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Quant. Biol.    2021, Vol. 9 Issue (4) : 411-425    https://doi.org/10.15302/J-QB-021-0247
RESEARCH ARTICLE
Functional characterization of disease/comorbidity-associated lncRNA
Jing Tang1,2, Yongheng Wang2, Jianbo Fu1, Xianglu Wu3, Zhijie Han1,2, Chuan Wang2, Maiyuan Guo2, Yingxiong Wang2,3, Yubin Ding3(), Bo Yang1(), Feng Zhu1()
1. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
2. College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
3. Joint International Research Laboratory of Reproductive and Development, Department of Reproductive Biology, School of Public Health, Chongqing Medical University, Chongqing 400016, China
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Abstract

Background: Functional characterization of the long noncoding RNAs (lncRNAs) in disease attracts great attention, which results in a limited number of experimentally characterized lncRNAs. The major problems underlying the lack of experimental verifications are considered to come from the significant false-positive assignments and extensive genetic-heterogeneity of disease. These problems are even worse when it comes to the functional characterization in comorbidity (simultaneous/sequential presence of multiple diseases in a patient, and showing much wider prevalence, poorer treatment-response and longer illness-course than a single disease).

Methods: Herein, FCCLnc was developed to characterize lncRNA function by (1) integrating diverse SNPs that were associated with 193 diseases standardized by International Classification of Diseases (ICD-11), (2) condition-specific expression of lncRNAs, (3) weighted correlation network of lncRNAs and protein-coding neighboring genes.

Results: FCCLnc can characterize lncRNA function in both disease and comorbidity by not only controlling false discovery but also tolerating their disease heterogeneity. Moreover, FCCLnc can provide interactive visualization and full download of lncRNA-centered co-expression network.

Conclusion: In summary, FCCLnc is unique in characterizing lncRNA function in diverse diseases and comorbidities and is highly expected to emerge to be an indispensable complement to other available tools. FCCLnc is accessible at https://idrblab.org/fcclnc/.
Keywords comorbidity      long noncoding RNA      functional characterization      disease-associated SNPs      guilt-by-association     
Corresponding Author(s): Yubin Ding,Bo Yang,Feng Zhu   
Just Accepted Date: 04 June 2021   Online First Date: 19 July 2021    Issue Date: 01 December 2021
 Cite this article:   
Jing Tang,Yongheng Wang,Jianbo Fu, et al. Functional characterization of disease/comorbidity-associated lncRNA[J]. Quant. Biol., 2021, 9(4): 411-425.
 URL:  
https://academic.hep.com.cn/qb/EN/10.15302/J-QB-021-0247
https://academic.hep.com.cn/qb/EN/Y2021/V9/I4/411
Fig.1  The workflow of FCCLnc.
Fig.2  Performance comparison between FCCLnc and WGCNA-DEA based on two indexes.
Dataset ID Sample details of each dataset Classification of disease by ICD-11 Expression unit Number of lncRNAs & mRNAs
GSE106388 [74] 15 mild asthma patients & 4 healthy controls CA23 Reads count 12,994 lncRNAs & 19,364 mRNAs
GSE112523 [75] 29 SCZ patients & 28 healthy controls 6A20 Reads count 12,179 lncRNAs & 18,437 mRNAs
GSE128682 [76] 14 ulcerative colitis patients & 16 healthy controls DD71 Reads count 1,756 lncRNAs & 17,355 mRNAs
GSE129398 [77] 12 obesity people & 10 controls of low BMI 5B81 Reads count 822 lncRNAs & 14,300 mRNAs
GSE131526 [78] 12 type-1 diabetes patients & 3 healthy controls 5A10 Reads count 6,798 lncRNAs & 19,614 mRNAs
TCGA-BC [79] 115 breast cancer patients & 113 healthy controls 2C60 FPKM 14,097 lncRNAs & 19,631 mRNAs
GSE78936 [80] 28 SCZ patients & 30 bipolar disorder patients 6A20 & 6A60 FPKM 5,494 lncRNAs & 18,025 mRNAs
GSE133099 [76] 6 type-2 diabetes patients & 6 obesity people 5A11 & 5B81 Reads count 8,929 lncRNAs & 17,518 mRNAs
Tab.1  Eight benchmark datasets collected for case study
Fig.3  
Fig.4  The co-expression network illustrating the regulation among lncRNAs and mRNAs in obesity patients comorbid with type-2 diabetes.
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