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Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

Relationship estimation from whole-genome sequence data.

Hong Li¹, Gustavo Glusman¹, Hao Hu²

¹Institute for Systems Biology, Seattle, Washington, United States of America.

|February 6, 2014

Summary

This summary is machine-generated.

Whole-genome sequencing (WGS) offers improved genetic relationship detection but introduces challenges. A new method, ERSA 2.0, effectively identifies and masks problematic genomic regions, enhancing accuracy for detecting familial relationships.

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

Area of Science:

Genomics and Bioinformatics
Population Genetics

Background:

Identity-by-descent (IBD) from single-nucleotide polymorphism (SNP) data enhances genetic relationship detection.
Whole-genome sequencing (WGS) offers higher marker density for potentially improved IBD segment detection and boundary resolution.

Purpose of the Study:

To evaluate complexities of WGS data for genetic relationship detection.
To develop a method for accurately identifying and masking problematic genomic regions in WGS data.
To assess the performance of the new method in detecting familial relationships.

Main Methods:

Genetic relationships were estimated from WGS data for known pairwise relationships and population controls.
Three established IBD methods (GERMLINE, fastIBD, ISCA) were used to identify excess pairwise IBD.
A novel method was developed and implemented in ERSA 2.0 to identify and mask genomic regions with excess IBD.

Main Results:

Spurious IBD segments in WGS data led to a 10-fold increase in false-positive relationships compared to microarray data.
ERSA 2.0 successfully resolved inflated cryptic relationship detection rates and improved accuracy.
ERSA 2.0 detected all 1st-6th degree relationships and 55% of 9th-11th degree relationships.
WGS data with ERSA 2.0 provides a 5%-15% increase in relationship detection power for distant relationships.

Conclusions:

Genomic regions with excess IBD pose challenges for relationship detection using WGS data.
ERSA 2.0 is an effective software solution for accurate relationship detection from WGS data.
WGS data, when processed with ERSA 2.0, enhances the power to detect close and distant familial relationships.