农学最新文献

[This corrects the article DOI: 10.1093/hr/uhad050.].

[This corrects the article DOI: 10.1093/hr/uhac113.].

China's local chicken breeds are rich in resources, and have formed different germplasm characteristics in the process of long-term selection and evolution. Scientific assessment of population genetic diversity and identification of inter-breed genetic structure are of great value to the protection and innovative utilization of local chicken breed resource. In order to evaluate the application effectiveness of 23K SNP chip "Youxin-1" in the analysis of genetic diversity and genetic structure of local chickens, we used RADseq to identify genomic genetic variation of 21 local chicken breeds and developed 23K chip "Youxin-1". The genetic statistics of each variety were calculated based on two sets of SNP data, and correlation, fitting and phylogenetic analysis were carried out to evaluate the application effectiveness of the chip. The results showed that the observed heterozygosity (Ho), polymorphism information content (PIC), inbred coefficient (F_ROH) and genetic differentiation coefficient (Fst) calculated based on the two SNP data sets were basically consistent in the 21 local chicken breeds. The genetic diversity of Langya chicken (LA), Piao chicken (PJ) and Wenchang chicken (WC) was relatively rich. The genetic diversity of Bian chickens (BJ), Langshan chickens (LS), Gushi chickens (GS), Dongxiang blue-eggshell chickens (DX) and Beijing fatty chickens (BY) was relatively poor, and the correlation coefficients of Ho, PIC, F_ROH and average Fst in the two groups were 0.794, 0.901, 0.926 and 0.984, respectively, all reaching extremely significant levels (P<0.01) with a high degree of fit (P<0.001) and R² were 0.644, 0.827, 0.916 and 0.927. For the two sets of SNP data, the evolutionary tree constructed by neighbor-joining (NJ) method and maximum likelihood (ML) method was reasonable, and the 21 local chicken breeds were generally divided into six categories, which was consistent with the formation history and geographical distribution of the varieties. The 23K chip also realized reasonable clustering of the five new varieties without individual deviation. There are some differences in the estimation of genetic statistics using SNP with different densities, and data standardization is needed. 23K chip has good efficacy in the analysis of genetic diversity and structure of local chickens.

The localization of the meiotic specific regulatory molecule Moa1 to the centromere is regulated by the kinetochore protein CENP-C, and participates in the cohesion of sister chromatids in the centromere region mediated by the cohesin Rec8. To examine the interaction of these proteins, we analyzed the interactions between Moa1 and Rec8, CENP-C by yeast two-hybrid assays and identified several amino acid residues in Moa1 required for the interaction with CENP-C and Rec8. The results revealed that the interaction between Moa1 and CENP-C is crucial for the Moa1 to participate in the regulation of monopolar attachment of sister kinetochores. However, mutation at S143 and T150 of Moa1, which are required for interaction with Rec8 in the two-hybrid assay, did not show significant defects. Mutations in amino acid residues may not be sufficient to interfere with the interaction between Moa1 and Rec8 in vivo. Further research is needed to determine the interaction domain between Moa1 and Rec8. This study revealed specific amino acid sites at which Moa1 affects the meiotic homologous chromosome segregation, providing a deeper understanding of the mechanism of meiotic chromosome segregation.

Heterosis is the phenomenon that the hybrid offspring outperform two-parent population. Hybridisation has been widely used in plant and animal production as it effectively improves the growth and developmental performance, reproductive performance and disease resistance of the offspring. Hybridization can effectively improve the growth and development performance, reproductive performance and disease resistance of offspring, so it is widely used in animal and plant production. Researchers have used cross-breeding techniques to cultivate excellent new agricultural and animal husbandry strains and supporting lines such as super-excellent Chaoyou 1000 hybrid rice, Xiaoyan No.6 hybrid wheat, Dumeng sheep, and Shanxia black pigs. However, there are still some urgent problems in the current hybrid dominance research: the existing hybrid dominance theory can only partially explain the phenomenon of plant and animal hybrid dominance, and the theory of animal hybrid dominance is less researched, and the accuracy of the existing hybrid dominance prediction methods is limited. China is the world's largest pork production and consumption country. Heterosis can effectively improve the production performance of pigs, and its application in the pig industry has important economic and research value. However, the existing research on pig hybrid production is in its infancy and needs to be further studied. In this review, we summarize the existing heterosis theory, heterosis prediction methods, and their application in pig production, to provide a reference for the application of heterosis in pig breeding.

Uterine leiomyosarcoma (uLMS) is a type of malignant soft-tissue tumor, which is developed from myometrium in the female reproductive system. This disease is difficult to be distinguished from benign uterine leiomyoma in the early stages, but it progresses aggressively and relentlessly. Hence, uLMS has a dismal prognosis and high rates of both misdiagnosis and missed diagnosis. Unfortunately, current studies of uLMS pathogenesis and disease biology are inadequate. uLMS disease models are also very limited, hindering the development of effective therapeutics. In this review, we focus on the pathological molecular biology of uLMS, and systematically review the molecular genetic features, epigenetic variants, experimental models, and clinical research progress of uLMS. We further discuss the development direction and potential needs of uLMS in the fields of tumor evolution, tumor microenvironment, and tumor therapy, with the aim of providing a better understanding of the pathobiological mechanism of uLMS and providing a reference for the development of potential diagnostic and therapeutic strategies.

The identification of enzyme functions plays a crucial role in understanding the mechanisms of biological activities and advancing the development of life sciences. However, existing enzyme EC number prediction methods did not fully utilize protein sequence information and still had shortcomings in identification accuracy. To address this issue, we proposed an EC number prediction network using hierarchical features and global features (ECPN-HFGF). This method first utilized residual networks to extract generic features from protein sequences, and then employed hierarchical feature extraction modules and global feature extraction modules to further extract hierarchical and global features of protein sequences. Subsequently, the prediction results of both feature types were combined, and a multitask learning framework was utilized to achieve accurate prediction of enzyme EC numbers. Experimental results indicated that the ECPN-HFGF method performed best in the task of predicting EC numbers for protein sequences, achieving macro F1 and micro F1 scores of 95.5% and 99.0%, respectively. The ECPN-HFGF method effectively combined hierarchical and global features of protein sequences, allowing for rapid and accurate EC number prediction. Compared to current commonly used methods, this method offers significantly higher prediction accuracy, providing an efficient approach for the advancement of enzymology research and enzyme engineering applications.