Life is rarely simple. From crop yields to disease risks, the biological characteristics people care most about are usually those considered "complex traits." Just as for height--the textbook example of a complex trait--attributes like risk for a particular human disease are shaped by multiple genetic and environmental influences, making it challenging to find the genes involved. To track down such genes, geneticists typically mate two individuals that differ in key ways--for example, a large mouse and a small mouse--and then study their descendents, looking for genes that tend to be inherited with the trait value of interest. But this method only implicates a broad genomic region, and the identities of the crucial gene/s often remain a mystery.
Now, geneticists are embracing a powerful approach that pinpoints more precise areas of the genome by founding the breeding population with multiple, genetically diverse parents. To encourage innovations in this rapidly developing field, the Genetics Society of America journals GENETICS and G3: Genes|Genomes|Genetics today published the first articles in an ongoing special collection on mapping complex trait genes in multiparental populations.
The 18 articles describe methods and applications in a wide range of organisms, including mice, fruit flies, and maize. Among the advances reported are the creation of a multiparental population of wheat, methods for use with the Diversity Outbred and Collaborative Cross mouse populations, and the identification of nicotine resistance genes in fruit flies. The power of the approach for disease genetics is highlighted in an article describing how a multiparental rat population was used to find a human gene variant that affects insulin levels.
"These collections of multiparental strains are extremely powerful and greatly accelerate discovery. For example, in one of the articles, researchers report using a multiparental population to rapidly identify fruit fly genome regions associated with the toxicity of chemotherapy drugs. The authors could then examine these regions to find several candidate causative genes," said Dirk-Jan de Koning, Professor at the Swedish University of Agricultural Sciences, Deputy Editor-in-Chief, Complex Traits, at G3, and an editor of the new collection. "Using standard two-parent crosses, they would have been stuck with unmanageably large regions each containing hundreds or even thousands of candidate genes."
Because the field is so new, geneticists are still developing the best methods for creating and analyzing multiparental populations. "This collection will move the field forward by stimulating discussion between different disciplines and research communities," said Lauren McIntyre, Professor at the University of Florida, and an editor of the collection. "To help foster this ongoing exchange, the collection will continue to publish new articles, and all associated data will be freely available."
In an editorial, McIntyre and de Koning describe how the idea for the multiparental populations collection was born and how scientific society journals like GENETICS and G3 can advance new research fields.
The full collection can be found at http://genetics.
GENETICS and G3: Community-Driven Science, Community-Driven Journals
De Koning, Dirk-Jan and Lauren M. McIntyre. GENETICS September 2014, 198:1-2, doi: 10.1534/genetics.114.169151
Usefulness of Multiparental Populations of Maize (Zea mays L.) for Genome-Based Prediction
Lehermeier, Christina, Nicole Krämer, Eva Bauer, Cyril Bauland, Christian Camisan, Laura Campo, Pascal Flament, Albrecht E. Melchinger, Monica Menz, Nina Meyer, Laurence Moreau, Jesús Moreno-González, Milena Ouzunova, Hubert Pausch, Nicolas Ranc, Wolfgang Schipprack, Manfred Schönleben, Hildrun Walter,
Alain Charcosset, and Chris-Carolin Schön. GENETICS September 2014, 198:3-16, doi: 10.1534/genetics.114.161943
Identification of a Novel Gene for Diabetic Traits in Rats, Mice, and Humans
Tsaih, Shirng-Wern, Katie Holl, Shuang Jia, Mary Kaldunski, Michael Tschannen, Hong He, Jaime Wendt Andrae, Shun-Hua Li, Alex Stoddard, Andrew Wiederhold, John Parrington, Margarida Ruas da Silva, Antony Galione, James Meigs, Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) Investigators, Raymond G. Hoffmann, Pippa Simpson, Howard Jacob, Martin Hessner, and Leah C. Solberg Woods. GENETICS September 2014, 198:17-29, doi: 10.1534/genetics.114.162982
Using Drosophila melanogaster To Identify Chemotherapy Toxicity Genes
Fine-Mapping Nicotine Resistance Loci in Drosophila Using a Multiparent Advanced Generation Inter-Cross Population
RNA-Seq Alignment to Individualized Genomes Improves Transcript Abundance Estimates in Multiparent Populations
Munger, Steven C., Narayanan Raghupathy, Kwangbom Choi, Allen K. Simons, Daniel M. Gatti, Douglas A. Hinerfeld, Karen L. Svenson, Mark P. Keller,
Alan D. Attie, Matthew A. Hibbs, Joel H. Graber, Elissa J. Chesler, and Gary A. Churchill. GENETICS September 2014, 198:59-73, doi: 10.1534/genetics.114.165886
Rapid Identification of Major-Effect Genes Using the Collaborative Cross
A General Modeling Framework for Genome Ancestral Origins in Multiparental Populations
High-Resolution Genetic Mapping of Complex Traits from a Combined Analysis of F2 and Advanced InterCross Mice
Parker, Clarissa C., Peter Carbonetto, Greta Sokoloff, Yeonhee J. Park, Mark Abney, and Abraham A. Palmer. GENETICS September 2014, 198:103-116, doi: 10.1534/genetics.114.167056
Characterizing Uncertainty in High-Density Maps from Multiparental Populations
Multiple Quantitative Trait Analysis Using Bayesian Networks
Bayesian Modeling of Haplotype Effects in Multiparent Populations
Whole-Genome Analysis of Multienvironment or Multitrait QTL in MAGIC
Adult Plant Development in Triticale (× Triticosecale Wittmack) Is Controlled by Dynamic Genetic Patterns of Regulation
Tobias Würschum, Wenxin Liu, Katharina V. Alheit, Matthew R. Tucker, Manje Gowda, Elmar A. Weissmann, Volker Hahn, and Hans Peter Maurer. G3: Genes|Genomes|Genetics September 2014, 4:1585, doi:10.1534/10.1534/g3.113.012989
Multi-Parental Mapping of Plant Height and Flowering Time QTL in Partially Isogenic Sorghum Families
An Eight-Parent Multiparent Advanced Generation Inter-Cross Population for Winter-Sown Wheat: Creation, Properties, and Validation
Ian J. Mackay, Pauline Bansept-Basler, Toby Barber, Alison R. Bentley, James Cockram,
Nick Gosman, Andy J. Greenland, Richard Horsnell, Rhian Howells, Donal M. O'Sullivan,
Gemma A. Rose, and Phil J. Howell. G3: Genes|Genomes|Genetics September 2014, 4:1603, doi:10.1534/10.1534/g3.113.012963
The Genetic Architecture of Maize (Zea mays L.) Kernel Weight Determination
Santiago Alvarez Prado, César G. López, M. Lynn Senior, and Lucas Borrás. G3: Genes|Genomes|Genetics September 2014, 4:1611, doi:10.1534/10.1534/g3.113.013243
Quantitative Trait Locus Mapping Methods for Diversity Outbred Mice
Daniel M. Gatti, Karen L. Svenson, Andrey Shabalin, Long-Yang Wu, William Valdar, Petr Simecek, Neal Goodwin, Riyan Cheng, Daniel Pomp, Abraham Palmer, Elissa J. Chesler, Karl W. Broman, and Gary A. Churchill. G3: Genes|Genomes|Genetics September 2014, 4:1623, doi:10.1534/10.1534/g3.113.013748
About the Genetics Society of America (GSA)
Founded in 1931, the Genetics Society of America (GSA) is the professional scientific society for genetics researchers and educators. The Society's more than 5,000 members worldwide work to deepen our understanding of the living world by advancing the field of genetics, from the molecular to the population level. GSA promotes research and fosters communication through a number of GSA-sponsored conferences including regular meetings that focus on particular model organisms. GSA publishes two peer-reviewed, peer-edited scholarly journals: GENETICS, which has published high quality original research across the breadth of the field since 1916, and G3: Genes|Genomes|Genetics, an open-access journal launched in 2011 to disseminate high quality foundational research in genetics and genomics. The Society also has a deep commitment to education and fostering the next generation of scholars in the field. For more information about GSA, please visit http://www.