The Genetic Architecture of Maize Flowering Time

Buckler, Edward S.; Holland, James B.; Bradbury, Peter J.; Acharya, Charlotte B.; Brown, Patrick J.; Browne, Chris; Ersoz, Elhan S.; Flint-García, Sherry; Garcia, A. R.; Glaubitz, Jeffrey C.; Goodman, M. M.; Harjes, Carlos; Guill, Kate; Kroon, Dallas E.; Larsson, Sara; Lepak, Nicholas; Li, Huihui; Mitchell, Sharon E.; Pressoir, Gaël; Peiffer, Jason A.; Rosas, Marco Oropeza; Rocheford, Torbert; Romay, M. Cinta; Romero, Susan; Salvo, Stella; Villeda, Hector Sanchez; Silva, H. Sofia da; Sun, Qi; Tian, Feng; Upadyayula, Narasimham; Ware, Doreen; Yates, Heather E.; Yu, Jianming; Zhang, Zhiwu; Kresovich, Stephen; McMullen, Michael D.

doi:10.1126/science.1174276

Cited by 1,277 publications

(1,321 citation statements)

References 29 publications

(23 reference statements)

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“…Nested association mapping ( NAM ) and BC 1 represent the previous two studies by Buckler et al . (2009) and Briggs et al . (2007), respectively.…”

Section: Discussionmentioning

confidence: 95%

“…In each trial, the 866 BC 2 S 3 RILs were grown in a single replicate employing an augmented incomplete randomized blocks design widely used to phenotype large populations (Buckler et al ., 2009; Kump et al ., 2011; Tian et al ., 2011; Huang et al ., 2015). Two maize inbred lines W22 and Mo17 were randomly inserted in each incomplete block as checks.…”

Section: Methodsmentioning

confidence: 99%

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The genetic architecture of leaf number and its genetic relationship to flowering time in maize

Wang

Zhang

et al. 2015

New Phytologist

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Summary The number of leaves and their distributions on plants are critical factors determining plant architecture in maize (Zea mays), and leaf number is frequently used as a measure of flowering time, a trait that is key to local environmental adaptation.Here, using a large set of 866 maize‐teosinte BC 2S3 recombinant inbred lines genotyped by using 19 838 single nucleotide polymorphism markers, we conducted a comprehensive genetic dissection to assess the genetic architecture of leaf number and its genetic relationship to flowering time.We demonstrated that the two components of total leaf number, the number of leaves above (LA) and below (LB) the primary ear, were under relatively independent genetic control and might be subject to differential directional selection during maize domestication and improvement. Furthermore, we revealed that flowering time and leaf number are commonly regulated at a moderate level. The pleiotropy of the genes ZCN8, dlf1 and ZmCCT on leaf number and flowering time were validated by near‐isogenic line analysis. Through fine mapping, qLA1‐1, a major‐effect locus that specifically affects LA, was delimited to a region with severe recombination suppression derived from teosinte.This study provides important insights into the genetic basis of traits affecting plant architecture and adaptation. The genetic independence of LA from LB enables the optimization of leaf number for ideal plant architecture breeding in maize.

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“…Nested association mapping ( NAM ) and BC 1 represent the previous two studies by Buckler et al . (2009) and Briggs et al . (2007), respectively.…”

Section: Discussionmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

The genetic architecture of leaf number and its genetic relationship to flowering time in maize

Wang

Zhang

et al. 2015

New Phytologist

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“…For instance, Monsanto's breeding program uses a subset of >50 different QTLs that exist for each of the characteristics of days to silking, days to anthesis, and grain oil content (Laurie et al, 2004;Buckler et al, 2009). Additionally, there are >100 QTLs associated with the development of root architecture in maize (Zurek et al, 2015), and breeding companies screen for a targeted subset of them within their breeding pipeline.…”

Section: Technologies Used To Expedite the Breeding Processmentioning

confidence: 99%

Bringing New Plant Varieties to Market: Plant Breeding and Selection Practices Advance Beneficial Characteristics while Minimizing Unintended Changes

et al. 2017

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Commercial‐scale plant breeding is a complex process in which new crop varieties are continuously being developed to improve yield and agronomic performance over current varieties. A wide array of naturally occurring genetic changes are sources of new characteristics available to plant breeders. During conventional plant breeding, genetic material is exchanged that has the potential to beneficially or adversely affect plant characteristics. For this reason, commercial‐scale breeders have implemented extensive plant selection practices to identify the top‐performing candidates with the desired characteristics while minimizing the advancement of unintended changes. Selection practices in maize (Zea mays L.) breeding involve phenotypic assessments of thousands of candidate lines throughout hundreds of different environmental conditions over many years. Desirable characteristics can also be introduced through genetic modification. For genetically modified (GM) crops, molecular analysis is used to select transformed plants with a single copy of an intact DNA insert and without disruption of endogenous genes. All the while, GM crops go through the same extensive phenotypic characterization as conventionally bred crops. Data from both conventional and GM maize breeding programs are presented to show the similarities between these two processes.

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“…Association studies have been carried out with some success for major crops (Buckler et al, 2009) and tree geneticists have also focussed their more recent efforts on association studies in large populations with low linkage disequilibrium (LD), aiming to overcome weaknesses in QTL analyses (Burdon and Wilcox, 2011). Promising results have been reported for various traits in several species (see, for example, González-Martínez et al, 2007;Beaulieu et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

et al. 2014

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Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach.

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The Genetic Architecture of Maize Flowering Time

Cited by 1,277 publications

References 29 publications

The genetic architecture of leaf number and its genetic relationship to flowering time in maize

The genetic architecture of leaf number and its genetic relationship to flowering time in maize

Bringing New Plant Varieties to Market: Plant Breeding and Selection Practices Advance Beneficial Characteristics while Minimizing Unintended Changes

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

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