Differences in canopy architecture play a role in determining both the light and water use efficiency.Canopy architecture is determined by several component traits,including leaf length,width,number,angle,and phyl-lot...Differences in canopy architecture play a role in determining both the light and water use efficiency.Canopy architecture is determined by several component traits,including leaf length,width,number,angle,and phyl-lotaxy.Phyllotaxy may be among the most difficult of the leaf canopy traits to measure accurately across large numbers of individual plants.As a result,in simulations of the leaf canopies of grain crops such as maize and sorghum,this trait is frequently approximated as alternating 180°angles between sequential leaves.We explore the feasibility of extracting direct measurements of the phyllotaxy of sequential leaves from 3D reconstructions of individual sorghum plants generated from 2D calibrated images and test the assumption of consistently alter-nating phyllotaxy across a diverse set of sorghum genotypes.Using a voxel-carving-based approach,we generate 3D reconstructions from multiple calibrated 2D images of 366 sorghum plants representing 236 sorghum geno-types from the sorghum association panel.The correlation between automated and manual measurements of phyllotaxy is only modestly lower than the correlation between manual measurements of phyllotaxy generated by two different individuals.Automated phyllotaxy measurements exhibited a repeatability of R^(2)=0.41 across imaging timepoints separated by a period of two days.A resampling based genome wide association study(GWAS)identified several putative genetic associations with lower-canopy phyllotaxy in sorghum.This study demonstrates the potential of 3D reconstruction to enable both quantitative genetic investigation and breeding for phyllotaxy in sorghum and other grain crops with similar plant architectures.展开更多
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 ...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.展开更多
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 stat...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.展开更多
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 practi...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.展开更多
A genome-wide association study(GWAS)identifies trait-associated loci,but identifying the causal genes can be a bottleneck,due in part to slow decay of linkage disequilibrium(LD).A transcriptome-wide association study...A genome-wide association study(GWAS)identifies trait-associated loci,but identifying the causal genes can be a bottleneck,due in part to slow decay of linkage disequilibrium(LD).A transcriptome-wide association study(TWAS)addresses this issue by identifying gene expression-phenotype associations or integrating gene expression quantitative trait loci with GWAS results.Here,we used self-pollinated soybean(Glycine max[L.]Merr.)as a model to evaluate the application of TWAS to the genetic dissection of traits in plant species with slow LD decay.We generated RNA sequencing data for a soybean diversity panel and identified the genetic expression regulation of 29286 soybean genes.Different TWAS solutions were less affected by LD and were robust to the source of expression,identifing known genes related to traits from different tissues and developmental stages.The novel pod-color gene L2 was identified via TWAS and functionally validated by genome editing.By introducing a new exon proportion feature,we significantly improved the detection of expression variations that resulted from structural variations and alternative splicing.As a result,the genes identified through our TWAS approach exhibited a diverse range of causal variations,including SNPs,insertions or deletions,gene fusion,copy number variations,and alternative splicing.Using this approach,we identified genes associated with flowering time,including both previously known genes and novel genes that had not previously been linked to this trait,providing insights complementary to those from GWAS.In summary,this study supports the application of TWAS for candidate gene identification in species with low rates of LD decay.展开更多
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 pote...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.展开更多
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(le...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.展开更多
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 min...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.展开更多
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...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).展开更多
基金supported by the Foundation for Food and Agriculture Research(602757)USDA-NIFA(2020-68013-32371 and 2024-67013-42449)+3 种基金Department of Energy the Office of Science(BER),U.S.DOE(DESC0020355)the National Science Foundation(IOS-2412930,2417510,and 2412928)the University of Nebraska-Lincoln's Complex Biosystems Graduate Programsupported by the National Science Foundation Graduate Research Fellowship Program under Grant No.2034837.
文摘Differences in canopy architecture play a role in determining both the light and water use efficiency.Canopy architecture is determined by several component traits,including leaf length,width,number,angle,and phyl-lotaxy.Phyllotaxy may be among the most difficult of the leaf canopy traits to measure accurately across large numbers of individual plants.As a result,in simulations of the leaf canopies of grain crops such as maize and sorghum,this trait is frequently approximated as alternating 180°angles between sequential leaves.We explore the feasibility of extracting direct measurements of the phyllotaxy of sequential leaves from 3D reconstructions of individual sorghum plants generated from 2D calibrated images and test the assumption of consistently alter-nating phyllotaxy across a diverse set of sorghum genotypes.Using a voxel-carving-based approach,we generate 3D reconstructions from multiple calibrated 2D images of 366 sorghum plants representing 236 sorghum geno-types from the sorghum association panel.The correlation between automated and manual measurements of phyllotaxy is only modestly lower than the correlation between manual measurements of phyllotaxy generated by two different individuals.Automated phyllotaxy measurements exhibited a repeatability of R^(2)=0.41 across imaging timepoints separated by a period of two days.A resampling based genome wide association study(GWAS)identified several putative genetic associations with lower-canopy phyllotaxy in sorghum.This study demonstrates the potential of 3D reconstruction to enable both quantitative genetic investigation and breeding for phyllotaxy in sorghum and other grain crops with similar plant architectures.
基金supported by the Office of Science(BER),U.S.Department of Energy,grant no.DE-SC0020355 to J.C.S.and Y.G.the National Science Foundation under grant OIA-1557417 to Y.G.and J.C.S.and OIA-1826781 to J.C.Ssupport from the Nebraska Research Initiative.
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.
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.
基金partially supported by the National Key R&D Program of China (2021YFD1201601)the Agricultural Science and Technology Innovation Program (ASTIP)of the Chinese Academy of Agricultural Sciences (CAAS-ZDRW202109)+1 种基金Hainan Yazhou Bay Seed Lab (B21HJ0221)supported by the UK Biotechnology and Biological Sciences Research Council as part of the Designing Future Wheat Project (BB/P016855/1)。
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.
基金supported by the National Key Research and Development Program of China(2021YFD1201600)the National Natural Science Foundation of China(32201759 and U22A20473)+3 种基金the China Scientific Innovation 2030 Project(2022ZD0401703)the Earmarked Fund for CARS(CARS-04-PS01)the Agricultural Science and Technology Innovation Program(ASTIPCAAS-ZDRW202109).
文摘A genome-wide association study(GWAS)identifies trait-associated loci,but identifying the causal genes can be a bottleneck,due in part to slow decay of linkage disequilibrium(LD).A transcriptome-wide association study(TWAS)addresses this issue by identifying gene expression-phenotype associations or integrating gene expression quantitative trait loci with GWAS results.Here,we used self-pollinated soybean(Glycine max[L.]Merr.)as a model to evaluate the application of TWAS to the genetic dissection of traits in plant species with slow LD decay.We generated RNA sequencing data for a soybean diversity panel and identified the genetic expression regulation of 29286 soybean genes.Different TWAS solutions were less affected by LD and were robust to the source of expression,identifing known genes related to traits from different tissues and developmental stages.The novel pod-color gene L2 was identified via TWAS and functionally validated by genome editing.By introducing a new exon proportion feature,we significantly improved the detection of expression variations that resulted from structural variations and alternative splicing.As a result,the genes identified through our TWAS approach exhibited a diverse range of causal variations,including SNPs,insertions or deletions,gene fusion,copy number variations,and alternative splicing.Using this approach,we identified genes associated with flowering time,including both previously known genes and novel genes that had not previously been linked to this trait,providing insights complementary to those from GWAS.In summary,this study supports the application of TWAS for candidate gene identification in species with low rates of LD decay.
基金supported by the National Natural Science Foundation of China(NSFC grants 31722048 and 31972411)the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences,and the Key Laboratory of Biology and Genetic Improvement of Horticultural Crops,Ministry of Agriculture and Rural Affairs,P.R.Chinasupported by the China Agricultural Research System—Green Manure(CARS-22).
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.
基金This work was supported by a University of Nebraska Agri-cultural Research Division seed grant to JCS,a National Sci-ence Foundation Award(OIA-1557417)to JCS and JY,and a UCARE fellowship to AP.
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.
基金This work is supported by National Science Foundation Awards MCB-1838307 and OIA-1826781 to J.C.S.In additionwe received support from the Quantitative Life Sciences Initiative at the University of Nebraska-Lincoln+1 种基金which in turn received support from the University of Nebraska Program of ExcellenceThis work was completed utilizing the Holla nd Computi ng Center of the University of Nebraska,which receives support from the Nebraska Research Initiative.
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.
基金supported by National Science Foundation under award MCB-1838307 to J.C.S.J.C.S.has an equity interest in a company breeding proso millet.
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).
