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Advancements in genotyping are rapidly decreasing marker costs and increasing genome coverage. This is facilitating the use of marker-assisted selection (MAS) in plant breeding. Commonly employed MAS strategies, however, are not well suited for agronomically important complex traits, requiring extra time for field-based phenotyping to identify agronomically superior lines. Genomic selection (GS) is an emerging alternative to MAS that uses all marker information to calculate genomic estimated breeding values (GEBVs) for complex traits. Selections are made directly on GEBV without further phenotyping. We developed an analytical framework to (i) compare gains from MAS and GS for complex traits and (ii) provide a plant breeding context for interpreting results from studies on GEBV accuracy. We designed MAS and GS breeding strategies with equal budgets for a high-investment maize (Zea mays L.) program and a low-investment winter wheat (Triticum aestivum L.) program. Results indicate that GS can outperform MAS on a per-year basis even at low GEBV accuracies. Using a previously reported GEBV accuracy of 0.53 for net merit in dairy cattle, expected annual gain from GS exceeded that of MAS by about threefold for maize and twofold for winter wheat. We conclude that if moderate selection accuracies can be achieved, GS could dramatically accelerate genetic gain through its shorter breeding cycle. doi: 10.2135/cropsci2009.11.0662

Seed dormancy, the main factor contributing to preharvest sprouting (PHS) resistance, is a complex trait and is strongly influenced by environmental growth conditions. In this study, three sets of single chromosome substitution lines, including 36 genotypes, in a durum wheat [Triticum turgidum L. ssp. durum (Desf.) Husn.] background with donor chromosomes originating from three wild emmer [T. turgidum L. ssp. dicoccoides (Korn. ex Asch. and Graebn.) Thell.] accessions were grown in nine field environments and evaluated for seed dormancy and PHS resistance. The substitution lines involving chromosome 3A were among the most dormant genotypes. Germination tests indicated that five chromosomes contained genes influencing seed dormancy at a level comparable to 3A. Results from PHS tests showed that PHS was affected by at least eight T. dicoccoides chromosomes including 3A. The chromosomes harboring genes for seed dormancy did not fully correspond with those for PHS resistance. The weak correlations between PHS and dormancy observed in this study indicate that different genes are affecting these traits and they may be differentially influenced by the environment. Nonetheless, our results revealed that genes present on five chromosomes, 2A, 2B, 3A, 4A, and 7B, were found to affect both PHS resistance and seed dormancy. These genotypes thus provide useful resources for further studies on genetic interactions that contribute to the overall phenotypic variation and on genetic dissection of quantitative trait loci underlying PHS resistance. doi: 10.2135/cropsci2009.10.0589

Despite important strides in marker technologies, the use of marker-assisted selection has stagnated for the improvement of quantitative traits. Biparental mating designs for the detection of loci affecting these traits (quantitative trait loci [QTL]) impede their application, and the statistical methods used are ill-suited to the traits' polygenic nature. Genomic selection (GS) has been proposed to address these deficiencies. Genomic selection predicts the breeding values of lines in a population by analyzing their phenotypes and high-density marker scores. A key to the success of GS is that it incorporates all marker information in the prediction model, thereby avoiding biased marker effect estimates and capturing more of the variation due to small-effect QTL. In simulations, the correlation between true breeding value and the genomic estimated breeding value has reached levels of 0.85 even for polygenic low heritability traits. This level of accuracy is sufficient to consider selecting for agronomic performance using marker information alone. Such selection would substantially accelerate the breeding cycle, enhancing gains per unit time. It would dramatically change the role of phenotyping, which would then serve to update prediction models and no longer to select lines. While research to date shows the exceptional promise of GS, work remains to be done to validate it empirically and to incorporate it into breeding schemes.

Association analysis is a method potentially useful for detection of marker-trait associations based on linkage disequilibrium, but little information is available on the application of this technique to plant breeding populations. With appropriate statistical methods, valid association analysis can be done in plant breeding populations; however, the most significant marker may not be closest to the functional gene. Bias can arise from (i) covariance among markers and QTL, frequently related to population structure or intense selection and (ii) differences in initial frequencies of marker alleles in the population, such that exclusive alleles tend to be in higher association. The potentials and limitations of germplasm bank collections, synthetic populations, and elite germplasm are compared, as experimental materials for association analysis integrated with plant breeding practice. Synthetics offer a favorable balance of power and precision for association analysis and would allow mapping of quantitative traits with increasing resolution through cycles of intermating. A model to describe the association between markers and genes as conditional probabilities in synthetic populations under recurrent selection is proposed, which can be computed on the basis of assumptions related to the history of the population. This model is useful for predicting the potential of different populations for association analysis and forecasting the response to marker-assisted selection., ASSOCIATION ANALYSIS (AA), also known as association mapping or linkage disequilibrium mapping, is a method that relies on linkage disequilibrium to study the relationship between phenotypic variation and genetic polymorphisms [...]

Hybridizations between hard and soft wheat types could be a source of novel variation for wheat quality improvement. This study was conducted to identify genomic regions related to differences in milling and baking quality between a soft and a hard cultivar of hexaploid wheat (Triticum aestivum L.). A population of 101 double-haploid lines was generated from a cross between Grandin, a hard spring wheat variety, and AC Reed, a soft spring wheat variety. The genetic map included 320 markers in 43 linkage groups and spanned 3555 cM. Quadrumat-milled flour yield, softness equivalent, flour protein content and alkaline water retention capacity were evaluated for three locations and one year, and Allis-Chalmers milling, mixograph, and cookie baking tests were completed without replication. The effect of qualitative variation for kernel texture, caused by the segregation of the Hardness gene, was controlled by regression on texture class. The residual variance was used for composite interval mapping, and QTLs on 1A, 1B, 1A/D, 2A, 2B, 2D, 3A/B, 4B, 5B and 6B were detected. The effect of some QTLs was opposite to the direction expected on the basis of parental phenotypes. The hard wheat parent contributed alleles favorable for soft wheat varieties at QTLs on LAS,L, 1BL-2, and 6B, whereas the soft parent contributed alleles for higher protein content at QTLs on 2BL-1, 4B-1, and 6B and higher flour yield on 2BL-2 and 4B-2. These results indicated that hard x soft wheat crosses have considerable potential for improving milling and baking quality of either class., THE TEXTURE OF GRAIN of hexaploid wheat is either hard or soft, each resulting in flour with different processing and end-use characteristics, which depend on protein hydration and development through [...]

Preharvest sprouting (PHS) can severely damage barley (Hordeum vulgare L.) malting quality and is of particular concern in locations with a high frequency of precipitation around harvest. Malting quality and PHS resistance are often negatively correlated, and the SD2 locus on chromosome 5H has been associated with both traits. Using three spring barley populations, PHS, seed dormancy, and germination rate were mapped over six time points to identify changes in genetic control of these traits during the after‐ripening period. HvAlaAT1 at the SD1 locus was associated with long‐term dormancy and reduced germination rate. Ninety lines were Sanger sequenced for HvGA20ox1, but variants were not associated with PHS or germination traits. The allelic state of HvMKK3 was strongly associated with genetic PHS susceptibility in North American spring two‐row barley germplasm and interactions between HvAlaAT1 and HvMKK3 were associated with changes in seed dormancy and germination rate over time. Several malting quality traits were associated with HvMKK3 alleles. Kompetitive allele‐specific polymerase chain reaction (KASP) markers were developed for the causal mutations in HvAlaAT1 and HvMKK3 and a diagnostic mutation in HvGA20ox1. Haplotypes with PHS resistance, short primary dormancy, and a high germination rate were identified that could be useful for breeding for PHS resistance and malting quality. Core Ideas: Pleiotropic effects of the SD2 locus in barley are associated with multiple alleles of HvMKK3.HvGA20ox1 variants had minor to no effect on dormancy or malting quality traits.Dormancy release and germination rate were associated with HvMKK3 and HvAlaAT1 interaction.KASP markers for dormancy genes can support breeding for PHS and malting quality. [ABSTRACT FROM AUTHOR]

Preharvest sprouting (PHS) resistance is essential in malting barley (Hordeum vulgare L.) production to prevent damage caused by late season moisture but may be negatively correlated with malting quality traits. The germination percentage and germination rate (GI) in malting barley are measures of both PHS resistance and suitability for malting. Functional principal component analysis (FPCA) and logistic regression on time series spring malting barley GE and GI were performed to identify genetic regions associated with germination trait changes from 0 to 22 wk after maturity. Both analysis methods identified the SD1 and SD2 regions known to affect germination traits, as well as one novel locus on chromosome 6H at 473 Mbp. Several other associations were detected with a single analysis method. Genomic prediction (GP) was used in conjunction with the time series models to test GE and GI predictability over time. Germination traits of unobserved lines at unobserved times were predicted with high accuracy using ridge regression GP coupled with FPCA or logistic regression. The results demonstrate applicability of time series data analysis in determining genetics of germination trait changes in malting barley and that time series germination is predictable. Threshold traits calculated with these time series models, such as the after‐ripening time needed until a line achieves a GE of 95%, can be used as an estimate for dormancy duration, which will be useful in breeding for combined PHS resistance and malting quality. Core Ideas: Functional principal component analysis (FPCA) and logistic regression are applicable to germination trait modeling.Association with FPCA and logistic models identified known and novel loci affecting germination.FPCA and logistic models coupled with genomic prediction predict traits with high accuracy.Time series modeling applies to breeding for preharvest sprouting resistance and malting traits. [ABSTRACT FROM AUTHOR]

The use of conventional breeding methods has resulted in consistent crop improvement within the cultivated gene pool by producing genotypes with new combinations of alleles that produce better phenotypes than either of the parents (transgressive segregation). Biotechnology has provided new methods to generate, identify, characterize, and manipulate genetic variation. Among these methods, marker assisted selection (MAS) with DNA markers has been applied in plant improvement programs. However, MAS is limited by the effort required to generate information about map location and breeding value of genes controlling important traits. Comparative genetic analysis across the domesticated grasses facilitates the identification and localization of gene sequences controlling specific traits of Interest. The emerging databases of gene sequences will allow directed discovery of genes in higher plants and classification of alleles present within breeding germplasm. Identification of the genes controlling a trait and knowledge of their DNA sequence would facilitate classification Of variation in the germplasm pool based on gem fingerprinting or characterization of variation in key DNA sequences. Classification of sequence variants at a targeted locus would substantially reduce the amount of work required to determine their relative breeding value and lead to the identification of superior alleles. Combining direct allele selection (DAS) with conventional selection, would allow more rapid and precise improvement of populations and breeding lines. Limitations of current technology can be minimized by transfer of genetic information across species, identification of highly variable genes, and focusing on the most important genes and traits for the species of interest., Modern breeding methods have resulted in consistent crop improvement by manipulating variation within cultivated gene pools throughout the twentieth century. Molecular techniques have been developed that enhance the fundamental biometrical [...]

Estimation of genetic diversity present in gene pools is an important determination for breeding programs. This study was conducted to determine the level of variation in durum wheat cultivars (Triticum turgidum L. var durum) based on different measures. Genetic diversity in durum wheat was measured in a collection of 113 improved cultivars and landraces of diverse ecogeographicai origin by means of restriction fragment length polymorphism (RFLP), morphophysiological traits, and coefficient of parentage (COP). Thirty-nine clones and a single restriction enzyme were used to measure the RFLP-based genetic distance. Average taxonomic distances were calculated for the morphophysiological traits evaluated in four location-years. Lower genetic distances were observed for both RFLP and morphophysiological traits for the improved cultivars and for some landraces from Morocco and Jordan, while genetic distances were larger for the rest of the landraces. Patterns of variation for morphophysiological traits were associated with days to heading, plant height, and harvest index. Landraces contained 99% of the total fragments observed in the pool of improved varieties and showed 13% unique fragments. Coefficient of parentage analysis revealed 15 ancestral lines that contributed 72% of the genetic make up of improved cultivars. Thirty-nine different ancestors contributed to the remaining 28%. Correlation of distances based on different measures was higher for average taxonomic distance and Nei's genetic distance (r = 0.47) while COP relationship with the other two measures was lower. Narrower genetic diversity in breeding lines based on the measures used, suggests the utilization of other sources of variation.

Fertility restoration for Triticum timopheevi Zhuk. cytoplasmic male sterility in wheat (Triticum aestivum L.) is controlled by both major fertility restorer (Rf) genes and modifier genes together with environment effects. Therefore, the breeding of efficient and stable male-fertility restorer lines (R-lines) should be facilitated by marker-assisted selection. This study was conducted to identify restriction fragment length polymorphism (RFLP) markers for the Rf genes, Rf1 and Rf4 in restorer line R113, and Rf3 and a Rf gene on 5D in cultivar Primepi. Polymorphic markers were mapped in testcross [F.sub.1] populations and their association with fertility restoration was analyzed by analysis of variance. The results indicated that Rf4 was linked to Xksug48 located on 6BS in R113, Rf3 was linked to Xbcd249 and Xcdo442 on lBS, and Xcdo786 may be associated with the 5D Rf gene in Primepi. In addition, in R113 two other chromosome regions with fertility restoration-associated loci were detected by CD0786 and H1 on 5AL and CDO1189 on 7BS. A locus on 5DS, detected by BCD1871, showed significant epistatic effect on the expression of Rf genes. In Primepi, a locus on 5AL, detected by Xbcd183 and Xbcd876, had effects similar to Xcdo786. Two loci in 'Qu Xian Early A', identified by Xbcd871 and Xwg1026, may be associated with genes controlling ease of restoration in this male-sterile line (A-line). Except for Xbcd1871 and Xwg1026, the effects of other significant RFLP loci were additive in both populations.

Resistance to preharvest sprouting (PHS) is difficult to incorporate into new varieties because heritability is low and selection is limited to one generation per year. Our objective was to identify genomic regions containing quantitative trait loci (QTL) associated with resistance to PHS in two recombinant inbred (R) populations of white wheat (Triticum aestivum L. em. Thell.) by restriction fragment length polymorphism (RFLP) markers. One populations of white lines from the cross of NY6432-18 (NY18) x |Clark's Cream' (CC). The second population consisted of 138 RI lines from the cross between sib lines NY 18 and NY6432-10 (NY10). The NY18/CC and NY18/10 populations were evaluated for PHS in six and seven environments, respectively, be examining physiologically mature spikes under simulated rainfall. The three parental lines were surveyed for polymorphism with 195 low-copy RFLP clones. Individual RI lines from the NY18/CC and NY18/NY10 populations were probed with 37 and 27 polymorphic clones, respectively. Eight regions of the genome (four from each population) were significantly associated with resistance to PHS. Based on multiple regression, specific sets of markers and their interactions accounted for 44% of the genetic variance for PHS in the NY18/CC and 51% in the NY18/NY10 populations. These markers could find utility in breeding programs as indirect selection criteria for improvement of PHS resistance.

Genomic selection (GS) can improve genetic gain of complex traits in plant breeding. Phenotyping agronomic traits of winter wheat (Triticum aestivum L.) for dual‐purpose use is expensive and time‐consuming. In this study, we compared the prediction accuracies of four GS models (RR‐BLUP, GBLUP, GAUSS, and BL) for forage yield (FY), plant height (PH) and heading date (HD) of the hard winter wheat diversity panel (n = 298) using random and stratified sampling methods. In addition, we determined the appropriate training population (TP) size and marker density for GS of the traits. Moderate to high prediction accuracies ranging from 0.66 to 0.69 for FY, 0.46 to 0.49 for PH, and 0.71 to 0.74 for HD were observed for the GS models. However, the sampling method had little or no impact on prediction accuracy. The RR‐BLUP, GBLUP, and GAUSS models produced slightly greater prediction accuracies than BL for all traits studied. Prediction accuracies increased with increasing TP size and marker density in all the GS models tested. However, increase of prediction accuracy started to plateau at nTP = 180 lines and 1,000; 1,500; or 3,000 SNPs suggesting that the minimum TP size and marker density were about 180 lines and 1,000 or more SNPs, depending on the model and trait. The impact of TP size on prediction accuracy was greater for RR‐BLUP, GAUSS, and GBLUP than for BL model. This study suggests that RR‐BLUP, GBLUP, and GAUSS are viable models for selecting the forage agronomic traits during dual‐purpose wheat breeding. [ABSTRACT FROM AUTHOR]

Breeding programs for wheat (Triticum aestivum L.) and other crops require one or more generations of seed increase before replicated trials can be sown to assess yield. Extensive phenotyping at this stage is challenging because of the small sizes of plots and large numbers of lines under evaluation, and therefore, breeders typically rely on visual selection to promote lines to yield evaluation. Aerial high‐throughput phenotyping (HTP) enables the rapid acquisition of traits that may be useful for selection among early generation lines. With the objective of assessing the potential for aerial measurements recorded on seed increase plots to improve indirect selection for grain yield (GY), two sets of 1,008 early generation bread wheat breeding lines were sown both as replicated yield trials (YTs) and as small, unreplicated plots (SPs) at the International Maize and Wheat Improvement Center during two breeding cycles. Normalized difference vegetation indices (NDVI) collected with an unmanned aerial vehicle (UAV) in the SPs were observed to be heritable and moderately correlated with GY assessed in YTs. Furthermore, NDVI was more predictive of GY than univariate genomic selection (GS), with still higher overall predictive abilities from multitrait approaches. A related experiment showed that selection based on NDVI would have outperformed visual selection, though this approach would have driven a directional response in phenology because of confounding between phenology, NDVI, and GY. A restricted selection index was proposed to address this issue. These results provide a promising outlook for the use of aerial HTP to improve selection at the early generation, seed‐limited stages of breeding programs. [ABSTRACT FROM AUTHOR]

Optimizing wheat (Triticum aestivum L.) genotypes for organic production can improve lagging yields worldwide. New genetic improvement programs, such as for organic wheat, require an understanding of genotype x environment interactions. Over 6 yr at 10 organically managed sites in the northeastern and northcentral United States, we assessed genotype x environment interactions for yield, test weight, protein, and falling number. We used an additive main effects and multiplicative interactions model to identify mega-environments with distinct variety performance throughout the northeastern United States. Results indicate that organic wheat breeding and variety testing programs should decentralize selection into multiple locations. After determining the impact of changes in genotype performance across years, we assessed genotypes for stability in yield, test weight, protein, and falling number. Breeding for stability should be prioritized for the northeastern and north-central United States, due to the large contribution of genotype x year interactions. [ABSTRACT FROM AUTHOR]

Interclass hybridization between soft and hard wheat (Triticum aestivum L.) results in new genetic combinations of potential value. We investigated whether interclass hybridization could improve end-use quality of both classes. Our objectives were to analyze quality traits in a population of recombinant inbred lines (RILs) derived from a cross between the good quality soft white wheat NY6432-18 (NY18), and good quality hard white wheat Clark's Cream (CC), identify quantitative trait loci (QTLs) for those traits, and use linkage analysis to determine which parent was contributing favorable alleles at specific QTLs for a given trait. The population was assessed for milling, protein and dough mixing, hydration, cookie and loaf traits. Traits were measured in two to six environments grown over three seasons in Ithaca, NY. The molecular map for the population contains 370 molecular markers including restiction fragment length polymorphisms (RFLPs), microsatellites, and markers derived from known function genes in wheat. Linkage groups have been located to all the wheat chromosomes except for 7D. Pinb derived from the puroindoline b gene on chromosome 5DS was the major QTL for milling, hydration, and cookie baking traits. The major QTL for mixograph peak time was at the Glu-Dy1 marker, derived from Glu-D1-2 gene on chromosome 1DL. The Glu-Ax1 and Glu-By1 markers were QTLs for mixograph peak height and tolerance, respectively. QTLs for flour protein quantity were detected on chromosome 2B. With the exception of the hydration traits, multiple regression models included alleles from both parents. Interclass hybridization may be an underexploited wheat breeding strategy for improvement of agronomic and quality traits in wheat., FEW WHEAT breeders routinely practice hybridizations among wheat classes because of the difficulty in recovering desired end-use quality characteristics. Hybridization between soft and hard wheat creates new associations among loci. [...]

Kernel morphology and texture influence the value of wheat (Triticum aestivum L.). The objectives of this study were to determine associations between kernel traits and molecular markers and to identify quantitative trait loci (QTLs) affecting kernel traits in a soft x hard white wheat cross. Seventy eight [F.sub.2:5]-derived recombinant inbred lines (RILs) from a cross between the soft white wheat NY6432-18 (NY18) and the hard white wheat `Clark's Cream' (CC) were developed by single seed descent. Kernel texture was measured by near infrared reflectance (NIR) on RIL grain samples from six environments. Digital image analysis (DIA) was used to measure kernel length, width, area, perimeter on grain samples from four environments. Test weight and thousand kernel weight (TKW) were also determined. Shape factor and density factor were calculated. The map for this population consisted of 313 molecular markers in 47 linkage groups located on all wheat homoeologous chromosome groups. Linkage groups that mapped to wheat homoeologous group 2 chromosomes were highly skewed towards NY18 alleles. Genotype effects and genotype X environment interactions were highly significant for most traits. QTLs for kernel width and kernel length also influenced kernel area and TKW, but did not influence each other. The pinB marker at the puroindoline B locus on chromosome 5DS explained over 60% of the phenotypic variation for kernel texture. QTLs for kernel traits were located on chromosomes 1A, 2B, 2D, 3B, 7A, and 7B., THE ECONOMIC VALUE of the U.S. wheat crop is determined by class, which depends in part on kernel morphology and texture, and by test weight. Inspectors for the U.S. Grain [...]

Seed size and shape are important traits that have been altered during domestication and are monitored in wheat (Triticum aestivum L.) breeding programs because they may impact yield and milling quality. Quantitative trait loci (QTL) for seed morphology were mapped in two doubled-haploid (DH) wheat populations using three seed axes and elliptic Fourier descriptors of shape. In the Synthetic W7984 × Opata M85 (SynOpDH) population, 31 QTL were detected on all chromosomes except 3D, 4D, 5D, 6B, and 7B. Seed shape QTL in SynOpDH were independent of genes Q, Gpc-B1, Ser5B, S1, S2, S3, and markers for rice (Oryza sativa L.) GW2 and GS3. Environmentally stable QTL on 1A and 2D, as well as a pleiotropic QTL on 5A were detected. QTL on chromosome 1A conditioned uniformly widened grains, 2D affected width, and 5A width and thickness. In the Cayuga × Caledonia DH population, 30 QTL affecting kernel morphology were detected on all chromosomes except 3A, 5D, 6A, 6B, 7A, and 7B. The most significant QTL in this population were on 3D affecting seed length and on 1D and 3B affecting uniform widening. Marker-assisted selection of these QTL for complex dimensions of seed shape may assist in breeding cultivars with improved yield or quality. [ABSTRACT FROM AUTHOR]

Seed dormancy, the main factor contributing to preharvest sprouting (PHS) resistance, is a complex trait and is strongly influenced by environmental growth conditions. In this study, three sets of single chromosome substitution lines, including 36 genotypes, in a durum wheat [Triticum turgidum L. ssp. durum (Desf.) Husn.] background with donor chromosomes originating from three wild emmer [T. turgidum L. ssp. dicoccoides (Körn. ex Asch. and Graebn.) Thell.] accessions were grown in nine field environments and evaluated for seed dormancy and PHS resistance. The substitution lines involving chromosome 3A were among the most dormant genotypes. Germination tests indicated that five chromosomes contained genes influencing seed dormancy at a level comparable to 3A. Results from PHS tests showed that PHS was affected by at least eight T. dicoccoides chromosomes including 3A. The chromosomes harboring genes for seed dormancy did not fully correspond with those for PHS resistance. The weak correlations between PHS and dormancy observed in this study indicate that different genes are affecting these traits and they may be differentially influenced by the environment. Nonetheless, our results revealed that genes present on five chromosomes, 2A, 2B, 3A, 4A, and 7B, were found to affect both PHS resistance and seed dormancy. These genotypes thus provide useful resources for further studies on genetic interactions that contribute to the overall phenotypic variation and on genetic dissection of quantitative trait loci underlying PHS resistance. [ABSTRACT FROM AUTHOR]

Examines if hybridization could improve the milling and baking qualities of wheat derived by crossing good quality soft white wheat (NY6432-18) and good quality hard white wheat (Clark's Cream). Milling traits; Dough mixing traits; Hydration traits.