Genomic Selection in multi-environment crop trials

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers

An evaluation of genotyping by sequencing (GBS) to map the <em>Breviaristatum-e (ari-e)</em> locus in cultivated barley

ABSTRACT: We explored the use of genotyping by sequencing (GBS) on a recombinant inbred line population (GPMx) derived from a cross between the two-rowed barley cultivar ‘Golden Promise’ (ari-e.GP/Vrs1) and the six-rowed cultivar ‘Morex’ (Ari-e/vrs1) to map plant height. We identified three Quantitative Trait Loci (QTL), the first in a region encompassing the spike architecture gene Vrs1 on chromosome 2H, the second in an uncharacterised centromeric region on chromosome 3H, and the third in a region of chromosome 5H coinciding with the previously described dwarfing gene Breviaristatum-e (Ari-e). BACKGROUND: Barley cultivars in North-western Europe largely contain either of two dwarfing genes; Denso on chromosome 3H, a presumed ortholog of the rice green revolution gene OsSd1, or Breviaristatum-e (ari-e) on chromosome 5H. A recessive mutant allele of the latter gene, ari-e.GP, was introduced into cultivation via the cv. ‘Golden Promise’ that was a favourite of the Scottish malt whisky industry for many years and is still used in agriculture today. RESULTS: Using GBS mapping data and phenotypic measurements we show that ari-e.GP maps to a small genetic interval on chromosome 5H and that alternative alleles at a region encompassing Vrs1 on 2H along with a region on chromosome 3H also influence plant height. The location of Ari-e is supported by analysis of near-isogenic lines containing different ari-e alleles. We explored use of the GBS to populate the region with sequence contigs from the recently released physically and genetically integrated barley genome sequence assembly as a step towards Ari-e gene identification. CONCLUSIONS: GBS was an effective and relatively low-cost approach to rapidly construct a genetic map of the GPMx population that was suitable for genetic analysis of row type and height traits, allowing us to precisely position ari-e.GP on chromosome 5H. Mapping resolution was lower than we anticipated. We found the GBS data more complex to analyse than other data types but it did directly provide linked SNP markers for subsequent higher resolution genetic analysis

Applying plant genomics to crop improvement

A report of the European Science Foundation-Wellcome Trust Conference on Crop Genomics, Trait Analysis and Breeding, Hinxton, UK, 8-11 November 2006

ELIGULUM-A regulates lateral branch and leaf development in barley

The shoot apical and axillary meristems control shoot development, effectively influencing lateral branch and leaf formation. The barley (Hordeum vulgare L.) uniculm2 (cul2) mutation blocks axillary meristem development and mutant plants lack lateral branches (tillers) that normally develop from the crown. A genetic screen for cul2 suppressors recovered two recessive alleles of ELIGULUM-A (ELI-A) that partially rescued the cul2 tillering phenotype. Mutations in ELI-A produce shorter plants with fewer tillers and disrupt the leaf blade-sheath boundary, producing liguleless leaves and reduced secondary cell wall development in stems and leaves. ELI-A is predicted to encode an un-annotated protein containing a RNaseH-like domain that is conserved in land plants. ELI-A transcripts accumulate at the preligule boundary, the developing ligule, leaf margins, cells destined to develop secondary cell walls, and cells surrounding leaf vascular bundles. Recent studies have identified regulatory similarities between boundary development in leaves and lateral organs. Interestingly, we observed ELI-A transcripts at the preligule boundary, suggesting that ELI-A contributes to boundary formation between the blade and sheath. However, we did not observe ELI-A transcripts at the axillary meristem boundary in leaf axils, suggesting that ELI-A is not involved in boundary development for axillary meristem development. Our results show that ELI-A contributes to leaf and lateral branch development by acting as a boundary gene during ligule development but not during lateral branch development.</p

<i>HvDep</i>1 Is a Positive Regulator of Culm Elongation and Grain Size in Barley and Impacts Yield in an Environment-Dependent Manner

Heterotrimeric G proteins are intracellular membrane-attached signal transducers involved in various cellular processes in both plants and animals. They consist of three subunits denoted as α, β and γ. The γ-subunits of the so-called AGG3 type, which comprise a transmembrane domain, are exclusively found in plants. In model species, these proteins have been shown to participate in the control of plant height, branching and seed size and could therefore impact the harvestable yield of various crop plants. Whether AGG3-type γ-subunits influence yield in temperate cereals like barley and wheat remains unknown. Using a transgenic complementation approach, we show here that the Scottish malting barley cultivar (cv.) Golden Promise carries a loss-of-function mutation in HvDep1, an AGG3-type subunit encoding gene that positively regulates culm elongation and seed size in barley. Somewhat intriguingly, agronomic field data collected over a 12-year period reveals that the HvDep1 loss-of-function mutation in cv. Golden Promise has the potential to confer either a significant increase or decrease in harvestable yield depending on the environment. Our results confirm the role of AGG3-type subunit-encoding genes in shaping plant architecture, but interestingly also indicate that the impact HvDep1 has on yield in barley is both genotypically and environmentally sensitive. This may explain why widespread exploitation of variation in AGG3-type subunit-encoding genes has not occurred in temperate cereals while in rice the DEP1 locus is widely exploited to improve harvestable yield

<i>desynaptic5 </i>carries a spontaneous semi-dominant mutation affecting <i>Disrupted Meiotic cDNA 1</i> in barley

Despite conservation of the process of meiosis, recombination landscapes vary between species, with large genome grasses such as barley (Hordeum vulgare L.) exhibiting a pattern of recombination that is very heavily skewed to the ends of chromosomes. We have been using a collection of semi-sterile desynaptic meiotic mutant lines to help elucidate how recombination is controlled in barley and the role of the corresponding wild-type (WT) meiotic genes within this process. Here we applied a combination of genetic segregation analysis, cytogenetics, and immunocytology to genetically map and characterize the meiotic mutant desynaptic5 (des5). We identified an exonic insertion in the positional candidate ortholog of Disrupted Meiotic cDNA 1 (HvDMC1) on chromosome 5H of des5. des5 exhibits a severe meiotic phenotype with disturbed synapsis, reduced crossovers, and chromosome mis-segregation. The meiotic phenotype and reduced fertility of des5 is similarly observed in Hvdmc1RNAi transgenic plants and HvDMC1p:GusPlus reporter lines show DMC1 expression specifically in the developing inflorescence. The des5 mutation maintains the reading frame of the gene and exhibits semi-dominance with respect to recombination in the heterozygote indicating the value of non-knockout mutations for dissection of the control of recombination in the early stages of meiosis.</p

Expression quantitative trait loci analysis in plants

An expression Quantitative Trait Locus or eQTL is a chromosomal region that accounts for a proportion of the variation in abundance of a mRNA transcript observed between individuals in a genetic mapping population. A single gene can have one or multiple eQTLs. Large scale mRNA profiling technologies advanced genome-wide eQTL mapping in a diverse range of organisms allowing thousands of eQTLs to be detected in a single experiment. When combined with classical or trait QTLs, correlation analyses can directly suggest candidates for genes underlying these traits. Furthermore, eQTL mapping data enables genetic regulatory networks to be modelled and potentially provide a better understanding of the underlying phenotypic variation. The mRNA profiling data sets can also be used to infer the chromosomal positions of thousands of genes, an outcome that is particularly valuable for species with unsequenced genomes where the chromosomal location of the majority of genes remains unknown. In this review we focus on eQTL studies in plants, addressing conceptual and technical aspects that include experimental design, genetic polymorphism prediction and candidate gene identification.</p

Genetic diversity and genome wide association study of β-glucan content in tetraploid wheat grains

Non-starch polysaccharides (NSPs) have many health benefits, including immunomodulatory activity, lowering serum cholesterol, a faecal bulking effect, enhanced absorption of certain minerals, prebiotic effects and the amelioration of type II diabetes. The principal components of the NSP in cereal grains are (1,3;1,4)-β-glucans and arabinoxylans. Although (1,3;1,4)-β-glucan (hereafter called β-glucan) is not the most representative component of wheat cell walls, it is one of the most important types of soluble fibre in terms of its proven beneficial effects on human health. In the present work we explored the genetic variability of β-glucan content in grains from a tetraploid wheat collection that had been genotyped with a 90k-iSelect array, and combined this data to carry out an association analysis. The β-glucan content, expressed as a percentage w/w of grain dry weight, ranged from 0.18% to 0.89% across the collection. Our analysis identified seven genomic regions associated with β-glucan, located on chromosomes 1A, 2A (two), 2B, 5B and 7A (two), confirming the quantitative nature of this trait. Analysis of marker trait associations (MTAs) in syntenic regions of several grass species revealed putative candidate genes that might influence β-glucan levels in the endosperm, possibly via their participation in carbon partitioning. These include the glycosyl hydrolases endo-β-(1,4)-glucanase (cellulase), β-amylase, (1,4)-β-xylan endohydrolase, xylanase inhibitor protein I, isoamylase and the glycosyl transferase starch synthase II

Identification of crop cultivars with consistently high lignocellulosic sugar release requires the use of appropriate statistical design and modelling

Background In this study, a multi-parent population of barley cultivars was grown in the field for two consecutive years and then straw saccharification (sugar release by enzymes) was subsequently analysed in the laboratory to identify the cultivars with the highest consistent sugar yield. This experiment was used to assess the benefit of accounting for both the multi-phase and multi-environment aspects of large-scale phenotyping experiments with field-grown germplasm through sound statistical design and analysis. Results Complementary designs at both the field and laboratory phases of the experiment ensured that non-genetic sources of variation could be separated from the genetic variation of cultivars, which was the main target of the study. The field phase included biological replication and plot randomisation. The laboratory phase employed re-randomisation and technical replication of samples within a batch, with a subset of cultivars chosen as duplicates that were randomly allocated across batches. The resulting data was analysed using a linear mixed model that incorporated field and laboratory variation and a cultivar by trial interaction, and ensured that the cultivar means were more accurately represented than if the non-genetic variation was ignored. The heritability detected was more than doubled in each year of the trial by accounting for the non-genetic variation in the analysis, clearly showing the benefit of this design and approach. Conclusions The importance of accounting for both field and laboratory variation, as well as the cultivar by trial interaction, by fitting a single statistical model (multi-environment trial, MET, model), was evidenced by the changes in list of the top 40 cultivars showing the highest sugar yields. Failure to account for this interaction resulted in only eight cultivars that were consistently in the top 40 in different years. The correspondence between the rankings of cultivars was much higher at 25 in the MET model. This approach is suited to any multi-phase and multi-environment population-based genetic experiment

Downregulation of Barley Regulator of Telomere Elongation Helicase 1 Alters the Distribution of Meiotic Crossovers

Programmed meiotic DNA double-strand breaks (DSBs), necessary for proper chromosomal segregation and viable gamete formation, are repaired by homologous recombination (HR) as crossovers (COs) or non-crossovers (NCOs). The mechanisms regulating the number and distribution of COs are still poorly understood. The regulator of telomere elongation helicase 1 (RTEL1) DNA helicase was previously shown to enforce the number of meiotic COs in Caenorhabditis elegans but its function in plants has been studied only in the vegetative phase. Here, we characterised barley RTEL1 gene structure and expression using RNA-seq data previously obtained from vegetative and reproductive organs and tissues. Using RNAi, we downregulated RTEL1 expression specifically in reproductive tissues and analysed its impact on recombination using a barley 50k iSelect SNP Array. Unlike in C. elegans, in a population segregating for RTEL1 downregulated by RNAi, high resolution genome-wide genetic analysis revealed a significant increase of COs at distal chromosomal regions of barley without a change in their total number. Our data reveal the important role of RTEL1 helicase in plant meiosis and control of recombination