Nested‐association mapping (NAM)‐based genetic dissection uncovers candidate genes for seed and pod weights in peanut (
            Arachis hypogaea
            )

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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Identification of favorable SNP alleles and candidate genes for seedlessness in Vitis vinifera L. using genome-wide association mapping

Euphytica ◽

10.1007/s10681-017-1919-z ◽

2017 ◽

Vol 213 (7) ◽

Cited By ~ 5

Author(s):

Heng Zhang ◽

Xiucai Fan ◽

Ying Zhang ◽

Jianfu Jiang ◽

Chonghuai Liu

Keyword(s):

Vitis Vinifera ◽

Association Mapping ◽

Candidate Genes ◽

Genome Wide Association ◽

Vitis Vinifera L ◽

Genome Wide

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A genomewide association mapping study using ultrasound-scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle

Journal of Animal Breeding and Genetics ◽

10.1111/jbg.12167 ◽

2015 ◽

Vol 132 (6) ◽

pp. 420-427 ◽

Cited By ~ 16

Author(s):

M.H.A. Santana ◽

R.V. Ventura ◽

Y.T. Utsunomiya ◽

H.H.R. Neves ◽

P.A. Alexandre ◽

...

Keyword(s):

Association Mapping ◽

Candidate Genes ◽

Carcass Traits ◽

Mapping Study ◽

Nellore Cattle ◽

Genomewide Association ◽

Association Mapping Study ◽

Genomic Regions

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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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Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Genes ◽

10.3390/genes12121897 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1897

Author(s):

Endale G. Tafesse ◽

Krishna K. Gali ◽

V. B. Reddy Lachagari ◽

Rosalind Bueckert ◽

Thomas D. Warkentin

Keyword(s):

Association Mapping ◽

Candidate Genes ◽

Vegetation Index ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Nucleotide Polymorphisms ◽

Adaptive Traits ◽

Flowering Duration ◽

Genome Wide ◽

A Genome

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.

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