Screening and Validation of Housekeeping Genes of the Root and Cotyledon of Cunninghamia lanceolata under Abiotic Stresses by Using Quantitative Real-Time PCR

Cunninghamia lanceolata (Chinese fir) is a fast-growing and commercially important conifer of the Cupressaceae family. Due to the unavailability of complete genome sequences and relatively poor genetic background information of the Chinese fir, it is necessary to identify and analyze the expression...

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Bibliographic Details
Main Authors: Wenlong Bao, Yanli Qu, Xiaoyi Shan, Yinglang Wan
Format: Article
Language:English
Published: MDPI AG 2016-07-01
Series:International Journal of Molecular Sciences
Subjects:
Online Access:http://www.mdpi.com/1422-0067/17/8/1198
Description
Summary:Cunninghamia lanceolata (Chinese fir) is a fast-growing and commercially important conifer of the Cupressaceae family. Due to the unavailability of complete genome sequences and relatively poor genetic background information of the Chinese fir, it is necessary to identify and analyze the expression levels of suitable housekeeping genes (HKGs) as internal reference for precise analysis. Based on the results of database analysis and transcriptome sequencing, we have chosen five candidate HKGs (Actin, GAPDH, EF1a, 18S rRNA, and UBQ) with conservative sequences in the Chinese fir and related species for quantitative analysis. The expression levels of these HKGs in roots and cotyledons under five different abiotic stresses in different time intervals were measured by qRT-PCR. The data were statistically analyzed using the following algorithms: NormFinder, BestKeeper, and geNorm. Finally, RankAggreg was applied to merge the sequences generated from three programs and rank these according to consensus sequences. The expression levels of these HKGs showed variable stabilities under different abiotic stresses. Among these, Actin was the most stable internal control in root, and GAPDH was the most stable housekeeping gene in cotyledon. We have also described an experimental procedure for selecting HKGs based on the de novo sequencing database of other non-model plants.
ISSN:1422-0067