Mapping QTL controlling soybean seed sucrose and oligosaccharides in a single family of soybean nested association mapping (SoyNAM) population

Nested association mapping (NAM) has been an invaluable approach for plant genetics community and can dissect the genetic architecture of complex traits. As the most popular NAM analysis strategy, joint multifamily mapping can combine all information from diverse genetic backgrounds and increase population size. However, it is influenced by the genetic heterogeneity of quantitative trait locus (QTL) across various subpopulations. Multi-locus association mapping has been proven to be powerful in many cases of QTL mapping and genome-wide association studies. Therefore, we developed a multi-locus association model of multiple families in the NAM population, which could discriminate the effects of QTLs in all subpopulations. A series of simulations with a real maize NAM genomic data were implemented. The results demonstrated that the new method improves the statistical power in QTL detection and the accuracy in QTL effect estimation. The new approach, along with single-family linkage mapping, was used to identify QTLs for three flowering time traits in the maize NAM population. As a result, most QTLs detected in single family linkage mapping were identified by the new method. In addition, the new method also mapped some new QTLs with small effects, although their functions need to be identified in the future.

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Development of an Aus-Derived Nested Association Mapping (Aus-NAM) Population in Rice

Plants ◽

10.3390/plants10061255 ◽

2021 ◽

Vol 10 (6) ◽

pp. 1255

Author(s):

Justine K. Kitony ◽

Hidehiko Sunohara ◽

Mikako Tasaki ◽

Jun-Ichi Mori ◽

Akihisa Shimazu ◽

...

Keyword(s):

Qtl Mapping ◽

Association Mapping ◽

Genome Wide Association Study ◽

Genetic Resource ◽

Agronomic Traits ◽

Single Family ◽

Nested Association Mapping ◽

Flowering Genes ◽

Common Parent ◽

Allelic Variations

A genetic resource for studying genetic architecture of agronomic traits and environmental adaptation is essential for crop improvements. Here, we report the development of a rice nested association mapping population (aus-NAM) using 7 aus varieties as diversity donors and T65 as the common parent. Aus-NAM showed broad phenotypic variations. To test whether aus-NAM was useful for quantitative trait loci (QTL) mapping, known flowering genes (Ehd1, Hd1, and Ghd7) in rice were characterized using single-family QTL mapping, joint QTL mapping, and the methods based on genome-wide association study (GWAS). Ehd1 was detected in all the seven families and all the methods. On the other hand, Hd1 and Ghd7 were detected in some families, and joint QTL mapping and GWAS-based methods resulted in weaker and uncertain peaks. Overall, the high allelic variations in aus-NAM provide a valuable genetic resource for the rice community.

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Genomic Dissection of Peduncle Morphology in Barley through Nested Association Mapping

Plants ◽

10.3390/plants10010010 ◽

2020 ◽

Vol 10 (1) ◽

pp. 10

Author(s):

Sebastian Zahn ◽

Thomas Schmutzer ◽

Klaus Pillen ◽

Andreas Maurer

Keyword(s):

Quantitative Trait Loci ◽

Association Mapping ◽

Cross Section ◽

Quantitative Trait ◽

Spring Barley ◽

Raw Material ◽

Total Thickness ◽

Nested Association Mapping ◽

Elite Cultivar ◽

Major Qtl

Straw biomass and stability are crucial for stable yields. Moreover, straw harbors the potential to serve as a valuable raw material for bio-economic processes. The peduncle is the top part of the last shoot internode and carries the spike. This study investigates the genetic control of barley peduncle morphology. Therefore, 1411 BC1S3 lines of the nested association mapping (NAM) population “Halle Exotic Barley 25” (HEB-25), generated by crossing the spring barley elite cultivar Barke with an assortment of 25 exotic barley accessions, were used. Applying 50k Illumina Infinium iSelect SNP genotyping yielded new insights and a better understanding of the quantitative trait loci (QTL) involved in controlling the peduncle diameter traits, we found the total thickness of peduncle tissues and the area of the peduncle cross-section. We identified three major QTL regions on chromosomes 2H and 3H mainly impacting the traits. Remarkably, the exotic allele at the QTL on chromosome 3H improved all three traits investigated in this work. Introgressing this QTL in elite cultivars might facilitate to adjust peduncle morphology for improved plant stability or enlarged straw biomass production independent of flowering time and without detrimental effects on grain yield.

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Genetic Vulnerability and the Relationship of Commercial Germplasms of Maize in Brazil with the Nested Association Mapping Parents

PLoS ONE ◽

10.1371/journal.pone.0163739 ◽

2016 ◽

Vol 11 (10) ◽

pp. e0163739 ◽

Cited By ~ 2

Author(s):

Luciano Rogério Braatz de Andrade ◽

Roberto Fritsche Neto ◽

Ítalo Stefanine Correia Granato ◽

Gustavo César Sant’Ana ◽

Pedro Patric Pinho Morais ◽

...

Keyword(s):

Association Mapping ◽

Nested Association Mapping ◽

Genetic Vulnerability ◽

Relationship Of ◽

The Relationship

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Metabolomic Assessment of Key Maize Resources: GC-MS and NMR Profiling of Grain from B73 Hybrids of the Nested Association Mapping (NAM) Founders and of Geographically Diverse Landraces

Journal of Agricultural and Food Chemistry ◽

10.1021/acs.jafc.5b04901 ◽

2016 ◽

Vol 64 (10) ◽

pp. 2162-2172 ◽

Cited By ~ 17

Author(s):

Tyamagondlu V. Venkatesh ◽

Alexander W. Chassy ◽

Oliver Fiehn ◽

Sherry Flint-Garcia ◽

Qin Zeng ◽

...

Keyword(s):

Association Mapping ◽

Nested Association Mapping

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Latent Space Phenotyping: Automatic Image-Based Phenotyping for Treatment Studies

Plant Phenomics ◽

10.34133/2020/5801869 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Jordan Ubbens ◽

Mikolaj Cieslak ◽

Przemyslaw Prusinkiewicz ◽

Isobel Parkin ◽

Jana Ebersbach ◽

...

Keyword(s):

Image Processing ◽

Association Mapping ◽

Stress Responses ◽

Interspecific Cross ◽

Response To Treatment ◽

Brassica Napus L ◽

Nested Association Mapping ◽

Latent Space ◽

Using Data ◽

Candidate Loci

Association mapping studies have enabled researchers to identify candidate loci for many important environmental tolerance factors, including agronomically relevant tolerance traits in plants. However, traditional genome-by-environment studies such as these require a phenotyping pipeline which is capable of accurately measuring stress responses, typically in an automated high-throughput context using image processing. In this work, we present Latent Space Phenotyping (LSP), a novel phenotyping method which is able to automatically detect and quantify response-to-treatment directly from images. We demonstrate example applications using data from an interspecific cross of the model C4 grass Setaria, a diversity panel of sorghum (S. bicolor), and the founder panel for a nested association mapping population of canola (Brassica napus L.). Using two synthetically generated image datasets, we then show that LSP is able to successfully recover the simulated QTL in both simple and complex synthetic imagery. We propose LSP as an alternative to traditional image analysis methods for phenotyping, enabling the phenotyping of arbitrary and potentially complex response traits without the need for engineering-complicated image-processing pipelines.

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