東京大学 · Neuroscience
Hiroki R. Ueda 교수의 연구실은 생체 시계와 유전자 발현의 시스템적 동역학을 중심으로, 다량의 유전자 발현 데이터를 기반으로 생물의 내부 시계를 규명하고자 합니다. 특히, 다이아몬드파리, 효모, 식물, 쥐, 인간 등 다양한 생물에서 전장 게놈 수준의 발현 패tern을 분석하여 시계 기반 유전자 조절 메커니즘을 규명하고 있습니다. 또한, 단일 시간점에서의 유전자 발현 프로파일을 통해 개인의 생체 시계를 정밀하게 측정할 수 있는 '분자 시계 방법'을 개발하여 정밀의료와 약물 투여 최적화에 기여하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Circadian rhythms govern the behavior, physiology, and metabolism of living organisms. Recent studies have revealed the role of several genes in the clock mechanism both in Drosophila and in mammals. To study how gene expression is globally regulated by the clock mechanism, we used a high density oligonucleotide probe array (GeneChip) to profile gene expression patterns in Drosophila under light-dark and constant dark conditions. We found 712 genes showing a daily fluctuation in mRNA levels unde
Highly parallel experimental biology is offering opportunities to not just accomplish work more easily, but to explore for underlying governing principles. Recent analysis of the large-scale organization of gene expression has revealed its complex and dynamic nature. However, the underlying dynamics that generate complex gene expression and cellular organization are not yet understood. To comprehensively and quantitatively elucidate these underlying gene expression dynamics, we have analyzed gen
The identification of molecular networks at the system level in mammals is accelerated by next-generation mammalian genetics without crossing, which requires both the efficient production of whole-body biallelic knockout (KO) mice in a single generation and high-performance phenotype analyses. Here, we show that the triple targeting of a single gene using the CRISPR/Cas9 system achieves almost perfect KO efficiency (96%-100%). In addition, we developed a respiration-based fully automated non-inv
Detection of individual body time (BT) via a single-time-point assay has been a longstanding unfulfilled dream in medicine, because BT information can be exploited to maximize potency and minimize toxicity during drug administration and thus will enable highly optimized medication. To achieve this dream, we created a "molecular timetable" composed of >100 "time-indicating genes," whose gene expression levels can represent internal BT. Here we describe a robust method called the "molecular-timeta
