Selection and validation of suitable reference genes for miRNA expression normalization by quantitative RT-PCR in citrus somatic embryogenic and adult tissues (Q39574157)

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scientific article published on 5 August 2012

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English	Selection and validation of suitable reference genes for miRNA expression normalization by quantitative RT-PCR in citrus somatic embryogenic and adult tissues	scientific article published on 5 August 2012

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scholarly article

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Selection and validation of suitable reference genes for miRNA expression normalization by quantitative RT-PCR in citrus somatic embryogenic and adult tissues (English)

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

microRNA expression

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author name string

Shu-Jun Kou

1

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Xiao-Meng Wu

2

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Zheng Liu

3

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Yuan-Long Liu

4

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Qiang Xu

5

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Wen-Wu Guo

6

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

publication date

5 August 2012

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

Plant Cell Reports

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

31

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

12

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Europe PubMed Central

PubMed publication ID

13 September 2017

2151-2163

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Europe PubMed Central

PubMed publication ID

13 September 2017

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1 reference

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Normalization strategy is critical for the outcome of miRNA expression analyses in the rat heart.

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The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RT-PCR) analysis in plants.

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snoU6 and 5S RNAs are not reliable miRNA reference genes in neuronal differentiation

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An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues

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A novel bud mutation that confers abnormal patterns of lycopene accumulation in sweet orange fruit (Citrus sinensis L. Osbeck).

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Reference genes for accurate transcript normalization in citrus genotypes under different experimental conditions

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A novel and universal method for microRNA RT-qPCR data normalization

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Normalization strategies for microRNA profiling experiments: a 'normal' way to a hidden layer of complexity?

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Characterization of genomic sequence showing strong association with polyembryony among diverse Citrus species and cultivars, and its synteny with Vitis and Populus

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Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues

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Differential expression of the microRNAs in superior and inferior spikelets in rice (Oryza sativa).

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Suitable reference genes for relative quantification of miRNA expression in prostate cancer

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Identification of suitable reference genes for real-time RT-PCR normalization in the grapevine-downy mildew pathosystem.

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21 January 2018

Global expression profiling of rice microRNAs by one-tube stem-loop reverse transcription quantitative PCR revealed important roles of microRNAs in abiotic stress responses

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Identification of miR-23a as a novel microRNA normalizer for relative quantification in human uterine cervical tissues

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Facile means for quantifying microRNA expression by real-time PCR

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Selection of reliable reference genes for gene expression studies in peach using real-time PCR

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Eleven golden rules of quantitative RT-PCR.

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Identifiers

10.1007/S00299-012-1325-X

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

PubMed publication ID

1 reference

Europe PubMed Central

PubMed publication ID

13 September 2017

ResearchGate publication ID

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