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      Reciprocal Genetics: Identifying QTL for General and Specific Combining Abilities in Hybrids Between Multiparental Populations from Two Maize ( Zea mays L.) Heterotic Groups

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          Abstract

          Several plant and animal species of agricultural importance are commercialized as hybrids to take advantage of the heterosis phenomenon. Understanding the genetic architecture of hybrid performances is therefore of key importance. We developed two multiparental maize ( Zea mays L.) populations, each corresponding to an important heterotic group (dent or flint) and comprised of six connected biparental segregating populations of inbred lines (802 and 822 lines for each group, respectively) issued from four founder lines. Instead of using “testers” to evaluate their hybrid values, segregating lines were crossed according to an incomplete factorial design to produce 951 dent–flint hybrids, evaluated for four biomass production traits in eight environments. QTL detection was carried out for the general-combining-ability (GCA) and specific-combining-ability (SCA) components of hybrid value, considering allelic effects transmitted from each founder line. In total, 42 QTL were detected across traits. We detected mostly QTL affecting GCA, 31% (41% for dry matter yield) of which also had mild effects on SCA. The small impact of dominant effects is consistent with the known differentiation between the dent and flint heterotic groups and the small percentage of hybrid variance due to SCA observed in our design (∼20% for the different traits). Furthermore, most (80%) of GCA QTL were segregating in only one of the two heterotic groups. Relative to tester-based designs, use of hybrids between two multiparental populations appears highly cost efficient to detect QTL in two heterotic groups simultaneously. This presents new prospects for selecting superior hybrid combinations with markers.

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          A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome

          SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations – IBM (B73×Mo17) and LHRF (F2×F252) – were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.
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            Domestication and Breeding of Tomatoes: What have We Gained and What Can We Gain in the Future?

            Background It has been shown that a large variation is present and exploitable from wild Solanum species but most of it is still untapped. Considering the thousands of Solanum accessions in different gene banks and probably even more that are still untouched in the Andes, it is a challenge to exploit the diversity of tomato. What have we gained from tomato domestication and breeding and what can we gain in the future? Scope This review summarizes progress on tomato domestication and breeding and current efforts in tomato genome research. Also, it points out potential challenges in exploiting tomato biodiversity and depicts future perspectives in tomato breeding with the emerging knowledge from tomato-omics. Conclusions From first domestication to modern breeding, the tomato has been continually subjected to human selection for a wide array of applications in both science and commerce. Current efforts in tomato breeding are focused on discovering and exploiting genes for the most important traits in tomato germplasm. In the future, breeders will design cultivars by a process named ‘breeding by design’ based on the combination of science and technologies from the genomic era as well as their practical skills.
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              The Composition of a Field of Maize

              G H Shull (1908)
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                Author and article information

                Journal
                Genetics
                Genetics
                genetics
                genetics
                genetics
                Genetics
                Genetics Society of America
                0016-6731
                1943-2631
                November 2017
                25 October 2017
                25 October 2017
                : 207
                : 3
                : 1167-1180
                Affiliations
                [* ]Génétique Quantitative et Evolution—Le Moulon, Institut National de la Recherche Agronomique, Université Paris–Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris–Saclay, F-91190 Gif-sur-Yvette, France
                []Unité Expérimentale 0394 SMH Maïs, Institut National de la Recherche Agronomique, F-40390 Saint-Martin-de-Hinx, France
                []Maïsadour Semences S.A., F-40001 Mont-de-Marsan, France
                [§ ]Euralis Semences, F-31700 Mondonville, France
                Author notes
                [1]

                Present address: Bayer CropScience N.V., B-9052 Ghent, Belgium.

                [2 ]Corresponding author: Génétique Quantitative et Evolution—Le Moulon, Ferme du Moulon, F-91190 Gif-sur-Yvette, France. E-mail: laurence.moreau@ 123456inra.fr
                Article
                300305
                10.1534/genetics.117.300305
                5669627
                28971957
                438d9347-d756-44fe-b02e-49b795915e91
                Copyright © 2017 by the Genetics Society of America

                Available freely online through the author-supported open access option.

                History
                : 05 January 2017
                : 04 September 2017
                Page count
                Figures: 3, Tables: 4, Equations: 4, References: 57, Pages: 14
                Categories
                Investigations
                Multiparental Populations
                Custom metadata
                highlight-article

                Genetics
                hybrids,qtl detection,additivity,dominance,silage maize,multiparental populations,mpp
                Genetics
                hybrids, qtl detection, additivity, dominance, silage maize, multiparental populations, mpp

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