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| 1 | Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: Progress and challenges显示文摘Many biochemical and physiological properties of plants that are of interest to breeders and geneticists have extremely low throughput and/or can only be measured destructively.This has limited the use of information on natural variation in nutrient and metabolite abundance,as well as photosynthetic capacity in quantitative genetic contexts where it is necessary to collect data from hundreds or thousands of plants.A number of recent studies have demonstrated the potential to estimate many of these traits from hyperspectral reflectance data,primarily in ecophysiological contexts.Here,we summarize recent advances in the use of hyperspectral reflectance data for plant phenotyping,and discuss both the potential benefits and remaining challenges to its application in plant genetics contexts.The performances of previously published models in estimating six traits fromhyperspectral reflectance data in maizewere evaluated on newsample datasets,and the resulting predicted trait values shown to be heritable(e.g.,explained by genetic factors)were estimated.The adoption of hyperspectral reflectance-based phenotyping beyond its current uses may accelerate the study of genes controlling natural variation in biochemical and physiological traits. | Marcin Grzybowski Nuwan K.Wijewardane Abbas Atefi Yufeng Ge James C.Schnable | 2021 | Plant Communications2021，2，4： | 2 |
| 2 | Semantic Segmentation of Sorghum Using Hyperspectral Data Identifies Genetic Associations显示文摘This study describes the evaluation of a range of approaches to semantic segmentation of hyperspectral images of sorghum plants,classifying each pixel as either nonplant or belonging to one of the three organ types(leaf,stalk,panicle).While many current methods for segmentation focus on separating plant pixels from background,organ-specific segmentation makes it feasible to measure a wider range of plant properties.Manually scored training data for a set of hyperspectral images collected from a sorghum association population was used to train and evaluate a set of supervised classification models.Many algorithms show acceptable accuracy for this classification task.Algorithms trained on sorghum data are able to accurately classify maize leaves and stalks,but fail to accurately classify maize reproductive organs which are not directly equivalent to sorghum panicles.Trait measurements extracted from semantic segmentation of sorghum organs can be used to identify both genes known to be controlling variation in a previously measured phenotypes(e.g.,panicle size and plant height)as well as identify signals for genes controlling traits not previously quantified in this population(e.g.,stalk/leaf ratio).Organ level semantic segmentation provides opportunities to identify genes controlling variation in a wide range of morphological phenotypes in sorghum,maize,and other related grain crops. | Chenyong Miao Alejandro Pages Zheng Xu Eric Rodene Jinliang Yang James C.Schnable | 2020 | Plant Phenomics2020，2，1： | 0 |
| 3 | A High-Throughput Phenotyping Pipeline for Image Processing and Functional Growth Curve Analysis显示文摘High-throughput phenotyping system has become more and more popular in plant science research.The data analysis for such a system typically involves two steps:plant feature extraction through image processing and statistical analysis for the extracted features.The current approach is to perform those two steps on different platforms.We develop the package“implant”in R for both robust feature extraction and functional data analysis.For image processing,the“implant”package provides methods including thresholding,hidden Markov random field model,and morphological operations.For statistical analysis,this package can produce nonparametric curve fitting with its confidence region for plant growth.A functional ANOVA model to test for the treatment and genotype effects on the plant growth dynamics is also provided. | Ronghao Wang Yumou Qiu Yuzhen Zhou Zhikai Liang James C.Schnable | 2020 | Plant Phenomics2020，2，1： | 0 |
| 4 | The genome of Orychophragmus violaceus provides genomic insights into the evolution of Brassicaceaepolyploidizationandits distinct traits显示文摘Orychophragmus violaceus,referred to as‘‘eryuelan’’(February orchid)in China,is an early-flowering ornamental plant.The high oil content and abundance of unsaturated fatty acids in O.violaceus seeds make it a potential high-quality oilseed crop.Here,we generated a whole-genome assembly for O.violaceus using Nanopore and Hi-C sequencing technologies.The assembled genome of O.violaceus was~1.3 Gb in size,with 12 pairs of chromosomes.Through investigation of ancestral genome evolution,we determined that the genome of O.violaceus experienced a tetraploidization event from a diploid progenitor with the translocated proto-Calepineae karyotype.Comparisons between the reconstructed subgenomes of O.violaceus identified indicators of subgenome dominance,indicating that subgenomes likely originated via allotetraploidy.O.violaceus was phylogenetically close to the Brassica genus,and tetraploidy in O.violaceus occurred approximately 8.57 million years ago,close in time to the whole-genome triplication of Brassica that likely arose via an intermediate tetraploid lineage.However,the tetraploidization in Orychophragmus was independent of the hexaploidization in Brassica,as evidenced by the results from detailed phylogenetic analyses and comparisons of the break and fusion points of ancestral genomic blocks.Moreover,identification of multi-copy genes regulating the production of high-quality oil highlighted the contributions of both tetraploidization and tandem duplication to functional innovation in O.violaceus.These findings provide novel insights into the polyploidization evolution of plant species and will promote both functional genomic studies and domestication/breeding efforts in O.violaceus. | Kang Zhang Yinqing Yang Xin Zhang Lingkui Zhang Yu Fu Zhongwei Guo Shumin Chen Jian Wu James C.Schnable Keke Yi Xiaowu Wang Feng Cheng | 2023 | Plant Communications2023，4，2： | 0 |
| 5 | Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean显示文摘Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points.Yet,most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data.Here,we used time-series phenotypic data collected with an unmanned aircraft system for a large panel of soybean(Glycine max(L.)Merr.)varieties to identify previously uncharacterized loci.Specifically,we focused on the dissection of canopy coverage(CC)variation from this rich data set.We also inferred the speed of canopy closure,an additional dimension of CC,from the time-series data,as it may represent an important trait for weed control.Genome-wide association studies(GWASs)identified 35 loci exhibiting dynamic associations with CC across developmental stages.The time-series data enabled the identification of 10 known flowering time and plant height quantitative trait loci(QTLs)detected in previous studies of adult plants and the identification of novel QTLs influencing CC.These novel QTLs were disproportionately likely to act earlier in development,which may explain why they were missed in previous single-time-point studies.Moreover,this time-series data set contributed to the high accuracy of the GWASs,which we evaluated by permutation tests,as evidenced by the repeated identification of loci across multiple time points.Two novel loci showed evidence of adaptive selection during domestication,with different genotypes/haplotypes favored in different geographic regions.In summary,the time-series data,with soybean CC as an example,improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves. | Delin Li Dong Bai Yu Tian Ying-Hui Li Chaosen Zhao Qi Wang Shiyu Guo Yongzhe Gu Xiaoyan Luan Ruizhen Wang Jinliang Yang Malcolm J.Hawkesford James C.Schnable Xiuliang Jin Li-Juan Qiu | 2023 | Journal of Integrative Plant Biology2023，65，1： | 0 |
| 6 | Genome–Phenome Wide Association in Maize and Arabidopsis Identifies a Common Molecular and Evolutionary Signature显示文摘Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes.Variations of one or several traits are often assessed separately.High-throughput phenotyping and data mining can capture dozens or hundreds of traits from the same individuals.Here,we test the association between markers within a gene and many traits simultaneously.This genome–phenome wide association study(GPWAS)is both a multi-marker and multi-trait test.Genes identified using GPWAS with 260 phenotypic traits in maize were enriched for genes independently linked to phenotypic variation.Traits associated with classical mutants were consistent with reported phenotypes for mutant alleles.Genes linked to phenomic variation in maize using GPWAS shared molecular,population genetic,and evolutionary features with classical mutants in maize.Genes linked to phenomic variation in Arabidopsis using GPWAS are significantly enriched in genes with known loss-of-function phenotypes.GPWAS may be an effective strategy to identify genes in which loss-of-function alleles produce mutant phenotypes.The shared signatures present in classical mutants and genes identified using GPWAS may be markers for genes with a role in specifying plant phenotypes generally or pleiotropy specifically. | Zhikai Liang Yumou Qiu James C.Schnable | 2020 | Molecular Plant2020，13，6： | 0 |
| 7 | Can the grains offer each other helping hands?Convergent molecular mechanisms associated with domestication and crop improvement in rice and maize显示文摘The grasses,Poaceae,are an extraordinarily ecologically success-ful clade,with more than 10000 described extant species.The grasses include more than 30 domesticated grain crops,ranging from maize(Zea mays),rice(Oryza sativa),and wheat(Triticum aes-tivum),which are collectively responsible for 50%of all calories consumed by humans around the world,to minor and orphan crops such as teff(Eragrostis tef),pearl millet(Pennisetum glaucum),proso millet(Panicum milaceum),and Job's tears(Coix lacryma-jobi)(Glémin and Bataillon,2009).Domestication of grain crops from their wild relatives involved a common suite of phenotypic changes,including loss of seed shattering,loss of dormancy,and increased apical dominance,which are collectively referred to as'domestication syndrome'(Glémin and Bataillon,2009). | Ravi V.Mural James C.Schnable | 2022 | Molecular Plant2022，15，5： | 0 |
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