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Summary: Recent advances in genome engineering technologies based on designed endonucleases (DE) allow specific and predictable alterations in plant genomes to generate value‐added traits in crops of choice. The EXZACT Precision technology, based on zinc finger nucleases (ZFN), has been successfully used in the past for introduction of precise mutations and transgenes to generate novel and desired phenotypes in several crop species. Current methods for delivering ZFNs into plant cells are based on traditional genetic transformation methods that result in stable integration of the nuclease in the genome. Here, we describe for the first time, an alternative ZFN delivery method where plant cells are transfected with ZFN protein that eliminates the need for stable nuclease genomic integration and allows generation of edited, but not transgenic cells or tissues. For this study, we designed ZFNs targeting the wheat IPK1 locus, purified active ZFN protein from bacterial cultures, complexed with cell‐penetrating peptides (CPP) and directly transfected the complex into either wheat microspores or embryos. NGS analysis of ZFN‐treated material showed targeted edits at the IPK1 locus in independent experiments. This is the first description of plant microspore genome editing by a ZFN when delivered as a protein complexed with CPP. [ABSTRACT FROM AUTHOR]

Cereal grain ethanol production may need to supplement biomass ethanol production to meet the increasing long-term demand for ethanol. A study was initiated to benchmark the relative performance of triticale (xTriticosecale ssp.) to wheat (Triticum aestivum L.) classes utilized for ethanol production. Ten cultivars: three triticale, two Canada prairie spring (CPS) wheat, three Canada western soft white spring (CWSWS) wheat, one Canada western red spring (CWRS) wheat, and one Canada western general purpose (CWGP) wheat cultivars were grown at 45 locations across Canada from 2006 to 2009. The locations were subgrouped by agroeco-logical zone for western Canada, by province for Ontario and Quebec, and Charlottetown, PEI, for the Maritimes. The greatest grain yield was usually observed for Hoffman (red spring wheat) followed by triticale cultivars and CWSWS cultivars. Ethanol yield varied by region as a reflection of grain yield, and differences among cultivars generally were: triticale (excluding Tyndal) = Hoffman = CWSWS > CPS > CWRS. Ethanol concentration was least for Tyndal triticale and AC Superb CWRS. Stability assessments indicated that Pronghorn and AC Ultima triticales and Bhishaj CWSWS wheat provide consistent and high ethanol yields. The other CWSWS cultivars, AC Sadash and AC Andrew, had similarly high ethanol yields but were variable, indicating that utilization outside the Parkland and Western Prairies agroecological zones could pose greater risk for ethanol plants over Pronghorn and AC Ultima. Ethanol fermentation plants could therefore increase efficiency by replacing CPS wheat feedstocks with select triticales and potentially improve the consistency of production by using select triticales in regions where CWSWS wheats are less stable. [ABSTRACT FROM AUTHOR]

A need has been identified for alternative crop(s) with high grain yield, low grain protein concentration, and high starch for the ethanol industry. The objective of this study was to benchmark the relative performance of triticale (xTriticosecale ssp.) to wheat (Triticum aestivum L.) classes currently utilized for ethanol production. Sixteen cultivars-three triticale, four Canada prairie spring (CPS) wheat, three Canada western soft white spring wheat (CWSWS), two Canada western red spring (CWRS) wheat, and four Canada western general purpose (CWGP) candidate cultivars-were grown at 36 locations across western Canada from 2006 to 2009. The performance of these cereal classes can generally be summarized as triticale = Hoffman (CWGP) = CWSWS > CPS white > CPS red> CWRS for most variables. The triticale and white wheats produced 12 and 13% more grain, respectively, than the hard red spring wheats. Among the triticales, AC Ultima's and Pronghorn's yield potential were most notable because they exceeded the CWRS cultivars AC Barrie and AC Superb by an average of 32% and the CPS red cultivars 5700PR and AC Crystal by 18%. The triticales and Hoffman matured later than most other cultivars. Pronghorn consistently displayed low levels of fusarium head blight (FHB), Septoria nodorum blotch, and powdery mildew, but elevated ergot levels were observed for all triticales. We conclude that triticale would be superior to CPS and CWRS wheat and similar to CWSWS in many agronomic traits desired by ethanol fermentation plants and is superior for biomass production. [ABSTRACT FROM AUTHOR]

Triticale (xTriticosecale Wittm. ex A. Camus) is primarily an animal feed crop with promising qualities for a bioindustrial crop. Development of genetically modified (GM) triticale is in progress and before release of GM cultivars, the potential for pollen-mediated gene flow (PMGF) needs to be assessed to determine if it can coexist with conventional cultivars without causing market harm. Small and large plot experiments were conducted to quantify PMGF using an experimental blue aleurone triticale line as pollen donor and 'AC Alta' as pollen receptor. Small plot experiments were conducted at two locations in both 2007 and 2009 in Alberta, Canada. There were no site or year differences. Average PMGF from 0.2 to 1.4 m was 0.76%. Large plot experiments were conducted at two locations in both 2008 and 2009 using a concentric donor (20 by 20 m) and receptor (120 by 120 m) design. Over 17 million seeds were screened. There were no significant differences between sites or years. Pollen-mediated gene flow best fit an exponential decay model in which the highest average PMGF (3.4%) occurred adjacent to the donor crop and rapidly declined to 0.09% by 50 m. Directional differences were detected with highest PMGF corresponding to prevailing wind directions at flowering. The estimated adventitious presence of GM triticale after harvest blending within a 50-m conventional field was 0.22%. Pollen-mediated gene flow in triticale is similar to spring wheat (Triticum aestivum L.) and should not prevent the coexistence of GM and conventional tritical using the 0.9% threshold established by the European Union. [ABSTRACT FROM AUTHOR]

Simple Summary: Genomic selection is a promising approach to select superior wheat lines with better resistance to Fusarium head blight. The accuracy of genomic selection is determined by many factors. In this study, we found a training population with large size, genomic selection models incorporating biological information, and multi-environment modelling led to considerably better predictabilities. A training population designed by the coefficient of determination (CDmean) could increase accuracy of prediction. Relatedness between training population (TP) and testing population is the key for accuracies of genomic selection across populations. Fusarium head blight (FHB) resistance is quantitatively inherited, controlled by multiple minor effect genes, and highly affected by the interaction of genotype and environment. This makes genomic selection (GS) that uses genome-wide molecular marker data to predict the genetic breeding value as a promising approach to select superior lines with better resistance. However, various factors can affect accuracies of GS and better understanding how these factors affect GS accuracies could ensure the success of applying GS to improve FHB resistance in wheat. In this study, we performed a comprehensive evaluation of factors that affect GS accuracies with a multi-parental population designed for FHB resistance. We found larger sample sizes could get better accuracies. Training population designed by CDmean based optimization algorithms significantly increased accuracies than random sampling approach, while mean of predictor error variance (PEVmean) had the poorest performance. Different genomic selection models performed similarly for accuracies. Including prior known large effect quantitative trait loci (QTL) as fixed effect into the GS model considerably improved the predictability. Multi-traits models had almost no effects, while the multi-environment model outperformed the single environment model for prediction across different environments. By comparing within and across family prediction, better accuracies were obtained with the training population more closely related to the testing population. However, achieving good accuracies for GS prediction across populations is still a challenging issue for GS application. [ABSTRACT FROM AUTHOR]