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1.
Plant Sci ; 295: 110396, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-32534615

RESUMO

The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly across research plots collecting high-resolution data sets on a wide array of traits. This has been made possible by recent advances in sensor technology and data processing. Nonetheless, more comprehensive often destructive phenotyping still has much to offer in breeding as well as research. This review considers the 'breeder friendliness' of phenotyping within three main domains: (i) the 'minimum data set', where being 'handy' or accessible and easy to collect and use is paramount, visual assessment often being preferred; (ii) the high throughput phenotyping (HTP), relatively new for most breeders, and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set; (iii) detailed characterization or 'precision' phenotyping, typically customized for a set of traits associated with a target environment and requiring significant time and resources. While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models, that can be built from the high-throughput and detailed precision phenotypes. This review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translational research to deliver other new breeding resources, and how the different categories of phenotyping listed above apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.

2.
Gigascience ; 8(11)2019 11 01.
Artigo em Inglês | MEDLINE | ID: mdl-31742599

RESUMO

BACKGROUND: Measurement of plant traits with precision and speed on large populations has emerged as a critical bottleneck in connecting genotype to phenotype in genetics and breeding. This bottleneck limits advancements in understanding plant genomes and the development of improved, high-yielding crop varieties. RESULTS: Here we demonstrate the application of deep learning on proximal imaging from a mobile field vehicle to directly estimate plant morphology and developmental stages in wheat under field conditions. We developed and trained a convolutional neural network with image datasets labeled from expert visual scores and used this "breeder-trained" network to classify wheat morphology and developmental stages. For both morphological (awned) and phenological (flowering time) traits, we demonstrate high heritability and very high accuracy against the "ground-truth" values from visual scoring. Using the traits predicted by the network, we tested genotype-to-phenotype association using the deep learning phenotypes and uncovered novel epistatic interactions for flowering time. Enabled by the time-series high-throughput phenotyping, we describe a new phenotype as the rate of flowering and show heritable genetic control for this trait. CONCLUSIONS: We demonstrated a field-based high-throughput phenotyping approach using deep learning that can directly measure morphological and developmental phenotypes in genetic populations from field-based imaging. The deep learning approach presented here gives a conceptual advancement in high-throughput plant phenotyping because it can potentially estimate any trait in any plant species for which the combination of breeder scores and high-resolution images can be obtained, capturing the expert knowledge from breeders, geneticists, pathologists, and physiologists to train the networks.


Assuntos
Bases de Dados de Ácidos Nucleicos , Aprendizado Profundo , Flores , Regulação da Expressão Gênica de Plantas , Estudos de Associação Genética , Genótipo , Triticum , Flores/genética , Flores/metabolismo , Triticum/genética , Triticum/metabolismo
3.
Front Plant Sci ; 10: 1278, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31781130

RESUMO

In this study, we anchored genotyping-by-sequencing data to the International Wheat Genome Sequencing Consortium Reference Sequence v1.0 assembly to generate over 40,000 high quality single nucleotide polymorphism markers on a panel of 376 elite European winter wheat varieties released between 1946 and 2007. We compared association mapping and genomic prediction accuracy for a range of productivity traits with previous results based on lower density dominant DArT markers. The results demonstrate that the availability of RefSeq v1.0 supports higher precision trait mapping and provides the density of markers required to obtain accurate predictions of traits controlled by multiple small effect loci, including grain yield.

4.
Theor Appl Genet ; 132(11): 3129-3141, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31535163

RESUMO

KEY MESSAGE: Wheat-barley group-7 recombinant chromosomes were selected using molecular cytogenetics and SNP markers; increased grain ß-glucan content was observed in wheat plants with two and four copies of HvCslF6. The soluble dietary fiber (1-3)(1-4) mixed linked ß-D-glucan from cereal grains is a valuable component of a healthy diet, which reduces risks of coronary disease and diabetes. Although wheat is an important cereal crop providing a substantial portion of daily calories and protein intake in the human diet, it has a low level of ß-glucan. Owing to the plasticity of the polyploid wheat genome, agronomically important traits absent in the wheat primary gene pool can be introgressed from distant relatives. Barley (Hordeum vulgare L.) has a high grain ß-glucan content. Earlier, we introgressed this trait into wheat in the form of whole arm compensating Robertsonian translocations (RobT) involving group-7 chromosomes of barley and all three sub-genomes of hexaploid wheat (Triticum aestivum L). In the presented research, we shortened the barley 7HL arms in these RobTs to small pericentromeric segments, using induced wheat-barley homoeologous recombination. The recombinants were selected using SNP markers and molecular cytogenetics. Plants, comprising barley cellulose synthase-like F6 gene (HvCslF6), responsible for ß-glucan synthesis, had a higher grain ß-glucan content than the wheat control. Three wheat-barley group-7 recombinant chromosomes involving the A, B and D sub-genomes laid the basis for a multiple-copy gene introgression to hexaploid wheat. It is hypothesized that further increases in the ß-glucan content in wheat grain can be obtained by increasing the number of HvCslF6 copies through combining several recombinant chromosomes in one line. The wheat lines with four copies of HvCslF6 exceeded the ß-glucan content of the lines with two copies.


Assuntos
Hordeum/genética , Sementes/química , Translocação Genética , Triticum/genética , beta-Glucanas/química , Cromossomos de Plantas/genética , Genes de Plantas , Glucosiltransferases/química , Polimorfismo de Nucleotídeo Único , Poliploidia , Recombinação Genética
5.
Nat Genet ; 51(10): 1530-1539, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31548720

RESUMO

Bread wheat improvement using genomic tools is essential for accelerating trait genetic gains. Here we report the genomic predictabilities of 35 key traits and demonstrate the potential of genomic selection for wheat end-use quality. We also performed a large genome-wide association study that identified several significant marker-trait associations for 50 traits evaluated in South Asia, Africa and the Americas. Furthermore, we built a reference wheat genotype-phenotype map, explored allele frequency dynamics over time and fingerprinted 44,624 wheat lines for trait-associated markers, generating over 7.6 million data points, which together will provide a valuable resource to the wheat community for enhancing productivity and stress resilience.


Assuntos
Resistência à Doença/genética , Genômica/métodos , Locos de Características Quantitativas , Estresse Fisiológico/imunologia , Triticum/crescimento & desenvolvimento , Triticum/imunologia , Ascomicetos/fisiologia , Mapeamento Cromossômico , Grão Comestível/genética , Grão Comestível/crescimento & desenvolvimento , Estudos de Associação Genética , Marcadores Genéticos , Genoma de Planta , Estudo de Associação Genômica Ampla , Melhoramento Vegetal , Doenças das Plantas/genética , Doenças das Plantas/microbiologia , Seleção Genética , Estresse Fisiológico/genética , Triticum/genética
6.
Int J Mol Sci ; 20(15)2019 Jul 26.
Artigo em Inglês | MEDLINE | ID: mdl-31357467

RESUMO

Genetic resistance against biotic stress is a major goal in many wheat breeding programs. However, modern wheat cultivars have a limited genetic variation for disease and pest resistance and there is always a possibility of the evolution of new diseases and pests to overcome previously identified resistance genes. A total of 125 synthetic hexaploid wheats (SHWs; 2n = 6x = 42, AABBDD, Triticum aestivum L.) were characterized for resistance to fungal pathogens that cause wheat rusts (leaf; Puccinia triticina, stem; P. graminis f.sp. tritici, and stripe; P. striiformis f.sp. tritici) and crown rot (Fusarium spp.); cereal cyst nematode (Heterodera spp.); and Hessian fly (Mayetiola destructor). A wide range of genetic variation was observed among SHWs for multiple (two to five) biotic stresses and 17 SHWs that were resistant to more than two stresses. The genomic regions and potential candidate genes conferring resistance to these biotic stresses were identified from a genome-wide association study (GWAS). This GWAS study identified 124 significant marker-trait associations (MTAs) for multiple biotic stresses and 33 of these were found within genes. Furthermore, 16 of the 33 MTAs present within genes had annotations suggesting their potential role in disease resistance. These results will be valuable for pyramiding novel genes/genomic regions conferring resistance to multiple biotic stresses from SHWs into elite bread wheat cultivars and providing further insights on a wide range of stress resistance in wheat.


Assuntos
Adaptação Biológica/genética , Estudo de Associação Genômica Ampla , Poliploidia , Estresse Fisiológico/genética , Triticum/fisiologia , Biologia Computacional/métodos , Resistência à Doença/genética , Interações Hospedeiro-Parasita/genética , Interações Hospedeiro-Patógeno/genética , Fenótipo , Locos de Características Quantitativas , Característica Quantitativa Herdável
7.
G3 (Bethesda) ; 9(9): 2963-2975, 2019 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-31296616

RESUMO

Oat (Avena sativa L.) has a high concentration of oils, comprised primarily of healthful unsaturated oleic and linoleic fatty acids. To accelerate oat plant breeding efforts, we sought to identify loci associated with variation in fatty acid composition, defined as the types and quantities of fatty acids. We genotyped a panel of 500 oat cultivars with genotyping-by-sequencing and measured the concentrations of ten fatty acids in these oat cultivars grown in two environments. Measurements of individual fatty acids were highly correlated across samples, consistent with fatty acids participating in shared biosynthetic pathways. We leveraged these phenotypic correlations in two multivariate genome-wide association study (GWAS) approaches. In the first analysis, we fitted a multivariate linear mixed model for all ten fatty acids simultaneously while accounting for population structure and relatedness among cultivars. In the second, we performed a univariate association test for each principal component (PC) derived from a singular value decomposition of the phenotypic data matrix. To aid interpretation of results from the multivariate analyses, we also conducted univariate association tests for each trait. The multivariate mixed model approach yielded 148 genome-wide significant single-nucleotide polymorphisms (SNPs) at a 10% false-discovery rate, compared to 129 and 73 significant SNPs in the PC and univariate analyses, respectively. Thus, explicit modeling of the correlation structure between fatty acids in a multivariate framework enabled identification of loci associated with variation in seed fatty acid concentration that were not detected in the univariate analyses. Ultimately, a detailed characterization of the loci underlying fatty acid variation can be used to enhance the nutritional profile of oats through breeding.


Assuntos
Avena/genética , Ácidos Graxos/genética , Estudo de Associação Genômica Ampla/métodos , Sementes/genética , Sementes/metabolismo , Avena/metabolismo , Ácidos Graxos/metabolismo , Genética Populacional , Genoma de Planta , Fenótipo , Polimorfismo de Nucleotídeo Único
8.
G3 (Bethesda) ; 9(9): 2925-2934, 2019 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-31300481

RESUMO

Genome-enabled prediction plays an essential role in wheat breeding because it has the potential to increase the rate of genetic gain relative to traditional phenotypic and pedigree-based selection. Since the performance of wheat lines is highly influenced by environmental stimuli, it is important to accurately model the environment and its interaction with genetic factors in prediction models. Arguably, multi-environmental best linear unbiased prediction (BLUP) may deliver better prediction performance than single-environment genomic BLUP. We evaluated pedigree and genome-based prediction using 35,403 wheat lines from the Global Wheat Breeding Program of the International Maize and Wheat Improvement Center (CIMMYT). We implemented eight statistical models that included genome-wide molecular marker and pedigree information as prediction inputs in two different validation schemes. All models included main effects, but some considered interactions between the different types of pedigree and genomic covariates via Hadamard products of similarity kernels. Pedigree models always gave better prediction of new lines in observed environments than genome-based models when only main effects were fitted. However, for all traits, the highest predictive abilities were obtained when interactions between pedigree, genomes, and environments were included. When new lines were predicted in unobserved environments, in almost all trait/year combinations, the marker main-effects model was the best. These results provide strong evidence that the different sources of genetic information (molecular markers and pedigree) are not equally useful at different stages of the breeding pipelines, and can be employed differentially to improve the design and prediction of the outcome of future breeding programs.


Assuntos
Genoma de Planta , Modelos Genéticos , Triticum/fisiologia , Interação Gene-Ambiente , Marcadores Genéticos , Fenótipo , Melhoramento Vegetal , Distribuição Aleatória , Reprodutibilidade dos Testes , Triticum/genética
9.
Theor Appl Genet ; 132(8): 2325-2351, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31172227

RESUMO

Allohexaploid (2n = 6x = 42) intermediate wheatgrass (Thinopyrum intermedium), abbreviated IWG, is an outcrossing perennial grass belonging to the tertiary gene pool of wheat. Perenniality would be valuable option for grain production, but attempts to introgress this complex trait from wheat-Thinopyrum hybrids have not been commercially successful. Efforts to breed IWG itself as a dual-purpose forage and grain crop have demonstrated useful progress and applications, but grain yields are significantly less than wheat. Therefore, genetic and physical maps have been developed to accelerate domestication of IWG. Herein, these maps were used to identify quantitative trait loci (QTLs) and candidate genes associated with IWG grain production traits in a family of 266 full-sib progenies derived from two heterozygous parents, M26 and M35. Transgressive segregation was observed for 17 traits related to seed size, shattering, threshing, inflorescence capacity, fertility, stem size, and flowering time. A total of 111 QTLs were detected in 36 different regions using 3826 genotype-by-sequence markers in 21 linkage groups. The most prominent QTL had a LOD score of 15 with synergistic effects of 29% and 22% over the family means for seed retention and percentage of naked seeds, respectively. Many QTLs aligned with one or more IWG gene models corresponding to 42 possible domestication orthogenes including the wheat Q and RHT genes. A cluster of seed-size and fertility QTLs showed possible alignment to a putative Z self-incompatibility gene, which could have detrimental grain-yield effects when genetic variability is low. These findings elucidate pathways and possible hurdles in the domestication of IWG.


Assuntos
Agropyron/genética , Mapeamento Cromossômico , Domesticação , Locos de Características Quantitativas/genética , Característica Quantitativa Herdável , Sequência de Bases , Cromossomos de Plantas/genética , Ligação Genética , Marcadores Genéticos , Genoma de Planta , Genótipo , Escore Lod , Fenótipo
11.
Front Plant Sci ; 10: 394, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31019521

RESUMO

Novel high-throughput phenotyping (HTP) approaches are needed to advance the understanding of genotype-to-phenotype and accelerate plant breeding. The first generation of HTP has examined simple spectral reflectance traits from images and sensors but is limited in advancing our understanding of crop development and architecture. Lodging is a complex trait that significantly impacts yield and quality in many crops including wheat. Conventional visual assessment methods for lodging are time-consuming, relatively low-throughput, and subjective, limiting phenotyping accuracy and population sizes in breeding and genetics studies. Here, we demonstrate the considerable power of unmanned aerial systems (UAS) or drone-based phenotyping as a high-throughput alternative to visual assessments for the complex phenological trait of lodging, which significantly impacts yield and quality in many crops including wheat. We tested and validated quantitative assessment of lodging on 2,640 wheat breeding plots over the course of 2 years using differential digital elevation models from UAS. High correlations of digital measures of lodging to visual estimates and equivalent broad-sense heritability demonstrate this approach is amenable for reproducible assessment of lodging in large breeding nurseries. Using these high-throughput measures to assess the underlying genetic architecture of lodging in wheat, we applied genome-wide association analysis and identified a key genomic region on chromosome 2A, consistent across digital and visual scores of lodging. However, these associations accounted for a very minor portion of the total phenotypic variance. We therefore investigated whole genome prediction models and found high prediction accuracies across populations and environments. This adequately accounted for the highly polygenic genetic architecture of numerous small effect loci, consistent with the previously described complex genetic architecture of lodging in wheat. Our study provides a proof-of-concept application of UAS-based phenomics that is scalable to tens-of-thousands of plots in breeding and genetic studies as will be needed to uncover the genetic factors and increase the rate of gain for complex traits in crop breeding.

12.
Nat Biotechnol ; 37(2): 139-143, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30718880

RESUMO

Disease resistance (R) genes from wild relatives could be used to engineer broad-spectrum resistance in domesticated crops. We combined association genetics with R gene enrichment sequencing (AgRenSeq) to exploit pan-genome variation in wild diploid wheat and rapidly clone four stem rust resistance genes. AgRenSeq enables R gene cloning in any crop that has a diverse germplasm panel.


Assuntos
Clonagem Molecular , Produtos Agrícolas/genética , Resistência à Doença/genética , Genes de Plantas , Doenças das Plantas/genética , Mapeamento Cromossômico , Estudos de Associação Genética , Variação Genética , Genômica , Genótipo , Modelos Genéticos , Fenótipo , Filogenia , Polimorfismo de Nucleotídeo Único , Plântula , Triticum/genética
13.
Theor Appl Genet ; 132(6): 1705-1720, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30778634

RESUMO

Genomic selection (GS) models have been validated for many quantitative traits in wheat (Triticum aestivum L.) breeding. However, those models are mostly constrained within the same growing cycle and the extension of GS to the case of across cycles has been a challenge, mainly due to the low predictive accuracy resulting from two factors: reduced genetic relationships between different families and augmented environmental variances between cycles. Using the data collected from diverse field conditions at the International Wheat and Maize Improvement Center, we evaluated GS for grain yield in three elite yield trials across three wheat growing cycles. The objective of this project was to employ the secondary traits, canopy temperature, and green normalized difference vegetation index, which are closely associated with grain yield from high-throughput phenotyping platforms, to improve prediction accuracy for grain yield. The ability to predict grain yield was evaluated reciprocally across three cycles with or without secondary traits. Our results indicate that prediction accuracy increased by an average of 146% for grain yield across cycles with secondary traits. In addition, our results suggest that secondary traits phenotyped during wheat heading and early grain filling stages were optimal for enhancing the prediction accuracy for grain yield.


Assuntos
Genética Populacional , Genoma de Planta , Genômica/métodos , Melhoramento Vegetal/métodos , Seleção Genética , Triticum/genética , Marcadores Genéticos , Fenótipo , Triticum/crescimento & desenvolvimento
14.
Front Plant Sci ; 10: 54, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30792723

RESUMO

Bread wheat is an important and the most consumed cereal worldwide. However, people with predominantly cereal-based diets are increasingly affected by micronutrient deficiencies, suggesting the need for biofortified wheat varieties. The limited genetic diversity in hexaploid wheat warrants exploring the wider variation present in wheat wild relatives, among these Aegilops tauschii, the wild progenitor of the bread wheat D genome. In this study, a panel of 167 Ae. tauschii accessions was phenotyped for grain Fe, Zn, Cu, and Mn concentrations for 3 years and was found to have wide variation for these micronutrients. Comparisons between the two genetic subpopulations of Ae. tauschii revealed that lineage 2 had higher mean values for Fe and Cu concentration than lineage 1. To identify potentially new genetic sources for improving grain micronutrient concentration, we performed a genome-wide association study (GWAS) on 114 non-redundant Ae. tauschii accessions using 5,249 genotyping-by-sequencing (GBS) markers. Best linear unbiased predictor (BLUP) values were calculated for all traits across the three growing seasons. A total of 19 SNP marker trait associations (MTAs) were detected for all traits after applying Bonferroni corrected threshold of -log10(P-value) ≥ 4.68. These MTAs were found on all seven chromosomes. For grain Fe, Zn, Cu, and Mn concentrations, five, four, three, and seven significant associations were detected, respectively. The associations were linked to the genes encoding transcription factor regulators, transporters, and phytosiderophore synthesis. The results demonstrate the utility of GWAS for understanding the genetic architecture of micronutrient accumulation in Ae. tauschii, and further efforts to validate these loci will aid in using them to diversify the D-genome of hexaploid wheat.

15.
G3 (Bethesda) ; 9(4): 1231-1247, 2019 04 09.
Artigo em Inglês | MEDLINE | ID: mdl-30796086

RESUMO

Hyperspectral reflectance phenotyping and genomic selection are two emerging technologies that have the potential to increase plant breeding efficiency by improving prediction accuracy for grain yield. Hyperspectral cameras quantify canopy reflectance across a wide range of wavelengths that are associated with numerous biophysical and biochemical processes in plants. Genomic selection models utilize genome-wide marker or pedigree information to predict the genetic values of breeding lines. In this study, we propose a multi-kernel GBLUP approach to genomic selection that uses genomic marker-, pedigree-, and hyperspectral reflectance-derived relationship matrices to model the genetic main effects and genotype × environment (G × E) interactions across environments within a bread wheat (Triticum aestivum L.) breeding program. We utilized an airplane equipped with a hyperspectral camera to phenotype five differentially managed treatments of the yield trials conducted by the Bread Wheat Improvement Program of the International Maize and Wheat Improvement Center (CIMMYT) at Ciudad Obregón, México over four breeding cycles. We observed that single-kernel models using hyperspectral reflectance-derived relationship matrices performed similarly or superior to marker- and pedigree-based genomic selection models when predicting within and across environments. Multi-kernel models combining marker/pedigree information with hyperspectral reflectance phentoypes had the highest prediction accuracies; however, improvements in accuracy over marker- and pedigree-based models were marginal when correcting for days to heading. Our results demonstrate the potential of using hyperspectral imaging to predict grain yield within a multi-environment context and also support further studies on the integration of hyperspectral reflectance phenotyping into breeding programs.


Assuntos
Melhoramento Vegetal/métodos , Triticum/genética , Interação Gene-Ambiente , Marcadores Genéticos , Genoma de Planta , Genótipo , México , Fenótipo , Seleção Genética , Triticum/crescimento & desenvolvimento
16.
Sci Rep ; 9(1): 1793, 2019 02 11.
Artigo em Inglês | MEDLINE | ID: mdl-30741967

RESUMO

Wheat (Triticum aestivum) genetic maps are a key enabling tool for genetic studies. We used genotyping-by-sequencing-(GBS) derived markers to map recombinant inbred line (RIL) and doubled haploid (DH) populations from crosses of W7984 by Opata, and used the maps to explore features of recombination control. The RIL and DH populations, SynOpRIL and SynOpDH, were composed of 906 and 92 individuals, respectively. Two high-density genetic linkage framework maps were constructed of 2,842 and 2,961 cM, harboring 3,634 and 6,580 markers, respectively. Using imputation, we added 43,013 and 86,042 markers to the SynOpRIL and SynOpDH maps. We observed preferential recombination in telomeric regions and reduced recombination in pericentromeric regions. Recombination rates varied between subgenomes, with the D genomes of the two populations exhibiting the highest recombination rates of 0.26-0.27 cM/Mb. QTL mapping identified two additive and three epistatic loci associated with crossover number. Additionally, we used published POPSEQ data from SynOpDH to explore the structural variation in W7984 and Opata. We found that chromosome 5AS is missing from W7984. We also found 2,332 variations larger than 100 kb. Structural variants were more abundant in distal regions, and overlapped 9,196 genes. The two maps provide a resource for trait mapping and genomic-assisted breeding.

17.
Front Plant Sci ; 10: 9, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30740115

RESUMO

Aegilops tauschii, the D-genome donor of bread wheat, Triticum aestivum, is a storehouse of genetic diversity, and an important resource for future wheat improvement. Genomic and population analysis of 549 Ae. tauschii and 103 wheat accessions was performed by using 13,135 high quality SNPs. Population structure, principal component, and cluster analysis confirmed the differentiation of Ae. tauschii into two lineages; lineage 1 (L1) and lineage 2 (L2), the latter being the wheat D-genome donor. Lineage L1 contributes only 2.7% of the total introgression from Ae. tauschii for a set of United States winter wheat lines, confirming the great amount of untapped genetic diversity in L1. Lineage L2 accessions had overall greater allelic diversity and wheat accessions had the least allelic diversity. Both lineages also showed intra-lineage differentiation with L1 being driven by longitudinal gradient and L2 differentiated by altitude. There has previously been little reported on natural hybridization between L1 and L2. We found nine putative inter-lineage hybrids in the population structure analysis, each containing numerous lineage-specific private alleles from both lineages. One hybrid was confirmed as a recombinant inbred between the two lineages, likely artificially post collection. Of the remaining eight putative hybrids, a group of seven from Georgia carry 713 SNPs with private alleles, which points to the possibility of a novel L1-L2 hybrid lineage. To facilitate the use of Ae. tauschii in wheat improvement, a MiniCore consisting of 29 L1 and 11 L2 accessions, has been developed based on genotypic, phenotypic and geographical data. MiniCore reduces the collection size by over 10-fold and captures 84% of the total allelic diversity in the whole collection.

18.
Sci Rep ; 9(1): 650, 2019 01 24.
Artigo em Inglês | MEDLINE | ID: mdl-30679756

RESUMO

Genebanks are valuable resources for crop improvement through the acquisition, ex-situ conservation and sharing of unique germplasm among plant breeders and geneticists. With over seven million existing accessions and increasing storage demands and costs, genebanks need efficient characterization and curation to make them more accessible and usable and to reduce operating costs, so that the crop improvement community can most effectively leverage this vast resource of untapped novel genetic diversity. However, the sharing and inconsistent documentation of germplasm often results in unintentionally duplicated collections with poor characterization and many identical accessions that can be hard or impossible to identify without passport information and unmatched accession identifiers. Here we demonstrate the use of genotypic information from these accessions using a cost-effective next generation sequencing platform to find and remove duplications. We identify and characterize over 50% duplicated accessions both within and across genebank collections of Aegilops tauschii, an important wild relative of wheat and source of genetic diversity for wheat improvement. We present a pipeline to identify and remove identical accessions within and among genebanks and curate globally unique accessions. We also show how this approach can also be applied to future collection efforts to avoid the accumulation of identical material. When coordinated across global genebanks, this approach will ultimately allow for cost effective and efficient management of germplasm and better stewarding of these valuable resources.

19.
Theor Appl Genet ; 132(1): 177-194, 2019 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-30341493

RESUMO

Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting grain yield (GY) in drought-stressed (DS) and late-sown heat-stressed (HS) environments of the International maize and wheat improvement center's elite yield trial nurseries. We observed that the average genomic prediction accuracies using fivefold cross-validations were 0.50 and 0.51 in the DS and HS environments, respectively. However, when a different nursery/year was used to predict another nursery/year, the average genomic prediction accuracies in the DS and HS environments decreased to 0.18 and 0.23, respectively. While genomic predictions clearly outperformed pedigree-based predictions across nurseries, they were similar to pedigree-based predictions within nurseries due to small family sizes. In populations with some full-sibs in the training population, the genomic and pedigree-based prediction accuracies were on average 0.27 and 0.35 higher than the accuracies in populations with only one progeny per cross, indicating the importance of genetic relatedness between the training and validation populations for good predictions. We also evaluated the item-based collaborative filtering approach for multivariate prediction of GY using the green normalized difference vegetation index from HTP. This approach proved to be the best strategy for across-nursery predictions, with average accuracies of 0.56 and 0.62 in the DS and HS environments, respectively. We conclude that GY is a challenging trait for across-year predictions, but GS and HTP can be integrated in increasing the size of populations screened and evaluating unphenotyped large nurseries for stress-resilience within years.


Assuntos
Clima , Modelos Genéticos , Melhoramento Vegetal/métodos , Triticum/genética , Grão Comestível/genética , Genoma de Planta , Genômica , Genótipo , Ensaios de Triagem em Larga Escala , Modelos Lineares , Linhagem , Fenótipo , Característica Quantitativa Herdável
20.
Glob Chang Biol ; 25(3): 850-868, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30468548

RESUMO

Many prior studies have uncovered evidence for local adaptation using reciprocal transplant experiments. However, these studies are rarely conducted for a long enough time to observe succession and competitive dynamics in a community context, limiting inferences for long-lived species. Furthermore, the genetic basis of local adaptation and genetic associations with climate has rarely been identified. Here, we report on a long-term (6-year) experiment conducted under natural conditions focused on Andropogon gerardii, the dominant grass of the North American Great Plains tallgrass ecosystem. We focus on this foundation grass that comprises 80% of tallgrass prairie biomass and is widely used in 20,000 km2 of restoration. Specifically, we asked the following questions: (a) Whether ecotypes are locally adapted to regional climate in realistic ecological communities. (b) Does adaptive genetic variation underpin divergent phenotypes across the climate gradient? (c) Is there evidence of local adaptation if the plants are exposed to competition among ecotypes in mixed ecotype plots? Finally, (d) are local adaptation and genetic divergence related to climate? Reciprocal gardens were planted with 3 regional ecotypes (originating from dry, mesic, wet climate sources) of Andropogon gerardii across a precipitation gradient (500-1,200 mm/year) in the US Great Plains. We demonstrate local adaptation and differentiation of ecotypes in wet and dry environments. Surprisingly, the apparent generalist mesic ecotype performed comparably under all rainfall conditions. Ecotype performance was underpinned by differences in neutral diversity and candidate genes corroborating strong differences among ecotypes. Ecotype differentiation was related to climate, primarily rainfall. Without long-term studies, wrong conclusions would have been reached based on the first two years. Further, restoring prairies with climate-matched ecotypes is critical to future ecology, conservation, and sustainability under climate change.


Assuntos
Adaptação Fisiológica/genética , Andropogon/fisiologia , Mudança Climática , Ecótipo , Variação Genética , Pradaria , Meio-Oeste dos Estados Unidos , Seleção Genética , Fatores de Tempo
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