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RNA-seq03:21

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 microarray-based...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Genome Annotation and Assembly03:36

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.
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.

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Related Experiment Video

Updated: May 11, 2026

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
12:33

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Published on: July 28, 2017

On contigs and coverage.

Franco P Preparata1

  • 1Computer Science Department, Brown University, Providence, RI 02912, USA. franco@cs.brown.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|May 17, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new Markov automaton model to determine the minimum genomic coverage needed for complete DNA assembly. It also analyzes how variable fragment lengths impact assembly contiguity.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The Lander-Waterman statistics is a foundational model for understanding genomic shotgun assembly.
  • Determining adequate coverage is crucial for achieving a complete and contiguous genome sequence.
  • Previous models often assume fixed-length fragments, which may not reflect biological reality.

Purpose of the Study:

  • To revisit the classic genomic coverage problem using a novel mathematical framework.
  • To evaluate the minimum coverage required for uninterrupted genome assembly (a single contig) with high confidence.
  • To analyze the impact of variable fragment length distributions on assembly outcomes.

Main Methods:

  • Development of a novel formulation based on the analysis of an autonomous Markov automaton.
  • Application of the Markov automaton to model the genomic shotgun assembly process.
  • Derivation of statistical evaluations for coverage requirements and fragment length effects.

Main Results:

  • An evaluation of the minimum multiplicity (coverage) needed to achieve uninterrupted covering with a specified confidence level.
  • A detailed analysis of how arbitrary distributions of fragment lengths affect assembly compared to fixed-length fragments.
  • Quantification of the relationship between coverage, fragment length variability, and contiguity.

Conclusions:

  • The novel Markov automaton approach provides a more nuanced understanding of genomic coverage.
  • Variable fragment lengths significantly influence the coverage required for successful genome assembly.
  • This work offers improved statistical insights for optimizing shotgun sequencing strategies.