Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction

Abstract Identification of biological process- and pathway-specific regulators is essential for advancing our understanding of regulation and formation of various phenotypic and complex traits. In this study, we applied two methods, triple-gene mutual interaction (TGMI) and Sparse Partial Least Squa...

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Autores principales:	Junyan Hong, Chathura Gunasekara, Cheng He, Sanzhen Liu, Jianqin Huang, Hairong Wei
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/761671a95f774f3f9e3caa1b5422783b
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spelling	oai:doaj.org-article:761671a95f774f3f9e3caa1b5422783b2021-12-02T16:07:03ZIdentification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction10.1038/s41598-021-92610-42045-2322https://doaj.org/article/761671a95f774f3f9e3caa1b5422783b2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92610-4https://doaj.org/toc/2045-2322Abstract Identification of biological process- and pathway-specific regulators is essential for advancing our understanding of regulation and formation of various phenotypic and complex traits. In this study, we applied two methods, triple-gene mutual interaction (TGMI) and Sparse Partial Least Squares (SPLS), to identify the regulators of multiple metabolic pathways in Arabidopsis thaliana and Populus trichocarpa using high-throughput gene expression data. We analyzed four pathways: (1) lignin biosynthesis pathway in A. thaliana and P. trichocarpa; (2) flavanones, flavonol and anthocyannin biosynthesis in A. thaliana; (3) light reaction pathway and Calvin cycle in A. thaliana. (4) light reaction pathway alone in A. thaliana. The efficiencies of two methods were evaluated by examining the positive known regulators captured, the receiver operating characteristic (ROC) curves and the area under ROC curves (AUROC). Our results showed that TGMI is in general more efficient than SPLS in identifying true pathway regulators and ranks them to the top of candidate regulatory gene lists, but the two methods are to some degree complementary because they could identify some different pathway regulators. This study identified many regulators that potentially regulate the above pathways in plants and are valuable for genetic engineering of these pathways.Junyan HongChathura GunasekaraCheng HeSanzhen LiuJianqin HuangHairong WeiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Junyan Hong Chathura Gunasekara Cheng He Sanzhen Liu Jianqin Huang Hairong Wei Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
description	Abstract Identification of biological process- and pathway-specific regulators is essential for advancing our understanding of regulation and formation of various phenotypic and complex traits. In this study, we applied two methods, triple-gene mutual interaction (TGMI) and Sparse Partial Least Squares (SPLS), to identify the regulators of multiple metabolic pathways in Arabidopsis thaliana and Populus trichocarpa using high-throughput gene expression data. We analyzed four pathways: (1) lignin biosynthesis pathway in A. thaliana and P. trichocarpa; (2) flavanones, flavonol and anthocyannin biosynthesis in A. thaliana; (3) light reaction pathway and Calvin cycle in A. thaliana. (4) light reaction pathway alone in A. thaliana. The efficiencies of two methods were evaluated by examining the positive known regulators captured, the receiver operating characteristic (ROC) curves and the area under ROC curves (AUROC). Our results showed that TGMI is in general more efficient than SPLS in identifying true pathway regulators and ranks them to the top of candidate regulatory gene lists, but the two methods are to some degree complementary because they could identify some different pathway regulators. This study identified many regulators that potentially regulate the above pathways in plants and are valuable for genetic engineering of these pathways.
format	article
author	Junyan Hong Chathura Gunasekara Cheng He Sanzhen Liu Jianqin Huang Hairong Wei
author_facet	Junyan Hong Chathura Gunasekara Cheng He Sanzhen Liu Jianqin Huang Hairong Wei
author_sort	Junyan Hong
title	Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
title_short	Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
title_full	Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
title_fullStr	Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
title_full_unstemmed	Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
title_sort	identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/761671a95f774f3f9e3caa1b5422783b
work_keys_str_mv	AT junyanhong identificationofbiologicalpathwayandprocessregulatorsusingsparsepartialleastsquaresandtriplegenemutualinteraction AT chathuragunasekara identificationofbiologicalpathwayandprocessregulatorsusingsparsepartialleastsquaresandtriplegenemutualinteraction AT chenghe identificationofbiologicalpathwayandprocessregulatorsusingsparsepartialleastsquaresandtriplegenemutualinteraction AT sanzhenliu identificationofbiologicalpathwayandprocessregulatorsusingsparsepartialleastsquaresandtriplegenemutualinteraction AT jianqinhuang identificationofbiologicalpathwayandprocessregulatorsusingsparsepartialleastsquaresandtriplegenemutualinteraction AT hairongwei identificationofbiologicalpathwayandprocessregulatorsusingsparsepartialleastsquaresandtriplegenemutualinteraction
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Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction

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