Human protein secretory pathway genes are expressed in a tissue-specific pattern to match processing demands of the secretome
Artikel i vetenskaplig tidskrift, 2017

Protein secretory pathway in eukaryal cells is responsible for delivering functional secretory proteins. The dysfunction of this pathway causes a range of important human diseases from congenital disorders to cancer. Despite the piled-up knowledge on the molecular biology and biochemistry level, the tissue-specific expression of the secretory pathway genes has not been analyzed on the transcriptome level. Based on the recent RNA-sequencing studies, the largest fraction of tissue-specific transcriptome encodes for the secretome (secretory proteins). Here, the question arises that if the expression levels of the secretory pathway genes have a tissue-specific tuning. In this study, we tackled this question by performing a meta-analysis of the recently published transcriptome data on human tissues. As a result, we detected 68 as called “extreme genes” which show an unusual expression pattern in specific gene families of the secretory pathway. We also inspected the potential functional link between detected extreme genes and the corresponding tissues enriched secretome. As a result, the detected extreme genes showed correlation with the enrichment of the nature and number of specific post-translational modifications in each tissue’s secretome. Our findings conciliate both the housekeeping and tissue-specific nature of the protein secretory pathway, which we attribute to a fine-tuned regulation of defined gene families to support the diversity of secreted proteins and their modifications.

Författare

Amir Feizi

Chalmers, Biologi och bioteknik, Systembiologi

Francesco Gatto

Chalmers, Biologi och bioteknik, Systembiologi

Mathias Uhlen

Danmarks Tekniske Universitet (DTU)

Kungliga Tekniska Högskolan (KTH)

Jens B Nielsen

Danmarks Tekniske Universitet (DTU)

Kungliga Tekniska Högskolan (KTH)

Chalmers, Biologi och bioteknik, Systembiologi

npj Systems Biology and Applications

20567189 (eISSN)

Vol. 3 1 22

Ämneskategorier

Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)

Bioinformatik och systembiologi

Genetik

DOI

10.1038/s41540-017-0021-4

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Senast uppdaterat

2024-01-03