A proportion of previously defined benign variants or variants of uncertain significance in humans, which are challenging to identify, may induce an abnormal splicing process. An increasing number of methods have been developed to predict splicing variants, but their performance has not been completely evaluated using independent benchmarks. Here, we manually sourced ∼50 000 positive/negative splicing variants from > 8000 studies and selected the independent splicing variants to evaluate the performance of prediction methods. These methods showed different performances in recognizing splicing variants in donor and acceptor regions, reminiscent of different weight coefficient applications to predict novel splicing variants. Of these methods, 66.67% exhibited higher specificities than sensitivities, suggesting that more moderate cut-off values are necessary to distinguish splicing variants. Moreover, the high correlation and consistent prediction ratio validated the feasibility of integration of the splicing prediction method in identifying splicing variants. We developed a splicing analytics platform called SPCards, which curates splicing variants from publications and predicts splicing scores of variants in genomes. SPCards also offers variant-level and gene-level annotation information, including allele frequency, non-synonymous prediction and comprehensive functional information. SPCards is suitable for high-throughput genetic identification of splicing variants, particularly those located in non-canonical splicing regions.

BackgroundThe expression pattern represents a quantitative phenotype that provides an in-depth view of the molecular mechanism in Parkinson’s disease (PD); however, the expression patterns of PD-associated genes (PAGs) and their relation to age at onset (AAO) remain unclear.MethodsThe known PD-causing genes and PD-risk genes, which were collected from latest published authoritative meta-analysis, were integrated as PAGs. The expression data from Genotype-Tissue Expression database, Allen Brian Map database, and BrainSpan database, were extracted to characterize the tissue specificity, inhibitory-excitatory neuron expression profile, and spatio-temporal expression pattern of PAGs, respectively. The AAO information of PD-causing gene was download from Gene4PD and MDSgene database.ResultsWe prioritized 107 PAGs and found that the PAGs were more likely to be expressed in brain-related tissues than non-brain tissues and that more PAGs had higher expression levels in excitatory neurons than inhibitory neurons. In addition, we identified two spatio-temporal expression modules of PAGs in human brain: the first module showed a higher expression level in the adult period than in the prenatal period, and the second module showed the opposite features. It showed that more PAGs belong to the first module that the second module. Furthermore, we found that the median AAO of patients with mutations in PD-causing genes of the first module was lower than that of the second module.ConclusionIn conclusion, this study provided comprehensive landscape of expression patterns, AAO features and their relationship for the first time, improving the understanding of pathogenesis, and precision medicine in PD.

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Increasing evidences suggest that mitochondrial dysfunction is implicated in diseases and aging, and whole-genome sequencing (WGS) is the most unbiased method in analyzing the mitochondrial genome (mtDNA). However, the genetic landscape of mtDNA in the Chinese population has not been fully examined. Here, we described the genetic landscape of mtDNA using WGS data from Chinese individuals (n = 3241). We identified 3892 mtDNA variants, of which 3349 (86%) were rare variants. Interestingly, we observed a trend toward extreme heterogeneity of mtDNA variants. Our study observed a distinct purifying selection on mtDNA, which inhibits the accumulation of harmful heteroplasmies at the individual level: (1) mitochondrial dN/dS ratios were much less than 1; (2) the dN/dS ratio of heteroplasmies was higher than homoplasmies; (3) heteroplasmies had more indels and predicted deleterious variants than homoplasmies. Furthermore, we found that haplogroup M (20.27%) and D (20.15%) had the highest frequencies in the Chinese population, followed by B (18.51%) and F (16.45%). The number of variants per individual differed across haplogroup groups, with a higher number of homoplasmies for the M lineage. Meanwhile, mtDNA copy number was negatively correlated with age but positively correlated with the female sex. Finally, we developed an mtDNA variation database of Chinese populations called MTCards (http://genemed.tech/mtcards/) to facilitate the query of mtDNA variants in this study. In summary, these findings contribute to different aspects of understanding mtDNA, providing a better understanding of the genetic basis of mitochondrial-related diseases.