Homologous haplotypes, expression, genetic effects and geographic distribution of the wheat yield gene TaGW2

BACKGROUND: TaGW2-6A, cloned in earlier research, strongly influences wheat grain width and TKW. Here, we mainly analyzed haplotypes of TaGW2-6B and their effects on TKW and interaction with haplotypes at TaGW2-6A. RESULTS: About 2.9 kb of the promoter sequences of TaGW2-6B and TaGW2-6D were cloned in 34 bread wheat cultivars. Eleven SNPs were detected in the promoter region of TaGW2-6B, forming 4 haplotypes, but no divergence was detected in the TaGW2-6D promoter or coding region. Three molecular markers including CAPS, dCAPS and ACAS, were developed to distinguish the TaGW2-6B haplotypes. Haplotype association analysis indicated that TaGW2-6B has a stronger influence than TaGW2-6A on TKW, and Hap-6B-1 was a favored haplotype increasing grain width and weight that had undergone strong positive selection in global wheat breeding. However, clear geographic distribution differences for TaGW2-6A haplotypes were found; Hap-6A-A was favored in Chinese, Australian and Russian cultivars, whereas Hap-6A-G was preferred in European, American and CIMMYT cultivars. This difference might be caused by a flowering and maturity time difference between the two haplotypes. Hap-6A-A is the earlier type. Haplotype interaction analysis between TaGW2-6A and TaGW2-6B showed additive effects between the favored haplotypes. Hap-6A-A/Hap-6B-1 was the best combination to increase TKW. Relative expression analysis of the three TaGW2 homoeologous genes in 22 cultivars revealed that TaGW2-6A underwent the highest expression. TaGW2-6D was the least expressed during grain development and TaGW2-6B was intermediate. Diversity of the three genes was negatively correlated with their effect on TKW. CONCLUSIONS: Genetic effects, expression patterns and historic changes of haplotypes at three homoeologous genes of TaGW2 influencing yield were dissected in wheat cultivars. Strong and constant selection to favored haplotypes has been found in global wheat breeding during the past century. This research also provides a valuable case for understanding interaction of genes that control complex traits in polyploid species

Identification of protein complexes from multi-relationship protein interaction networks

BACKGROUND: Protein complexes play an important role in biological processes. Recent developments in experiments have resulted in the publication of many high-quality, large-scale protein-protein interaction (PPI) datasets, which provide abundant data for computational approaches to the prediction of protein complexes. However, the precision of protein complex prediction still needs to be improved due to the incompletion and noise in PPI networks. RESULTS: There exist complex and diverse relationships among proteins after integrating multiple sources of biological information. Considering that the influences of different types of interactions are not the same weight for protein complex prediction, we construct a multi-relationship protein interaction network (MPIN) by integrating PPI network topology with gene ontology annotation information. Then, we design a novel algorithm named MINE (identifying protein complexes based on Multi-relationship protein Interaction NEtwork) to predict protein complexes with high cohesion and low coupling from MPIN. CONCLUSIONS: The experiments on yeast data show that MINE outperforms the current methods in terms of both accuracy and statistical significance

UCP2 Inhibits ROS-Mediated Apoptosis in A549 under Hypoxic Conditions

The Crosstalk between a tumor and its hypoxic microenvironment has become increasingly important. However, the exact role of UCP2 function in cancer cells under hypoxia remains unknown. In this study, UCP2 showed anti-apoptotic properties in A549 cells under hypoxic conditions. Over-expression of UCP2 in A549 cells inhibited reactive oxygen species (ROS) accumulation (P<0.001) and apoptosis (P<0.001) compared to the controls when the cells were exposed to hypoxia. Moreover, over-expression of UCP2 inhibited the release of cytochrome C and reduced the activation of caspase-9. Conversely, suppression of UCP2 resulted in the ROS generation (P = 0.006), the induction of apoptosis (P<0.001), and the release of cytochrome C from mitochondria to the cytosolic fraction, thus activating caspase-9. These data suggest that over-expression of UCP2 has anti-apoptotic properties by inhibiting ROS-mediated apoptosis in A549 cells under hypoxic conditions

A New Classification Method of Infrasound Events Using Hilbert-Huang Transform and Support Vector Machine

Infrasound is a type of low frequency signal that occurs in nature and results from man-made events, typically ranging in frequency from 0.01 Hz to 20 Hz. In this paper, a classification method based on Hilbert-Huang transform (HHT) and support vector machine (SVM) is proposed to discriminate between three different natural events. The frequency spectrum characteristics of infrasound signals produced by different events, such as volcanoes, are unique, which lays the foundation for infrasound signal classification. First, the HHT method was used to extract the feature vectors of several kinds of infrasound events from the Hilbert marginal spectrum. Then, the feature vectors were classified by the SVM method. Finally, the present of classification and identification accuracy are given. The simulation results show that the recognition rate is above 97.7%, and that approach is effective for classifying event types for small samples

A capsule network-based method for identifying transcription factors

Transcription factors (TFs) are typical regulators for gene expression and play versatile roles in cellular processes. Since it is time-consuming, costly, and labor-intensive to detect it by using physical methods, it is desired to develop a computational method to detect TFs. Here, we presented a capsule network-based method for identifying TFs. This method is an end-to-end deep learning method, consisting mainly of an embedding layer, bidirectional long short-term memory (LSTM) layer, capsule network layer, and three fully connected layers. The presented method obtained an accuracy of 0.8820, being superior to the state-of-the-art methods. These empirical experiments showed that the inclusion of the capsule network promoted great performances and that the capsule network-based representation was superior to the property-based representation for distinguishing between TFs and non-TFs. We also implemented the presented method into a user-friendly web server, which is freely available at http://www.biolscience.cn/Capsule_TF/ for all scientific researchers

Structural analysis of type 3 resistant starch from Canna edulis during in vitro simulated digestion and its post-digested residue impact on human gut microbiota

IntroductionResistant starch (RS) has garnered attention for its health benefits, including modulating the gut microbiota and promoting the production of short-chain fatty acids (SCFAs).MethodsThis study investigates structural changes of type 3 resistant starch from Canna edulis (CE) during in vitro simulated digestion and explores its health-relevant properties using healthy individuals’ fecal microbiota.ResultsCE, prepared with a RS content of 59.38%, underwent a comprehensive analysis employing X-ray diffraction (XRD), fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). During simulated digestion, XRD analysis demonstrated a significant rise in CE’s relative crystallinity from 38.92 to 49.34%. SEM illustrated the transition of CE from a smooth to a rough surface, a notable morphological shift. Post-digestion, CE was introduced into microbial fermentation. Notably, propionic acid and valeric acid levels significantly increased compared to the control group. Furthere more, beneficial Bifidobacterium proliferated while pathogenic Escherichia-Shigella was suppressed. When comparing CE to the well-known functional food fructo-oligosaccharide (FOS), CE showed a specific ability to support the growth of Bifidobacterium and stimulate the production of short-chain fatty acids (SCFAs) without causing lactic acid accumulation.DiscussionCE demonstrates potential as a functional health food, with implications for gut health enhancement and SCFAs production