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Updated: May 17, 2025

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

Published on: August 12, 2019

Mapping-based genome size estimation.

Shakunthala Natarajan^1,2, Jessica Gehrke¹, Boas Pucker^3,4

¹Plant Biotechnology and Bioinformatics, Institute of Plant Biology & BRICS, TU Braunschweig, Mendelssohnstrasse 4, 38106, Braunschweig, Germany.

|May 14, 2025

Summary

This summary is machine-generated.

Accurately estimating genome size is difficult. This study introduces Mapping-based Genome Size Estimation (MGSE), a novel method using high contiguity assemblies and read mappings for precise genome size determination across diverse species.

Keywords:

Genome size Long read sequencing Long reads Nanopore sequencing Next generation sequencing Read mapping Short reads

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Area of Science:

Genomics
Bioinformatics

Background:

Accurate genome size measurement is crucial for genetic and evolutionary studies.
Current methods like biochemical assays and k-mer analysis provide only estimations, lacking precision.
High contiguity genome assemblies are essential for accurate genomic analyses.

Purpose of the Study:

To present a novel, accurate method for estimating genome size using high contiguity assemblies and read mappings.
To demonstrate the broad applicability and utility of this new approach across various plant and non-plant species.
To provide accessible tools for the scientific community to perform genome size estimations.

Main Methods:

Developed and implemented Mapping-based Genome Size Estimation (MGSE), a computational approach.
Utilized high contiguity genome assemblies and read mapping data for size prediction.
Validated the method on diverse datasets including Arabidopsis thaliana, Beta vulgaris, Oryza sativa, Brachypodium distachyon, Solanum lycopersicum, Vitis vinifera, Zea mays, Escherichia coli, Saccharomyces cerevisiae, and Caenorhabditis elegans.

Main Results:

MGSE accurately estimates genome sizes using either short or long reads with a minimum 5-fold coverage.
The method's effectiveness was demonstrated across a wide range of plant and model organism genomes.
Comparative analyses showed MGSE's advantage over traditional estimation techniques.

Conclusions:

Mapping-based Genome Size Estimation (MGSE) offers a robust and accurate alternative for determining genome sizes.
The MGSE approach is broadly applicable, extending beyond plant genomics to other eukaryotic and prokaryotic organisms.
Open-source availability of MGSE and associated scripts facilitates wider adoption and research in genomics.