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Systematic analysis of gene expression patterns associated with postmortem interval in human tissues

Open access
Zhu, Yizhang, Wang, Likun, Yin, Yuxin, Yang, Ence·2017·Scientific Reports
DOI 10.1038/s41598-017-05882-0PMC PMC5511187
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Abstract

Postmortem mRNA degradation is considered to be the major concern in gene expression research utilizing human postmortem tissues. A key factor in this process is the postmortem interval (PMI), which is defined as the interval between death and sample collection. However, global patterns of postmortem mRNA degradation at individual gene levels across diverse human tissues remain largely unknown. In this study, we performed a systematic analysis of alteration of gene expression associated with PMI in human tissues. From the Genotype-Tissue Expression (GTEx) database, we evaluated gene expression levels of 2,016 high-quality postmortem samples from 316 donors of European descent, with PMI ranging from 1 to 27 hours. We found that PMI-related mRNA degradation is tissue-specific, gene-specific, and even genotype-dependent, thus drawing a more comprehensive picture of PMI-associated gene expression across diverse human tissues. Additionally, we also identified 266 differentially variable (DV) genes, such as DEFB4B and IFNG, whose expression is significantly dispersed between short PMI (S-PMI) and long PMI (L-PMI) groups. In summary, our analyses provide a comprehensive profile of PMI-associated gene expression, which will help interpret gene expression patterns in the evaluation of postmortem tissues.

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Figure 1 Postmortem Interval distribution of samples in 15 human tissues. Each histogram denotes the distribution of samples with different PMIs in hours.
Figure 1 Postmortem Interval distribution of samples in 15 human tissues. Each histogram denotes the distribution of samples with different PMIs in hours.CC BY · PubMed Central
Figure 2 Visualization of gene expression associated with PMI. (a) Heat map of 1,413 PMI-associated genes (row) on 85 samples (column). Colors represent residual gene expression values with red for low expression and blue for high expression. The PMI of each individual is displayed at the bottom and also illustrated in color bar at the top with color changes from red to green with PMI increased. (b) Scatter plot of two representative PMI-associated gene expression patterns of VEGFA and Srp72 in whole blood and muscle skeletal respectively. The dots represent the expression of samples. Spearman-R value in the title represents the Spearman correlation coefficient of gene expression and PMI across all samples.
Figure 2 Visualization of gene expression associated with PMI. (a) Heat map of 1,413 PMI-associated genes (row) on 85 samples (column). Colors represent residual gene expression values with red for low expression and blue for high expression. The PMI of each individual is displayed at the bottom and also illustrated in color bar at the top with color changes from red to green with PMI increased. (b) Scatter plot of two representative PMI-associated gene expression patterns of VEGFA and Srp72 in whole blood and muscle skeletal respectively. The dots represent the expression of samples. Spearman-R value in the title represents the Spearman correlation coefficient of gene expression and PMI across all samples.CC BY · PubMed Central
Figure 3 Examples of genotype-by-PMI interaction affecting the expression level of the gene. (a) The interaction between rs12406273 and PMI affecting RIC8A gene expression in tibial artery and whole blood. (b) The interaction of rs1521177 and PMI affecting SPIN3 gene expression in esophageal mucosa and whole blood. For each subplot, the larger panel on the left shows all samples, while the three smaller panels on the right show the samples with major allele homozygous, heterozygous and minor allele homozygous (with a cross) respectively.
Figure 3 Examples of genotype-by-PMI interaction affecting the expression level of the gene. (a) The interaction between rs12406273 and PMI affecting RIC8A gene expression in tibial artery and whole blood. (b) The interaction of rs1521177 and PMI affecting SPIN3 gene expression in esophageal mucosa and whole blood. For each subplot, the larger panel on the left shows all samples, while the three smaller panels on the right show the samples with major allele homozygous, heterozygous and minor allele homozygous (with a cross) respectively.CC BY · PubMed Central
Figure 4 Examples of differential gene expression dispersion among PMI groups. (a) Increased gene expression variance of DEFB4B in esophageal mucosa between PMI groups (left:121–696 mins vs. 707–1,515 mins; right: all samples). (b) Decreased gene expression variance of IFNG in lung between PMI groups (left:156–757 mins vs. 760–1,485 mins; right: all samples). Each PMI group was plotted with jitter along the x-axis to show samples of different PMI. The red dotted line represents the median PMI of all samples.
Figure 4 Examples of differential gene expression dispersion among PMI groups. (a) Increased gene expression variance of DEFB4B in esophageal mucosa between PMI groups (left:121–696 mins vs. 707–1,515 mins; right: all samples). (b) Decreased gene expression variance of IFNG in lung between PMI groups (left:156–757 mins vs. 760–1,485 mins; right: all samples). Each PMI group was plotted with jitter along the x-axis to show samples of different PMI. The red dotted line represents the median PMI of all samples.CC BY · PubMed Central

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Metadata

Authors
Zhu, Y., Wang, L., Yin, Y., & Yang, E.
Affiliations
Peking University (CN)
Corresponding author
  • Yin, Yuxin
  • Yang, Ence
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2017-07-14
Volume
7
Issue
1
Pages
5435-5435
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-017-05882-0
PMC
PMC5511187
OpenAlex
W2734938713
Cited by
129
References
46
Citations by year
2026: 12 · 2025: 15 · 2024: 17 · 2023: 9 · 2022: 19 · 2021: 21 · 2020: 13 · 2019: 15 · 2018: 8
FWCI
4.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (111 Project, 31401132, B07001)
  • Peking University
  • Higher Education Discipline Innovation Project (B07001)
  • National Key Research and Development Program of China (#2016YFA0500302)
  • Peking University Health Science Center
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords
postmortem interval, gene expression, tissue-specific gene expression, genotype-dependent gene expression, interferon-gamma, GTEx
MeSH terms
Autopsy, Cadaver, Genotype, Humans, Interferon-gamma, Organ Specificity, Postmortem Changes, RNA, Messenger, Time Factors, Gene Expression, Databases, Factual, Gene Expression Profiling, RNA Stability, beta-Defensins, White People

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