Genetic variation at flowering time loci in wild and cultivated barley

The worldwide spread of barley cultivation required adaptation to agricultural environments far distant from those found in its centre of domestication. An important component of this adaptation is the timing of flowering, achieved predominantly in response to day length and temperature. Here, we use a collection of cultivars, landraces and wild barley accessions to investigate the origins and distribution of allelic diversity at four major flowering time loci, mutations at which have been under selection during the spread of barley cultivation into Europe. Our findings suggest that while mutant alleles at the PPD-H1 and PPD-H2 photoperiod loci occurred pre-domestication, the mutant vernalization non-responsive alleles utilized in landraces and cultivars at the VRN-H1 and VRN-H2 loci occurred post-domestication. The transition from wild to cultivated barley is associated with a doubling in the number of observed multi-locus flowering-time haplotypes, suggesting that the resulting phenotypic variation has aided adaptation to cultivation in the diverse ecogeographic locations encountered. Despite the importance of early-flowering alleles during the domestication of barley in Europe, we show that novel VRN alleles associated with early flowering in wild barley have been lost in domesticates, highlighting the potential of wild germplasm as a source of novel allelic variation for agronomic traits

Molecular and phenotypic characterization of the alternative seasonal growth habit and flowering time in barley (Hordeum vulgare ssp. vulgare L.)

Barley can be classified into three major agronomic types, based on its seasonal growth habit (SGH): spring, winter and alternative. Winter varieties require exposure to vernalization to promote subsequent flowering and are autumn-sown. Spring varieties proceed to flowering in the absence of vernalization and are sown in the spring. The ‘alternative’ (also known as ‘facultative’) SGH is only loosely defined and can be sown in autumn or spring. Here, we investigate the molecular genetic basis of alternative barley. Analysis of the major barley vernalization (VRN-H1, VRN-H2) and photoperiod (PPD-H1, PPD-H2) response genes in a collection of 386 varieties found alternative SGH to be characterized by specific allelic combinations. Spring varieties possessed spring loci at one or both of the vernalization response loci, combined with long-day non-responsive ppd-H1 alleles and wild-type alleles at the short-day photoperiod response locus, PPD-H2. Winter varieties possessed winter alleles at both vernalization loci, in combination with the mutant ppd-H2 allele conferring delayed flowering under short-day photoperiods. In contrast, all alternative varieties investigated possessed a single spring allele (either at VRN-H1 or at VRN-H2) combined with mutant ppd-H2 alleles. This allelic combination is found only in alternative types and is diagnostic for alternative SGH in the collection studied. Analysis of flowering time under controlled environment found alternative varieties flowered later than spring control lines, with the difference most pronounced under short-day photoperiods. This work provides genetic characterization of the alternative SGH phenotype, allowing precise manipulation of SGH and flowering time within breeding programmes, and provides the molecular tools for classification of all three SGH categories within national variety registration processes

Genome‐wide association mapping of Hagberg falling number, protein content, test weight and grain yield in UK wheat

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome‐wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R(2) ≥ .5 with the same QTL. Genome‐wide association studies identified marker‐trait associations for all four traits. For HFN (h (2 )= .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h (2 )= 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h (2 )= 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement

Molecular genetic analysis of cereal β-amylase genes using exon-primed intron-crossing (EPIC) PCR

The proteins encoded by cereal β-amylase genes bamy1 and bamy2 genes play an important role in seedling germination and in the brewing process. Here, we use exon-primed intron-crossing (EPIC) to analyse Bmy1 and Bmy2 genetic diversity among 38 accessions belonging to six Poaceae tribes. DNA sequence alignment of multiple Poaceae species β-amylase sequences allowed design of EPIC primers that simultaneously amplify Bmy1 and Bmy2 in all the cereal species investigated. The genetic variation observed in the samples investigated is analysed and discussed, and illustrates the effectiveness of this approach for intra- and interspecific analysis in plant species.Peer reviewe

A large-scale pedigree resource of wheat reveals evidence for adaptation and selection by breeders

<div><p>Information on crop pedigrees can be used to help maximise genetic gain in crop breeding and allow efficient management of genetic resources. We present a pedigree resource of 2,657 wheat (<i>Triticum aestivum</i> L.) genotypes originating from 38 countries, representing more than a century of breeding and variety development. Visualisation of the pedigree enables illustration of the key developments in United Kingdom wheat breeding, highlights the wide genetic background of the UK wheat gene pool, and facilitates tracing the origin of beneficial alleles. A relatively high correlation between pedigree- and marker-based kinship coefficients was found, which validated the pedigree and enabled identification of errors in the pedigree or marker data. Using simulations with a combination of pedigree and genotype data, we found evidence for significant effects of selection by breeders. Within crosses, genotypes are often more closely related than expected by simulations to one of the parents, which indicates selection for favourable alleles during the breeding process. Selection across the pedigree was demonstrated on a subset of the pedigree in which 110 genotyped varieties released before the year 2000 were used to simulate the distribution of marker alleles of 45 genotyped varieties released after the year 2000, in the absence of selection. Allelic diversity in the 45 varieties was found to deviate significantly from the simulated distributions at a number of loci, indicating regions under selection over this period. The identification of one of these regions as coinciding with a strong yield component quantitative trait locus (QTL) highlights both the potential of the remaining loci as wheat breeding targets for further investigation, as well as the utility of this pedigree-based methodology to identify important breeding targets in other crops. Further evidence for selection was found as greater linkage disequilibrium (LD) for observed versus simulated genotypes within all chromosomes. This difference was greater at shorter genetic distances, indicating that breeder selections have conserved beneficial linkage blocks. Collectively, this work highlights the benefits of generating detailed pedigree resources for crop species. The wheat pedigree database developed here represents a valuable community resource and will be updated as new varieties are released at <a href="https://www.niab.com/pages/id/501/UK_Wheat_varieties_Pedigree" target="_blank">https://www.niab.com/pages/id/501/UK_Wheat_varieties_Pedigree</a>.</p></div

μCT trait analysis reveals morphometric differences between domesticated temperate small grain cereals and their wild relatives

Wheat and barley are two of the founder crops domesticated in the Fertile Crescent, and currently represent crops of major economic importance in temperate regions. Due to impacts on yield, quality and end-use, grain morphometric traits remain an important goal for modern breeding programmes and are believed to have been selected for by human populations. To directly and accurately assess the three-dimensional (3D) characteristics of grains, we combine X-ray microcomputed tomography (μCT) imaging techniques with bespoke image analysis tools and mathematical modelling to investigate how grain size and shape vary across wild and domesticated wheat and barley. We find that grain depth and, to a lesser extent, width are major drivers of shape change and that these traits are still relatively plastic in modern bread wheat varieties. Significant changes in grain depth are also observed to be associated with differences in ploidy. Finally, we present a model that can accurately predict the wild or domesticated status of a grain from a given taxa based on the relationship between three morphometric parameters (length, width and depth) and suggest its general applicability to both archaeological identification studies and breeding programmes.Agências financiadoras: Biotechnology and Biological Sciences Research Council (BBSRC) grant, 'National Capability in Crop Phenotyping' (BB/J004464/1); (BB/CAP1730/1) BBSRC grant, 'MAGIC CARPET' (BB/M011666/1) NERC (NE/M010805/1) ERC (339941)info:eu-repo/semantics/publishedVersio

The New Wheat Vernalization Response Allele Vrn-D1s is Caused by DNA Transposon Insertion in the First Intron

Vernalization requirement in hexaploid bread wheat (Triticum aestivum L.) is largely controlled by a series of homoeologous VERNALIZATION (VRN) genes, VRN-A1, VRN-B1 and VRN-D1. Here we analyse sequence from the promoter and first intron of VRN-D1 in 77 hexaploid accessions, representing five wheat species (T. compactum, T. sphaerococcum, T. spelta, T. vavilovii and T. macha) from different eco-geographic areas within 35 countries. Polymorphism was detected for promoter area of VRN-D1 gene. This polymorphism was caused by mutations which are associated with a new haplotype of the Vrn-D1 gene. Analysis of VRN-D1 intron-1 revealed a novel insertional mutation within the ‘vernalization critical’ region in T. spelta and T. compactum. This allelic variant, termed here Vrn-D1s, is predicted to result in vernalization non-responsive alleles. Analysis of the 844 bp insertion revealed it to be a novel transposable DNA-element not previously described in Triticum (DTA_Chimera_KF800714), belonging to the hAT superfamily. Lastly, we describe a PCR-based assay that discriminates the wild-type vrn-D1 allele from the predicted spring Vrn-D1s allele.Peer reviewe

Genome dynamics explain the evolution of flowering time CCT domain gene families in the Poaceae

Numerous CCT domain genes are known to control flowering in plants. They belong to the CONSTANS-like (COL) and PREUDORESPONSE REGULATOR (PRR) gene families, which in addition to a CCT domain possess B-box or response-regulator domains, respectively. Ghd7 is the most recently identified COL gene to have a proven role in the control of flowering time in the Poaceae. However, as it lacks B-box domains, its inclusion within the COL gene family, technically, is incorrect. Here, we show Ghd7 belongs to a larger family of previously uncharacterized Poaceae genes which possess just a single CCT domain, termed here CCT MOTIF FAMILY (CMF) genes. We molecularly describe the CMF (and related COL and PRR) gene families in four sequenced Poaceae species, as well as in the draft genome assembly of barley (Hordeum vulgare). Genetic mapping of the ten barley CMF genes identified, as well as twelve previously unmapped HvCOL and HvPRR genes, finds the majority map to colinear positions relative to their Poaceae orthologues. Combined inter-/intra-species comparative and phylogenetic analysis of CMF, COL and PRR gene families indicates they evolved prior to the monocot/dicot divergence ~200 mya, with Poaceae CMF evolution described as the interplay between whole genome duplication in the ancestral cereal, and subsequent clade-specific mutation, deletion and duplication events. Given the proven role of CMF genes in the modulation of cereals flowering, the molecular, phylogenetic and comparative analysis of the Poaceae CMF, COL and PRR gene families presented here provides the foundation from which functional investigation can be undertaken

Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture for long-term genetic gains in wheat

Cereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand multi-trait selection within a breeding context, and how it might be optimized, we analysed genotypic and phenotypic data from a genetically diverse, 16-founder wheat multi-parent advanced generation inter-cross population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90 % of traits, improving grain yield prediction accuracy by 3–52 %. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10–36 %. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimized long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, involving optimized antagonistic trait relationships. We found multi-trait selection indices could effectively optimize undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results (i) suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes, and (ii) provide insights into mechanisms for continued genetic gain in a limited genepool and optimization of multiple traits for crop improvement