HaploCatcher: An R package for prediction of haplotypes.

Wheat (Triticum aestivum L.) is crucial to global food security but is often threatened by diseases, pests, and environmental stresses. Wheat-stem sawfly (Cephus cinctus Norton) poses a major threat to food security in the United States, and solid-stem varieties, which carry the stem-solidness locus (Sst1), are the main source of genetic resistance against sawfly. Marker-assisted selection uses molecular markers to identify lines possessing beneficial haplotypes, like that of the Sst1 locus. In this study, an R package titled "HaploCatcher" was developed to predict specific haplotypes of interest in genome-wide genotyped lines. A training population of 1056 lines genotyped for the Sst1 locus, known to confer stem solidness, and genome-wide markers was curated to make predictions of the Sst1 haplotypes for 292 lines from the Colorado State University wheat breeding program. Predicted Sst1 haplotypes were compared to marker-derived haplotypes. Our results indicated that the training set was substantially predictive, with kappa scores of 0.83 for k-nearest neighbors and 0.88 for random forest models. Forward validation on newly developed breeding lines demonstrated that a random forest model, trained on the total available training data, had comparable accuracy between forward and cross-validation. Estimated group means of lines classified by haplotypes from PCR-derived markers and predictive modeling did not significantly differ. The HaploCatcher package is freely available and may be utilized by breeding programs, using their own training populations, to predict haplotypes for whole-genome sequenced early generation material.

Genetic characterization of root architectural traits in barley (Hordeum vulgare L.) using SNP markers.

Increasing attention is paid to providing new tools to breeders for targeted breeding for specific root traits that are beneficial in low-fertility, drying soils; however, such information is not available for barley (Hordeum vulgare L.). A panel of 191 barley accessions (originating from Australia, Europe, and Africa) was phenotyped for 26 root and shoot traits using the semi-hydroponic system and genotyped using 21 062 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The population structure analysis of the barley panel identified six distinct groups. We detected 1199 significant (P<0.001) marker-trait associations (MTAs) with r2 values up to 0.41. The strongest MTAs were found for root diameter in the top 20 cm and the longest root length. Based on the physical locations of these MTAs in the barley reference genome, we identified 37 putative QTLs for the root traits, and three QTLs for shoot traits, with nine QTLs located in the same physical regions. The genomic region 640-653 Mb on chromosome 7H was significant for five root length-related traits, where 440 annotated genes were located. The putative QTLs for various root traits identified in this study may be useful for genetic improvement regarding the adaptation of new barley cultivars to suboptimal environments and abiotic stresses.

Skim exome capture genotyping in wheat.

Next-generation sequencing (NGS) technology advancements continue to reduce the cost of high-throughput genome-wide genotyping for breeding and genetics research. Skim sequencing, which surveys the entire genome at low coverage, has become feasible for quantitative trait locus (QTL) mapping and genomic selection in various crops. However, the genome complexity of allopolyploid crops such as wheat (Triticum aestivum L.) still poses a significant challenge for genome-wide genotyping. Targeted sequencing of the protein-coding regions (i.e., exome) reduces sequencing costs compared to whole genome re-sequencing and can be used for marker discovery and genotyping. We developed a method called skim exome capture (SEC) that combines the strengths of these existing technologies and produces targeted genotyping data while decreasing the cost on a per-sample basis compared to traditional exome capture. Specifically, we fragmented genomic DNA using a tagmentation approach, then enriched those fragments for the low-copy genic portion of the genome using commercial wheat exome baits and multiplexed the sequencing at different levels to achieve desired coverage. We demonstrated that for a library of 48 samples, ∼7-8× target coverage was sufficient for high-quality variant detection. For higher multiplexing levels of 528 and 1056 samples per library, we achieved an average coverage of 0.76× and 0.32×, respectively. Combining these lower coverage SEC sequencing data with genotype imputation using a customized wheat practical haplotype graph database that we developed, we identified hundreds of thousands of high-quality genic variants across the genome. The SEC method can be used for high-resolution QTL mapping, genome-wide association studies, genomic selection, and other downstream applications.

Multi-trait genomic selection improves the prediction accuracy of end-use quality traits in hard winter wheat.

Improvement of end-use quality remains one of the most important goals in hard winter wheat (HWW) breeding. Nevertheless, the evaluation of end-use quality traits is confined to later development generations owing to resource-intensive phenotyping. Genomic selection (GS) has shown promise in facilitating selection for end-use quality; however, lower prediction accuracy (PA) for complex traits remains a challenge in GS implementation. Multi-trait genomic prediction (MTGP) models can improve PA for complex traits by incorporating information on correlated secondary traits, but these models remain to be optimized in HWW. A set of advanced breeding lines from 2015 to 2021 were genotyped with 8725 single-nucleotide polymorphisms and was used to evaluate MTGP to predict various end-use quality traits that are otherwise difficult to phenotype in earlier generations. The MTGP model outperformed the ST model with up to a twofold increase in PA. For instance, PA was improved from 0.38 to 0.75 for bake absorption and from 0.32 to 0.52 for loaf volume. Further, we compared MTGP models by including different combinations of easy-to-score traits as covariates to predict end-use quality traits. Incorporation of simple traits, such as flour protein (FLRPRO) and sedimentation weight value (FLRSDS), substantially improved the PA of MT models. Thus, the rapid low-cost measurement of traits like FLRPRO and FLRSDS can facilitate the use of GP to predict mixograph and baking traits in earlier generations and provide breeders an opportunity for selection on end-use quality traits by culling inferior lines to increase selection accuracy and genetic gains.

Quantitative trait loci for rolled leaf in a wheat EMS mutant from Jagger.

KEY MESSAGE: Two QTLs with major effects on rolled leaf trait were consistently detected on chromosomes 1A (QRl.hwwg-1AS) and 5A (QRl.hwwg-5AL) in the field experiments. Rolled leaf (RL) is a morphological strategy to protect plants from dehydration under stressed field conditions. Identification of quantitative trait loci (QTLs) underlining RL is essential to breed drought-tolerant wheat cultivars. A mapping population of 154 recombinant inbred lines was developed from the cross between JagMut1095, a mutant of Jagger, and Jagger to identify quantitative trait loci (QTLs) for the RL trait. A linkage map of 3106 cM was constructed with 1003 unique SNPs from 21 wheat chromosomes. Two consistent QTLs were identified for RL on chromosomes 1A (QRl.hwwg-1AS) and 5A (QRl.hwwg-5AL) in all field experiments. QRl.hwwg-1AS explained 24-56% of the phenotypic variation and QRl.hwwg-5AL explained up to 20% of the phenotypic variation. The combined percent phenotypic variation associated with the two QTLs was up to 61%. Analyses of phenotypic and genotypic data of recombinants generated from heterogeneous inbred families of JagMut1095 × Jagger delimited QRl.hwwg-1AS to a 6.04 Mb physical interval. This work lays solid foundation for further fine mapping and map-based cloning of QRl.hwwg-1AS.

QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster.

In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.

Redox-engineering enhances maize thermotolerance and grain yield in the field.

Increasing populations and temperatures are expected to escalate food demands beyond production capacities, and the development of maize lines with better performance under heat stress is desirable. Here, we report that constitutive ectopic expression of a heterologous glutaredoxin S17 from Arabidopsis thaliana (AtGRXS17) can provide thermotolerance in maize through enhanced chaperone activity and modulation of heat stress-associated gene expression. The thermotolerant maize lines had increased protection against protein damage and yielded a sixfold increase in grain production in comparison to the non-transgenic counterparts under heat stress field conditions. The maize lines also displayed thermotolerance in the reproductive stages, resulting in improved pollen germination and the higher fidelity of fertilized ovules under heat stress conditions. Our results present a robust and simple strategy for meeting rising yield demands in maize and, possibly, other crop species in a warming global environment.

Characterization of the genetic basis of local adaptation of wheat landraces from Iran and Pakistan using genome-wide association study.

Characterization of genomic regions underlying adaptation of landraces can reveal a quantitative genetics framework for local wheat (Triticum aestivum L.) adaptability. A collection of 512 wheat landraces from the eastern edge of the Fertile Crescent in Iran and Pakistan were genotyped using genome-wide single nucleotide polymorphism markers generated by genotyping-by-sequencing. The minor allele frequency (MAF) and the heterozygosity (H) of Pakistani wheat landraces (MAF = 0.19, H = 0.008) were slightly higher than the Iranian wheat landraces (MAF = 0.17, H = 0.005), indicating that Pakistani landraces were slightly more genetically diverse. Population structure analysis clearly separated the Pakistani landraces from Iranian landraces, which indicates two separate adaptability trajectories. The large-scale agro-climatic data of seven variables were quite dissimilar between Iran and Pakistan as revealed by the correlation coefficients. Genome-wide association study identified 91 and 58 loci using agroclimatic data, which likely underpin local adaptability of the wheat landraces from Iran and Pakistan, respectively. Selective sweep analysis identified significant hits on chromosomes 4A, 4B, 6B, 7B, 2D, and 6D, which were colocalized with the loci associated with local adaptability and with some known genes related to flowering time and grain size. This study provides insight into the genetic diversity with emphasis on the genetic architecture of loci involved in adaptation to local environments, which has breeding implications.

High-resolution genome-wide association study and genomic prediction for disease resistance and cold tolerance in wheat.

KEY MESSAGE: High-resolution genome-wide association study (GWAS) facilitated QTL fine mapping and candidate gene identification, and the GWAS based genomic prediction models were highly predictive and valuable in wheat genomic breeding. Wheat is a major staple food crop and provides more than one-fifth of the daily calories and dietary proteins for humans. Genome-wide association study (GWAS) and genomic selection (GS) for wheat stress resistance and tolerance related traits are critical to understanding their genetic architecture for improvement of breeding selection efficiency. However, the insufficient marker density in previous studies limited the utility of GWAS and GS in wheat genomic breeding. Here, we conducted a high-resolution GWAS for wheat leaf rust (LR), yellow rust (YR), powdery mildew (PM), and cold tolerance (CT) by genotyping a panel of 768 wheat cultivars using genotyping-by-sequencing. Among 153 quantitative trait loci (QTLs) identified, 81 QTLs were delimited to ≤ 1.0 Mb intervals with three validated using bi-parental populations. Furthermore, 837 stress resistance-related genes were identified in the QTL regions with 12 showing induced expression by YR and PM pathogens. Genomic prediction using 2608, 4064, 3907, and 2136 pre-selected SNPs based on GWAS and genotypic correlations between the SNPs showed high prediction accuracies of 0.76, 0.73, and 0.78 for resistance to LR, YR, and PM, respectively, and 0.83 for resistance to cold damage. Our study laid a solid foundation for large-scale QTL fine mapping, candidate gene validation and GS in wheat.

Characterization of an Incomplete Leaf Rust Resistance Gene on Chromosome 1RS and Development of KASP Markers for Lr47 in Wheat.

Leaf rust, caused by Puccinia triticina, is one of the most common wheat (Triticum aestivum) diseases in the Great Plains of the United States. A population of recombinant inbred lines from CI 17884 × 'Bainong 418' was evaluated for responses to leaf rust race Pt52-2 and genotyped using single nucleotide polymorphism (SNP) markers. Quantitative trait locus analysis identified a minor gene for resistance to leaf rust, designated QLr.stars-1RS, on the 1BL.1RS translocation segment in 'Bainong 418', and another leaf rust resistance gene, Lr47, on chromosome 7A of CI 17884. Lr47, originally identified in CI 17884 and located in a wheat-T. speltoides translocation segment 7S#1S, remains one of only a few race-specific resistance genes still effective in the Great Plains. A set of 7A-specific simple sequence repeat markers were developed and used to genotype CI 17884 and a pair of near-isogenic lines differing in the presence or absence of 7S#1S, PI 603918, and 'Pavon F76'. Haplotype analysis indicated that the estimated length of 7S#1S was 157.23 to 174.42 Megabases, accounting for ∼23% of the 7A chromosome. Two SNPs on 7S#1S and four SNPs on the 1RS chromosome arm were converted to Kompetitive allele-specific PCR (KASP) markers, which were subsequently validated in a panel of cultivars and elite breeding lines released within the last decade. Of these, one- and two-KASP markers are specific to the 1RS chromosome arm and 7S#1S, respectively, indicating that they can facilitate the introgression of Lr47 and QLr.stars-1RS into locally adapted wheat cultivars and breeding lines.

Adaptive genetic potential and plasticity of trait variation in the foundation prairie grass Andropogon gerardii across the US Great Plains' climate gradient: Implications for climate change and restoration.

Plant response to climate depends on a species' adaptive potential. To address this, we used reciprocal gardens to detect genetic and environmental plasticity effects on phenotypic variation and combined with genetic analyses. Four reciprocal garden sites were planted with three regional ecotypes of Andropogon gerardii, a dominant Great Plains prairie grass, using dry, mesic, and wet ecotypes originating from western KS to Illinois that span 500-1,200 mm rainfall/year. We aimed to answer: (a) What is the relative role of genetic constraints and phenotypic plasticity in controlling phenotypes? (b) When planted in the homesite, is there a trait syndrome for each ecotype? (c) How are genotypes and phenotypes structured by climate? and (d) What are implications of these results for response to climate change and use of ecotypes for restoration? Surprisingly, we did not detect consistent local adaptation. Rather, we detected co-gradient variation primarily for most vegetative responses. All ecotypes were stunted in western KS. Eastward, the wet ecotype was increasingly robust relative to other ecotypes. In contrast, fitness showed evidence for local adaptation in wet and dry ecotypes with wet and mesic ecotypes producing little seed in western KS. Earlier flowering time in the dry ecotype suggests adaptation to end of season drought. Considering ecotype traits in homesite, the dry ecotype was characterized by reduced canopy area and diameter, short plants, and low vegetative biomass and putatively adapted to water limitation. The wet ecotype was robust, tall with high biomass, and wide leaves putatively adapted for the highly competitive, light-limited Eastern Great Plains. Ecotype differentiation was supported by random forest classification and PCA. We detected genetic differentiation and outlier genes associated with primarily precipitation. We identified candidate gene GA1 for which allele frequency associated with plant height. Sourcing of climate adapted ecotypes should be considered for restoration.

High-Resolution Genome-wide Association Study Identifies Genomic Regions and Candidate Genes for Important Agronomic Traits in Wheat.

Wheat (Triticum aestivum) is a major staple food crop worldwide. Genetic dissection of important agronomic traits is essential for continuous improvement of wheat yield to meet the demand of the world's growing population. We conducted a large-scale genome-wide association study (GWAS) using a panel of 768 wheat cultivars that were genotyped with 327 609 single-nucleotide polymorphisms generated by genotyping-by-sequencing and detected 395 quantitative trait loci (QTLs) for 12 traits under 7 environments. Among them, 273 QTLs were delimited to ≤1.0-Mb intervals and 7 of them are either known genes (Rht-D, Vrn-B1, and Vrn-D1) that have been cloned or known QTLs (TaGA2ox8, APO1, TaSus1-7B, and Rht12) that were previously mapped. Eight putative candidate genes were identified for three QTLs that enhance spike seed setting and grain size using gene expression data and were validated in three bi-parental populations. Protein sequence analysis identified 33 putative wheat orthologs that have high identity with rice genes in QTLs affecting similar traits. Large r2 values for additive effects observed among the QTLs for most traits indicated that the phenotypes of these identified QTLs were highly predictable. Results from this study demonstrated that significantly increasing GWAS population size and marker density greatly improves detection and identification of candidate genes underlying a QTL, solidifying the foundation for large-scale QTL fine mapping, candidate gene validation, and developing functional markers for genomics-based breeding in wheat.

Genomic diversity in pearl millet inbred lines derived from landraces and improved varieties.

BACKGROUND: Genetic improvement of pearl millet is lagging behind most of the major crops. Development of genomic resources is expected to expedite breeding for improved agronomic traits, stress tolerance, yield, and nutritional quality. Genotyping a breeding population with high throughput markers enables exploration of genetic diversity, population structure, and linkage disequilibrium (LD) which are important preludes for marker-trait association studies and application of genomic-assisted breeding. RESULTS: Genotyping-by-sequencing (GBS) libraries of 309 inbred lines derived from landraces and improved varieties from Africa and India generated 54,770 high quality single nucleotide polymorphism (SNP) markers. On average one SNP per 29 Kb was mapped in the reference genome, with the telomeric regions more densely mapped than the pericentromeric regions of the chromosomes. Population structure analysis using 30,208 SNPs evenly distributed in the genome divided 309 accessions into five subpopulations with different levels of admixture. Pairwise genetic distance (GD) between accessions varied from 0.09 to 0.33 with the average distance of 0.28. Rapid LD decay implied low tendency of markers inherited together. Genetic differentiation estimates were the highest between subgroups 4 and 5, and the lowest between subgroups 1 and 2. CONCLUSIONS: Population genomic analysis of pearl millet inbred lines derived from diverse geographic and agroecological features identified five subgroups mostly following pedigree differences with different levels of admixture. It also revealed the prevalence of high genetic diversity in pearl millet, which is very useful in defining heterotic groups for hybrid breeding, trait mapping, and holds promise for improving pearl millet for yield and nutritional quality. The short LD decay observed suggests an absence of persistent haplotype blocks in pearl millet. The diverse genetic background of these lines and their low LD make this set of germplasm useful for traits mapping.

Genetic dissection of heat-responsive physiological traits to improve adaptation and increase yield potential in soft winter wheat.

BACKGROUND: Climate change, including higher temperatures (HT) has a detrimental impact on wheat productivity and modeling studies predict more frequent heat waves in the future. Wheat growth can be impaired by high daytime and nighttime temperature at any developmental stage, especially during the grain filling stage. Leaf chlorophyll content, leaf greenness, cell membrane thermostability, and canopy temperature have been proposed as candidate traits to improve crop adaptation and yield potential of wheat under HT. Nonetheless, a significant gap exists in knowledge of genetic backgrounds associated with these physiological traits. Identifying genetic loci associated with these traits can facilitate physiological breeding for increased yield potential under high temperature stress condition in wheat. RESULTS: We conducted genome-wide association study (GWAS) on a 236 elite soft wheat association mapping panel using 27,466 high quality single nucleotide polymorphism markers. The panel was phenotyped for three years in two locations where heat shock was common. GWAS identified 500 significant marker-trait associations (MTAs) (p ≤ 9.99 × 10- 4). Ten MTAs with pleiotropic effects detected on chromosomes 1D, 2B, 3A, 3B, 6A, 7B, and 7D are potentially important targets for selection. Five MTAs associated with physiological traits had pleiotropic effects on grain yield and yield-related traits. Seventy-five MTAs were consistently expressed over several environments indicating stability and more than half of these stable MTAs were found in genes encoding different types of proteins associated with heat stress. CONCLUSIONS: We identified 500 significant MTAs in soft winter wheat under HT stress. We found several stable loci across environments and pleiotropic markers controlling physiological and agronomic traits. After further validation, these MTAs can be used in marker-assisted selection and breeding to develop varieties with high stability for grain yield under high temperature.

Multiplex restriction amplicon sequencing: a novel next-generation sequencing-based marker platform for high-throughput genotyping.

To enable rapid selection of traits in marker-assisted breeding, markers must be technically simple, low-cost, high-throughput and randomly distributed in a genome. We developed such a technology, designated as Multiplex Restriction Amplicon Sequencing (MRASeq), which reduces genome complexity by polymerase chain reaction (PCR) amplification of amplicons flanked by restriction sites. The first PCR primers contain restriction site sequences at 3'-ends, preceded by 6-10 bases of specific or degenerate nucleotide sequences and then by a unique M13-tail sequence which serves as a binding site for a second PCR that adds sequencing primers and barcodes to allow sample multiplexing for sequencing. The sequences of restriction sites and adjacent nucleotides can be altered to suit different species. Physical mapping of MRASeq SNPs from a biparental population of allohexaploid wheat (Triticum aestivum L.) showed a random distribution of SNPs across the genome. MRASeq generated thousands of SNPs from a wheat biparental population and natural populations of wheat and barley (Hordeum vulgare L.). This novel, next-generation sequencing-based genotyping platform can be used for linkage mapping to screen quantitative trait loci (QTL), background selection in breeding and many other genetics and breeding applications of various species.

A deletion mutation in TaHRC confers Fhb1 resistance to Fusarium head blight in wheat.

Fusarium head blight (FHB), which is mainly caused by Fusarium graminearum, is a destructive wheat disease that threatens global wheat production. Fhb1, a quantitative trait locus discovered in Chinese germplasm, provides the most stable and the largest effect on FHB resistance in wheat. Here we show that TaHRC, a gene that encodes a putative histidine-rich calcium-binding protein, is the key determinant of Fhb1-mediated resistance to FHB. We demonstrate that TaHRC encodes a nuclear protein conferring FHB susceptibility and that a deletion spanning the start codon of this gene results in FHB resistance. Identical sequences of the TaHRC-R allele in diverse accessions indicate that Fhb1 had a single origin, and phylogenetic and haplotype analyses suggest that the TaHRC-R allele most likely originated from a line carrying the Dahongpao haplotype. This discovery opens a new avenue to improve FHB resistance in wheat, and possibly in other cereal crops, by manipulating TaHRC sequence through bioengineering approaches.

Genetic Diversity, Population Structure, and Linkage Disequilibrium of Pearl Millet.

CORE IDEAS: Mapping of GBS reads of 398 accessions to the draft genome sequence identified 82,112 SNPs Model-based clustering analysis revealed a hierarchical genetic structure of six subgroups Greater LD decay in the west-African subpopulation is likely due to long history of recombination Genetic differentiation analysis among subpopulations revealed variation in selection signatures Pearl millet [Cenchrus americanus (L.) Morrone syn. Pennisetum glaucum (L.) R. Br.] is one of the most extensively cultivated cereals in the world, after wheat (Triticum aestivum L.), maize (Zea mays L.), rice (Oryza sativa L.), barley (Hordeum vulgare L.), and sorghum [Sorghum bicolor (L.) Moench]. It is the main component of traditional farming systems and a staple food in the arid and semiarid regions of Africa and southern Asia. However, its genetic improvement is lagging behind other major cereals and the yield is still low. Genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers were screened on a total of 398 accessions from different geographic regions to assess genetic diversity, population structure, and linkage disequilibrium (LD). By mapping the GBS reads to the reference genome sequence, 82,112 genome-wide SNPs were discovered. The telomeric regions of the chromosomes have the higher SNP density than in pericentromeric regions. Model-based clustering analysis of the population revealed a hierarchical genetic structure of six subgroups that mostly overlap with the geographic origins or sources of the genotypes but with differing levels of admixtures. A neighbor-joining phylogeny analysis revealed that germplasm from western Africa rooted the dendrogram with much diversity within each subgroup. Greater LD decay was observed in the west-African subpopulation than in the other subpopulations, indicating a long history of recombination among landraces. Also, genome scan of genetic differentiatation detected different selection histories among subpopulations. These results have potential application in the development of genomic-assisted breeding in pearl millet and heterotic grouping of the lines for improved hybrid performance.

Local adaptation, genetic divergence, and experimental selection in a foundation grass across the US Great Plains' climate gradient.

Many prior studies have uncovered evidence for local adaptation using reciprocal transplant experiments. However, these studies are rarely conducted for a long enough time to observe succession and competitive dynamics in a community context, limiting inferences for long-lived species. Furthermore, the genetic basis of local adaptation and genetic associations with climate has rarely been identified. Here, we report on a long-term (6-year) experiment conducted under natural conditions focused on Andropogon gerardii, the dominant grass of the North American Great Plains tallgrass ecosystem. We focus on this foundation grass that comprises 80% of tallgrass prairie biomass and is widely used in 20,000 km2 of restoration. Specifically, we asked the following questions: (a) Whether ecotypes are locally adapted to regional climate in realistic ecological communities. (b) Does adaptive genetic variation underpin divergent phenotypes across the climate gradient? (c) Is there evidence of local adaptation if the plants are exposed to competition among ecotypes in mixed ecotype plots? Finally, (d) are local adaptation and genetic divergence related to climate? Reciprocal gardens were planted with 3 regional ecotypes (originating from dry, mesic, wet climate sources) of Andropogon gerardii across a precipitation gradient (500-1,200 mm/year) in the US Great Plains. We demonstrate local adaptation and differentiation of ecotypes in wet and dry environments. Surprisingly, the apparent generalist mesic ecotype performed comparably under all rainfall conditions. Ecotype performance was underpinned by differences in neutral diversity and candidate genes corroborating strong differences among ecotypes. Ecotype differentiation was related to climate, primarily rainfall. Without long-term studies, wrong conclusions would have been reached based on the first two years. Further, restoring prairies with climate-matched ecotypes is critical to future ecology, conservation, and sustainability under climate change.

Identification of markers linked to genes for sprouting tolerance (independent of grain color) in hard white winter wheat (HWWW).

KEY MESSAGE: Hard red wheats can donate genes to hard white wheats for tolerance to preharvest sprouting, the effects are quantitative in nature, and may be tracked with previously described DNA markers. ABSTRACT: Pre-harvest sprouting (PHS) of wheat (Triticum aestivum L.) can negatively impact end-use quality and seed viability at planting. Due to preferences for white over red wheat in international markets, white wheat with PHS tolerance has become increasingly desired for worldwide wheat production. In general, however, red wheat is more tolerant of sprouting than white wheat. The main objective of this study was the identification of PHS tolerance conditioned by genes donated from hard red winter wheat, using markers applicable to the Great Plains hard white wheat gene pool. Three red wheat by white wheat populations, Niobrara/NW99L7068, NE98466/NW99L7068 and Jagalene/NW99L7068 were developed, and white-seeded progenies were analyzed for PHS tolerance and used to identify markers for the trait. In the three populations, marker loci with significant allelic effects were most commonly located on chromosomes of group 2, 3, 4 and 5, though additional markers were detected across the wheat genome. Chromosome 3A was the only chromosome with significant markers in all three populations. Markers were inconsistent across the three populations, and markers linked to tolerance-inducing loci were identified in both tolerant and susceptible parents. Additive effects of marker loci were common. In the present investigation, a wide range of PHS tolerance was observed, even though all lines were fixed for the recently reported positive TaPHS1 allele. PHS tolerance is controlled by additive major gene effects with minor gene effects where variations of minor gene effects were still unclear.

Using Next Generation Sequencing for Multiplexed Trait-Linked Markers in Wheat.

With the advent of next generation sequencing (NGS) technologies, single nucleotide polymorphisms (SNPs) have become the major type of marker for genotyping in many crops. However, the availability of SNP markers for important traits of bread wheat (Triticum aestivum L.) that can be effectively used in marker-assisted selection (MAS) is still limited and SNP assays for MAS are usually uniplex. A shift from uniplex to multiplex assays will allow the simultaneous analysis of multiple markers and increase MAS efficiency. We designed 33 locus-specific markers from SNP or indel-based marker sequences that linked to 20 different quantitative trait loci (QTL) or genes of agronomic importance in wheat and analyzed the amplicon sequences using an Ion Torrent Proton Sequencer and a custom allele detection pipeline to determine the genotypes of 24 selected germplasm accessions. Among the 33 markers, 27 were successfully multiplexed and 23 had 100% SNP call rates. Results from analysis of "kompetitive allele-specific PCR" (KASP) and sequence tagged site (STS) markers developed from the same loci fully verified the genotype calls of 23 markers. The NGS-based multiplexed assay developed in this study is suitable for rapid and high-throughput screening of SNPs and some indel-based markers in wheat.