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Related Concept Videos

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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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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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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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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.
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Related Experiment Video

Updated: Apr 23, 2026

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs
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ARYANA: Aligning Reads by Yet Another Approach.

Milad Gholami, Aryan Arbabi, Ali Sharifi-Zarchi

    BMC Bioinformatics
    |September 26, 2014
    PubMed
    Summary

    ARYANA is a new, fast gapped read aligner that significantly outperforms existing tools like Bowtie2 and BWA. Its novel seed-and-extend approach enhances speed and accuracy for next-generation sequencing data.

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Fast gapped sequence search remains a challenge despite numerous algorithms.
    • High demand for efficient read alignment in de novo assembly and genomic analysis.
    • Next-generation sequencing technologies necessitate faster and more accurate alignment tools.

    Purpose of the Study:

    • Introduce ARYANA, a novel, high-speed gapped read aligner.
    • Improve upon existing read alignment software in terms of speed and efficiency.
    • Provide a flexible algorithmic platform for developing specialized aligners.

    Main Methods:

    • Developed ARYANA using BWA indexing infrastructure with a new alignment engine.
    • Implemented a seed-and-extend algorithmic framework to replace time-consuming backtracking.

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  • Integrated novel techniques: dynamic seed selection, bidirectional seed extension, reset-free hash tables, and gap-filling dynamic programming.

    • Main Results:

    • ARYANA demonstrates significantly higher speed compared to Bowtie2, BWA, and SeqAlto.
    • Achieved comparable generality and accuracy to existing aligners.
    • Showcased superior performance in speed and alignment rate as read length increases.

    Conclusions:

    • ARYANA offers a substantial advancement in fast gapped read alignment.
    • Its efficiency scales well with increasing read lengths, aligning with sequencing technology trends.
    • The ARYANA engine provides a foundation for developing mission-specific aligners for diverse applications.