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Effect of sample handling on gene expression in single cells of islets of Langerhans.
ID Valentinčič, Katarina (Author), ID Jakše, Jernej (Mentor) More about this mentor... This link opens in a new window, ID Theis, Fabian (Comentor)

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Abstract
This study investigates how sample preparation, storage, and processing impact gene expression analysis in single cells of pancreatic islets, with an emphasis on distinguishing technical artefacts from actual biological changes, especially in the context of Type 2 Diabetes (T2D). We found that batch effects influenced gene expression profiles using two datasets, one previously published and one new dataset. Dataset 2 showed increased stress-related gene expression, including pathways linked to the endoplasmic reticulum (ER) stress and cytokine signalling. In contrast, Dataset 1 was characterized by gene sets associated with cell proliferation, indicating possibly less stress. The study also explored the overlap between technical stress effects and T2D-related biological changes. While there were some similarities, such as increased apoptosis in specific beta cell subtypes, the overlap was limited, suggesting that technical stress does not fully replicate the complex biological changes associated with T2D. Additionally, the analysis revealed that certain technical factors, such as pre-distribution insulin content and the number of head leaks, influenced the proportions of beta cell subtypes, underscoring the importance of considering these variables in scRNA-seq studies. The findings highlight the need for careful control and interpretation of technical variability in scRNA-seq analyses to study the biological effects of T2D accurately.

Language:English
Keywords:batch effects, beta cells, bioinformatics, differential gene expression analysis, gene set enrichment analysis, scRNA-seq, type 2 diabetes
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:BF - Biotechnical Faculty
Year:2024
PID:20.500.12556/RUL-162612 This link opens in a new window
COBISS.SI-ID:209083651 This link opens in a new window
Publication date in RUL:26.09.2024
Views:145
Downloads:66
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Secondary language

Language:Slovenian
Title:Vpliv rokovanja z vzorci na izražanje genov v posameznih celicah Langerhansovih otočkov.
Abstract:
V sklopu naše raziskave smo želeli ugotoviti, kako rokovanje z vzorci, njihovo shranjevanje in obdelava vpliva na izražanje genov v posameznih celicah Langerhansovih otočkov trebušne slinavke, s poudarkom na razločevanju med tehničnimi artefakti in dejanskimi biološkimi spremembami, predvsem v okviru sladkorne bolezni tipa 2. S primerjavo dveh serij vzorcev smo ugotovili, da res vpliva na izražanje genov, saj so imele celice, iz predhodno že objavljene Serije 2, povečano izražanje s stresom povezanih genskih setov, vključno z biološkimi potmi kot sta stres endoplazmatskega retikuluma in signaliziranje s citokini. Nasprotno pa so celice iz Serije 1 karakterizirali genski seti, povezani s celičnimi delitvami, kar nakazuje, da so bile te verjetno izpostavljene manjšemu stresu. V okviru študije smo želeli tudi ugotoviti, kakšne so podobnosti med učinki stresa, ki izhaja iz rokovanja z vzorci, in biološkimi spremembami, ki so posledice sladkorne bolezni tipa 2. Čeprav smo opazili nekatere podobnosti, kot je več apoptoze v določenih podtipih beta celic, so bile le-te omejene, torej tehnični stres nima povsem enakega vpliva kot kompleksne biološke spremembe, ki so povezane s sladkorno boleznijo tipa 2. Poleg tega je analiza pokazala, da določeni tehnični dejavniki, kot sta vsebnost inzulina pred distribucijo in število iztekanj pankreatičnega soka iz glave trebušne slinavke, vplivajo na razmerje med podtipi beta celic, zaradi česar bi morali tudi te dejavnike upoštevati pri scRNA-seq analizah. Naša spoznanja kažejo na pomembnost natančnega nadzora in pazljivosti pri interpretaciji tehnične variabilnosti v scRNA-seq analizah, če želimo korektno raziskovati biološke spremembe pri sladkorni bolezni tipa 2.

Keywords:analiza diferencialnega genskega izražanja, beta celice, bioinformatika, diabetes tipa 2, obogatitev genskih setov, scRNA-seq, vpliv učinkov serij

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