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Genomewide selection is hailed for its ability to facilitate greater genetic gains per unit time. Over breeding cycles, the requisite linkage disequilibrium (LD) between quantitative trait loci and markers is expected to change as a result of recombination, selection, and drift, leading to a decay in prediction accuracy. Previous research has identified the need to update the training population using data that may capture new LD generated over breeding cycles; however, optimal methods of updating have not been explored. In a barley (Hordeum vulgare L.) breeding simulation experiment, we examined prediction accuracy and response to selection when updating the training population each cycle with the best predicted lines, the worst predicted lines, both the best and worst predicted lines, random lines, criterion-selected lines, or no lines. In the short term, we found that updating with the best predicted lines or the best and worst predicted lines resulted in high prediction accuracy and genetic gain, but in the long term, all methods (besides not updating) performed similarly. We also examined the impact of including all data in the training population or only the most recent data. Though patterns among update methods were similar, using a smaller but more recent training population provided a slight advantage in prediction accuracy and genetic gain. In an actual breeding program, a breeder might desire to gather phenotypic data on lines predicted to be the best, perhaps to evaluate possible cultivars. Therefore, our results suggest that an optimal method of updating the training population is also very practical. [ABSTRACT FROM AUTHOR]

Robust predictions of genetic variances for important traits would facilitate greater genetic gains in plant breeding. Previous attempts to predict the genetic variance ( σ G 2 ) of traits in bi-parental breeding populations were inconsistent and context specific. The weakness of methods that consider the phenotypic distance, genetic distance, and relationship-based distance of pairs of parents, which we collectively term historical methods, stems from the fact that they do not explicitly model the segregation of the underlying genetic effects for a trait within a population. To address this issue, we propose the use of three modern methods made possible by the commonplace use of genomewide molecular marker data and genomic selection in modern breeding programs. These modern methods utilize both phenotypic and genotypic records to, in varying degrees, explicitly model the segregation of informative genomewide markers to predict σ G 2 in bi-parental breeding populations. In this study, we evaluate the accuracy of historical and modern methods to predict σ G 2 using 40 field-tested bi-parental barley breeding populations evaluated during 2003–2010 for Fusarium head blight severity. In general, the modern methods predicted the field-based estimates of σ G 2 more accurately than the historical methods. Specifically, the modern method that most explicitly models the segregation of informative genomewide markers, called ‘PopVar,’ was the most accurate σ G 2 prediction method. [ABSTRACT FROM AUTHOR]

Predicting genetic variances of biparental populations has been a long-standing goal for plant breeders. The ability to discriminate among crosses with similarly predicted high means but different levels of genetic variance (VG) should improve the effectiveness of breeding. We developed a procedure that uses established progeny simulation and genomic prediction strategies to predict the population mean (μ) and VG, the mean of the desired 10% of the progeny (superior progeny mean [μsp]), and correlated responses of multiple traits for biparental populations. The proposed procedure, PopVar, is herein demonstrated using a training population (TP) composed of 383 breeding lines that have been genotyped and phenotyped for yield and deoxynivalenol (DON). Marker effects estimated from the TP were used to calculate genotypic estimated breeding values (GEBVs) of 200 simulated recombinant inbred lines (RILs) per cross. Values of μ, VG, and μsp were then calculated directly from the RIL GEBVs. We found that μ explained 82 and 88% of variation in μsp for yield and DON, respectively, and adding VG to the regression model increased those respective R2 values to 99.5 and 99.6%. The results of correlated response revealed that although yield and DON are unfavorably correlated, the correlation was near zero or slightly negative in some simulated crosses, indicating the potential to increase yield while decreasing DON. This work extends the current benefits of genomic selection to include the ability to design crosses that maximize genetic variance with more favorable correlations among traits. PopVar is available as an R package that researchers and breeders are encouraged to use for empirical evaluation of the methodology. [ABSTRACT FROM AUTHOR]

The general applicability of genomic selection (GS) to plant breeding and principles guiding its use have been established by simulation and empirical cross-validation studies. More recently, studies have demonstrated genetic gains over multiple cycles of selection in a variety of crop species. In this study, we provide additional evidence for the effectiveness of GS in an actual breeding program by demonstrating significant gains of 186.1 kg ha−1 and − 1.85 ppm for grain yield and deoxynivalenol, respectively, two unfavorably correlated quantitative traits, across 3 cycles of selection in a spring six-row barley breeding population. With its general effectiveness established, the next step is to increase the accuracy of predictions used in GS and thereby increase genetic gains. For this, we first showed that updating the training population (TP) with phenotyped lines from recent breeding cycles, specifically selected lines, had an overall positive effect on prediction accuracy. Additionally, we investigated four recently proposed algorithms that seek to optimize the composition of a TP. Overall, the optimization algorithms improved prediction accuracy when compared to a randomly selected TP subset of the same size, but which algorithm performed best was dependent on the trait being predicted and other factors discussed within. This retrospective investigation highlights the importance of maintaining and optimizing the TP when using GS in applied breeding to maximize prediction accuracy, thereby maximizing gain from selection and resource utilization efficiency. [ABSTRACT FROM AUTHOR]

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In-field estimation of alfalfa ( Medicago sativa L.) yield and nutritive value can inform management decisions to optimize forage quality and production. However, acquisition of timely information at the field scale is limited using traditional measurements such as destructive sampling and assessment of plant maturity. Remote sensing technologies (e.g., measurement of canopy reflectance) have the potential to enable rapid measurements at the field scale. Canopy reflectance (350–2500 nm) and Light Detection and Ranging (LiDAR)-estimated canopy height were measured in conjunction with destructive sampling of alfalfa across a range of maturities at Rosemount, MN in 2014 and 2015. Sets of specific spectral wavebands were determined via stepwise regression to predict alfalfa yield and nutritive value and models were reduced by spectral range to improve utility. Cumulative growing degree units (GDUs) and canopy height were tested as model covariates. An alternative GDU calculation (GDU ALT ) using a temporally graduating base temperature was also tested against the traditional static base temperature. The inclusion of GDU ALT increased prediction accuracy for all response variables by 9–17%. Models using a common set of seven wavebands, combined with GDU ALT , explained 81–90% of the variability in yield, crude protein (CP), neutral detergent fiber (NDF), and NDF digestibility (NDFd; 48-h in-vitro), respectively. This research establishes potential for remote sensing measurements to be integrated with air temperature information to achieve rapid and accurate predictions of alfalfa yield and nutritive value at the field scale for optimized harvest management. [ABSTRACT FROM AUTHOR]

Key message: Oat crown rust is one of the most damaging diseases of oat. We identified a new source of resistance and developed KASP and TaqMan markers for selection in breeding programs.Abstract: A new highly effective resistance to oat crown rust (Puccinia coronata f. sp. avenae) was identified in the diploid oat Avena strigosa PI 258731 and introgressed into hexaploid cultivated oat. Young plants with this resistance show moderate susceptibility, whereas older plant tissues and adult plants are resistant with no virulent isolates encountered in over 8 years of testing. Resistance was incorporated into hexaploid oat by embryo rescue, colchicine chromosome doubling followed by backcrosses with a hexaploid parent, and selection for stable transmission of resistance. To mitigate flag leaf and panicle chlorosis/necrosis associated with the resistance, crosses were made with derived resistant lines to breeding lines of divergent parentage followed by selection. Subsequently, two F2 sister lines, termed MNBT1020-1 and MNBT1021-1, were identified in which the chlorosis/necrosis was reduced. These two lines performed well in replicated multi-location state trials in 2015 and 2016 out-yielding all cultivar entries. Segregating F2:3 plants resulting from crosses of MNBT lines to susceptible parents were genotyped with the oat 6K SNP array, and SNP loci with close linkage to the resistance were identified. KASP assays generated from linked SNPs showed accurate discrimination of the resistance in derivatives of the resistant MNBT lines crossed to susceptible breeding lines. A TaqMan marker was developed and correctly identified homozygous resistance in over 95% of 379 F4 plants when rust was scored in F4:5 plants in the field. Thus, a novel highly effective resistance and associated molecular markers are available for use in breeding, genetic analysis, and functional studies. [ABSTRACT FROM AUTHOR]

Vitamin E refers to eight distinct compounds collectively known as tocochromanols and can be further divided into two classes, tocotrienols and tocopherols. Tocochromanols are the major lipid-soluble antioxidants in maize (Zea mays L.) grain. Enhancing vitamin E content of maize through plant breeding has important implications for human and animal nutrition. Four inbred lines exhibiting unique variation for tocochromanol compounds were chosen from the Goodman maize diversity panel to construct two biparental mapping populations (N6xNC296 and E2558xCo125). The N6xNC296 population was developed to analyze segregation for α-tocopherol and α-tocotrienol content. The E2558WxCo125 population was developed to analyze segregation for the ratio of total tocotrienols to tocopherols. The tocochromanol variation in two replicates of each population was quantified using liquid chromatography-diode array detection. Using high-density linkage mapping, novel quantitative trait loci (QTL) in the N6xNC296 population were mapped using tocopherol ratio traits. These QTL contain the candidate gene homogentisate phytyltransferase (ZmVTE2) within the respective support intervals. This locus was not mapped in a previous genome-wide association study that analyzed tocochromanols in the Goodman diversity panel. Transgressive segregation was observed for γ- and α-tocochromanols in these populations, which facilitated QTL identification. These QTL and transgressive segregant families can be used in selection programs for vitamin E enhancement in maize. This work illustrates the complementary nature of biparental mapping populations and genome-wide association studies to further characterize genetic variation of tocochromanol content in maize grain. [ABSTRACT FROM AUTHOR]

An oil-in-sea ice mesocosm experiment was conducted at the University of Manitoba Sea-Ice Environmental Research Facility from January to March 2016 in which geophysical and electromagnetic parameters of the ice were measured, and general observations about the oil-contaminated ice were made. From the experimental measurements, the presence of crude oil appears to affect the temperature and bulk salinity profiles as well as the normalized radar cross section (NRCS) of the contaminated young sea ice. The measured temperature and bulk salinity profiles of the ice, as well as the crude oil distribution within the ice, were used to model the permittivity profile of the oil-contaminated ice by adapting two mixture models commonly used to describe sea ice to account for the presence of oil. Permittivity modeling results were used to simulate the NRCS of the oil-contaminated sea ice in an effort to determine the accuracy of the models. In addition, the application of X-ray microtomography in modeling the dielectric profile of oil-contaminated sea ice was examined. The sensitivity of the permittivity models for oil-contaminated sea ice to changes in temperature, frequency, and oil volume fraction was also examined. [ABSTRACT FROM AUTHOR]

Tocopherols, tocotrienols, and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot Arabidopsis thaliana , which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are nonphotosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5000-line U.S. maize (Zea mays) nested association mapping panel. Fifty-two quantitative trait loci for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted given that, like most major cereal crops, maize grain is nonphotosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops. [ABSTRACT FROM AUTHOR]

This paper presents a multidisciplinary case study on a crude oil injection experiment in an artificially grown young sea ice environment under controlled conditions. In particular, the changes in the geophysical and electromagnetic responses of the sea ice to oil introduction are investigated for this experiment. Furthermore, we perform a preliminary study on the detection of oil spills utilizing the normalized radar cross section (NRCS) data collected by a C-band scatterometer is presented. To this end, an inversion scheme is introduced that retrieves the effective complex permittivity of the domain prior and after oil injection by comparing the simulated and calibrated measured NRCS data, while roughness parameters calculated using lidar are utilized as prior information. Once the complex permittivity values are obtained, the volume fraction of oil within the sea ice is found using a mixture formula. Based on this volume fraction, a binary detection of oil presence seems to be possible for this test case. Finally, the possible sources of error in the retrieved effective volume fraction, which is an overestimate of the actual value, are identified and discussed by macrolevel and microlevel analyses through bulk salinity measurements and X-ray imagery of the samples, as well as a brief chemical analysis. [ABSTRACT FROM PUBLISHER]

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A. [ABSTRACT FROM AUTHOR]