The Landscape of Autophagy-Related (ATG) Genes and Functional Characterization of TaVAMP727 to Autophagy in Wheat

Autophagy is an indispensable biological process and plays crucial roles in plant growth and plant responses to both biotic and abiotic stresses. This study systematically identified autophagy-related proteins (ATGs) in wheat and its diploid and tetraploid progenitors and investigated their genomic organization, structure characteristics, expression patterns, genetic variation, and regulation network. We identified a total of 77, 51, 29, and 30 ATGs in wheat, wild emmer, T. urartu and A. tauschii, respectively, and grouped them into 19 subfamilies. We found that these autophagy-related genes (ATGs) suffered various degrees of selection during the wheat’s domestication and breeding processes. The genetic variations in the promoter region of Ta2A_ATG8a were associated with differences in seed size, which might be artificially selected for during the domestication process of tetraploid wheat. Overexpression of TaVAMP727 improved the cold, drought, and salt stresses resistance of the transgenic Arabidopsis and wheat. It also promoted wheat heading by regulating the expression of most ATGs. Our findings demonstrate how ATGs regulate wheat plant development and improve abiotic stress resistance. The results presented here provide the basis for wheat breeding programs for selecting varieties of higher yield which are capable of growing in colder, drier, and saltier areas.

Response to Early Generation Genomic Selection for Yield in Wheat

We investigated increasing genetic gain for grain yield using early generation genomic selection (GS). A training set of 1,334 elite wheat breeding lines tested over three field seasons was used to generate Genomic Estimated Breeding Values (GEBVs) for grain yield under irrigated conditions applying markers and three different prediction methods: (1) Genomic Best Linear Unbiased Predictor (GBLUP), (2) GBLUP with the imputation of missing genotypic data by Ridge Regression BLUP (rrGBLUP_imp), and (3) Reproducing Kernel Hilbert Space (RKHS) a.k.a. Gaussian Kernel (GK). F2 GEBVs were generated for 1,924 individuals from 38 biparental cross populations between 21 parents selected from the training set. Results showed that F2 GEBVs from the different methods were not correlated. Experiment 1 consisted of selecting F2s with the highest average GEBVs and advancing them to form genomically selected bulks and make intercross populations aiming to combine favorable alleles for yield. F4:6 lines were derived from genomically selected bulks, intercrosses, and conventional breeding methods with similar numbers from each. Results of field-testing for Experiment 1 did not find any difference in yield with genomic compared to conventional selection. Experiment 2 compared the predictive ability of the different GEBV calculation methods in F2 using a set of single plant-derived F2:4 lines from randomly selected F2 plants. Grain yield results from Experiment 2 showed a significant positive correlation between observed yields of F2:4 lines and predicted yield GEBVs of F2 single plants from GK (the predictive ability of 0.248, P < 0.001) and GBLUP (0.195, P < 0.01) but no correlation with rrGBLUP_imp. Results demonstrate the potential for the application of GS in early generations of wheat breeding and the importance of using the appropriate statistical model for GEBV calculation, which may not be the same as the best model for inbreds.

Genetic and Morpho-Agronomic Characterization of Sicilian Tetraploid Wheat Germplasm

Cereal landraces are a very valuable resource in contemporary agriculture. A renewed focus for breeding purposes could ameliorate some negative consequences of modern agriculture and conventional breeding, such as the loss of genetic diversity. One strategy combining molecular genotyping and characterization of morpho-agronomic traits related to productivity is proposed to assess a group of tetraploid wheat landraces named Bufala, historically cultivated in the mountain areas of Sicily and characterized by adaptability in terms of cold tolerance, ability to grow in marginal soils, weed competitiveness and resistance to diseases. A total of 55 SSR molecular markers were used to detect patterns of diversity in 30 rivet and durum wheat genotypes. Furthermore, phenotyping was then conducted for 8 morpho-agronomic traits. Discriminant analysis of principal components (DAPC), STRUCTURE and phylogenetical analysis allowed to identify three groups, two of them genetically close and including both Bufala and Bufala-related rivet landraces. To the third group, old and more recent durum wheat varieties, constituting the outgroup, were assigned. Clustering was confirmed by Principal Component Analysis (PCA). Finally, a correlation analysis showed that Bufala genotypes are characterized by lower ear density, major ear length and later earing time compared with the other studied genotypes. The levels of diversity and population structure could be an important contribution to parent selection in tetraploid wheat breeding programs, as well as to germplasm conservation and management.

Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis

Key message Including additive and additive-by-additive epistasis in a NOIA parametrization did not yield orthogonal partitioning of genetic variances, nevertheless, it improved predictive ability in a leave-one-out cross-validation for wheat grain yield. Abstract Additive-by-additive epistasis is the principal non-additive genetic effect in inbred wheat lines and is potentially useful for developing cultivars based on total genetic merit; nevertheless, its practical benefits have been highly debated. In this article, we aimed to (i) evaluate the performance of models including additive and additive-by-additive epistatic effects for variance components (VC) estimation of grain yield in a wheat-breeding population, and (ii) to investigate whether including additive-by-additive epistasis in genomic prediction enhance wheat grain yield predictive ability (PA). In total, 2060 sixth-generation (F6) lines from Nordic Seed A/S breeding company were phenotyped in 21 year-location combinations in Denmark, and genotyped using a 15 K-Illumina-BeadChip. Three models were used to estimate VC and heritability at plot level: (i) “I-model” (baseline), (ii) “I + GA-model”, extending I-model with an additive genomic effect, and (iii) “I + GA + GAA-model”, extending I + GA-model with an additive-by-additive genomic effects. The I + GA-model and I + GA + GAA-model were based on the Natural and Orthogonal Interactions Approach (NOIA) parametrization. The I + GA + GAA-model failed to achieve orthogonal partition of genetic variances, as revealed by a change in estimated additive variance of I + GA-model when epistasis was included in the I + GA + GAA-model. The PA was studied using leave-one-line-out and leave-one-breeding-cycle-out cross-validations. The I + GA + GAA-model increased PA significantly (16.5%) compared to the I + GA-model in leave-one-line-out cross-validation. However, the improvement due to including epistasis was not observed in leave-one-breeding-cycle-out cross-validation. We conclude that epistatic models can be useful to enhance predictions of total genetic merit. However, even though we used the NOIA parameterization, the variance partition into orthogonal genetic effects was not possible.

Main directions and issues of durum winter wheat breeding under climate changing

The current paper has presented the study results (2015–2020) of the influence of changing weather conditions on durum winter wheat productivity and grain quality. The purpose of the study was to identify the main stress factors limiting durum winter wheat productivity under changing climate conditions and to determine the direction and issues for further breeding. The objects of the study were the varieties ‘Amazonka’, ‘Agat Donskoy’, ‘Kristella’, ‘Lazurit’, ‘Oniks’, ‘Diona’, ‘Eyrena’, ‘Yakhont’, ‘Kiprida’, ‘Yubilyarka’, ‘Yantarina’, ‘Uslada’, ‘Donchanka’ (a standard variety) developed by the FSBSI Agricultural Research Center “Donskoy”. There have been studied the meteorological data (average daily temperatures and precipitation) through the years of study as well. On the basis of the analysis, there have been established main stress factors of these years that affected productivity, namely drought in different vegetation periods with the pre-sowing and sowing periods in August and September of 2019; the periods ‘sprouts-tillering’ in October, December and the periods ‘tillering-stem extension’ in March, April; grain filling period in 2020; atmospheric drought during the period of active vegetation in April, June of 2018; excessive moisture with rainfalls and squally winds that caused lodging, diseases, grain flowing off and discoloration in 2014–2015, 2015–2016. The agricultural year 2016–2017 was the most favorable in terms of temperature regime, precipitation and their distribution (at the level of the long-term average), with an average varietal productivity of 9.49 t/ha. Yield decrease depending on this or that stress factor (in comparison with the favorable year of 2017) was on 54.5% in 2019, 32.5% in 2020 and on 21.4 in 2015 and 27.2% in 2016. The exception was the year of 2018, when with sufficient soil moisture, productivity was on 26.3% more than in 2017. Due to the study results of winter durum wheat varieties according to their traits and properties to the indicated stress factors in 2015–2020, there have been identified the issues for each direction, the solution of which will be aimed at developing stress-resistant, resistant to lodging and diseases varieties with large stable yields and high grain quality.

Molecular labeling of Vrn, Ppd genes and vernalization response of the ultra-early lines of spring bread wheat Triticum aestivum L.

Background. The knowledge of genetic control of vernalization response in the ultra-early accessions can facilitate bread wheat breeding for a high adaptive capacity. Materials and methods. The study involved the ultra-early lines Rico (k-65588) and Rimax (k-67257) as the earliest maturing lines in the VIR bread wheat collection, as well as 10 Rifor lines (k-67120, k-67121, k-67250-67256) with a high rate of development before heading. A late ripening accession ‘Forlani Roberto’ (k-42641) and ‘Leningradskaya 6’ variety (k-64900), regionally adapted to Northwestern Russia, were also studied. The alleles of the Vrn and Ppd genes were identified by the PCR analysis using the allele-specific primers published in literature sources. The response to vernalization (30 days at 3°C) and a short 12-hour day were determined using a methodology accepted at VIR. Results. The ultra-early lines respond to a short 12-hour day and 30-day vernalization very poorly. The genotype of ultra-early wheat lines is mainly represented by three genes, Vrn-A1, Vrn-B1a, and Vrn-D1, which ensure insensitivity to vernalization alongside with the expression of Ppd-D1a, which controls the response to photoperiod. The ultra-early lines Rifor 4 and Rifor 5 have a recessive allele vrn-A1a, like the original ‘Forlani Roberto’ accession. The lines Rifor 4 and Rifor 5 are vernalization-insensitive under the long day and have a very weak response under the short day (3.5±0.42 days and 4.0±0.61 days, respectively). However, ‘Forlani Roberto’ with the vrn-A1a gene responds to vernalization in the same way under any photoperiod (12.3±1.58 days and 12.2±0.74 days). Conclusion The ultra-early lines of bread wheat Rifor 4 and Rifor 5 with the vrn-A1a gene can have no response to vernalization or have a low level response. This effect can be a reason for the formation of a complex of modifier genes along with the dominant gene Vrn-D1, which forms during the hybridization of F7-8 Rico × Forlani Roberto. The ultra-early lines of bread wheat Rico, Rimax and Rifor (k-67120, k-67121, k-67250-67256) can serve as effective sources of genes for earliness in common wheat breeding.

Identification of the Yield Traits Related Haplotype Combinations of Transcription Factor Genes TaHDZ34 in Common Wheat

Improvement of yield-traits is one of the predominating objectives in wheat breeding. Homeodomain-leucine zipper (HD-ZIP) transcription factor plays significant roles in plant growth and development. The TaHDZ34 (A, B and D sub-genomics) genes consisting of three members of the HD-ZIP IV transcription factor gene subfamily in wheat (Triticum aestivum L.) were cloned. Two haplotypes of TaHDZ34-7A, TaHDZ34-7B or TaHDZ34-7D were respectively identified after the sequence polymorphism analysis, and three functional molecular markers were developed. The TaHDZ34 genes were divided into eight haplotype combinations. Association analysis and distinct population validation jointly indicated that TaHDZ34 had the function of modulating grain number per spike, effective spikelet number per spike, 1,000 kernel weight, and flag leaf area per plant in wheat. Among all haplotype combinations of TaHDZ34, Hap-ABD was the most excellent one. Subcelluar localization showed that TaHDZ34-7A was localized in the nucleus. Interaction proteins of TaHDZ34-7A protein proved to be involved in protein synthesis/degradation, energy production and transportation, and photosynthesis processes. Geographic distribution and frequencies of TaHDZ34 haplotype combinations suggested that the Hap-Abd and Hap-AbD were preferential selection in Chinese wheat breeding programs. The high-yield related haplotype combinations Hap-ABD of TaHDZ34 provided beneficial genetic resources for marker-assisted selection of new wheat cultivars.

Wheat Breeding through Genetic and Physical Mapping 2

Following the success of the first topic, the special issue of “Wheat breeding through genetic and physical mapping 2” has been re-proposed in order to keep current the recent advancement in research on genetic and physical mapping of candidate genes for agronomically important traits, in studies of the regulatory sequence for biotic and abiotic stress resistance [...]