Google North America, San Francisco, USA.
Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India.
BMC Bioinformatics. 2021 May 10;22(1):237. doi: 10.1186/s12859-021-04151-2.
MicroRNAs (miRNAs) function in post-transcriptional regulation of gene expression by binding to target messenger RNAs (mRNAs). Because of the key part that miRNAs play, understanding the correct regulatory role of miRNAs in diverse patho-physiological conditions is of great interest. Although it is known that miRNAs act combinatorially to regulate genes, precise identification of miRNA-gene interactions and their specific functional roles in regulatory comodules remains a challenge. We developed THEIA, an effective method for simultaneously predicting miRNA-gene interactions and regulatory comodules, which group functionally related miRNAs and genes via non-negative matrix factorization (NMF).
We apply THEIA to RNA sequencing data from breast invasive carcinoma samples and demonstrate its effectiveness in discovering biologically significant regulatory comodules that are significantly enriched in spatial miRNA clusters, biological pathways, and various cancers.
THEIA is a theoretically rigorous optimization algorithm that simultaneously predicts the strength and direction (i.e., up-regulation or down-regulation) of the effect of modules of miRNAs on a gene. We posit that if THEIA is capable of recovering known clusters of genes and miRNA, then the clusters found by our method not previously identified by literature are also likely to have biological significance. We believe that these novel regulatory comodules found by our method will be a springboard for further research into the specific functional roles of these new functional ensembles of miRNAs and genes,especially those related to diseases like breast cancer.
MicroRNAs（miRNAs）通过与靶信使 RNA（mRNA）结合在基因表达的转录后调控中发挥作用。由于 miRNAs 起着关键作用，因此了解 miRNAs 在各种病理生理条件下的正确调节作用具有重要意义。尽管已知 miRNAs 以组合的方式起作用来调节基因，但精确识别 miRNA-基因相互作用及其在调节协同模块中的特定功能作用仍然是一个挑战。我们开发了 THEIA，这是一种同时预测 miRNA-基因相互作用和调节协同模块的有效方法，它通过非负矩阵分解（NMF）将功能相关的 miRNAs 和基因分组。
我们将 THEIA 应用于来自乳腺浸润性癌样本的 RNA 测序数据，并证明其在发现具有生物学意义的调节协同模块方面的有效性，这些模块在空间 miRNA 簇、生物途径和各种癌症中显著富集。
THEIA 是一种理论上严格的优化算法，它同时预测 miRNA 模块对基因的影响的强度和方向（即上调或下调）。我们假设如果 THEIA 能够恢复已知的基因和 miRNA 簇，那么我们方法发现的以前未被文献识别的簇也可能具有生物学意义。我们相信，我们方法发现的这些新的调节协同模块将成为进一步研究这些新的 miRNA 和基因功能组合的特定功能作用的跳板，特别是那些与乳腺癌等疾病相关的作用。
