Maternal products are exclusive factors to drive oogenesis and early embryonic development. As disrupting maternal gene functions is either time-consuming or technically challenging, early developmental programs regulated by maternal factors remain mostly elusive. We provide a transgenic approach to inactivate maternal genes in zebrafish primary oocytes. By introducing three tandem single guide RNA (sgRNA) expression cassettes and a green fluorescent protein (GFP) reporter into Tg(zpc:zcas9) embryos, we efficiently obtained maternal nanog and ctnnb2 mutants among GFP-positive F1 offspring. Notably, most of these maternal mutants displayed either sgRNA site–spanning genomic deletions or unintended large deletions extending distantly from the sgRNA targets, suggesting a prominent deletion-prone tendency of genome editing in the oocyte. Thus, our method allows maternal gene knockout in the absence of viable and fertile homozygous mutant adults. This approach is particularly time-saving and can be applied for functional screening of maternal factors and generating genomic deletions in zebrafish.

Single nucleotide polymorphisms (SNPs) make up the most common form of mutations in human cytochrome P450 enzymes family, and have the potential to bring with different drug responses or specific diseases in individual patients. Here, based on machine learning technology, we aim to explore an effective set of sequence-based features for improving prediction of SNPs by using support vector machine algorithms. The features are derived from the target residues and flanking protein sequences, such as amino acid types, sequences composition, physicochemical properties, position-specific scoring matrix, phylogenetic entropy and the number of possible codons of target residues. In order to deal with the imbalance data with a majority of non-SNPs and a minority of SNPs, a preprocessing strategy based on fuzzy set theory was applied to the datasets. Our final model achieves the performance of 93.8% in sensitivity, 88.8% in specificity, 91.3% in accuracy and 0.971 of AUC value, which is significantly higher than the previous DNA sequence-based or protein sequence-based methods. Furthermore, our study also suggested the roles of individual features for prediction of SNPs. The most important features consist of the amino acid type, the number of available codons, position-specific scoring matrix and phylogenetic entropy. The improved model will be a promising tool for SNP predictions, and assist in the research of genome mutation and personalized prescriptions.

Maternal products are those mRNAs and proteins deposited during oogenesis, which play critical roles in controlling oocyte formation, fertilization, and early embryonic development. However, loss-of-function studies for these maternal factors are still lacking, mainly because of the prolonged period of transgenerational screening and technical barriers that prevent the generation of maternal (M) and maternal and zygotic (MZ) mutant embryos. By the transgenic expression of multiple sgRNAs targeting a single gene of interest in the background of a transgenic line Tg(zpc:zcas9) with oocyte-specific cas9 expression, we have successfully obtained maternal or maternal–zygotic mutant for single genes in F1 embryos. In this work, we tandemly connected a maternal GFP marker and eight sgRNA expression units to target dvl2 and dvl3a simultaneously and introduced this construct to the genome of Tg(zpc:zcas9) by meganuclease I-Sce I. As expected, we confirmed the existence of Mdvl2;Mdvl3a embryos with strong defective convergence and extension movement during gastrulation among outcrossed GFP positive F1 offspring. The MZdvl2;MZdvl3a embryos were also obtained by crossing the mutant carrying mosaic F0 female with dvl2+/−;dvl3a−/− male fish. This proof-of-principle thus highlights the potential of this conditional knockout strategy to circumvent the current difficulty in the study of genes with multiple functionally redundant paralogs.

Progressive accumulation of misfolded SNCA/α-synuclein is key to the pathology of Parkinson’s disease (PD). Drugs aiming at degrading SNCA may be an efficient therapeutic strategy for PD. Our previous study showed that mesencephalic astrocyte-derived neurotrophic factor (MANF) facilitated the removal of misfolded SNCA and rescued dopaminergic (DA) neurons, but the underlying mechanisms remain unknown. In this study, we showed that AAV8-MANF relieved Parkinsonian behavior in rotenone-induced PD model and reduced SNCA accumulation in the substantia nigra. By establishing wildtype (WT) SNCA overexpression cellular model, we found that chaperone-mediated-autophagy (CMA) and macroautophagy were both participated in MANF-mediated degradation of SNCAWT. Nuclear factor erythroid 2-related factor (Nrf2) was activated to stimulating macroautophagy activity when CMA pathway was impaired. Using A53T mutant SNCA overexpression cellular model to mimic CMA dysfunction situation, we concluded that macroautophagy rather than CMA was responsible to the degradation of SNCAA53T, and this degradation was mediated by Nrf2 activation. Hence, our findings suggested that MANF has potential therapeutic value for PD. Nrf2 and its role in MANF-mediated degradation may provide new sights that target degradation pathways to counteract SNCA pathology in PD.

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Objective To quantify bradykinesia in Parkinson's disease (PD) with a Kinect depth camera-based motion analysis system and to compare PD and healthy control (HC) subjects. Methods Fifty PD patients and twenty-five HCs were recruited. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was used to evaluate the motor symptoms of PD. Kinematic features of five bradykinesia-related motor tasks were collected using Kinect depth camera. Then, kinematic features were correlated with the clinical scales and compared between groups. Results Significant correlations were found between kinematic features and clinical scales ( P < 0.05). Compared with HCs, PD patients exhibited a significant decrease in the frequency of finger tapping ( P < 0.001), hand movement ( P < 0.001), hand pronation-supination movements ( P = 0.005), and leg agility ( P = 0.003). Meanwhile, PD patients had a significant decrease in the speed of hand movements ( P = 0.003) and toe tapping ( P < 0.001) compared with HCs. Several kinematic features exhibited potential diagnostic value in distinguishing PD from HCs with area under the curve (AUC) ranging from 0.684–0.894 ( P < 0.05). Furthermore, the combination of motor tasks exhibited the best diagnostic value with the highest AUC of 0.955 (95% CI = 0.913–0.997, P < 0.001). Conclusion The Kinect-based motion analysis system can be applied to evaluate bradykinesia in PD. Kinematic features can be used to differentiate PD patients from HCs and combining kinematic features from different motor tasks can significantly improve the diagnostic value.