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

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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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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