Browsing by Author "Yenisert, Ferhan"

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CilioGenics: an integrated method and database for predicting novel ciliary genes
(Oxford University Press, 2024) Pir, Mustafa Samet; Begar, Efe; Yenisert, Ferhan; Demirci, Hasan C.; Korkmaz, Mustafa E.; Karaman, Asli; Tsiropoulou, Sofia; Firat-Karalar, Elif Nur; Blacque, Oliver E.; Oner, Sukru S.; Doluca, Osman; Cevik, Sebiha; Kaplan, Oktay Ismail; 0000-0002-4645-7626; 0000-0002-0935-1929; 0000-0002-8733-0920; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Pir, Mustafa Samet; Yenisert, Ferhan; Demirci, Hasan C.; Korkmaz, Mustafa E.; Cevik, Sebiha; Kaplan, Oktay Ismail
Uncovering the full list of human ciliary genes holds enormous promise for the diagnosis of cilia-related human diseases, collectively known as ciliopathies. Currently, genetic diagnoses of many ciliopathies remain incomplete (1–3). While various independent approaches theoretically have the potential to reveal the entire list of ciliary genes, approximately 30% of the genes on the ciliary gene list still stand as ciliary candidates (4,5). These methods, however, have mainly relied on a single strategy to uncover ciliary candidate genes, making the categorization challenging due to variations in quality and distinct capabilities demonstrated by different methodologies. Here, we develop a method called CilioGenics that combines several methodologies (single-cell RNA sequencing, protein-protein interactions (PPIs), comparative genomics, transcription factor (TF) network analysis, and text mining) to predict the ciliary capacity of each human gene. Our combined approach provides a CilioGenics score for every human gene that represents the probability that it will become a ciliary gene. Compared to methods that rely on a single method, CilioGenics performs better in its capacity to predict ciliary genes. Our top 500 gene list includes 258 new ciliary candidates, with 31 validated experimentally by us and others. Users may explore the whole list of human genes and CilioGenics scores on the CilioGenics database (https://ciliogenics.com /).
Identifying Taxonomic Biomarkers of Colorectal Cancer in Human Intestinal Microbiota Using Multiple Feature Selection Methods
(Institute of Electrical and Electronics Engineers Inc., 2022) Jabeer, Amhar; Kocak, Aysegul; Akkas, Huseyin; Yenisert, Ferhan; Nalbantoglu, Ozkan Ufuk; Yousef, Malik; Bakir Gungor, Burcu; 0000-0002-6367-7823; 0000-0002-2272-6270; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Jabeer, Amhar; Kocak, Aysegul; Akkas, Huseyin; Yenisert, Ferhan; Bakir Gungor, Burcu
A variety of bacterial species called gut microbiota work together to maintain a steady intestinal environment. The gastrointestinal tract contains tremendous amount of different species including archaea, bacteria, fungi, and viruses. While these organisms are crucial immune system stabilizers, the dysbiosis of the intestinal flora has been related to gastrointestinal disorders including Colorectal cancer (CRC), intestinal cancer, irritable bowel syndrome and inflammatory bowel disease. In the last decade, next-generation sequencing (NGS) methods have accelerated the identification of human gut flora. CRC is a deathly condition that has been on the rise in the last century, affecting half a million people each year. Since early CRC diagnosis is critical for an effective treatment, there is an immediate requirement for a classification system that can expedite CRC diagnosis. In this study, via analyzing the available metagenomics data on CRC, we aim to facilitate the CRC diagnosis via finding biomarkers linked with CRC, and via building a classification model. We have obtained the metagenomic sequencing data of the healthy individuals and CRC patients from a metagenome-wide association analysis and we have classified this data according to the disease stages. Conditional Mutual Information Maximization (CMIM), Fast Correlation Based Filter (FCBF), Extreme Gradient Boosting (XGBoost), min redundancy max relevance (mRMR), Information Gain (IG) and Select K Best (SKB) feature selection algorithms were utilized to cope with the complexity of the features. We observed that the SKB, IG, and XGBoost techniques made significant contributions to decrease the microbiota in use for CRC diagnosis, thereby reducing cost and time. We realized that our Random Forest classifier outperformed Adaboost, Support Vector Machine, Decision Tree, Logitboost and stacking ensemble classifiers in terms of CRC classification performance. Our results reiterated some known and some potential microbiome associated mechanisms in CRC, which could aid the design of new diagnostics based on the microbiome.
WDR31 displays functional redundancy with GTPase-activating proteins (GAPs) ELMOD and RP2 in regulating IFT complex and recruiting the BBSome to cilium
(LIFE SCIENCE ALLIANCE LLC, 2023) Cevik, Sebiha; Peng, Xiaoyu; Beyer, Tina; Pir, Mustafa Samet; Yenisert, Ferhan; Woerz, Franziska; Hoffmann, Felix; Altunkaynak, Betul; Pir, Betul; Boldt, Karsten; Karaman, Asli; Cakiroglu, Miray; Oner, S. Sadik; Cao, Ying; Ueffing, Marius; Kaplan, Oktay İsmail; 0000-0002-0935-1929; 0000-0002-6302-8997; 0000-0002-4645-7626; 0000-0002-1028-8197; 0000-0002-2693-689X; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Cevik, Sebiha; Pir, Mustafa Samet; Yenisert, Ferhan; Altunkaynak, Betul; Pir, Betul; Kaplan, Oktay İsmail
The correct intraflagellar transport (IFT) assembly at the ciliary base and the IFT turnaround at the ciliary tip are key for the IFT to perform its function, but we still have poor understanding about how these processes are regulated. Here, we identify WDR31 as a new ciliary protein, and analysis from zebrafish and Caeno-rhabditis elegans reveals the role of WDR31 in regulating the cilia morphology. We find that loss of WDR-31 together with RP-2 and ELMD-1 (the sole ortholog ELMOD1-3) results in ciliary accumu-lations of IFT Complex B components and KIF17 kinesin, with fewer IFT/BBSome particles traveling along cilia in both anterograde and retrograde directions, suggesting that the IFT/BBSome entry into the cilia and exit from the cilia are impacted. Furthermore, anterograde IFT in the middle segment travels at increased speed in wdr-31;rpi-2;elmd-1. Remarkably, a non-ciliary protein leaks into the cilia of wdr-31;rpi-2;elmd-1, possibly because of IFT de-fects. This work reveals WDR31-RP-2-ELMD-1 as IFT and BBSome trafficking regulators.