From association to prediction: statistical methods for the dissection and selection of complex traits in plants

Lipka, Alexander E.; Kandianis, Catherine B.; Hudson, Matthew E.; Yu, Jianming; Drnevich, Jenny; Bradbury, Peter J.; Gore, Michael A.

doi:10.1016/j.pbi.2015.02.010

Cited by 129 publications

(112 citation statements)

References 74 publications

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“…These characteristics are useful not only for quantitative analysis of genotype-environment interactions, which is essential for increasing crop performance [3][4][5], but also for improving crop management strategies such as fertilization, irrigation, and optimization of harvesting [6][7][8]. Several studies have shown interactions between geometric parameters of plants and crop yield as well as biomass [3,5,[9][10][11].…”

Section: Introductionmentioning

confidence: 99%

In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

Sun

Paterson

2017

Remote Sensing

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A LiDAR-based high-throughput phenotyping (HTP) system was developed for cotton plant phenotyping in the field. The HTP system consists of a 2D LiDAR and an RTK-GPS mounted on a high clearance tractor. The LiDAR scanned three rows of cotton plots simultaneously from the top and the RTK-GPS was used to provide the spatial coordinates of the point cloud during data collection. Configuration parameters of the system were optimized to ensure the best data quality. A height profile for each plot was extracted from the dense three dimensional point clouds; then the maximum height and height distribution of each plot were derived. In lab tests, single plants were scanned by LiDAR using 0.5 • angular resolution and results showed an R 2 value of 1.00 (RMSE = 3.46 mm) in comparison to manual measurements. In field tests using the same angular resolution; the LiDAR-based HTP system achieved average R 2 values of 0.98 (RMSE = 65 mm) for cotton plot height estimation; compared to manual measurements. This HTP system is particularly useful for large field application because it provides highly accurate measurements; and the efficiency is greatly improved compared to similar studies using the side view scan.

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Section: Introductionmentioning

confidence: 99%

In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

Sun

Paterson

2017

Remote Sensing

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“…For example, only two allelic variations are analyzed (one per parent) in a biparental population, which means that various alleles occurring in other plants are missed. A GWAS that analyzes associations between nucleotide polymorphisms and phenotypic variance using a diverse population set is a powerful tool for the identification of genes associated with agronomic traits, because this strategy can be used to detect many natural allelic variations simultaneously in a single study [4][5][6] . Recent advances in high-throughput sequencing technologies have enabled rapid and accurate resequencing of a large number of genomes [7][8][9][10][11][12][13][14][15] .…”

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confidence: 99%

“…However, it is often difficult to identify unknown genes associated with the QTLs owing to two major reasons [4][5][6] . The first is that diversity panels of crop species often represent strong population structure that generates spurious associations between the phenotype and unlinked markers.…”

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confidence: 99%

“…The first is that diversity panels of crop species often represent strong population structure that generates spurious associations between the phenotype and unlinked markers. Although several statistically robust models have been developed, it must be noted that false positives arising from population structure in crops may not be completely controlled [4][5][6] . To address this problem, a reconstruction of population has been proposed, which is represented by a 'nested association mapping population' [22][23][24][25] and a 'multiparent advanced generation intercrossing population' [26][27][28] .…”

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Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice

et al. 2016

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A genome-wide association study (GWAS) can be a powerful tool for the identification of genes associated with agronomic traits in crop species, but it is often hindered by population structure and the large extent of linkage disequilibrium. In this study, we identified agronomically important genes in rice using GWAS based on whole-genome sequencing, followed by the screening of candidate genes based on the estimated effect of nucleotide polymorphisms. Using this approach, we identified four new genes associated with agronomic traits. Some genes were undetectable by standard SNP analysis, but we detected them using gene-based association analysis. This study provides fundamental insights relevant to the rapid identification of genes associated with agronomic traits using GWAS and will accelerate future efforts aimed at crop improvement.

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“…When larger collections are established on ecological and population genetic principles to capture as much representative variation as possible, whole genome sequencing can be deployed to develop purpose-built large-scale introgression populations [47]. Advanced backcross introgression populations, with some of the characteristics of Nested Association Mapping populations [150], can be ideal for both mapping domestication and agronomic traits and for transferring adaptive traits controlled by one or many genes into cultivated backgrounds [151].…”

Section: Use Of Crop Wild Relatives-introgressionmentioning

confidence: 99%

The Impact of Genetic Changes during Crop Domestication

et al. 2018

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Abstract:Humans have domesticated hundreds of plant and animal species as sources of food, fiber, forage, and tools over the past 12,000 years, with manifold effects on both human society and the genetic structure of the domesticated species. The outcomes of crop domestication were shaped by selection driven by human preferences, cultivation practices, and agricultural environments, as well as other population genetic processes flowing from the ensuing reduction in effective population size. It is obvious that any selection imposes a reduction of diversity, favoring preferred genotypes, such as nonshattering seeds or increased palatability. Furthermore, agricultural practices greatly reduced effective population sizes of crops, allowing genetic drift to alter genotype frequencies. Current advances in molecular technologies, particularly of genome sequencing, provide evidence of human selection acting on numerous loci during and after crop domestication. Population-level molecular analyses also enable us to clarify the demographic histories of the domestication process itself, which, together with expanded archaeological studies, can illuminate the origins of crops. Domesticated plant species are found in 160 taxonomic families. Approximately 2500 species have undergone some degree of domestication, and 250 species are considered to be fully domesticated. The evolutionary trajectory from wild to crop species is a complex process. Archaeological records suggest that there was a period of predomestication cultivation while humans first began the deliberate planting of wild stands that had favorable traits. Later, crops likely diversified as they were grown in new areas, sometimes beyond the climatic niche of their wild relatives. However, the speed and level of human intentionality during domestication remains a topic of active discussion. These processes led to the so-called domestication syndrome, that is, a group of traits that can arise through human preferences for ease of harvest and growth advantages under human propagation. These traits included reduced dispersal ability of seeds and fruits, changes to plant structure, and changes to plant defensive characteristics and palatability. Domestication implies the action of selective sweeps on standing genetic variation, as well as new genetic variation introduced via mutation or introgression. Furthermore, genetic bottlenecks during domestication or during founding events as crops moved away from their centers of origin may have further altered gene pools. To date, a few hundred genes and loci have been identified by classical genetic and association mapping as targets of domestication and postdomestication divergence. However, only a few of these have been characterized, and for even fewer is the role of the wild-type allele in natural populations understood. After domestication, only favorable haplotypes are retained around selected genes, which creates a genetic valley with extremely low genetic diversity. These "selective sweeps" can allow mildly deleterious...

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From association to prediction: statistical methods for the dissection and selection of complex traits in plants

Cited by 129 publications

References 74 publications

In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice

The Impact of Genetic Changes during Crop Domestication

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