exhibited photobleaching. Molecular analysis indicated that photobleached spikes or grains resulted from the reduction of endogenous PDS transcript abundances, suggesting that BSMV:PDS was able to induce PDS silencing in wheat spikes and grains. Inoculation onto wheat spikes from heading to flowering stage was optimal for efficient silencing of PDS in wheat spikes. Furthermore, we used the BSMV-based system to reduce the transcript level of 1Bx14, a gene encoding for High-molecular-weight glutenin subunit 1Bx14 (HMW-GS 1Bx14), by 97 % in the grains of the BSMV:1Bx14 infected spikes at 15dpi, compared with that in BSMV:00 infected spikes, and the reduction persisted until at least 25 dpi. The amount of the HMW-GS 1Bx14 was also detectably decreased. The percentage of glutenin macropolymeric proteins in total proteins was significantly reduced in the grains of 1Bx14-silenced plants as compared with that in the grains of BSMV:00 infected control plants, indicating that HMW-GS 1Bx14 is one of major components participating in the formation of glutenin macropolymers in wheat grains.

Conclusion

This is one of the first reports of successful application of BSMV-based virus-induced-gene-silencing (VIGS) for gene knockdown in wheat spikes and grains and its application in functional analysis of the 1Bx14 gene. The established BSMV-VIGS system will be very useful in future research on functional analysis of genes contributing to grain quality and the metabolic networks in developing seeds of wheat.

Background

Prediction of ribonucleic acid (RNA) secondary structure remains one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. Thus far, few studies have been reported on the acceleration of the Zuker algorithm on general-purpose processors or on extra accelerators such as Field Programmable Gate-Array (FPGA) and Graphics Processing Units (GPU). To the best of our knowledge, no implementation combines both CPU and extra accelerators, such as GPUs, to accelerate the Zuker algorithm applications.

Results

In this paper, a CPU-GPU hybrid computing system that accelerates Zuker algorithm applications for RNA secondary structure prediction is proposed. The computing tasks are allocated between CPU and GPU for parallel cooperate execution. Performance differences between the CPU and the GPU in the task-allocation scheme are considered to obtain workload balance. To improve the hybrid system performance, the Zuker algorithm is optimally implemented with special methods for CPU and GPU architecture.

Conclusions

Speedup of 15.93× over optimized multi-core SIMD CPU implementation and performance advantage of 16% over optimized GPU implementation are shown in the experimental results. More than 14% of the sequences are executed on CPU in the hybrid system. The system combining CPU and GPU to accelerate the Zuker algorithm is proven to be promising and can be applied to other bioinformatics applications.