Ultra-deep sequencing reveals the microRNA expression pattern of the human stomach - PubMed (original) (raw)

. 2010 Oct 8;5(10):e13205.

doi: 10.1371/journal.pone.0013205.

André S Khayat, Artur Silva, Dayse O Alencar, Jessé Lobato, Larissa Luz, Daniel G Pinheiro, Leonardo Varuzza, Monica Assumpção, Paulo Assumpção, Sidney Santos, Dalila L Zanette, Wilson A Silva Jr, Rommel Burbano, Sylvain Darnet

Affiliations

Ultra-deep sequencing reveals the microRNA expression pattern of the human stomach

Ândrea Ribeiro-dos-Santos et al. PLoS One. 2010.

Abstract

Background: While microRNAs (miRNAs) play important roles in tissue differentiation and in maintaining basal physiology, little is known about the miRNA expression levels in stomach tissue. Alterations in the miRNA profile can lead to cell deregulation, which can induce neoplasia.

Methodology/principal findings: A small RNA library of stomach tissue was sequenced using high-throughput SOLiD sequencing technology. We obtained 261,274 quality reads with perfect matches to the human miRnome, and 42% of known miRNAs were identified. Digital Gene Expression profiling (DGE) was performed based on read abundance and showed that fifteen miRNAs were highly expressed in gastric tissue. Subsequently, the expression of these miRNAs was validated in 10 healthy individuals by RT-PCR showed a significant correlation of 83.97% (P<0.05). Six miRNAs showed a low variable pattern of expression (miR-29b, miR-29c, miR-19b, miR-31, miR-148a, miR-451) and could be considered part of the expression pattern of the healthy gastric tissue.

Conclusions/significance: This study aimed to validate normal miRNA profiles of human gastric tissue to establish a reference profile for healthy individuals. Determining the regulatory processes acting in the stomach will be important in the fight against gastric cancer, which is the second-leading cause of cancer mortality worldwide.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Distribution of small RNAs sequenced from human gastric cardia tissue using deep-sequencing.

Figure 2

Figure 2. Distribution of microRNA by read count number in human gastric cardia.

The read count is based on quantity of read detected during the deep-sequencing of small RNA library of gastric cardia, using SOLiD system. For microRNA detection was used the miRBase release 15.0.

Figure 3

Figure 3. Most expressed microRNAs in human gastric cardia.

The read count is based on quantity of read detected during the deep-sequencing of small RNA library of gastric cardia, using SOLiD system.

Figure 4

Figure 4. Heatmap of normalized expression of the 15 most expressed mature miRNAs in human gastric tissue and their comparison with other normal tissues published in the mammalian microRNA expression atlas (Landgraf, P. et al. (2007). Cell 129: 1401–1414).

The heatmap was generated using gene pattern software with normalized expression of microRNA (read count number for specific microRNA/total of count number of microRNA). Color scale indicates the percent of total count reads number 0 to 0.2 (0 to 20%). Human tissue description and abbreviation: hsa_B-cell-CD19 (B cells from peripheral blood); hsa_B-cell-CD19-pool (B cells from peripheral blood (pool from 4 healthy donors)); hsa_B-cell-CD19-2 (B cells from peripheral blood); hsa_DC-unstim (myeloid dendritic cells not stimulated); hsa_DC-stim (myeloid dendritic cells stimulated with endotoxin); hsa_DC-unstim (myeloid dendritic cells not stimulated); hsa_DC-stim (myeloid dendritic cells stimulated with endotoxin); hsa_Fibrobl-CMV(Foreskin fibroblasts; Primary fibroblasts lytically infected with Cytomegalovirus); hsa_Frontal-cortex-adult; (Brain_normal adult; sample from Brodman area 9 (superior frontal gyrus) of a 20 year old healthy male, 6 hours postmortem); hsa_Granulocytes-CD1; (Granulocytes; Granulocyte cells from peripheral blood (pool from 4 healthy donors)); hsa_HSC-CD34 (pluripotent hematopoetic stem cell CD34+ - sorted cells); hsa_NK-CD56;(NK cells from peripheral blood (pool from 4 healthy donors)); hsa_Podocytes-Moins-undiff (Podocytes_undifferentiated); hsa_Podocytes-Moins-diff (Podocytes_differentiated); hsa_T-cell-CD4 (T helper cells, peripheral blood (pool from 4 healthy donors)); hsa_T-cell-CD4-2 (T helper cells); hsa_T-cell-CD4-naive(CD4+ CD45 RA+(CD45RO−) native cells); hsa_T-cell-CD4-effector (CD4+, CD45RO+, CD27−, CCR7−. Effector cells); hsa_T-cell-CD4-memory (CD4+CD45RO+(CD45RA−) memory cells); hsa_T-cell-CD8-2 (cytotoxic T-cells); hsa_T-cell-CD8 (cytotoxic T-cells, peripheral blood(pool from 4 healthy donors); hsa_T-cell-CD8-naive (CD8+, CD45RA+, CD27+, CCR7+); hsa_USSC (unrestricted somatic stem cells from umbilical cord); hsa_USSC-d1(unrestricted somatic stem cells from umbilical cord induced 1 day to osteoblasts); hsa_USSC-d3 (unrestricted somatic stem cells from umbilical cord induced 3 day to osteoblasts); hsa_USSC-d7 (unrestricted somatic stem cells from umbilical cord induced 7 day to osteoblasts).

Figure 5

Figure 5. Quantification by Real Time PCR of high expressed microRNAs in human gastric cardia.

The quantification is based on Ct and was normalized by endogenous expression control. The 2−ΔCt for each miR is the mean of ten determination originated from gastric cardia tissue of ten different individuals.

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