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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Nucleic Acid Structure01:25

Nucleic Acid Structure

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The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
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RNA-seq03:21

RNA-seq

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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. 
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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
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Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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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: Jun 4, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis
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ReAlign-N: an integrated realignment approach for multiple nucleic acid sequence alignment, combining global and

Yixiao Zhai1,2, Tong Zhou1,2, Yanming Wei2,3

  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, Pidu Zone, Chengdu 610054, China.

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ReAlign-N improves nucleic acid sequence alignment accuracy by integrating global and local strategies. This new method is faster and uses less memory than existing tools for large-scale analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate multiple sequence alignment (MSA) is critical for biological sequence analysis.
  • Existing tools struggle with evolutionary variations in nucleic acid sequences, necessitating realignment.
  • There is a lack of specialized realignment methods for long nucleic acid sequences.

Purpose of the Study:

  • To introduce ReAlign-N, a novel realignment method for multiple nucleic acid sequence alignment.
  • To enhance the accuracy and efficiency of nucleic acid sequence alignment.
  • To address the limitations of current tools in handling complex evolutionary relationships.

Main Methods:

  • ReAlign-N combines global and local realignment strategies.
  • Global realignment uses K-Band and memory-saving dynamic programming for efficiency.
  • Local realignment employs full matching and entropy scoring, with MAFFT for refinement.

Main Results:

  • ReAlign-N demonstrates superior performance over initial alignments on simulated and real datasets.
  • The method achieves higher accuracy in multiple nucleic acid sequence alignment.
  • ReAlign-N significantly reduces running times and memory usage compared to ReformAlign.

Conclusions:

  • ReAlign-N offers an effective solution for accurate multiple nucleic acid sequence realignment.
  • The tool is efficient and memory-saving, suitable for large-scale datasets.
  • ReAlign-N advances the field of bioinformatics by providing a specialized tool for nucleic acid sequence analysis.