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Genome Biol. 2015 Sep 11;16:167. doi: 10.1186/s13059-015-0716-z.

Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays.

Author information

1
Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. m.dellacqua@sssup.it.
2
The Jackson Laboratory, Bar Harbor, Maine, USA. dan.gatti@jax.com.
3
Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. giorgio.pea@gmail.com.
4
Current address: Thermo Fisher Scientific, Via G.B Tiepolo 18, 20900, Monza, MB, Italy. giorgio.pea@gmail.com.
5
Institute of Applied Genomics, Udine, Italy. fcattonaro@igatechnology.com.
6
Department of Plant Biotechnology and Bioinformatics, Ghent University, Gent, Belgium. frcop@psb.vib-ugent.be.
7
Institute of Applied Genomics, Udine, Italy. folegandros89@gmail.com.
8
Department of Agricultural and Environmental Sciences, University of Udine, Udine, Italy. folegandros89@gmail.com.
9
Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. ayelaelae@gmail.com.
10
Current address: Department of Agricultural Research, Nay Pyi Taw, Myanmar. ayelaelae@gmail.com.
11
Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. hthtaung@gmail.com.
12
Current address: Plant Biotechnology Center, Yangon, Myanmar. hthtaung@gmail.com.
13
Department of Plant Biotechnology and Bioinformatics, Ghent University, Gent, Belgium. hinel@psb.vib-ugent.be.
14
Department of Plant Systems Biology, VIB, Gent, Belgium. hinel@psb.vib-ugent.be.
15
Department of Plant Biotechnology and Bioinformatics, Ghent University, Gent, Belgium. jobau@psb.vib-ugent.be.
16
Department of Plant Systems Biology, VIB, Gent, Belgium. jobau@psb.vib-ugent.be.
17
Department of Agricultural Sciences, University of Bologna, Bologna, Italy. elisabetta.frascaroli@unibo.it.
18
The Jackson Laboratory, Bar Harbor, Maine, USA. gary.churchill@jax.org.
19
Department of Plant Biotechnology and Bioinformatics, Ghent University, Gent, Belgium. dirk.inze@psb.vib-ugent.be.
20
Department of Plant Systems Biology, VIB, Gent, Belgium. dirk.inze@psb.vib-ugent.be.
21
Institute of Applied Genomics, Udine, Italy. michele.morgante@uniud.it.
22
Department of Agricultural and Environmental Sciences, University of Udine, Udine, Italy. michele.morgante@uniud.it.
23
Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. marioenrico.pe@sssup.it.

Abstract

BACKGROUND:

Maize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize.

RESULTS:

We produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping.

CONCLUSIONS:

We demonstrate MAGIC maize's value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers.

PMID:
26357913
PMCID:
PMC4566846
DOI:
10.1186/s13059-015-0716-z
[Indexed for MEDLINE]
Free PMC Article

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