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lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

Types of RNA

Types of RNA

Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in regulating gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA Performs Diverse...

Ribosomal RNA Synthesis

Ribosomal RNA Synthesis

Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
Ribosome biogenesis begins with the synthesis of 5S and 45S pre-rRNAs by distinct RNA polymerases. The primary transcripts are extensively processed and modified before they are bound and folded by ribosomal proteins and assembly factors,...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Related Experiment Video

Updated: Dec 31, 2025

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Published on: April 10, 2018

Machine Learning-Based Annotation of Long Noncoding RNAs Using PLncPRO.

Niraj K Khemka¹, Urminder Singh¹, Anuj K Dwivedi¹

¹School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.

Methods in Molecular Biology (Clifton, N.J.)

|January 2, 2020

Summary

This summary is machine-generated.

Identifying plant long noncoding RNAs (lncRNAs) is challenging. This study introduces PLncPRO, a machine learning tool using random forests for accurate lncRNA identification and annotation in plants.

Keywords:

Machine learning Noncoding RNA PLncPRO RNA-seq lncRNA

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Last Updated: Dec 31, 2025

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Published on: April 10, 2018

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

Chromatin Isolation by RNA Purification ChIRP

Chromatin Isolation by RNA Purification ChIRP

Published on: March 25, 2012

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Long noncoding RNAs (lncRNAs) are crucial regulators in diverse biological processes across species.
Accurate identification of lncRNAs is essential for understanding their biological significance.
Distinguishing lncRNAs from coding transcripts remains a significant challenge in bioinformatics.

Purpose of the Study:

To develop and present a machine learning-based approach for accurate identification of plant long noncoding RNAs.
To introduce the PLncPRO tool for lncRNA prediction in plant transcript sequences.

Main Methods:

Utilized a machine learning-based random forest algorithm.
Developed the plant long noncoding RNA prediction by random forests (PLncPRO) tool.
Provided stepwise instructions for using PLncPRO to annotate lncRNA sequences.

Main Results:

Successfully developed a machine learning approach for plant lncRNA identification.
Demonstrated the utility of PLncPRO in recognizing lncRNAs from transcript sequences.
Provided a practical tool with clear instructions for researchers.

Conclusions:

Machine learning, specifically the random forest algorithm, offers an effective solution for plant lncRNA identification.
PLncPRO is a valuable tool for accurate lncRNA annotation in plant genomics research.
Accurate lncRNA identification is achievable and crucial for advancing plant biology.