在大麻Sativa L中全基因组视图和自然反意义转录的特征
Chang Zhang1, Mei Jiang1,2, Jingting Liu1
1Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 151, Malianwa North Road, Haidian District, 100193, Beijing, China.
Plant molecular biology
|April 17, 2024
概括
这项研究在Cannabis Sativa L.中确定了307个天然反感转录 (NAT),揭示了它们在基因调节中的作用以及它们通过nat-siRNAs对大麻素生物合成的潜在参与.
科学领域:
- 分子生物学分子生物学
- 植物科学 植物科学
- 基因组学就是基因组学.
背景情况:
- 自然反意义转录 (NAT) 是复杂的调节性RNA,对基因表达至关重要.
- 在经济重要植物Cannabis Sativa L.中,NATs在很大程度上仍然没有特征.
- 了解C. Sativa中的NAT对于其医学和经济应用至关重要.
研究的目的:
- 为了全面预测和描述整个C. Sativa基因组中的NAT.
- 调查C. Sativa NATs的功能作用和监管潜力.
- 为了识别来自NAT (nat-siRNAs) 的小干扰RNA (siRNAs) 和它们的潜在目标.
主要方法:
- 使用链特异性RNA测序 (ssRNA-Seq) 数据对NATs的全基因组预测.
- 通过链特异的定量逆转录PCR (ssRT-qPCR) 验证NAT表达特征.
- 功能性丰富分析和预测NAT衍生的siRNA及其目标相互作用.
主要成果:
- 在C. Sativa中共鉴定了307种NAT,包括104种cis-NAT和203种trans-NAT.
- 功能分析表明,NAT参与了DNA聚合酶,RNA-DNA杂交核糖核酶活性和核酸结合.
- 预测了621个cis-和5,679个trans-nat-siRNAs,可能调节大麻素和纤维素生物合成.
结论:
- 这项研究提供了C. Sativa中NAT的第一个全面的全基因组识别.
- 已识别的NAT及其衍生的nat-siRNA在植物内的基因调节中起着重要作用.
- 这些发现提供了关于大麻素生产和C. Sativa.中其他重要过程背后的分子机制的见解.
更多相关视频
09:31Laser-assisted Microdissection LAM as a Tool for Transcriptional Profiling of Individual Cell Types
Published on: May 10, 2016
9.3K
10:40Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
Published on: December 22, 2017
10.5K
相关概念视频
lncRNA - Long Non-coding RNAs
8.6K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
8.6K
Genome-wide Association Studies-GWAS
13.4K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
13.4K
