Identification of DEP domain-containing proteins by a machine learning method and experimental analysis of their expression in human HCC tissues

Abstract

The Dishevelled/EGL-10/Pleckstrin (DEP) domain-containing (DEPDC) proteins have seven members. However, whether this superfamily can be distinguished from other proteins based only on the amino acid sequences, remains unknown. Here, we describe a computational method to segregate DEPDCs and non-DEPDCs. First, we examined the Pfam numbers of the known DEPDCs and used the longest sequences for each Pfam to construct a phylogenetic tree. Subsequently, we extracted 188-dimensional (188D) and 20D features of DEPDCs and non-DEPDCs and classified them with random forest classifier. We also mined the motifs of human DEPDCs to find the related domains. Finally, we designed experimental verification methods of human DEPDC expression at the mRNA level in hepatocellular carcinoma (HCC) and adjacent normal tissues. The phylogenetic analysis showed that the DEPDCs superfamily can be divided into three clusters. Moreover, the 188D and 20D features can both be used to effectively distinguish the two protein types. Motif analysis revealed that the DEP and RhoGAP domain was common in human DEPDCs, human HCC and the adjacent tissues that widely expressed DEPDCs. However, their regulation was not identical. In conclusion, we successfully constructed a binary classifier for DEPDCs and experimentally verified their expression in human HCC tissues.

MiR-93-5p Promotes Cell Proliferation through Down-Regulating PPARGC1A in Hepatocellular Carcinoma Cells by Bioinformatics Analysis and Experimental Verification

“…Moreover, Charos et al utilized ChIP-seq to obtain PPARGC1A binding sites across the genome in hepatoma cells HepG2 [ 10 ]. Conserved motif analysis [ 39 , 40 , 41 ] showed that the majority of PPARGC1A binding sites are located in multiple regulatory factor binding regions including RNAPII. Additionally, these regions are frequently located at the promoter of target genes, such as genes CEBPB [ 42 ].…”

Predicting Amyloidogenic Proteins in the Proteomes of Plants

“…Identification of novel amyloid proteins is laborious and time-consuming, but bioinformatic predictions in combination with recently developed proteomic approaches [ 72 , 73 , 74 , 75 ] are useful in this regard. In addition, future development of novel, more efficient bioinformatic algorithms based on the machine learning, which is actively using now for protein analysis [ 76 , 77 ], could also contribute to the progress in the proteomics of amyloids.…”

Construction and Investigation of a circRNA-Associated ceRNA Regulatory Network in Tetralogy of Fallot

“…Total RNA content was extracted from the tissues by using Trizol Reagent (Invitrogen, CA, USA) and reversely transcribed into cDNA by using the PrimeScript RT reagent Kit (TaKaRa, Tokyo, Japan) according to manufacturer's instructions. The relative expression levels of mRNA (normalized to β-actin) was analyzed by the 2 −ΔΔCt relative quanti cation method, the relative circRNA expression was calculated with the 2 −ΔCt method [19]. QPCR were performed using SYBE Green qPCR kit (TOYOBO, Tokyo, Japan) in the StepOne PCR system (Applied Biosystems).…”