Genome-wide epigenetic dynamics during postnatal skeletal muscle growth in Hu sheep.

Hypertrophy and fiber transformation are two prominent features of postnatal skeletal muscle development. However, the role of epigenetic modifications is less understood. ATAC-seq, whole genome bisulfite sequencing, and RNA-seq were applied to investigate the epigenetic dynamics of muscle in Hu sheep at 3 days, 3 months, 6 months, and 12 months after birth. All 6865 differentially expressed genes were assigned into three distinct tendencies, highlighting the balanced protein synthesis, accumulated immune activities, and restrained cell division in postnatal development. We identified 3742 differentially accessible regions and 11799 differentially methylated regions that were associated with muscle-development-related pathways in certain stages, like D3-M6. Transcription factor network analysis, based on genomic loci with high chromatin accessibility and low methylation, showed that ARID5B, MYOG, and ENO1 were associated with muscle hypertrophy, while NR1D1, FADS1, ZFP36L2, and SLC25A1 were associated with muscle fiber transformation. Taken together, these results suggest that DNA methylation and chromatin accessibility contributed toward regulating the growth and fiber transformation of postnatal skeletal muscle in Hu sheep.

Dynamic Changes in the Global Transcriptome of Postnatal Skeletal Muscle in Different Sheep.

Sheep growth performance, mainly skeletal muscle growth, provides direct economic benefits to the animal husbandry industry. However, the underlying genetic mechanisms of different breeds remain unclear. We found that the cross-sectional area (CSA) of skeletal muscle in Dorper (D) and binary cross-breeding (HD) was higher than that in Hu sheep (H) from 3 months to 12 months after birth. The transcriptomic analysis of 42 quadriceps femoris samples showed that a total of 5053 differential expression genes (DEGs) were identified. The differences in the global gene expression patterns, the dynamic transcriptome of skeletal muscle development, and the transcriptome of the transformation of fast and slow muscles were explored using weighted correlation network analysis (WGCNA) and allele-specific expression analysis. Moreover, the gene expression patterns of HD were more similar to D rather than H from 3 months to 12 months, which might be the reason for the difference in muscle growth in the three breeds. Additionally, several genes (GNB2L1, RPL15, DVL1, FBXO31, etc.) were identified as candidates related to skeletal muscle growth. These results should serve as an important resource revealing the molecular basis of muscle growth and development in sheep.

An FPGA-Based Ultra-High-Speed Object Detection Algorithm with Multi-Frame Information Fusion.

An ultra-high-speed algorithm based on Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) for hardware implementation at 10,000 frames per second (FPS) under complex backgrounds is proposed for object detection. The algorithm is implemented on the field-programmable gate array (FPGA) in the high-speed-vision platform, in which 64 pixels are input per clock cycle. The high pixel parallelism of the vision platform limits its performance, as it is difficult to reduce the strides between detection windows below 16 pixels, thus introduce non-negligible deviation of object detection. In addition, limited by the transmission bandwidth, only one frame in every four frames can be transmitted to PC for post-processing, that is, 75% image information is wasted. To overcome the mentioned problem, a multi-frame information fusion model is proposed in this paper. Image data and synchronization signals are first regenerated according to image frame numbers. The maximum HOG feature value and corresponding coordinates of each frame are stored in the bottom of the image with that of adjacent frames'. The compensated ones will be obtained through information fusion with the confidence of continuous frames. Several experiments are conducted to demonstrate the performance of the proposed algorithm. As the evaluation result shows, the deviation is reduced with our proposed method compared with the existing one.