Genetic variation of γ-tocopherol methyltransferase gene contributes to elevated α-tocopherol content in soybean seeds

<p>Abstract</p> <p>Background</p> <p>Improvement of α-tocopherol content is an important breeding aim to increase the nutritional value of crops. Several efforts have been conducted to improve the α-tocopherol content in soybean [<it>Glycine max </it>(L.) Merr.] through transgenic technology by overexpressing genes related to α-tocopherol biosynthesis or through changes to crop management practices. Varieties with high α-tocopherol content have been identified in soybean germplasms. The heritability of this trait has been characterized in a cross between high α-tocopherol variety Keszthelyi Aproszemu Sarga (KAS) and low α-tocopherol variety Ichihime. In this study, the genetic mechanism of the high α-tocopherol content trait of KAS was elucidated.</p> <p>Results</p> <p>Through QTL analysis and fine mapping in populations from a cross between KAS and a Japanese variety Ichihime, we identified <it>γ-TMT3</it>, which encodes <it>γ</it>-tocopherol methyltransferase, as a candidate gene responsible for high α-tocopherol concentration in KAS. Several nucleotide polymorphisms including two nonsynonymous mutations were found in the coding region of <it>γ-TMT3 </it>between Ichihime and KAS, but none of which was responsible for the difference in α-tocopherol concentration. Therefore, we focused on transcriptional regulation of <it>γ-TMT3 </it>in developing seeds and leaves. An F₅line that was heterozygous for the region containing <it>γ-TMT3 </it>was self-pollinated. From among the progeny, plants that were homozygous at the <it>γ-TMT3 </it>locus were chosen for further evaluation. The expression level of <it>γ-TMT3 </it>was higher both in developing seeds and leaves of plants homozygous for the <it>γ-TMT3 </it>allele from KAS. The higher expression level was closely correlated with high α-tocopherol content in developing seeds. We generated transgenic Arabidopsis plants harboring GUS gene under the control of <it>γ-TMT3 </it>promoter from KAS or Ichihime. The GUS activity assay showed that the activity of <it>γ-TMT3 </it>promoter from KAS was higher than that of Ichihime.</p> <p>Conclusions</p> <p>The genetic variation in <it>γ-TMT3</it>, which plays a major role in determining α-tocopherol concentration, provides significant information about the regulation of tocopherol biosynthesis in soybean seeds. This knowledge will help breeding programs to develop new soybean varieties with high α-tocopherol content.</p

Genome‐wide association and genomic prediction for biomass yield in a genetically diverse \u3ci\u3eMiscanthus sinensis\u3c/i\u3e germplasm panel phenotyped at five locations in Asia and North America

To improve the efficiency of breeding of Miscanthus for biomass yield, there is a need to develop genomics‐assisted selection for this long‐lived perennial crop by relating genotype to phenotype and breeding value across a broad range of environments. We present the first genome‐wide association (GWA) and genomic prediction study of Miscanthus that utilizes multilocation phenotypic data. A panel of 568 Miscanthus sinensis accessions was genotyped with 46,177 single nucleotide polymorphisms (SNPs) and evaluated at one subtropical and five temperate locations over 3 years for biomass yield and 14 yield‐component traits. GWA and genomic prediction were performed separately for different years of data in order to assess reproducibility. The analyses were also performed for individual field trial locations, as well as combined phenotypic data across groups of locations. GWA analyses identified 27 significant SNPs for yield, and a total of 504 associations across 298 unique SNPs across all traits, sites, and years. For yield, the greatest number of significant SNPs was identified by combining phenotypic data across all six locations. For some of the other yield‐component traits, greater numbers of significant SNPs were obtained from single site data, although the number of significant SNPs varied greatly from site to site. Candidate genes were identified. Accounting for population structure, genomic prediction accuracies for biomass yield ranged from 0.31 to 0.35 across five northern sites and from 0.13 to 0.18 for the subtropical location, depending on the estimation method. Genomic prediction accuracies of all traits were similar for single‐location and multilocation data, suggesting that genomic selection will be useful for breeding broadly adapted M. sinensis as well as M. sinensis optimized for specific climates. All of our data, including DNA sequences flanking each SNP, are publicly available. By facilitating genomic selection in M. sinensis and Miscanthus × giganteus, our results will accelerate the breeding of these species for biomass in diverse environments

Biomass yield in a genetically diverse \u3ci\u3eMiscanthus sinensis\u3c/i\u3e germplasm panel evaluated at five locations revealed individuals with exceptional potential

To breed improved biomass cultivars of Miscanthus ×giganteus, it will be necessary to select the highest‐yielding and best‐adapted genotypes of its parental species, Miscanthus sinensis and Miscanthus sacchariflorus. We phenotyped a diverse clonally propagated panel of 569 M. sinensis and nine natural diploid M. ×giganteus at one subtropical (Zhuji, China) and five temperate locations (Sapporo, Japan; Leamington, Ontario, Canada; Fort Collins, CO; Urbana, IL; and Chuncheon, Korea) for dry biomass yield and 14 yield‐component traits, in trials grown for 3 years. Notably, dry biomass yield of four Miscanthus accessions exceeded 80 Mg/ha in Zhuji, China, approaching the highest observed for any land plant. Additionally, six M. sinensis in Sapporo, Japan and one in Leamington, Canada also yielded more than the triploid M. ×giganteus ‘1993‐1780’ control, with values exceeding 20 Mg/ha. Diploid M. ×giganteus was the best‐yielding group at the northern sites. Genotypeby‐ environment interactions were modest among the five northern trial sites but large between Zhuji, and the northern sites. M. sinensisaccessions typically yielded best at trial sites with latitudes similar to collection sites, although broad adaptation was observed for accessions from southern Japan. Genotypic heritabilities for third year yields ranged from 0.71 to 0.88 within locations. Compressed circumference was the best predictor of yield. These results establish a baseline of data for initiating selection to improve biomass yield of M. sinensis and M. ×giganteus in a diverse set of relevant geographies

Training Population Optimization for Genomic Selection in Miscanthus

Miscanthus is a perennial grass with potential for lignocellulosic ethanol production. To ensure its utility for this purpose, breeding efforts should focus on increasing genetic diversity of the nothospecies Miscanthus x giganteus (M·g) beyond the single clone used in many programs. Germplasm from the corresponding parental speciesM. sinensis (Msi) and M. sacchariflorus (Msa) could theoretically be used as training sets for genomic prediction of M·g clones with optimal genomic estimated breeding values for biofuel traits. To this end, we first showed that subpopulation structure makes a substantial contribution to the genomic selection (GS) prediction accuracies within a 538-member diversity panel of predominately Msi individuals and a 598-member diversity panels of Msa individuals. We then assessed the ability of these two diversity panels to train GS models that predict breeding values in an interspecific diploid 216-member M·g F2 panel. Low and negative prediction accuracies were observed when various subsets of the two diversity panels were used to train theseGSmodels. To overcome the drawback of having only one interspecific M·g F2 panel available, we also evaluated prediction accuracies for traits simulated in 50 simulated interspecific M·g F2 panels derived from different sets of Msi and diploidMsa parents. The results revealed that genetic architectures with common causalmutations across Msi and Msa yielded the highest prediction accuracies. Ultimately, these results suggest that the ideal training set should contain the same causal mutations segregating within interspecific M·g populations, and thus efforts should be undertaken to ensure that individuals in the training and validation sets are as closely related as possible

Large-scale deployment of a rice 6 K SNP array for genetics and breeding applications

Abstract Background Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A 6 K SNP array represents a cost-benefit “sweet spot” for routine genetics and breeding applications in rice. Selection of informative SNPs across species and subpopulations during chip design is essential to obtain useful polymorphism rates for target germplasm groups. This paper summarizes results from large-scale deployment of an Illumina 6 K SNP array for rice. Results Design of the Illumina Infinium 6 K SNP chip for rice, referred to as the Cornell_6K_Array_Infinium_Rice (C6AIR), includes 4429 SNPs from re-sequencing data and 1571 SNP markers from previous BeadXpress 384-SNP sets, selected based on polymorphism rate and allele frequency within and between target germplasm groups. Of the 6000 attempted bead types, 5274 passed Illumina’s production quality control. The C6AIR was widely deployed at the International Rice Research Institute (IRRI) for genetic diversity analysis, QTL mapping, and tracking introgressions and was intensively used at Cornell University for QTL analysis and developing libraries of interspecific chromosome segment substitution lines (CSSLs) between O. sativa and diverse accessions of O. rufipogon or O. meridionalis. Collectively, the array was used to genotype over 40,000 rice samples. A set of 4606 SNP markers was used to provide high quality data for O. sativa germplasm, while a slightly expanded set of 4940 SNPs was used for O. sativa X O. rufipogon populations. Biparental polymorphism rates were generally between 1900 and 2500 well-distributed SNP markers for indica x japonica or interspecific populations and between 1300 and 1500 markers for crosses within indica, while polymorphism rates were lower for pairwise crosses within U.S. tropical japonica germplasm. Recently, a second-generation array containing ~7000 SNP markers, referred to as the C7AIR, was designed by removing poor-performing SNPs from the C6AIR and adding markers selected to increase the utility of the array for elite tropical japonica material. Conclusions The C6AIR has been successfully used to generate rapid and high-quality genotype data for diverse genetics and breeding applications in rice, and provides the basis for an optimized design in the C7AIR

Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i>

AbstractAccelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus

Biomass yield in a genetically diverse <i>Miscanthus sacchariflorus</i> germplasm panel phenotyped at five locations in Asia, North America and Europe

Miscanthus is a high-yielding bioenergy crop that is broadly adapted to temperate and tropical environments. Commercial cultivation of Miscanthus is predominantly limited to a single sterile triploid clone of Miscanthus ×giganteus, a hybrid between Miscanthus sacchariflorus and Miscanthus sinensis. To expand the genetic base of M. ×giganteus, the substantial diversity within its progenitor species should be used for cultivar improvement and diversification. Here we phenotyped a diversity panel of 605 M. sacchariflorus from six previously described genetic groups and 27 M. ×giganteus genotypes for dry biomass yield and 16 yield-component traits, in field trials grown over three years at one subtropical location (Zhuji, China) and four temperate locations (Foulum, Denmark; Sapporo, Japan; Urbana, Illinois; and Chuncheon, South Korea). There was considerable diversity in yield and yield-component traits among and within genetic groups of M. sacchariflorus, and across the five locations. Biomass yield of M. sacchariflorus ranged from 0.003-34.0 Mg ha-1 in year 3. Variation among the genetic groups was typically greater than within, so selection of genetic group should be an important first step for breeding with M. sacchariflorus. The Yangtze 2x genetic group (=ssp. lutarioriparius) of M. sacchariflorus had the tallest and thickest culms at all locations tested. Notably, the Yangtze 2x genetic group's exceptional culm length and yield-potential was driven primarily by a large number of nodes (>29 nodes culm-1 average over all locations), which was consistent with the especially late flowering of this group. The S Japan 4x, the N China/Korea/Russia 4x and the N China 2x genetic groups were also promising genetic resources for biomass yield, culm length and culm thickness, especially for temperate environments. Culm length was the best indicator of yield potential in M. sacchariflorus. These results will inform breeders’ selection of M. sacchariflorus genotypes for population improvement and adaptation to target production environments