• Molecules and Cells
• /
• v.46 no.1
• /
• pp.21-32
• /
• 2023

MicroRNAs (miRNAs) play cardinal roles in regulating biological pathways and processes, resulting in significant physiological effects. To understand the complex regulatory network of miRNAs, previous studies have utilized massivescale datasets of miRNA targeting and attempted to computationally predict the functional targets of miRNAs. Many miRNA target prediction tools have been developed and are widely used by scientists from various fields of biology and medicine. Most of these tools consider seed pairing between miRNAs and their mRNA targets and additionally consider other determinants to improve prediction accuracy. However, these tools exhibit limited prediction accuracy and high false positive rates. The utilization of additional determinants, such as RNA modifications and RNA-binding protein binding sites, may further improve miRNA target prediction. In this review, we discuss the determinants of functional miRNA targeting that are currently used in miRNA target prediction and the potentially predictive but unappreciated determinants that may improve prediction accuracy.

• Genomics & Informatics
• /
• v.3 no.3
• /
• pp.53-62
• /
• 2005

MicroRNAs play an important role in regulating gene expression, but their target identification is a difficult task due to their short length and imperfect complementarity. Burge and coworkers developed a program called TargetScan that allowed imperfect complementarity and established a procedure favoring targets with multiple binding sites conserved in multiple organisms. We improved their algorithm in two major aspects - (i) using well-defined UTR (untranslated region) database, (ii) examining the extent of conservation inside the 3' UTR specifically. Average length in our UTR database, based on the ECgene annotation, is more than twice longer than the Ensembl. Then, TargetScan was used to identify putative binding sites. The extent of conservation varies significantly inside the 3' UTR. We used the 'tight' tracks in the UCSC genome browser to select the conserved binding sites in multiple species. By combining the longer 3' UTR data, TargetScan, and tightly conserved blocks of genomic DNA, we identified 107 putative target genes with multiple binding sites conserved in multiple species, of which 85 putative targets are novel.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.286-288
• /
• 2005

MicroRNA (miRNA)는 작은 크기의 RNA분자로서 동식물의 유전자 발현 과점을 직접적으로 조절하는 인자로 알려져 있다. MiRNA는 보통 목표 유전자의 3'-UTR 영역에 상보성을 갖고 결합함으로써 작용하며 특히 miRNA의 5'부분의 8 nt 정도가 seed로서 중요하다고 알려져 있다. 반면 최근의 연구에 따르면 seed 부분의 서열의 조성 및 양상이 변화함에 따라 특이도가 결정됨을 알 수 있지만 기존의 컴퓨터를 이용한 miRNA 목표 유전자 예측 방법들은 이러한 정보를 활용하지 못한다. 본 논문에서는 열역학적인 수치와 서열의 조성뿐 아니라 miRNA:mRNA pair의 위치에 기반한 정보들을 학습에 자질로서 포함하여 목표 유전자를 예측한다. 그 결과는 위치 기반 자질이 학습 성능 향상에 중요하게 기여함을 보여준다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.212-216
• /
• 2008

기존의 알려진 데이터에 기반하여 분류 알고리즘을 통해 새로운 생물학적인 사실을 예측하는 것은 생물학 연구에 매우 유용하다. 하지만 생물학 데이터 분류 문제에서 positive 데이터만 존재할 뿐, negative 데이터는 존재하지 않는 경우가 많다. 이와 같은 상황에서는 많은 경우에 임의로 negative data를 구성하여 사용하게 된다. 하지만, negative 데이터는 실제로 negative임이 보장된 것이 아니고, 임의로 생성된 데이터의 특성에 따라 분류 성능 및 모델의 특성에 많은 차이를 보일 수 있다. 따라서 본 논문에서는 단일 클래스 분류 알고리즘 중 하나인 support vector data description(SVDD) 방법을 이용하여 실제 microRNA target 예측 문제에서 positive 데이터만을 이용하여 학습하고 분류를 수행하였다. 이를 통해 일반적인 이진 분류 방법에 비해 이와 같은 방법이 실제 생물학 문제에 보다 적합하게 적용될 수 있음을 확인한다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11b
• /
• pp.259-261
• /
• 2005

분류 방법으로서의 SVM(Support Vector Machine)은 커널 방법과 함께 사용됨으로써 그 유용성을 크게 향상시켰다. 커널 방법은 일반적으로 입력 데이터의 자질(feature)로 나타내는 공간으로부터 높은 차원의 공간으로 데이터를 사상(mapping)시키는 역할을 하게 되나, 기본적으로는 데이터간에 새로운 거리(metric)를 부설해주는 역할을 하는 것이다. 지금까지 나온 다양한 커널 방법은 구조화된(structured) 데이터에 대해 커널 형태로 거리를 부여하는 방법을 제시한다. 본 논문에서는 DNA의 작용을 모델링하여 만든 새로운 커널이 miRNA(micro RNA)와 mRNA(messenger RNA)쌍에 대한 발현 여부를 분류해 내기 위해 커널 형식으로 거리를 부여하는 방법을 보인다. 이 방법은 실리콘 컴퓨터가 아닌 실제 DNA분자로 실험할 수 있도록 설계된 것을 고려할 때 여러 종류의 DNA 코드를 분석하는 데 사용될 수 있는 새로운 분자컴퓨팅 방법이다.

• Genomics & Informatics
• /
• v.3 no.1
• /
• pp.15-23
• /
• 2005

Background MicroRNAs (miRNAs) are a class of noncoding RNAs found in various organisms such as plants and mammals. However, most of the mRNAs regulated by miRNAs are unknown. Furthermore, miRNA targets in genomes cannot be identified by standard sequence comparison since their complementarity to the target sequence is imperfect in general. In this paper, we propose a kernel-based method for the efficient prediction of miRNA targets. To help in distinguishing the false positives from potentially valid targets, we elucidate the features common in experimentally confirmed targets. Results The performance of our prediction method was evaluated by five-fold cross-validation. Our method showed 0.64 and 0.98 in sensitivity and in specificity, respectively. Also, the proposed method reduced the number of false positives by half compared with TargetScan. We investigated the effect of feature sets on the classification of miRNA targets. Finally, we predicted miRNA targets for several miRNAs in the Caenorhabditis elegans (C. elegans) 3' untranslated region (3' UTR) database. Condusions The targets predicted by the suggested method will help in validating more miRNA targets and ultimately in revealing the role of small RNAs in the regulation of genomes. Our algorithm for miRNA target site detection will be able to be improved by additional experimental­knowledge. Also, the increase of the number of confirmed targets is expected to reveal general structural features that can be used to improve their detection.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.4
• /
• pp.1675-1679
• /
• 2014

Objectives: MicroRNAs (miRNAs) are important regulators of many physiological and pathological processes, including tumorigenesis and metastasis. In this study, we sought to determine the underlying molecular mechanisms of metastatic cervical carcinoma by performing miRNA profiling. Methods: Tissue samples were collected from ten cervical squamous cancer patients who underwent hysterectomy and pelvic lymph node (PLN) dissection in our hospital, including four PLN-positive (metastatic) cases and six PLN-negative (non-metastatic) cases. A miRNA microarray platform with 1223 probes was used to determine the miRNA expression profiles of these two tissue types and case groups. MiRNAs having at least 4-fold differential expression between PLN-positive and PLN-negative cervical cancer tissues were bioinformatically analyzed for target gene prediction. MiRNAs with tumor-associated target genes were validated by quantitative reverse transcription-polymerase chain reaction (RT-PCR). Results: Thirty-nine miRNAs were differentially expressed (>4-fold) between the PLN-positive and PLN-negative groups, of which, 22 were up-regulated and 17 were down-regulated. Sixty-nine percent of the miRNAs (27/39) had tumor-associated target genes, and the expression levels of six of those (miR-126, miR-96, miR-144, miR-657, miR-490-5p, and miR-323-3p) were confirmed by quantitative (q)RT-PCR. Conclusions: Six MiRNAs with predicted tumor-associated target genes encoding proteins that are known to be involved in cell adhesion, cytoskeletal remodeling, cell proliferation, cell migration, and apoptosis were identified. These findings suggest that a panel of miRNAs may regulate multiple and various steps of the metastasis cascade by targeting metastasis-associated genes. Since these six miRNAs are predicted to target tumor-associated genes, it is likely that they contribute to the metastatic potential of cervical cancer and may aid in prognosis or molecular therapy.

• Clinical and Experimental Reproductive Medicine
• /
• v.47 no.1
• /
• pp.42-53
• /
• 2020

Objective: Recently, microRNA (miRNA) has been identified both as a powerful regulator involved in various biological processes through the regulation of numerous genes and as an effective biomarker for the prediction and diagnosis of various disease states. The objective of this study was to identify and validate miRNAs and their target genes involved in inflammation in placental tissue. Methods: Microarrays were utilized to obtain miRNA and gene expression profiles from placentas with or without inflammation obtained from nine normal pregnant women and 10 preterm labor patients. Quantitative real-time polymerase chain reaction and Western blots were performed to validate the miRNAs and differentially-expressed genes in the placentas with inflammation. Correlations between miRNA and target gene expression were confirmed by luciferase assays in HTR-8/SVneo cells. Results: We identified and validated miRNAs and their target genes that were differentially expressed in placentas with inflammation. We also demonstrated that several miRNAs (miR-371a-5p, miR-3065-3p, miR-519b-3p, and miR-373-3p) directly targeted their target genes (LEF1, LOX, ITGB4, and CD44). However, some miRNAs and their direct target genes showed no correlation in tissue samples. Interestingly, miR-373-3p and miR-3065-3p were markedly regulated by lipopolysaccharide (LPS) treatment, although the expression of their direct targets CD44 and LOX was not altered by LPS treatment. Conclusion: These results provide candidate miRNAs and their target genes that could be used as placental biomarkers of inflammation. These candidates may be useful for further miRNA-based biomarker development.

• Molecules and Cells
• /
• v.37 no.5
• /
• pp.412-417
• /
• 2014

It has been reported that exogenously introduced micro-RNA (exo-miRNA) competes with endogenously expressed miRNAs (endo-miRNAs) in human cells, resulting in a detectable upregulation of mRNAs with endo-miRNA target sites (TSs). However, the detailed mechanisms of the competition between exo- and endo-miRNAs remain uninvestigated. In this study, using 74 microarrays that monitored the whole-transcriptome response after introducing miRNAs or siRNAs into HeLa cells, we systematically examined the derepression of mRNAs with exo- and/or endo-miRNA TSs. We quantitatively assessed the effect of the number of endo-miRNA TSs on the degree of mRNA derepression. As a result, we observed that the number of endo-miRNA TSs was significantly associated with the degree of derepression, supporting that the derepression resulted from the competition between exo- and endo-miRNAs. However, when we examined whether the site proficiency of exo-miRNA TSs could also influence mRNA derepression, to our surprise, we discovered a strong positive correlation. Our analysis indicates that site proficiencies of both exo- and endo-miRNA TSs are important determinants for the degree of mRNA derepression, implying that the derepression of mRNAs in response to exo-miRNA is more complex than that currently perceived. Our observations may lead to a more complete understanding of the detailed mechanisms of the competition between exo- and endo-miRNAs and to a more accurate prediction of miRNA targets. Our analysis also suggests an interesting hypothesis that long 3'-UTRs may function as molecular buffer against gene expression regulation by individual miRNAs.

• Asian-Australasian Journal of Animal Sciences
• /
• v.26 no.3
• /
• pp.309-315
• /
• 2013

MicroRNAs are a class of endogenous small RNAs that play important roles in post-transcriptional gene regulation by directing degradation of mRNAs or facilitating repression of target gene translation. In this study, three small RNA cDNA libraries from the mammary gland tissues of Laoshan dairy goats (Capra hircus) were constructed and sequenced, individually. Through Solexa high-throughput sequencing and bioinformatics analysis, we obtained 50 presumptive novel miRNAs candidates, and 55,448 putative target genes were predicted. GO annotations and KEGG pathway analyses showed the majority of target genes were involved in various biological processes and metabolic pathways. Our results discovered more information about the regulation network between miRNAs and mRNAs and paved a foundation for the molecular genetics of mammary gland development in goats.