瞬时受体电位香草酸亚家族1介导针刺治疗病理性疼痛的作用

Acupuncture,a traditional oriental intervention for chronic pain,has been gaining worldwide popularity.Transient receptor potential vanilloid subfamily 1(TRPV1)is a key factor mediating pain production and sensitization.According to multiple studies,TRPV1 is involved the acupuncture-induced relief of pathological pain.Herein,we systematically screened the experimental reports on TRPV1 involvement in acupuncture analgesia,and reviewed the role of TRPV1 in acupuncture in inhibiting different pathological pain and unresolved problems,including inflammatory pain,neuropathic pain,visceral pain,fibromyalgia and cancer pain.At localized acupoints,TRPV1 was involved in the initiation of acupuncture signals.Acupuncture could inhibit the development of pathological pain as well as the transmission of pain signals by suppressing TRPV1 expression and opening activity from the peripheral dorsal root ganglia to the central spinal cord.Furthermore,acupuncture can not only inhibit the expression of TRPV1,but also promote the expression of TRPV1 in the brain to alleviate pain sensation and depression-like behavior.Moreover,the mechanism by which acupuncture regulates TRPV1 may involve neuro-immune crosstalk.In conclusion,the regulation of TRPV1 expression and function may be one of the primary mechanisms by which acupuncture relieves pathological pain,laying the groundwork for future basic research on acupuncture's pain-relieving effects.

Computational Assessment of the Expression-modulating Potential for Non-coding Variants

Large-scale genome-wide association studies(GWAS)and expression quantitative trait locus(eQTL)studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression.However,pinpointing causal variants effectively and efficiently remains a serious challenge.Here,we developed CARMEN,a novel algorithm to identify functional non-coding expression-modulating variants.Multiple evaluations demonstrated CARMEN’s superior performance over state-of-the-art tools.Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms(SNPs).CARMEN scales well with the massive datasets,and is available online as a web server at http://carmen.gao-lab.org.

Systematic identification and annotation of multiple-variant compound effects at transcription factor binding sites in human genome

Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple tools have been developed to assess functional effects of genetic variants at TFBSs, they usually assume that each variant works in isolation and neglect the potential ＂interference＂ among multiple variants within the same TFBS. In this study, we presented COPE-TFBS （Context-Oriented Predictor for variant Effect on Transcription Factor Binding Site）, a novel method that considers sequence context to accurately predict variant effects on TFBSs. We systematically re-analyzed the sequencing data from both the 1000 Genomes Project and the Genotype-Tissue Expression （GTEx） Project via COPE-TFBS, and identified numbers of novel TFBSs, transformed TFBSs and discordantly annotated TFBSs resulting from multiple variants, further highlighting the necessity of sequence context in accurately annotating genetic variants.

REVA as A Well-curated Database for Human Expressionmodulating Variants

More than 90%of disease-and trait-associated human variants are noncoding.By systematically screening multiple large-scale studies,we compiled REVA,a manually curated database for over 11.8 million experimentally tested noncoding variants with expression-modulating potentials.We provided 2424 functional annotations that could be used to pinpoint the plausible regulatory mechanism of these variants.We further benchmarked multiple state-of-the-art computational tools and found that their limited sensitivity remains a serious challenge for effective large-scale analysis.REVA provides high-quality experimentally tested expression-modulating variants with extensive functional annotations,which will be useful for users in the noncoding variant community.REVA is freely available at http://reva.gao-lab.org.