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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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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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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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Related Experiment Video

Updated: Mar 7, 2026

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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Ultra-long Read Sequencing for Whole Genomic DNA Analysis

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Meta-aligner: long-read alignment based on genome statistics.

Damoon Nashta-Ali1, Ali Aliyari1, Ahmad Ahmadian Moghadam2

  • 1Department of Electrical Engineering, Sharif University of Technology, Tehran, Azadi, Iran.

BMC Bioinformatics
|February 25, 2017
PubMed
Summary

Meta-aligner efficiently aligns long, noisy sequencing reads to reference genomes with high accuracy. This tool balances speed and precision, improving performance for PacBio long-reads and high error rates.

Keywords:
AlignmentGenome structureLong-read sequencingRepeat regions

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Sequencing technologies are producing longer, noisier reads.
  • Accurate read alignment is crucial for downstream genomic analysis.
  • Aligner speed impacts overall sequencing cost, creating an accuracy-speed tradeoff.

Purpose of the Study:

  • To develop an efficient and accurate long-read aligner.
  • To address the challenge of balancing accuracy and speed in read alignment.

Main Methods:

  • Introducing Meta-aligner, a novel read alignment tool.
  • Integrating existing short and long-read aligners as subcomponents.
  • Utilizing reference genome statistics and automatic read/genome statistics estimation.
  • Implementation in C++ for POSIX-like operating systems.

Main Results:

  • Meta-aligner demonstrates efficient and accurate alignment of long and very long reads.
  • Performance is enhanced by leveraging reference genome statistics.
  • Automatic estimation of read and genome statistics optimizes alignment.

Conclusions:

  • Meta-aligner achieves high recall and precision, particularly for long reads with high error rates.
  • Significant performance improvements are observed for PacBio long-reads compared to traditional methods.