Long-read sequencing reveals the landscape of aberrant alternative splicing and novel therapeutic target in colorectal cancer.

BACKGROUND: Alternative splicing complexity plays a vital role in carcinogenesis and cancer progression. Improved understanding of novel splicing events and the underlying regulatory mechanisms may contribute new insights into developing new therapeutic strategies for colorectal cancer (CRC). METHODS: Here, we combined long-read sequencing technology with short-read RNA-seq methods to investigate the transcriptome complexity in CRC. By using experiment assays, we explored the function of newly identified splicing isoform TIMP1 Δ4-5. Moreover, a CRISPR/dCasRx-based strategy to induce the TIMP1 exon 4-5 exclusion was introduced to inhibit neoplasm growth. RESULTS: A total of 90,703 transcripts were identified, of which > 62% were novel compared with current transcriptome annotations. These novel transcripts were more likely to be sample specific, expressed at relatively lower levels with more exons, and oncogenes displayed a characteristic to generate more transcripts in CRC. Clinical outcome data analysis showed that 1472 differentially expressed alternative splicing events (DEAS) were tightly associated with CRC patients' prognosis, and many novel isoforms were likely to be important determinants for patient survival. Among these, newly identified splicing isoform TIMP1 Δ4-5 was significantly downregulated in CRC. Further in vitro and in vivo assays demonstrated that ectopic expression of TIMP1 Δ4-5 significantly suppresses tumor cell growth and metastasis. Serine/arginine-rich splicing factor 1 (SRSF1) acts as a onco-splicing regulator through sustaining the inclusion of TIMP1 exon 4-5. Furthermore, CRISPR/dCasRx-based strategies designed to induce TIMP1 exon 4-5 exclusion have the potential to restrain the CRC growth. CONCLUSIONS: This data provides a rich resource for deeper studies of gastrointestinal malignancies. Newly identified splicing isoform TIMP1 Δ4-5 plays an important role in mediating CRC progression and may be a potential therapy target in CRC.

Classification of Fluorescently Labelled Maize Kernels Using Convolutional Neural Networks.

Accurate real-time classification of fluorescently labelled maize kernels is important for the industrial application of its advanced breeding techniques. Therefore, it is necessary to develop a real-time classification device and recognition algorithm for fluorescently labelled maize kernels. In this study, a machine vision (MV) system capable of identifying fluorescent maize kernels in real time was designed using a fluorescent protein excitation light source and a filter to achieve optimal detection. A high-precision method for identifying fluorescent maize kernels based on a YOLOv5s convolutional neural network (CNN) was developed. The kernel sorting effects of the improved YOLOv5s model, as well as other YOLO models, were analysed and compared. The results show that using a yellow LED light as an excitation light source combined with an industrial camera filter with a central wavelength of 645 nm achieves the best recognition effect for fluorescent maize kernels. Using the improved YOLOv5s algorithm can increase the recognition accuracy of fluorescent maize kernels to 96%. This study provides a feasible technical solution for the high-precision, real-time classification of fluorescent maize kernels and has universal technical value for the efficient identification and classification of various fluorescently labelled plant seeds.

Adiponectin modulates steroid hormone secretion, granulosa cell proliferation and apoptosis via binding its receptors during hens' high laying period.

Adiponectin is an important adipocytokine and plays the roles in multiple metabolic processes via binding its receptors - AdipoR1 and AdipoR2, which has also been found to participate in the regulation of the reproductive system of animals, in particular by influencing the secretion of ovarian steroid hormones. To further investigate the expression of adiponectin and its receptors in follicles after in vitro incubation, and their role in the steroid synthesis of laying hens' ovaries, we performed qRT-PCR and ELISA to detect the expressions of AdipoQ, AdipoR1, and AidpoR2, and determined the key genes involved in steroidogenesis and the secretion of estradiol (E2) and progesterone (P4) through the in vitro activation of adiponectin (AipoRon) and overexpression or knockdown of AdipoR1 and AdipoR2. Our results revealed that adiponectin and its receptors wildly exist in follicles and granulosa cells, and AdipoRon (5 and 10 µg/mL) had no effect on granulosa cell proliferation and apoptosis but significantly stimulated the secretion of adiponectin and its receptors in granulosa cells after incubation for 24 h. Furthermore, AdipoRon could significantly stimulate the secretion of P4 and inhibit E2 level compared to those of the control group through modulating the key genes expression of steroidogenesis (CYP19A1, StAR, CYP11A1, FSHR, and LHR). The secretion of E2 was also decreased in granulosa cells by the treatments of overexpression and knockdown of AdipoR1/2, however, there was no difference in terms of the level of P4 and StAR expression between them if there was overexpression or knockdown of AdipoR1/2. In addition, it was shown that the secretion of E2 only exhibits a marked drop if co-processing 10 µg/mL AdipoRon and pGMLV AdipoR2 compared to single treatments. Taken together, the study highlighted the role of adiponectin and its receptors in the regulation of steroid synthesis and secretion in ovarian granulosa cells in laying hens.

MicroRNAs and their regulatory networks in Chinese Gushi chicken abdominal adipose tissue during postnatal late development.

BACKGROUND: Abdominal fat is the major adipose tissue in chickens. The growth status of abdominal fat during postnatal late development ultimately affects meat yield and quality in chickens. MicroRNAs (miRNAs) are endogenous small noncoding RNAs that regulate gene expression at the post-transcriptional level. Studies have shown that miRNAs play an important role in the biological processes involved in adipose tissue development. However, few studies have investigated miRNA expression profiles and their interaction networks associated with the postnatal late development of abdominal adipose tissue in chickens. RESULTS: We constructed four small RNA libraries from abdominal adipose tissue obtained from Chinese domestic Gushi chickens at 6, 14, 22, and 30 weeks. A total of 507 known miRNAs and 53 novel miRNAs were identified based on the four small RNA libraries. Fifty-one significant differentially expressed (SDE) miRNAs were identified from six combinations by comparative analysis, and the expression patterns of these SDE miRNAs were divided into six subclusters by cluster analysis. Gene ontology enrichment analysis showed that the SDE miRNAs were primarily involved in the regulation of fat cell differentiation, regulation of lipid metabolism, regulation of fatty acid metabolism, and unsaturated fatty acid metabolism in the lipid metabolism- or deposition-related biological process categories. In addition, we constructed differentially expressed miRNA-mRNA interaction networks related to abdominal adipose development. The results showed that miRNA families, such as mir-30, mir-34, mir-199, mir-8, and mir-146, may have key roles in lipid metabolism, adipocyte proliferation and differentiation, and cell junctions during abdominal adipose tissue development in chickens. CONCLUSIONS: This study determined the dynamic miRNA transcriptome and characterized the miRNA-mRNA interaction networks in Gushi chicken abdominal adipose tissue for the first time. The results expanded the number of known miRNAs in abdominal adipose tissue and provide novel insights and a valuable resource to elucidate post-transcriptional regulation mechanisms during postnatal late development of abdominal adipose tissue in chicken.

[Fluid solid interaction analysis of bioprosthetic heart valve].

This paper constructs numerical models of bioprosthetic heart valve and blood. The fluid solid interaction is carried out using penalty function method. The mechanical property of the bioprosthetic heart valve during cardiac cycle is simulated with ANSYS software. Results show that the Von Mises stress concentrates at the junction of attachment edge and coaptation edge. The open time of bioprosthetic heart valve is consistent with that of actural measurement. The peak velocity of blood is in the range of physiology. This model provides more realistic mechanical property of bioprosthetic heart valve during cardiac cycle compared to pure solid model, and facilitates design and optimization of bioprosthetic heart valve.