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Evaluation of Appropriate Reference Genes for Reverse Transcription-Quantitative PCR Studies in Different Tissues of a Desert Poplar via Comparision of Different Algorithms.

Wang HL, Li L, Tang S, Yuan C, Tian Q, Su Y, Li HG, Zhao L, Yin W, Zhao R, Xia X - Int J Mol Sci (2015)

Bottom Line: To support the suitability of the identified reference genes and to compare the relative merits of these different algorithms, we analyzed and compared the relative expression levels of nine P. euphratica functional genes in different tissues.Our results indicate that a combination of multiple reference genes recommended by GrayNorm algorithm (e.g., a combination of Actin, EF1α, GAPDH, RP, UBQ in root) should be used instead of a single reference gene.These results are valuable for research of gene identification in different P. euphratica tissues.

View Article: PubMed Central - PubMed

Affiliation: National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China. whling@bjfu.edu.cn.

ABSTRACT
Despite the unshakable status of reverse transcription-quantitative PCR in gene expression analysis, it has certain disadvantages, including that the results are highly dependent on the reference genes selected for data normalization. Since inappropriate endogenous control genes will lead to inaccurate target gene expression profiles, the validation of suitable internal reference genes is essential. Given the increasing interest in functional genes and genomics of Populus euphratica, a desert poplar showing extraordinary adaptation to salt stress, we evaluated the expression stability of ten candidate reference genes in P. euphratica roots, stems, and leaves under salt stress conditions. We used five algorithms, namely, ΔCt, NormFinder, geNorm, GrayNorm, and a rank aggregation method (RankAggreg) to identify suitable normalizers. To support the suitability of the identified reference genes and to compare the relative merits of these different algorithms, we analyzed and compared the relative expression levels of nine P. euphratica functional genes in different tissues. Our results indicate that a combination of multiple reference genes recommended by GrayNorm algorithm (e.g., a combination of Actin, EF1α, GAPDH, RP, UBQ in root) should be used instead of a single reference gene. These results are valuable for research of gene identification in different P. euphratica tissues.

No MeSH data available.


Related in: MedlinePlus

Relative expression levels of nine P. euphratica functional genes. Expression analysis of nine genes in response to different stages of salt stress in different tissues, based on the reference genes displayed in Table 4 recommended by different algorithms. The expression levels were log2 transformed for easily comparing the up- or down- regulation, and the “1” in Y-axis and “0” in X-axis which show “1” fold change means unchanged. A to I represent nine different genes. Error bars indicate standard errors (n = 3, Bars ± SE). Columns labeled with letters “a,b,c…” indicate significant differences at p < 0.05 between different expression levels.
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ijms-16-20468-f006: Relative expression levels of nine P. euphratica functional genes. Expression analysis of nine genes in response to different stages of salt stress in different tissues, based on the reference genes displayed in Table 4 recommended by different algorithms. The expression levels were log2 transformed for easily comparing the up- or down- regulation, and the “1” in Y-axis and “0” in X-axis which show “1” fold change means unchanged. A to I represent nine different genes. Error bars indicate standard errors (n = 3, Bars ± SE). Columns labeled with letters “a,b,c…” indicate significant differences at p < 0.05 between different expression levels.

Mentions: The relative expression levels of nine P. euphratica functional genes, PeCOBL4, PeFLA12-1, PeFLA12-2, PeFLA12-3, PeFLA12-4, PeHKT1, PeKUP3, PeNhaD1 and PeNHX2, in different tissues were analyzed by RT-qPCR. Non-normalized expression levels were compared with normalized expression levels using the reference genes selected by the various algorithms as displayed in Table 4. The non-normalized data change by using the normalization factor based on expression of the selected reference genes comprised in a normalization factor (NF). Various NFs have various effects on gene of interest expression. The smaller the difference between the normalized and non-normalized data, the more accurate the results are [46]. Figure 6 shows the induction or repression of genes by salt stress, some genes were initially induced then repressed. However, the maximum values and expression fold changes differed significantly when normalization was performed using different combinations of reference genes as proposed by the different algorithms. For example, it is known that the expression patterns of the FLA genes vary quite consistently according to the plant tissues being assessed. The mRNAs encoded by these four genes were previously found to be highly expressed in P. euphratica under salt stress [32]. As expected, steady-state mRNA levels for the FLA genes were induced by salt stress significantly (Figure 6). When the relative expression levels of nine functional genes were normalized with the combination recommended by GrayNorm, the fold changes were smaller comparing with ΔCt, geNorm, NormFinder or RankAggreg, and the values were closer to the non-normalized data. This indicates that GrayNorm, at least in this experiment, suggests the most optimal combination of reference genes giving the highest possible accuracy.


Evaluation of Appropriate Reference Genes for Reverse Transcription-Quantitative PCR Studies in Different Tissues of a Desert Poplar via Comparision of Different Algorithms.

Wang HL, Li L, Tang S, Yuan C, Tian Q, Su Y, Li HG, Zhao L, Yin W, Zhao R, Xia X - Int J Mol Sci (2015)

Relative expression levels of nine P. euphratica functional genes. Expression analysis of nine genes in response to different stages of salt stress in different tissues, based on the reference genes displayed in Table 4 recommended by different algorithms. The expression levels were log2 transformed for easily comparing the up- or down- regulation, and the “1” in Y-axis and “0” in X-axis which show “1” fold change means unchanged. A to I represent nine different genes. Error bars indicate standard errors (n = 3, Bars ± SE). Columns labeled with letters “a,b,c…” indicate significant differences at p < 0.05 between different expression levels.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4613214&req=5

ijms-16-20468-f006: Relative expression levels of nine P. euphratica functional genes. Expression analysis of nine genes in response to different stages of salt stress in different tissues, based on the reference genes displayed in Table 4 recommended by different algorithms. The expression levels were log2 transformed for easily comparing the up- or down- regulation, and the “1” in Y-axis and “0” in X-axis which show “1” fold change means unchanged. A to I represent nine different genes. Error bars indicate standard errors (n = 3, Bars ± SE). Columns labeled with letters “a,b,c…” indicate significant differences at p < 0.05 between different expression levels.
Mentions: The relative expression levels of nine P. euphratica functional genes, PeCOBL4, PeFLA12-1, PeFLA12-2, PeFLA12-3, PeFLA12-4, PeHKT1, PeKUP3, PeNhaD1 and PeNHX2, in different tissues were analyzed by RT-qPCR. Non-normalized expression levels were compared with normalized expression levels using the reference genes selected by the various algorithms as displayed in Table 4. The non-normalized data change by using the normalization factor based on expression of the selected reference genes comprised in a normalization factor (NF). Various NFs have various effects on gene of interest expression. The smaller the difference between the normalized and non-normalized data, the more accurate the results are [46]. Figure 6 shows the induction or repression of genes by salt stress, some genes were initially induced then repressed. However, the maximum values and expression fold changes differed significantly when normalization was performed using different combinations of reference genes as proposed by the different algorithms. For example, it is known that the expression patterns of the FLA genes vary quite consistently according to the plant tissues being assessed. The mRNAs encoded by these four genes were previously found to be highly expressed in P. euphratica under salt stress [32]. As expected, steady-state mRNA levels for the FLA genes were induced by salt stress significantly (Figure 6). When the relative expression levels of nine functional genes were normalized with the combination recommended by GrayNorm, the fold changes were smaller comparing with ΔCt, geNorm, NormFinder or RankAggreg, and the values were closer to the non-normalized data. This indicates that GrayNorm, at least in this experiment, suggests the most optimal combination of reference genes giving the highest possible accuracy.

Bottom Line: To support the suitability of the identified reference genes and to compare the relative merits of these different algorithms, we analyzed and compared the relative expression levels of nine P. euphratica functional genes in different tissues.Our results indicate that a combination of multiple reference genes recommended by GrayNorm algorithm (e.g., a combination of Actin, EF1α, GAPDH, RP, UBQ in root) should be used instead of a single reference gene.These results are valuable for research of gene identification in different P. euphratica tissues.

View Article: PubMed Central - PubMed

Affiliation: National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China. whling@bjfu.edu.cn.

ABSTRACT
Despite the unshakable status of reverse transcription-quantitative PCR in gene expression analysis, it has certain disadvantages, including that the results are highly dependent on the reference genes selected for data normalization. Since inappropriate endogenous control genes will lead to inaccurate target gene expression profiles, the validation of suitable internal reference genes is essential. Given the increasing interest in functional genes and genomics of Populus euphratica, a desert poplar showing extraordinary adaptation to salt stress, we evaluated the expression stability of ten candidate reference genes in P. euphratica roots, stems, and leaves under salt stress conditions. We used five algorithms, namely, ΔCt, NormFinder, geNorm, GrayNorm, and a rank aggregation method (RankAggreg) to identify suitable normalizers. To support the suitability of the identified reference genes and to compare the relative merits of these different algorithms, we analyzed and compared the relative expression levels of nine P. euphratica functional genes in different tissues. Our results indicate that a combination of multiple reference genes recommended by GrayNorm algorithm (e.g., a combination of Actin, EF1α, GAPDH, RP, UBQ in root) should be used instead of a single reference gene. These results are valuable for research of gene identification in different P. euphratica tissues.

No MeSH data available.


Related in: MedlinePlus