Identification of novel tissue-specific genes by analysis of microarray databases: a human and mouse model

Abstract

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI's Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved.

Figure 1. Steps for selecting kidney-specific genes.

Tissue-specific genes were determined as follows: i) Gene expression values for each tissue were averaged; ii) The averaged values were divided by an averaged value for kidney; iii) The results were averaged and sorted in ascending order with a lower value representing higher tissue-specific expression. Highly ranked genes with lower values are candidates for kidney-specific genes; iv) An alternative method for finding tissue-specificity is to divide an average gene expression value for kidney by an average of averages of gene expression values in other tissues.

Figure 2. Expression of adult human and mouse gene transcripts detected by PCR reaction and agarose gel electrophoresis.

Lanes 1–6 contain PCR products from human and lanes 7–12 contain PCR products from mouse. Lanes 1 and 7: kidney, lanes 2 and 8: liver, lanes 3 and 9: lung, lanes 4 and 10: heart, lanes 5 and 11: muscle, and lanes 6 and 12: adipose. Housekeeping genes, human and mouse cyclophilin (cyc), serve as a loading control.

Figure 3. AMDHD1 (amidohydrolase domain containing 1) mRNA expression.

A, Real-time PCR for AMDHD1 mRNA tissue distribution. Total RNA were isolated from the white adipose tissue (WAT), brown adipose tissue (BAT), liver, muscle, heart, lung, spleen, and kidney of adult mice. The mRNA expression was measured by quantitative real-time reverse transcription PCR (qRT-PCR) (n = 3). The bar represents mean ± SEM. Statistical significance is indicated by ***(P<0.001). Housekeeping gene cyclophilin (cyc) was used to normalize the mRNA expression. B–E, Analysis of microarray DataSets obtained from the NCBI website, which contains expression profiles for AMDHD1. B: GDS1729 (n = 5 per group), C: GDS1916 (n = 3 per group), D: GDS2577 (n = 3–4 per group), and E: GDS1517 (n = 5 per group). HNF4α: hepatocyte nuclear factor 4 alpha; dpc: days post conception; aph: after partial hepatectomy.

Figure 4. PRUNE2 (prune homolog 2) mRNA expression.

A, Real-time PCR for PRUNE2 mRNA tissue distribution. Total RNA were isolated from the white adipose tissue (WAT), brown adipose tissue (BAT), liver, muscle, heart, lung, spleen, and kidney of adult mice. The mRNA expression was measured by quantitative real-time reverse transcription PCR (qRT-PCR) (n = 3). The bar represents mean ± SEM. Statistical significance is indicated by ***(P<0.001). Housekeeping gene cyclophilin (cyc) was used to normalize the mRNA expression. B–E, Analysis of microarray DataSets obtained from the NCBI website that contains expression profiles for PRUNE2. B: GDS2727 (n = 3 per group), C: GDS2746 (n = 6–8 per group), D: GDS651 (n = 11–15 per group), and E: GDS3673 (n = 5 per group). ERRα: estrogen-related receptor alpha; Lmna: lamin A/C.

Figure 5. ACVR1C (activin A receptor, type IC) mRNA expression.

A, Real-time PCR for ACVR1C mRNA tissue distribution. Total RNA were isolated from the white adipose tissue (WAT), brown adipose tissue (BAT), liver, muscle, heart, lung, spleen, and kidney of adult mice. The mRNA expression was measured by quantitative real-time reverse transcription PCR (qRT-PCR) (n = 3). The bar represents mean ± SEM. Statistical significance is indicated by ***(P<0.001). Housekeeping gene cyclophilin (cyc) was used to normalize the mRNA expression. B and C, Analysis of microarray DataSets obtained from the NCBI website containing expression profiles for ACVR1C. B: GDS3135 (n = 4 per group) and C: GDS3665 (n = 5 per group). D–G, Relative expression of DLK1, FABP4, SCD1, and ACVR1C in the stromal-vascular (SV) and fat cell (FC) fractions from mouse inguinal adipose tissue. Each bar indicates mean and SEM (n = 5). Statistical significance by Student’s t test is shown: *, P<0.05; **, P<0.01. The gene expression was normalized to cyclophilin (cyc) mRNA expression. H–J, Developmental regulation of ACVR1C during adipogenic differentiation of 3T3-L1 cells. The bar represents mean ± SEM (n = 3). Letters a and b show significant differences in gene expression among several time-points (day 0, 2, 4, 6, and 8) in adipocyte differentiation at P<0.05. The mRNA abundance was measured by quantitative real-time reverse transcription PCR (qRT-PCR) and normalized to cyclophilin (cyc) mRNA.