Validation of cross-progeny variance genomic prediction using simulations and experimental data in winter elite bread wheat.

From simulations and experimental data, the quality of cross progeny variance genomic predictions may be high, but depends on trait architecture and necessitates sufficient number of progenies. Genomic predictions are used to select genitors and crosses in plant breeding. The usefulness criterion (UC) is a cross-selection criterion that necessitates the estimation of parental mean (PM) and progeny standard deviation (SD).

Genetic regions determine tolerance to nitrogen deficiency in European elite bread wheats grown under contrasting nitrogen stress scenarios.

Clustering 24 environments in four contrasting nitrogen stress scenarios enabled the detection of genetic regions determining tolerance to nitrogen deficiency in European elite bread wheats. Increasing the nitrogen use efficiency of wheat varieties is an important goal for breeding. However, most genetic studies of wheat grown at different nitrogen levels in the field report significant interactions with the genotype.

Phenomic selection in wheat breeding: prediction of the genotype-by-environment interaction in multi-environment breeding trials.

Phenomic prediction of wheat grain yield and heading date in different multi-environmental trial scenarios is accurate. Modelling the genotype-by-environment interaction effect using phenomic data is a potentially low-cost complement to genomic prediction. The performance of wheat cultivars in multi-environmental trials (MET) is difficult to predict because of the genotype-by-environment interactions (G × E).

Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection.

Phenomic selection is a promising alternative or complement to genomic selection in wheat breeding. Models combining spectra from different environments maximise the predictive ability of grain yield and heading date of wheat breeding lines. Phenomic selection (PS) is a recent breeding approach similar to genomic selection (GS) except that genotyping is replaced by near-infrared (NIR) spectroscopy.

Bread wheat milling behavior: effects of genetic and environmental factors, and modeling using grain mechanical resistance traits.

Genetic (Pinb-D1 alleles) and environment (through vitreousness) have important effects on bread wheat milling behavior. SKCS optimal values corresponding to soft vitreous or hard mealy grains were defined to obtain the highest total flour yield. Near-isogenic lines of bread wheat that differ in hardness, due to distinct puroindoline-b alleles (the wild type, Pinb-D1a, or the mutated forms, Pinb-D1b or Pinb-D1d), were grown in different environments and under two nitrogen fertilization levels, to study genetic and environmental effects on milling behavior.

Relationships between wheat grain physical characteristics studied through near-isogenic lines with distinct puroindoline-b allele.

Genetic (different forms of puroindoline-b) and environment (through variations in vitreousness), have important effects on wheat grain mechanical properties. The two methods of hardness measurements (NIRS, SKCS) do not give the same information. Bread wheat near-isogenic lines differing in hardness, due to distinct puroindoline-b alleles (the wild type, Pinb-D1a, or the mutated forms, Pinb-D1b or Pinb-D1d), were grown for three years in seven sites and under two nitrogen fertilization levels, to study genetic and environmental effects on grain mechanical properties.

Genome-wide prediction of three important traits in bread wheat.

Five genomic prediction models were applied to three wheat agronomic traits-grain yield, heading date and grain test weight-in three breeding populations, each comprising about 350 doubled haploid or recombinant inbred lines evaluated in three locations during a 3-year period. The prediction accuracy, measured as the correlation between genomic estimated breeding value and observed trait, was in the range of previously published values for yield ( = 0.2-0.

Combined meta-genomics analyses unravel candidate genes for the grain dietary fiber content in bread wheat (Triticum aestivum L.).

Grain dietary fiber content in wheat not only affects its end use and technological properties including milling, baking and animal feed but is also of great importance for health benefits. In this study, integration of association genetics (seven detected loci on chromosomes 1B, 3A, 3D, 5B, 6B, 7A, 7B) and meta-QTL (three consensus QTL on chromosomes 1B, 3D and 6B) analyses allowed the identification of seven chromosomal regions underlying grain dietary fiber content in bread wheat. Based either on a diversity panel or on bi-parental populations, we clearly demonstrate that this trait is mainly driven by a major locus located on chromosome 1B associated with a log of p value >13 and a LOD score >8, respectively.