Genome Assembly Pipeline
Genome Assembly Pipeline - Related Videos
03:36
Genome Annotation and Assembly
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2021
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.
08:31
Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
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Cited by 2 •
2013
Single Virus Genomics (SVG) is a method to isolate and amplify the genomes of single virons. Viral suspensions of a mixed assemblage are sorted using flow cytometry onto a microscope slide with discrete wells containing agarose, thereby capturing the virion and reducing genome shearing during downstream processing. Whole genome amplification is achieved using multiple displacement amplification (MDA) resulting in genomic material that is suitable for sequencing.
06:02
A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
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2025
This protocol provides a streamlined computational pipeline for quantifying nascent enhancer transcripts. By integrating chromatin accessibility, chromatin feature, and transcriptional data, it enables accurate detection and strand-specific analysis of enhancer activity in complex intragenic regions, while remaining accessible to researchers without extensive bioinformatics training.
08:37
A Rapid and Facile Pipeline for Generating Genomic Point Mutants in C. elegans Using CRISPR/Cas9 Ribonucleoproteins
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Cited by 1 •
2018
Here, we present a method to engineer the genome of C. elegans using CRISPR-Cas9 ribonucleoproteins and homology dependent repair templates.
12:04
Mouse Genome Engineering Using Designer Nucleases
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Cited by 14 •
2014
Designer nucleases such as zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) can be used to modify the genome of mouse preimplantation embryos by triggering both the nonhomologous end joining (NHEJ) and homologous recombination (HR) pathways. These advances enable the rapid generation of mice with precise genetic modifications.
FAQs
Read quality control and error correction protect the reconstruction from unreliable sequence evidence. Quality control identifies problematic reads before assembly, while correction reduces sequencing errors that could create false overlaps or incorrect k-mers. These steps improve the consistency of downstream joining, so the resulting contigs and scaffolds provide a more dependable basis for identifying genes and detecting variants.
Overlap-based reconstruction joins reads by recognizing directly shared sequence regions. Graph-based approaches can instead use shared k-mers, which are short sequence words found within multiple reads, to represent relationships among fragments. The selected strategy affects how sequence evidence is organized into contigs and scaffolds, making algorithm choice an important part of assembly performance.
Read accuracy, sequencing coverage, repeat content, and algorithm selection are major influences on assembly quality. Low read accuracy can introduce errors, insufficient coverage can limit reconstruction, and repeated regions can complicate joining fragments. Because these factors interact with computational choices, standardized pipelines help produce results that are more consistent and suitable for genetic interpretation.
A typical workflow begins with read quality control and error correction, followed by alignment or graph-based reconstruction. Overlapping sequences or shared k-mers are then used to join fragments into contigs and scaffolds. A polishing stage reduces remaining errors. Keeping these stages organized allows researchers to evaluate how each computational decision contributes to the final assembly.
Contigs and scaffolds represent successive assembly products formed after sequence fragments are joined. They provide the reconstructed sequence framework used for later genetic analysis, while polishing addresses errors that remain after reconstruction. This final refinement matters because unresolved sequence inaccuracies can affect confidence in gene identification, variant detection, and other conclusions drawn from the assembled genome.
In genetics, assembled genomes provide a reference framework for identifying genes, detecting variants, comparing genomes, and studying genome structure. These applications depend on the reliability of the assembly, because errors or incomplete reconstruction can influence biological conclusions. A carefully designed pipeline therefore connects computational processing with downstream questions about inheritance, genome organization, and genetic differences.