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1.
Plant Cell Environ ; 2020 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-32666553

RESUMO

Crop domestication and improvement often concurrently affect plant resistance to pests and production of secondary metabolites, creating challenges for isolating the ecological implications of selection for specific metabolites. Cucurbitacins are bitter triterpenoids with extreme phenotypic differences between Cucurbitaceae lineages, yet we lack integrated models of herbivore preference, cucurbitacin accumulation, and underlying genetic mechanisms. In Cucurbita pepo, we dissected the effect of cotyledon cucurbitacins on preference of a specialist insect pest (Acalymma vittatum) for multiple tissues, assessed genetic loci underlying cucurbitacin accumulation in diverse germplasm and a biparental F2 population (from a cross between two independent domesticates), and characterized quantitative associations between gene expression and metabolites during seedling development. Acalymma vittatum affinity for cotyledons is mediated by cucurbitacins, but other traits contribute to whole-plant resistance. Cotyledon cucurbitacin accumulation was associated with population structure, and our genetic mapping identified a single locus, Bi-4, containing genes relevant to transport and regulation - not biosynthesis - that diverged between lineages. These candidate genes were expressed during seedling development, most prominently a putative secondary metabolite transporter. Taken together, these findings support the testable hypothesis that breeding for plant resistance to insects involves targeting genes for regulation and transport of defensive metabolites, in addition to core biosynthesis genes. This article is protected by copyright. All rights reserved.

2.
Plant Signal Behav ; : 1790824, 2020 Jul 07.
Artigo em Inglês | MEDLINE | ID: mdl-32631108

RESUMO

Plant epidermal cuticles are composed of hydrophobic lipids that provide a barrier to non-stomatal water loss, and arose in land plants as an adaptation to the dry terrestrial environment. The expanding maize adult leaf displays a dynamic, proximodistal gradient of cuticle development, from the leaf base to the tip. Recently, our gene co-expression network analyses together with reverse genetic analyses suggested a previously undescribed function for PHYTOCHROME-mediated light signaling during cuticular wax deposition. The present work extends these findings by identifying a role for a specific LIPID TRANSFER PROTEIN (LTP) in cuticle development, and validating it via transgenic experiments in Arabidopsis. Given that LTPs and cuticles both evolved in land plants and are absent from aquatic green algae, we propose that during plant evolution, LTPs arose as one of the innovations of land plants that enabled development of the cuticle.

3.
Theor Appl Genet ; 2020 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-32613265

RESUMO

KEY MESSAGE: Heritable variation in phenotypes extracted from multi-spectral images (MSIs) and strong genetic correlations with end-of-season traits indicates the value of MSIs for crop improvement and modeling of plant growth curve. Vegetation indices (VIs) derived from multi-spectral imaging (MSI) platforms can be used to study properties of crop canopy, providing non-destructive phenotypes that could be used to better understand growth curves throughout the growing season. To investigate the amount of variation present in several VIs and their relationship with important end-of-season traits, genetic and residual (co)variances for VIs, grain yield and moisture were estimated using data collected from maize hybrid trials. The VIs considered were Normalized Difference Vegetation Index (NDVI), Green NDVI, Red Edge NDVI, Soil-Adjusted Vegetation Index, Enhanced Vegetation Index and simple Ratio of Near Infrared to Red (Red) reflectance. Genetic correlations of VIs with grain yield and moisture were used to fit multi-trait models for prediction of end-of-season traits and evaluated using within site/year cross-validation. To explore alternatives to fitting multiple phenotypes from MSI, random regression models with linear splines were fit using data collected in 2016 and 2017. Heritability estimates ranging from (0.10 to 0.82) were observed, indicating that there exists considerable amount of genetic variation in these VIs. Furthermore, strong genetic and residual correlations of the VIs, NDVI and NDRE, with grain yield and moisture were found. Considerable increases in prediction accuracy were observed from the multi-trait model when using NDVI and NDRE as a secondary trait. Finally, random regression with a linear spline function shows potential to be used as an alternative to mixed models to fit VIs from multiple time points.

4.
New Phytol ; 2020 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-32557592

RESUMO

Understanding the genetic and physiological basis of abiotic stress tolerance under field conditions is key to varietal crop improvement in the face of climate variability. Here, we investigate dynamic physiological responses to water stress in silico and their relationships to genotypic variation in hydraulic traits of cotton (Gossypium hirsutum), an economically important species for renewable textile fiber production. In conjunction with an ecophysiological process-based model, heterogeneous data (plant hydraulic traits, spatially-distributed soil texture, soil water content and canopy temperature) were used to examine hydraulic characteristics of cotton, evaluate their consequences on whole plant performance under drought, and explore potential genotype × environment effects. Cotton was found to have R-shaped hydraulic vulnerability curves (VCs), which were consistent under drought stress initiated at flowering. Stem VCs, expressed as percent loss of conductivity, differed across genotypes, whereas root VCs did not. Simulation results demonstrated how plant physiological stress can depend on the interaction between soil properties and irrigation management, which in turn affect genotypic rankings of transpiration in a time-dependent manner. Our study shows how a process-based modeling framework can be used to link genotypic variation in hydraulic traits to differential acclimating behaviors under drought.

5.
Phytopathology ; 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32539639

RESUMO

Phytophthora capsici is a soilborne oomycete plant pathogen that causes severe vegetable crop losses in New York (NY) State and worldwide. This pathogen is difficult to manage, in part due to its production of long-lasting sexual spores and its tendency to quickly evolve fungicide resistance. We single-nucleotide polymorphism (SNP) genotyped 252 P. capsici isolates, predominantly from NY, in order to conduct a genome-wide association study for mating type and mefenoxam sensitivity. The population structure and extent of chromosomal copy number variation in this collection of isolates were also characterized. Population structure analyses showed isolates largely clustered by the field site where they were collected, with values of FST between pairs of fields ranging from 0.10 to 0.31. Thirty-three isolates were putative aneuploids, demonstrating evidence for having up to four linkage groups present in more than two copies, and an additional two isolates appeared to be genome-wide triploids. Mating type was mapped to a region on scaffold 4, consistent with previous findings, and mefenoxam sensitivity was associated with several SNP markers at a novel locus on scaffold 62. We identified several candidate genes for mefenoxam sensitivity, including a homolog of yeast ribosome synthesis factor Rrp5, but failed to locate near the scaffold 62 locus any subunits of RNA Polymerase I, the hypothesized target site of phenylamide fungicides in oomycetes. This work expands our knowledge of the population biology of P. capsici and provides a foundation for functional validation of candidate genes associated with epidemiologically important phenotypes.

6.
Proc Natl Acad Sci U S A ; 117(22): 12464-12471, 2020 06 02.
Artigo em Inglês | MEDLINE | ID: mdl-32424100

RESUMO

Plant cuticles are composed of wax and cutin and evolved in the land plants as a hydrophobic boundary that reduces water loss from the plant epidermis. The expanding maize adult leaf displays a dynamic, proximodistal gradient of cuticle development, from the leaf base to the tip. Laser microdissection RNA Sequencing (LM-RNAseq) was performed along this proximodistal gradient, and complementary network analyses identified potential regulators of cuticle biosynthesis and deposition. A weighted gene coexpression network (WGCN) analysis suggested a previously undescribed function for PHYTOCHROME-mediated light signaling during the regulation of cuticular wax deposition. Genetic analyses reveal that phyB1 phyB2 double mutants of maize exhibit abnormal cuticle composition, supporting the predictions of our coexpression analysis. Reverse genetic analyses also show that phy mutants of the moss Physcomitrella patens exhibit abnormal cuticle composition, suggesting an ancestral role for PHYTOCHROME-mediated, light-stimulated regulation of cuticle development during plant evolution.

7.
G3 (Bethesda) ; 10(5): 1671-1683, 2020 May 04.
Artigo em Inglês | MEDLINE | ID: mdl-32184371

RESUMO

The cuticle, a hydrophobic layer of cutin and waxes synthesized by plant epidermal cells, is the major barrier to water loss when stomata are closed at night and under water-limited conditions. Elucidating the genetic architecture of natural variation for leaf cuticular conductance (g c) is important for identifying genes relevant to improving crop productivity in drought-prone environments. To this end, we conducted a genome-wide association study of g c of adult leaves in a maize inbred association panel that was evaluated in four environments (Maricopa, AZ, and San Diego, CA, in 2016 and 2017). Five genomic regions significantly associated with g c were resolved to seven plausible candidate genes (ISTL1, two SEC14 homologs, cyclase-associated protein, a CER7 homolog, GDSL lipase, and ß-D-XYLOSIDASE 4). These candidates are potentially involved in cuticle biosynthesis, trafficking and deposition of cuticle lipids, cutin polymerization, and cell wall modification. Laser microdissection RNA sequencing revealed that all these candidate genes, with the exception of the CER7 homolog, were expressed in the zone of the expanding adult maize leaf where cuticle maturation occurs. With direct application to genetic improvement, moderately high average predictive abilities were observed for whole-genome prediction of g c in locations (0.46 and 0.45) and across all environments (0.52). The findings of this study provide novel insights into the genetic control of g c and have the potential to help breeders more effectively develop drought-tolerant maize for target environments.

8.
BMC Res Notes ; 13(1): 71, 2020 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-32051026

RESUMO

OBJECTIVES: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. DATA DESCRIPTION: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

9.
Plant Biotechnol J ; 18(5): 1211-1222, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-31677224

RESUMO

Oat ranks sixth in world cereal production and has a higher content of health-promoting compounds compared with other cereals. However, there is neither a robust oat reference genome nor transcriptome. Using deeply sequenced full-length mRNA libraries of oat cultivar Ogle-C, a de novo high-quality and comprehensive oat seed transcriptome was assembled. With this reference transcriptome and QuantSeq 3' mRNA sequencing, gene expression was quantified during seed development from 22 diverse lines across six time points. Transcript expression showed higher correlations between adjacent time points. Based on differentially expressed genes, we identified 22 major temporal co-expression (TCoE) patterns of gene expression and revealed enriched gene ontology biological processes. Within each TCoE set, highly correlated transcripts, putatively commonly affected by genetic background, were clustered and termed genetic co-expression (GCoE) sets. Seventeen of the 22 TCoE sets had GCoE sets with median heritabilities higher than 0.50, and these heritability estimates were much higher than that estimated from permutation analysis, with no divergence observed in cluster sizes between permutation and non-permutation analyses. Linear regression between 634 metabolites from mature seeds and the PC1 score of each of the GCoE sets showed significantly lower p-values than permutation analysis. Temporal expression patterns of oat avenanthramides and lipid biosynthetic genes were concordant with previous studies of avenanthramide biosynthetic enzyme activity and lipid accumulation. This study expands our understanding of physiological processes that occur during oat seed maturation and provides plant breeders the means to change oat seed composition through targeted manipulation of key pathways.

10.
G3 (Bethesda) ; 10(2): 731-754, 2020 02 06.
Artigo em Inglês | MEDLINE | ID: mdl-31843806

RESUMO

The evolution and domestication of cotton is of great interest from both economic and evolutionary standpoints. Although many genetic and genomic resources have been generated for cotton, the genetic underpinnings of the transition from wild to domesticated cotton remain poorly known. Here we generated an intraspecific QTL mapping population specifically targeting domesticated cotton phenotypes. We used 466 F2 individuals derived from an intraspecific cross between the wild Gossypium hirsutum var. yucatanense (TX2094) and the elite cultivar G. hirsutum cv. Acala Maxxa, in two environments, to identify 120 QTL associated with phenotypic changes under domestication. While the number of QTL recovered in each subpopulation was similar, only 22 QTL were considered coincident (i.e., shared) between the two locations, eight of which shared peak markers. Although approximately half of QTL were located in the A-subgenome, many key fiber QTL were detected in the D-subgenome, which was derived from a species with unspinnable fiber. We found that many QTL are environment-specific, with few shared between the two environments, indicating that QTL associated with G. hirsutum domestication are genomically clustered but environmentally labile. Possible candidate genes were recovered and are discussed in the context of the phenotype. We conclude that the evolutionary forces that shape intraspecific divergence and domestication in cotton are complex, and that phenotypic transformations likely involved multiple interacting and environmentally responsive factors.

11.
G3 (Bethesda) ; 10(2): 769-781, 2020 02 06.
Artigo em Inglês | MEDLINE | ID: mdl-31852730

RESUMO

The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits.

12.
G3 (Bethesda) ; 9(12): 4235-4243, 2019 12 03.
Artigo em Inglês | MEDLINE | ID: mdl-31645422

RESUMO

Bulliform cells comprise specialized cell types that develop on the adaxial (upper) surface of grass leaves, and are patterned to form linear rows along the proximodistal axis of the adult leaf blade. Bulliform cell patterning affects leaf angle and is presumed to function during leaf rolling, thereby reducing water loss during temperature extremes and drought. In this study, epidermal leaf impressions were collected from a genetically and anatomically diverse population of maize inbred lines. Subsequently, convolutional neural networks were employed to measure microscopic, bulliform cell-patterning phenotypes in high-throughput. A genome-wide association study, combined with RNAseq analyses of the bulliform cell ontogenic zone, identified candidate regulatory genes affecting bulliform cell column number and cell width. This study is the first to combine machine learning approaches, transcriptomics, and genomics to study bulliform cell patterning, and the first to utilize natural variation to investigate the genetic architecture of this microscopic trait. In addition, this study provides insight toward the improvement of macroscopic traits such as drought resistance and plant architecture in an agronomically important crop plant.


Assuntos
Regulação da Expressão Gênica de Plantas , Aprendizado de Máquina , Folhas de Planta/genética , Característica Quantitativa Herdável , Zea mays/genética , Estudo de Associação Genômica Ampla
13.
Commun Biol ; 2: 295, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31396575

RESUMO

Graphics are becoming increasingly important for scientists to effectively communicate their findings to broad audiences, but most researchers lack expertise in visual media. We suggest collaboration between scientists and graphic designers as a way forward and discuss the results of a pilot project to test this type of collaboration.


Assuntos
Recursos Audiovisuais , Pesquisa Biomédica , Comportamento Cooperativo , Apresentação de Dados , Disseminação de Informação , Comunicação Interdisciplinar , Pesquisadores , Atitude do Pessoal de Saúde , Gráficos por Computador , Humanos , Percepção Visual
14.
G3 (Bethesda) ; 9(9): 3023-3033, 2019 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-31337639

RESUMO

Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The usefulness of endophenotypes for delineating the regulatory landscape of the genome and genetic dissection of complex trait variation remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299-genotype and seven-tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation acts through altered transcript abundance for maize kernel traits, including 30 grain carotenoid abundance traits, 20 grain tocochromanol abundance traits, and 22 field-measured agronomic traits. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the largely independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits than the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This not only improves the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Transcriptoma , Zea mays/genética , Análise de Variância , Regulação da Expressão Gênica de Plantas , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Fenótipo , Proteínas de Plantas/genética , Locos de Características Quantitativas
15.
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
16.
Heliyon ; 5(6): e01855, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31194086

RESUMO

A two-year field experiment was carried out in a randomized complete block design with two replications in 2015/16 and 2016/17 cropping seasons at the National Root Crops Research Institute, Umudike (05° 29'N; 07° 33'E; 122 m above sea level) in Nigeria. The objectives of the study were to assess growth, disease status and yield responses of twenty-eight (28) newly developed high- and low-cyanide cassava genotypes in low-land humid tropics of Umudike, Nigeria. Plant height, stem girth, canopy diameter, number of leaves/plant, cassava mosaic disease (CMD) and cassava bacterial blight (CBB) incidence and severity as well as bulking rate and fresh root yield varied significantly (P < 0.05) amongst the high- and low-cyanide cassava genotypes in both cropping seasons. Also, the results showed that bitter cassava genotypes exhibited greater tolerance to CMD than sweet cassava. However, there was no significant (P > 0.05) difference in bulking rate and fresh root yield between the two groups. The Pearson's and Spearman's ranked associations between fresh root yield of the cassava genotypes and other variables analysed across the two cropping seasons were highly significant (P ≤ 0.01) and positive contrary to the other variables. However, they exhibited different degrees of associations amongst themselves, especially CMD incidence that indicated highly significant and positive association with severity. The principal component analysis across the two cropping seasons indicated eigen-values of the four axes > unity with cumulative variance of 68.98 %. Most of the characters that contributed to the 22.35 % observed variability in principal component (PC1) were CMD incidence and severity, and number of leaves/plant while PC2 also exhibited high vector load from plant attributes such as number of leaves/plant, bulking rate ha-1 and canopy diameter. The bi-plot clustering indicated that genotypes (BI-56, NR110439 and B1-29) exhibited strong similarity amongst themselves across the tested variables. The combined fresh root yield sequence of the first ten high yielder genotypes was in the order: NR110439 > TMS010354 > NR110315 > NR 110238 > NR 110228 > NR 060169 > BI-117 > BI-50 > NR110084 > NR 110181. These cassava genotypes were considered to be better endowed genetically, hence their improvement can be encouraged to ensure high and sustainable root yield. A poly-linear and positive regression was recorded between CMD and root yield as well as between CBB and root yield indicating that they affected fresh root yield of high- and low-cyanide cassava genotypes and demands attention also in cassava improvement studies.

17.
Plant Genome ; 12(1)2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30951088

RESUMO

Sweet corn ( L.), a highly consumed fresh vegetable in the United States, varies for tocochromanol (tocopherol and tocotrienol) levels but makes only a limited contribution to daily intake of vitamin E and antioxidants. We performed a genome-wide association study of six tocochromanol compounds and 14 derivative traits across a sweet corn inbred line association panel to identify genes associated with natural variation for tocochromanols and vitamin E in fresh kernels. Concordant with prior studies in mature maize kernels, an association was detected between γ-tocopherol methyltransferase (vte4) and α-tocopherol content, along with () and () for tocotrienol variation. Additionally, two kernel starch synthesis genes, () and (), were associated with tocotrienols, with the strongest evidence for in combination with fixed, strong and alleles, accounting for the greater amount of tocotrienols in and lines. In prediction models with genome-wide markers, predictive abilities were higher for tocotrienols than tocopherols, and these models were superior to those that used marker sets targeting a priori genes involved in the biosynthesis and/or genetic control of tocochromanols. Through this quantitative genetic analysis, we have established a key step for increasing tocochromanols in fresh kernels of sweet corn for human health and nutrition.


Assuntos
Tocoferóis/metabolismo , Tocotrienóis/metabolismo , Zea mays/genética , Genes de Plantas , Marcadores Genéticos , Variação Genética , Estudo de Associação Genômica Ampla , Genômica , Fenótipo , Melhoramento Vegetal , Zea mays/metabolismo
18.
Nutrients ; 11(4)2019 Apr 12.
Artigo em Inglês | MEDLINE | ID: mdl-31013776

RESUMO

Improving the nutritional quality of Fe in maize (Zea mays) represents a biofortification strategy to alleviate iron deficiency anemia. Therefore, the present study measured iron content and bioavailability via an established bioassay to characterize Fe quality in parts of the maize kernel. Comparisons of six different varieties of maize demonstrated that the germ fraction is a strong inhibitory component of Fe bioavailability. The germ fraction can contain 27-54% of the total kernel Fe, which is poorly available. In the absence of the germ, Fe in the non-germ components can be highly bioavailable. More specifically, increasing Fe concentration in the non-germ fraction resulted in more bioavailable Fe. Comparison of wet-milled fractions of a commercial maize variety and degerminated corn meal products also demonstrated the inhibitory effect of the germ fraction on Fe bioavailability. When compared to beans (Phaseolus vulgaris) containing approximately five times the concentration of Fe, degerminated maize provided more absorbable Fe, indicating substantially higher fractional bioavailability. Overall, the results indicate that degerminated maize may be a better source of Fe than whole maize and some other crops. Increased non-germ Fe density with a weaker inhibitory effect of the germ fraction are desirable qualities to identify and breed for in maize.


Assuntos
Biofortificação/métodos , Cruzamento , Manipulação de Alimentos , Ferro/farmacocinética , Valor Nutritivo , Sementes/química , Zea mays/química , Disponibilidade Biológica , Células CACO-2 , Humanos , Absorção Intestinal , Ácido Fítico , Especificidade da Espécie , Zea mays/classificação
19.
G3 (Bethesda) ; 9(6): 1945-1955, 2019 06 05.
Artigo em Inglês | MEDLINE | ID: mdl-31010822

RESUMO

Rapid development and adoption of biofortified, provitamin A-dense orange maize (Zea mays L.) varieties could be facilitated by a greater understanding of the natural variation underlying kernel color, including as it relates to carotenoid biosynthesis and retention in maize grain. Greater abundance of carotenoids in maize kernels is generally accompanied by deeper orange color, useful for distinguishing provitamin A-dense varieties to consumers. While kernel color can be scored and selected with high-throughput, low-cost phenotypic methods within breeding selection programs, it remains to be well established as to what would be the logical genetic loci to target for selection for kernel color. We conducted a genome-wide association study of maize kernel color, as determined by colorimetry, in 1,651 yellow and orange inbreds from the Ames maize inbred panel. Associations were found with y1, encoding the first committed step in carotenoid biosynthesis, and with dxs2, which encodes the enzyme responsible for the first committed step in the biosynthesis of the isoprenoid precursors of carotenoids. These genes logically could contribute to overall carotenoid abundance and thus kernel color. The lcyE and zep1 genes, which can affect carotenoid composition, were also found to be associated with colorimeter values. A pathway-level analysis, focused on genes with a priori evidence of involvement in carotenoid biosynthesis and retention, revealed associations for dxs3 and dmes1, involved in isoprenoid biosynthesis; ps1 and vp5, within the core carotenoid pathway; and vp14, involved in cleavage of carotenoids. Collectively, these identified genes appear relevant to the accumulation of kernel color.


Assuntos
Genoma de Planta , Estudo de Associação Genômica Ampla , Genômica , Redes e Vias Metabólicas , Pigmentação , Zea mays/genética , Zea mays/metabolismo , Estudos de Associação Genética , Genômica/métodos , Fenótipo , Polimorfismo de Nucleotídeo Único
20.
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
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