In silico investigation of potential COVID-19-associated microRNA signatures

Seyedehsadaf Asfa; Didem Ökmen; Athanasia Pavlopoulou

doi:10.17826/cumj.1415977

EN TR

In silico investigation of potential COVID-19-associated microRNA signatures

Abstract

Purpose: The global pandemic COVID-19, caused by the coronavirus SARS-CoV-2, is persistent despite the increasing vaccination rates, with new cases being reported per week. MicroRNAs, that is, non-coding RNA species that regulate gene expression at the post-transcriptional level, play a pivotal role in the SARS-CoV-2 life cycle, pathophysiology and host’s anticoronaviral responses. The objective of this study was the in silico discovery of functionally associated miRNAs that likely co-regulate COVID-19-related genes Materials and Methods: In the present study, an integrative bioinformatics approach was employed, including database searching, gene set enrichment analysis, network-based and microRNA target prediction methods, towards the discovery of epigenetic determinants of COVID-19. Results: An intricate microRNA-target gene network was constructed, and a set of 8 highly interacting microRNAs, that potentially co-target and co-regulate key COVID-19-related genes, was detected. These miRNAs and their corresponding genes are likely involved in the host’s response to SARS-CoV-2 infection. Conclusion: The 8 functionally associated miRNAs could constitute a signature for COVID-19 diagnosis.

Keywords

COVID19 , bioinformatics , host response genes , microRNAs

Potansiyel COVID-19 ilişkili mikroRNA’ların bilgisayar ortamında araştırılması

Öz

Amaç: Koronavirüs SARS-CoV-2'nin neden olduğu küresel COVID-19 pandemisi, artan aşılama oranlarına rağmen varlığını sürdürmekte ve her hafta yeni vakalar rapor edilmektedir. Transkripsiyon sonrası seviyede gen ekspresyonunu düzenleyen kodlamayan RNA türleri olan mikroRNA'lar, SARS-CoV-2 yaşam döngüsünde, patofizyolojisinde ve konağın antikoronaviral yanıtlarında çok önemli bir rol oynarlar. Bu çalışmada, COVID-19 ile ilişkili genleri düzenlemesi muhtemel, işlevsel olarak ilişkili miRNA'ları in silico araştırıp bulmak amaçlanmıştır. Gereç ve Yöntem: Bu çalışmada, COVID-19'un epigenetik belirleyicilerini bulmaya yönelik veri tabanı araştırması, gen seti zenginleştirme analizi ve internet tabanlı mikroRNA’ya yönelik hedef tahmin yöntemlerini içeren bütünleştirici bir biyoinformatik yaklaşım kullanılmıştır. Bulgular: Karmaşık bir mikroRNA-hedef gen ağı oluşturularak, potansiyel olarak hedeflenen ve COVID-19 ile ilgili önemli genleri düzenleyen yüksek düzeyde etkileşime sahip 8 mikroRNA'dan oluşan bir dizi tespit edildi. Bu miRNA'lar ve bunlara karşılık gelen genler SARS-CoV-2 enfeksiyonuna verilen yanıtta rol oynayabilir. Sonuç: İşlevsel olarak ilişkili 8 miRNA, COVID-19 tanısı için önemli bulgular olabilirler.

Anahtar Kelimeler

biyoinformatik , COVID-19 enfeksiyonu ile ilişkili genler , antivirüs mikroRNA , protein-protein etkileşimleri , gen seti zenginleştirme analiz , ; mikroRNA-gen ağı

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Klinik Tıp Bilimleri (Diğer)

Bölüm

Araştırma Makalesi

Yazarlar

Seyedehsadaf Asfa Bu kişi benim
0000-0001-9134-7517
Türkiye

Didem Ökmen
0000-0003-3159-2005
Türkiye

Athanasia Pavlopoulou ^*
0000-0002-0815-3808
Türkiye

Yayımlanma Tarihi

29 Mart 2024

Gönderilme Tarihi

7 Ocak 2024

Kabul Tarihi

12 Mart 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 49 Sayı: 1

DOI

https://doi.org/10.17826/cumj.1415977

IZ

https://izlik.org/JA49LR58RN

MLA

Asfa, Seyedehsadaf, vd. “In silico investigation of potential COVID-19-associated microRNA signatures”. Cukurova Medical Journal, c. 49, sy 1, Mart 2024, ss. 170-8, doi:10.17826/cumj.1415977.

Bu eser Creative Commons Atıf-Gayriticari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.

In silico investigation of potential COVID-19-associated microRNA signatures

Abstract

Keywords

Potansiyel COVID-19 ilişkili mikroRNA’ların bilgisayar ortamında araştırılması

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster