Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach

Assessing the Impacts of Adaptation to Native-Range Habitats and Contemporary Founder Effects on Genetic Diversity in an Invasive Fish

Species invading non-native habitats can cause irreversible environmental damage and economic harm. Yet, how introduced species become widespread invaders remains poorly understood. Adaptation within native-range habitats and rapid adaptation to new environments may both influence invasion success. Here, we examine these hypotheses using 7058 SNPs from 36 native, 40 introduced and 19 farmed populations of tench, a fish native to Eurasia. We examined genetic structure among these populations and accounted for long-term evolutionary history within the native range to assess whether introduced populations exhibited lower genetic diversity than native populations. Subsequent to infer genotype-environment correlations within native-range habitats, we assessed whether adaptation to native environments may have shaped the success of some introduced populations. At the broad scale, two glacial refugia contributed to the ancestry and genomic diversity of tench. However, native, introduced and farmed populations of admixed origin exhibited up to 10-fold more genetic diversity (i.e., observed heterozygosity, expected heterozygosity and allelic richness) compared to populations with predominantly single-source ancestry. The effects of introduction to a new location were also apparent as introduced populations exhibited fewer private alleles (mean = 9.9 and 18.9 private alleles in introduced and native populations, respectively) and higher population-specific Fst compared to native populations, highlighting their distinctiveness relative to the pool of allelic frequencies across tench populations. Finally, introduced populations with varying levels of genetic variation and similar genetic compositions have become established and persisted under strikingly different climatic and ecological conditions. Our results suggest that lack of prior adaptation and low genetic variation may not consistently hinder the success of introduced populations for species with a demonstrated ability to expand their native range.

Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance

KEY MESSAGE

Single nucleotide polymorphism (SNP) markers in wheat and their prospects in breeding with special reference to rust resistance. Single nucleotide polymorphism (SNP)-based markers are increasingly gaining momentum for screening and utilizing vital agronomic traits in wheat. To date, more than 260 million SNPs have been detected in modern cultivars and landraces of wheat. This rapid SNP discovery was made possible through the release of near-complete reference and pan-genome assemblies of wheat and its wild relatives, coupled with whole genome sequencing (WGS) of thousands of wheat accessions. Further, genotyping customized SNP sites were facilitated by a series of arrays (9 to 820Ks), a cost effective substitute WGS. Lately, germplasm-specific SNP arrays have been introduced to characterize novel traits and detect closely linked SNPs for marker-assisted breeding. Subsequently, the kompetitive allele-specific PCR (KASP) assay was introduced for rapid and large-scale screening of specific SNP markers. Moreover, with the advances and reduction in sequencing costs, ample opportunities arise for generating SNPs artificially through mutations and in combination with next-generation sequencing and comparative genomic analyses. In this review, we provide historical developments and prospects of SNP markers in wheat breeding with special reference to rust resistance where over 50 genetic loci have been characterized through SNP markers. Rust resistance is one of the most essential traits for wheat breeding as new strains of the Puccinia fungus, responsible for rust diseases, evolve frequently and globally.

Genetic resources of African mahogany in Brazil: genomic diversity and structure of forest plantations

BACKGROUND

African mahogany species (Khaya sp.) have been introduced to Brazil gaining increasing economic interest over the last years, as they produce high quality wood for industrial applications. To this date, however, the knowledge available on the genetic basis of African mahogany plantations in Brazil is limited, which has driven this study to examine the extent of genetic diversity and structure of three cultivated species (Khaya grandifoliola, Khaya senegalensis and Khaya ivorensis) and their prospects for forest breeding.

RESULTS

In total, 115 individuals were genotyped (48 of K. grandifoliola, 34 of K. senegalensis and 33 of K. ivorensis) for 3,330 filtered neutral loci obtained from genotyping-by-sequencing for the three species. The number of SNPs varied from 2,951 in K. ivorensis to 4,754 in K. senegalensis. Multiloci clustering, principal component analysis, Bayesian structure and network analyses showed a clear genetic separation among the three species. Structure analysis also showed internal structure within each species, highlighting genetic subgroups that could be sampled for selecting distinct genotypes for further breeding, although the genetic distances are moderate to low.

CONCLUSION

In our study, SNP markers efficiently assessed the genomic diversity of African mahogany forest plantations in Brazil. Our genetic data clearly separated the three Khaya species. Moreover, pairwise estimates of genetic distances among individuals within each species showed considerable genetic divergence among individuals. By genotyping 115 pre-selected individuals with desirable growth traits, allowed us not only to recommend superior genotypes but also to identify genetically distinct individuals for use in breeding crosses.

Training set optimization is a feasible alternative for perennial orphan crop domestication and germplasm management: an Acrocomia aculeata example

Orphan perennial native species are gaining importance as sustainability in agriculture becomes crucial to mitigate climate change. Nevertheless, issues related to the undomesticated status and lack of improved germplasm impede the evolution of formal agricultural initiatives. Acrocomia aculeata - a neotropical palm with potential for oil production - is an example. Breeding efforts can aid the species to reach its full potential and increase market competitiveness. Here, we present genomic information and training set optimization as alternatives to boost orphan perennial native species breeding using Acrocomia aculeata as an example. Furthermore, we compared three SNP calling methods and, for the first time, presented the prediction accuracies of three yield-related traits. We collected data for two years from 201 wild individuals. These trees were genotyped, and three references were used for SNP calling: the oil palm genome, de novo sequencing, and the A. aculeata transcriptome. The traits analyzed were fruit dry mass (FDM), pulp dry mass (PDM), and pulp oil content (OC). We compared the predictive ability of GBLUP and BayesB models in cross- and real validation procedures. Afterwards, we tested several optimization criteria regarding consistency and the ability to provide the optimized training set that yielded less risk in both targeted and untargeted scenarios. Using the oil palm genome as a reference and GBLUP models had better results for the genomic prediction of FDM, OC, and PDM (prediction accuracies of 0.46, 0.45, and 0.39, respectively). Using the criteria PEV, r-score and core collection methodology provides risk-averse decisions. Training set optimization is an alternative to improve decision-making while leveraging genomic information as a cost-saving tool to accelerate plant domestication and breeding. The optimized training set can be used as a reference for the characterization of native species populations, aiding in decisions involving germplasm collection and construction of breeding populations.

Genetic constitution and variability in synthetic populations of intermediate wheatgrass, an outcrossing perennial grain crop

Intermediate wheatgrass (IWG) is a perennial grass that produces nutritious grain while offering substantial ecosystem services. Commercial varieties of this crop are mostly synthetic panmictic populations that are developed by intermating a few selected individuals. As development and generation advancement of these synthetic populations is a multiyear process, earlier synthetic generations are tested by the breeders and subsequent generations are released to the growers. A comparison of generations within IWG synthetic cultivars is currently lacking. In this study, we used simulation models and genomic prediction to analyze population differences and trends of genetic variance in 4 synthetic generations of MN-Clearwater, a commercial cultivar released by the University of Minnesota. Little to no differences were observed among the 4 generations for population genetic, genetic kinship, and genome-wide marker relationships measured via linkage disequilibrium. A reduction in genetic variance was observed when 7 parents were used to generate synthetic populations while using 20 led to the best possible outcome in determining population variance. Genomic prediction of plant height, free threshing ability, seed mass, and grain yield among the 4 synthetic generations showed a few significant differences among the generations, yet the differences in values were negligible. Based on these observations, we make 2 major conclusions: (1) the earlier and latter synthetic generations of IWG are mostly similar to each other with minimal differences and (2) using 20 genotypes to create synthetic populations is recommended to sustain ample genetic variance and trait expression among all synthetic generations.

Milletomics: a metabolomics centered integrated omics approach toward genetic progression

Producing alternative staple foods like millet will be essential to feeding ten billion people by 2050. The increased demand for millet is driving researchers to improve its genetic variation. Millets include protein, dietary fiber, phenolic substances, and flavonoid components. Its climate resilience makes millet an appealing crop for agronomic sustainability. Integrative omics technologies could potentially identify and develop millets with desirable phenotypes that may have high agronomic value. Millets' salinity and drought tolerance have been enhanced using transcriptomics. In foxtail, finger, and pearl millet, proteomics has discovered salt-tolerant protein, phytohormone-focused protein, and drought tolerance. Metabolomics studies have revealed that certain metabolic pathways including those involving lignin, flavonoids, phenylpropanoid, and lysophospholipids are critical for many processes, including seed germination, photosynthesis, energy metabolism, and the synthesis of bioactive chemicals necessary for drought tolerance. Metabolomics integration with other omics revealed metabolome engineering and trait-specific metabolite creation. Integrated metabolomics and ionomics are still in the development stage, but they could potentially assist in comprehending the pathway of ionomers to control nutrient levels and biofortify millet. Epigenomic analysis has shown alterations in DNA methylation patterns and chromatin structure in foxtail and pearl millets in response to abiotic stress. Whole-genome sequencing utilizing next-generation sequencing is the most proficient method for finding stress-induced phytoconstituent genes. New genome sequencing enables novel biotechnological interventions including genome-wide association, mutation-based research, and other omics approaches. Millets can breed more effectively by employing next-generation sequencing and genotyping by sequencing, which may mitigate climate change. Millet marker-assisted breeding has advanced with high-throughput markers and combined genotyping technologies.

36-year study reveals stability of a wild wheat population across microhabitats

Long-term genetic studies of wild populations are very scarce, but are essential for connecting ecological and population genetics models, and for understanding the dynamics of biodiversity. We present a study of a wild wheat population sampled over a 36-year period at high spatial resolution. We genotyped 832 individuals from regular sampling along transects during the course of the experiment. Genotypes were clustered into ecological microhabitats over scales of tens of metres, and this clustering was remarkably stable over the 36 generations of the study. Simulations show that it is difficult to determine whether this spatial and temporal stability reflects extremely limited dispersal or fine-scale local adaptation to ecological parameters. Using a common-garden experiment, we showed that the genotypes found in distinct microhabitats differ phenotypically. Our results provide a rare insight into the population genetics of a natural population over a long monitoring period.

Improving complex agronomic and domestication traits in the perennial grain crop intermediate wheatgrass with genetic mapping and genomic prediction

The perennial grass Thinopyrum intermedium (intermediate wheatgrass [IWG]) is being domesticated as a food crop. With a deep root system and high biomass, IWG can help reduce soil and water erosion and limit nutrient runoff. As a novel grain crop undergoing domestication, IWG lags in yield, seed size, and other agronomic traits compared to annual grains. Better characterization of trait variation and identification of genetic markers associated with loci controlling the traits could help in further improving this crop. The University of Minnesota's Cycle 5 IWG breeding population of 595 spaced plants was evaluated at two locations in 2021 and 2022 for agronomic traits plant height, grain yield, and spike weight, and domestication traits shatter resistance, free grain threshing, and seed size. Pairwise trait correlations were weak to moderate with the highest correlation observed between seed size and height (0.41). Broad-sense trait heritabilities were high (0.68-0.77) except for spike weight (0.49) and yield (0.44). Association mapping using 24,284 genome-wide single nucleotide polymorphism markers identified 30 main quantitative trait loci (QTLs) across all environments and 32 QTL-by-environment interactions (QTE) at each environment. The genomic prediction model significantly improved predictions when parents were used in the training set and significant QTLs and QTEs used as covariates. Seed size was the best predicted trait with model predictive ability (r) of 0.72; yield was predicted moderately well (r = 0.45). We expect this discovery of significant genomic loci and mostly high trait predictions from genomic prediction models to help improve future IWG breeding populations.

The population genomics of Conyza spp. in soybean macroregions suggest the spread of herbicide resistance through intraspecific and interspecific gene flow

Herbicide-resistant Conyza spp. are a threat to many crops. These widespread weeds are closely related species and often cooccur. To characterize the origins of their resistance and the mechanisms underlying their spread, we assessed the genomic variation in glyphosate-resistant Conyza spp. in Brazil. Twenty populations were sampled from soybean fields across four macroregions (MRSs). A genotyping-by-sequencing study resulted in 2,998 single-nucleotide polymorphisms (SNPs) obtained for C. bonariensis (L.) and the closely related C. sumatrensis (Retz) E. Walker. Higher genomic diversity (π) and heterozygosity (HO/HE) and lower inbreeding coefficient (FIS) values were detected in populations of Conyza spp. from MRS 1 (southern) than in those from other MRSs. Strong genomic structure clustered individuals into three groups (FST = 0.22; p value = 0.000) associated with the MRSs. Thus, resistance to glyphosate originated from independent selection in different MRSs across Brazil. Our dataset supports the occurrence of intraspecific gene flow in Brazil and identified individuals of C. bonariensis that did not group within species. These findings suggest that allelic introgressions within and among species have impacted the evolution and spread of resistance to glyphosate in Conyza spp. We discuss how to mitigate new resistance cases, particularly for the released stacked traits herbicide tolerance in soybeans.

Genetic dissection of value-added quality traits and agronomic parameters through genome-wide association mapping in bread wheat (T. aestivum L.)

Bread wheat (T. aestivum) is one of the world's most widely consumed cereals. Since micronutrient deficiencies are becoming more common among people who primarily depend upon cereal-based diets, a need for better-quality wheat varieties has been felt. An association panel of 154 T. aestivum lines was evaluated for the following quality traits: grain appearance (GA) score, grain hardness (GH), phenol reaction (PR) score, protein percent, sodium dodecyl sulfate (SDS) sedimentation value, and test weight (TWt). In addition, the panel was also phenotyped for grain yield and related traits such as days to heading, days to maturity, plant height, and thousand kernel weight for the year 2017-18 at the Borlaug Institute for South Asia (BISA) Ludhiana and Jabalpur sites. We performed a genome-wide association analysis on this panel using 18,351 genotyping-by-sequencing (GBS) markers to find marker-trait associations for quality and grain yield-related traits. We detected 55 single nucleotide polymorphism (SNP) marker trait associations (MTAs) for quality-related traits on chromosomes 7B (10), 1A (9), 2A (8), 3B (6), 2B (5), 7A (4), and 1B (3), with 3A, 4A, and 6D, having two and the rest, 4B, 5A, 5B, and 1D, having one each. Additionally, 20 SNP MTAs were detected for yield-related traits based on a field experiment conducted in Ludhiana on 7D (4) and 4D (3) chromosomes, while 44 SNP MTAs were reported for Jabalpur on chromosomes 2D (6), 7A (5), 2A (4), and 4A (4). Utilizing these loci in marker-assisted selection will benefit from further validation studies for these loci to improve hexaploid wheat for better yield and grain quality.

Genomic architecture and population structure of Boreogadus saida from Canadian waters

The polar cod, Boreogadus saida, is an abundant and ubiquitous forage fish and a crucial link in Arctic marine trophic dynamics. Our objective was to unravel layers of genomic structure in B. saida from Canadian waters, specifically screening for potential hybridization with the Arctic cod, Arctogadus glacialis, large chromosomal inversions, and sex-linked regions, prior to interpreting population structure. Our analysis of 53,384 SNPs in 522 individuals revealed hybridization and introgression between A. glacialis and B. saida. Subsequent population level analyses of B. saida using 12,305 SNPs in 511 individuals revealed three large (ca. 7.4-16.1 Mbp) chromosomal inversions, and a 2 Mbp region featuring sex-linked loci. We showcase population structuring across the Western and Eastern North American Arctic, and subarctic regions ranging from the Hudson Bay to the Canadian Atlantic maritime provinces. Genomic signal for the inferred population structure was highly aggregated into a handful of SNPs (13.8%), pointing to potentially important adaptive evolution across the Canadian range. Our study provides a high-resolution perspective on the genomic structure of B. saida, providing a foundation for work that could be expanded to the entire circumpolar range for the species.

Genomic regions influencing the hyperspectral phenome of deoxynivalenol infected wheat

The quantitative nature of fusarium head blight (FHB) resistance requires further exploration of the wheat genome to identify regions conferring resistance. In this study, we explored the application of hyperspectral imaging of Fusarium-infected wheat kernels and identified regions of the wheat genome contributing significantly to the accumulation of Deoxynivalenol (DON) mycotoxin. Strong correlations were identified between hyperspectral reflectance values for 204 wavebands in the 397-673 nm range and DON mycotoxin. Dimensionality reduction using principal components was performed for all 204 wavebands and 38 sliding windows across the range of wavebands. The first principal component (PC1) of all 204 wavebands explained 70% of the total variation in waveband reflectance values and was highly correlated with DON mycotoxin. PC1 was used as a phenotype in a genome wide association study and a large effect QTL on chromosome 2D was identified for PC1 of all wavebands as well as nearly all 38 sliding windows. The allele contributing variation in PC1 values also led to a substantial reduction in DON. The 2D polymorphism affecting DON levels localized to the exon of TraesCS2D02G524600 which is upregulated in wheat spike and rachis tissues during FHB infection. This work demonstrates the value of hyperspectral imaging as a correlated trait for investigating the genetic basis of resistance and developing wheat varieties with enhanced resistance to FHB.

Fine mapping of stem rust resistance derived from soft red winter wheat cultivar AGS2000 to an NLR gene cluster on chromosome 6D

The Puccinia graminis f. sp. tritici (Pgt) Ug99-emerging virulent races present a major challenge to global wheat production. To meet present and future needs, new sources of resistance must be found. Identification of markers that allow tracking of resistance genes is needed for deployment strategies to combat highly virulent pathogen races. Field evaluation of a DH population located a QTL for stem rust (Sr) resistance, QSr.nc-6D from the breeding line MD01W28-08-11 to the distal region of chromosome arm 6DS where Sr resistance genes Sr42, SrCad, and SrTmp have been identified. A locus for seedling resistance to Pgt race TTKSK was identified in a DH population and an RIL population derived from the cross AGS2000 × LA95135. The resistant cultivar AGS2000 is in the pedigree of MD01W28-08-11 and our results suggest that it is the source of Sr resistance in this breeding line. We exploited published markers and exome capture data to enrich marker density in a 10 Mb region flanking QSr.nc-6D. Our fine mapping in heterozygous inbred families identified three markers co-segregating with resistance and delimited QSr.nc-6D to a 1.3 Mb region. We further exploited information from other genome assemblies and identified collinear regions of 6DS harboring clusters of NLR genes. Evaluation of KASP assays corresponding to our co-segregating SNP suggests that they can be used to track this Sr resistance in breeding programs. However, our results also underscore the challenges posed in identifying genes underlying resistance in such complex regions in the absence of genome sequence from the resistant genotypes.

Targeting Induced Local Lesions in Genomes (TILLING): advances and opportunities for fast tracking crop breeding

The intensification of food production via conventional crop breeding alone is inadequate to cater for global hunger. The development of precise and expeditious high throughput reverse genetics approaches has hugely benefited modern plant breeding programs. Targeting Induced Local Lesions in Genomes (TILLING) is one such reverse genetics approach which employs chemical/physical mutagenesis to create new genetic sources and identifies superior/novel alleles. Owing to technical limitations and sectional applicability of the original TILLING protocol, it has been timely modified. Successions include: EcoTILLING, Double stranded EcoTILLING (DEcoTILLING), Self-EcoTILLING, Individualized TILLING (iTILLING), Deletion-TILLING (De-TILLING), PolyTILLING, and VeggieTILLING. This has widened its application to a variety of crops and needs. They can characterize mutations in coding as well as non-coding regions and can overcome complexities associated with the large genomes. Combining next generation sequencing tools with the existing TILLING protocols has enabled screening of huge germplasm collections and mutant populations for the target genes. In silico TILLING platforms have transformed TILLING into an exciting breeding approach. The present review outlines these multifarious TILLING modifications for precise mutation detection and their application in advance breeding programmes together with relevant case studies. Appropriate use of these protocols will open up new avenues for crop improvement in the twenty first century.

Diving into broad-scale and high-resolution population genomics to decipher drivers of structure and climatic vulnerability in a marine invertebrate

Species with widespread distributions play a crucial role in our understanding of climate change impacts on population structure. In marine species, population structure is often governed by both high connectivity potential and selection across strong environmental gradients. Despite the complexity of factors influencing marine populations, studying species with broad distribution can provide valuable insights into the relative importance of these factors and the consequences of climate-induced alterations across environmental gradients. We used the northern shrimp Pandalus borealis and its wide latitudinal distribution to identify current drivers of population structure and predict the species' vulnerability to climate change. A total of 1514 individuals sampled across 24° latitude were genotyped at high geographic (54 stations) and genetic (14,331 SNPs) resolutions to assess genetic variation and environmental correlations. Four populations were identified in addition to finer substructure associated with local adaptation. Geographic patterns of neutral population structure reflected predominant oceanographic currents, while a significant proportion of the genetic variation was associated with gradients in salinity and temperature. Adaptive landscapes generated using climate projections suggest a larger genomic offset in the southern extent of the P. borealis range, where shrimp had the largest adaptive standing genetic variation. Our genomic results combined with recent observations point to further deterioration in southern regions and an impending vulnerable status in the regions at higher latitudes for P. borealis. They also provide rare insights into the drivers of population structure and climatic vulnerability of a widespread meroplanktonic species, which is crucial to understanding future challenges associated with invertebrates essential to ecosystem functioning.

Characterization of Quantitative Trait Loci for Leaf Rust Resistance from CI 13227 in Three Winter Wheat Populations

Leaf rust is a widespread foliar wheat disease causing substantial yield losses worldwide. Slow rusting is "adult plant" resistance that significantly slows epidemic development and thereby reduces yield loss. Wheat accession CI 13227 was previously characterized as having slow-rusting resistance. To validate the quantitative trait loci (QTLs) and develop diagnostic markers for slow rusting resistance in CI 13227, a new population of recombinant inbred lines of CI 13227 × Everest was evaluated for latent period, final severity, area under the disease progress curve, and infection type in greenhouses and genotyped using genotyping-by-sequencing. Four QTLs were identified on chromosome arms 2BL, 2DS, 3BS, and 7BL, explaining 6.82 to 28.45% of the phenotypic variance for these traits. Seven kompetitive allele-specific polymorphism markers previously reported to be linked to the QTLs in two other CI 13227 populations were validated. In addition, the previously reported QLr.hwwg-7AL was remapped to 2BL (renamed QLr.hwwg-2BL) after adding new markers in this study. Phenotypic data showed that the recombinant inbred lines harboring two or three of the QTLs had a significantly longer latent period. QLr.hwwg-2DS on 2DS showed a major effect on all rust resistance traits and was finely mapped to a 2.7-Mb interval by two newly developed flanking markers from exome capture. Three disease-resistance genes and two transporter genes were identified as the putative candidates for QLr.hwwg-2DS. The validated QTLs can be used as slow-rusting resistance resources, and the markers developed in this study will be useful for marker-assisted selection.

Species divergence and environmental adaptation of Picea asperata complex at the whole genome level

To study the interspecific differentiation characteristics of species originating from recent radiation, the genotyping-by-sequencing (GBS) technique was used to explore the kinship, population structure, gene flow, genetic variability, genotype-environment association and selective sweeps of Picea asperata complex with similar phenotypes from a genome-wide perspective. The following results were obtained: 14 populations of P. asperata complex could be divided into 5 clades; P. wilsonii and P. neoveitchii diverged earlier and were more distantly related to the remaining 6 spruce species. Various geological events have promoted the species differentiation of P. asperata complex. There were four instances of gene flow among P. koraiensis, P. meyeri, P. asperata, P. crassifolia and P. mongolica. The population of P. mongolica had the highest level of nucleotide diversity, and P. neoveitchii may have experienced a bottleneck recently. Genotype-environment association found that a total of 20,808 genes were related to the environmental variables, which enhanced the adaptability of spruce in different environments. Genes that were selectively swept in the P. asperata complex were primarily associated with plant stress resistance. Among them were some genes involved in plant growth and development, heat stress, circadian rhythms and flowering. In addition to the commonly selected genes, different spruce species also displayed unique genes subjected to selective sweeps that improved their adaptability to different habitats. Understanding the interspecific gene flow and adaptive evolution of Picea species is beneficial to further understanding the species relationships of spruce and can provide a basis for studying spruce introgression and functional genomics.

Genotyping-by-sequencing informs conservation of Andean palms sources of non-timber forest products

Conservation and sustainable management of lineages providing non-timber forest products are imperative under the current global biodiversity loss. Most non-timber forest species, however, lack genomic studies that characterize their intraspecific variation and evolutionary history, which inform species' conservation practices. Contrary to many lineages in the Andean biodiversity hotspot that exhibit high diversification, the genus Parajubaea (Arecaceae) has only three species despite the genus' origin 22 million years ago. Two of the three palm species, P. torallyi and P. sunkha, are non-timber forest species endemic to the Andes of Bolivia and are listed as IUCN endangered. The third species, P. cocoides, is a vulnerable species with unknown wild populations. We investigated the evolutionary relationships of Parajubaea species and the genetic diversity and structure of wild Bolivian populations. Sequencing of five low-copy nuclear genes (3753 bp) challenged the hypothesis that P. cocoides is a cultigen that originated from the wild Bolivian species. We further obtained up to 15,134 de novo single-nucleotide polymorphism markers by genotyping-by-sequencing of 194 wild Parajubaea individuals. Our total DNA sequencing effort rejected the taxonomic separation of the two Bolivian species. As expected for narrow endemic species, we observed low genetic diversity, but no inbreeding signal. We found three genetic clusters shaped by geographic distance, which we use to propose three management units. Different percentages of missing genotypic data did not impact the genetic structure of populations. We use the management units to recommend in situ conservation by creating new protected areas, and ex situ conservation through seed collection.

Genetic diversity analysis of big-bracted dogwood (Cornus florida and C. kousa) cultivars, interspecific hybrids, and wild-collected accessions using RADseq

Big-bracted dogwoods are popular ornamental trees known for their beautiful spring blooms with showy bracts and four-season appeal. The two most widely grown species are Cornus florida and Cornus kousa, native to Eastern North America and East Asia. Despite their horticultural prominence, there is little information available regarding genetic diversity, population structure, relatedness, and subspecies origins of dogwood cultivars. In this study, 313 cultivars, wild-collected plants, and Rutgers University breeding selections, focusing on C. florida, C. kousa, and interspecific hybrids, were genotyped using restriction-site associated DNA sequencing (RADseq) generating thousands of single nucleotide polymorphism (SNP) and insertion deletion (Indel) markers. The research results showed high genetic diversity among C. florida and C. kousa wild-collected plants and cultivars. For C. florida, pink-bracted plants formed a distinct clade from those with white-bracts with the Mexican C. florida ssp. urbiniana forming an outgroup. For C. kousa, Chinese-collected plants (ssp. chinensis) were a distinct subspecies with clear separation from Japanese and Korean accessions (ssp. kousa) and cultivars were designated as ssp. chinensis, ssp. kousa, or ssp. hybrid. Using this information, a Kompetitive allele specific PCR (KASP) assay genotyping panel was designed to determine C. kousa trees' subspecies makeup. Results revealed many cases of genetically identical cultivars being sold under different names, especially for pink-bracted cultivars of both species. Additionally, reported parent-progeny relationships were evaluated and either validated or discredited. Finally, the hybrid germplasm analysis validated pedigrees of interspecific F1 hybrids and found many of the recent Rutgers breeding selections contain small regions of pacific dogwood (C. nuttallii) DNA introgressed into C. kousa backgrounds. This diversity study elucidates origins, diversity, and relationships of a large population of big-bracted dogwoods. The results can inform plant breeders, arboreta, and the ornamental plant industry, as most modern cultivars and popular historic cultivars are represented.

Genetic analysis of agronomic and physiological traits associated with latex yield revealed complex genetic bases in Hevea brasiliensis

Hevea brasiliensis, a natural rubber producing species, is widely cultivated due to its high rubber yield potential. Natural rubber is synthesised in the rubber particles of laticifers. Latex diagnosis (LD) was established to characterise the physiological state of the laticiferous system by measuring its physiological parameters, i.e., sucrose, inorganic phosphorous (Pi), thiols and total solid content (TSC). Rubber clones are often classified in three groups i.e., quick starters, medium starters and slow starters. To better understand the genetic bases of latex yield, a biparental population was generated from a cross between the quick-starter clone PB 260 and the medium-starter clone SP 217. LD was performed during the peak latex production season and used to calculate sucrose loading. The agronomic and physiological parameters associated with latex yield led to the classification of genotypes according to the rubber clonal typology and to the identification of quantitative trait loci (QTL) using a high-density map. Inorganic phosphorous content was positively associated with yield during the first year of production thus enabling identification of quick-starter clones. In addition, the LD-based clonal typology led to determine the long-term yield potential and the use of appropriate ethephon stimulation. QTL analysis successfully identified several QTLs related to yield, sucrose, Pi and TSC. One QTL related to sucrose loading was identified in the same position as the QTL for sucrose on linkage group 1. To our knowledge, this is the first study to report QTL analysis for this trait. The use of a high-density map enables the identification of genes underlying QTLs. Several putative genes underlying QTLs related to yield, sucrose and TSC were identified.

Genotyping-by-sequencing targets genic regions and improves resolution of genome-wide association studies in autotetraploid potato

KEY MESSAGE

De novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over 'fixed' SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker-trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm. This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a 'fixed' SNP Infinium array platform and a 'flexible and open' genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker-trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL 'hotspots' for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.

Montane diversification as a mechanism of speciation in neotropical butterflies

The mountains in the Atlantic Forest domain are environments that harbor a high biodiversity, including species adapted to colder climates that were probably influenced by the climatic variations of the Pleistocene. To understand the phylogeographic pattern and assess the taxonomic boundaries between two sister montane species, a genomic study of the butterflies Actinote mantiqueira and A. alalia (Nymphalidae: Acraeini) was conducted. Analyses based on partial sequences of the mitochondrial gene COI (barcode region) failed to recover any phylogenetic or genetic structure discriminating the two species or sampling localities. However, single nucleotide polymorphisms gathered using Genotyping-by-Sequencing provided a strong isolation pattern in all analyses (genetic distance, phylogenetic hypothesis, clustering analyses, and F ST statistics) which is consistent with morphology, separating all individuals of A. alalia from all populations of A. mantiqueira. The three sampled mountain ranges where A. mantiqueira populations occur-Serra do Mar, Serra da Mantiqueira, and Poços de Caldas Plateau-were identified as three isolated clusters. Paleoclimate simulations indicate that both species' distributions changed according to climatic oscillations in the Pleistocene period, with the two species potentially occurring in areas of lower altitude during glacial periods when compared to the interglacial periods (as the present). Besides, a potential path between their distribution through the Serra do Mar Mountain range was inferred. Therefore, the Pleistocene climatic fluctuation had a significant impact on the speciation process between A. alalia and A. mantiqueira, which was brought on by isolation at different mountain summits during interglacial periods, as shown by the modeled historical distribution and the observed genetic structure.

Population genetics of Todarodes pacificus (Cephalopoda: Ommastrephidae) in the northwest Pacific Ocean via GBS sequencing

The common squid, Todarodes pacificus, is an important commercial species that inhabits the northwest Pacific Ocean, particularly the East Japan Sea, the Pacific coast of Japan, and the East China Sea. In this study, we chose 29 individuals from three areas: one type from the Sea of Japan and two types from the East China Sea. A total of 43,529 SNPs were obtained using genotyping-by-sequencing (GBS). Our analyses revealed low genetic diversity and genetic differentiation in each type. Heterozygote deficiency and inbreeding have caused this low level of genetic diversity. Population structure analysis indicated that the three types were genetically similar, which may be attributed to strong gene flow combined with the demographic history events during the last 2 million years. This new GBS application technique provides valuable information for the conservation of marine species genetics and could be useful for the effective management of this resource.

Loss of daylength sensitivity by splice site mutation in Cannabis pseudo-response regulator

Photoperiod insensitivity (auto-flowering) in drug-type Cannabis sativa circumvents the need for short day (SD) flowering requirements making outdoor cultivation in high latitudes possible. However, the benefits of photoperiod insensitivity are counterbalanced by low cannabinoid content and poor flower quality in auto-flowering genotypes. Despite recent studies in cannabis flowering, a mechanistic understanding of photoperiod insensitivity is still lacking. We used a combination of genome-wide association study and genetic fine-mapping to identify the genetic cause of auto-flowering in cannabis. We then used gene expression analyses and transient transformation assays to characterize flowering time control. Herein, we identify a splice site mutation within circadian clock gene PSEUDO-RESPONSE REGULATOR 37 (CsPRR37) in auto-flowering cannabis. We show that CsPRR37 represses FT expression and its circadian oscillations transition to a less repressive state during SD as compared to long days (LD). We identify several key circadian clock genes whose expression is altered in auto-flowering cannabis, particularly under non-inductive LD. Research into the pervasiveness of this mutation and others affecting flowering time will help elucidate cannabis domestication history and advance cannabis breeding toward a more sustainable outdoor cultivation system.

Identifying novel sources of resistance to wheat stem sawfly in five wild wheat species

BACKGROUND

The wheat stem sawfly (WSS, Cephus cinctus) is a major pest of wheat (Triticum aestivum) and can cause significant yield losses. WSS damage results from stem boring and/or cutting, leading to the lodging of wheat plants. Although solid-stem wheat genotypes can effectively reduce larval survival, they may have lower yields than hollow-stem genotypes and show inconsistent solidness expression. Because of limited resistance sources to WSS, evaluating diverse wheat germplasm for novel resistance genes is crucial. We evaluated 91 accessions across five wild wheat species (Triticum monococcum, T. urartu, T. turgidum, T. timopheevii, and Aegilops tauschii) and common wheat cultivars (T. aestivum) for antixenosis (host selection) and antibiosis (host suitability) to WSS. Host selection was measured as the number of eggs after adult oviposition, and host suitability was determined by examining the presence or absence of larval infestation within the stem. The plants were grown in the greenhouse and brought to the field for WSS infestation. In addition, a phylogenetic analysis was performed to determine the relationship between the WSS traits and phylogenetic clustering.

RESULTS

Overall, Ae. tauschii, T. turgidum and T. urartu had lower egg counts and larval infestation than T. monococcum, and T. timopheevii. T. monococcum, T. timopheevii, T. turgidum, and T. urartu had lower larval weights compared with T. aestivum.

CONCLUSION

This study shows that wild relatives of wheat could be a valuable source of alleles for enhancing resistance to WSS and identifies specific germplasm resources that may be useful for breeding. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Enhancing winter wheat prediction with genomics, phenomics and environmental data

In the realm of multi-environment prediction, when the goal is to predict a complete environment using the others as a training set, the efficiency of genomic selection (GS) falls short of expectations. Genotype by environment interaction poses a challenge in achieving high prediction accuracies. Consequently, current efforts are focused on enhancing efficiency by integrating various types of inputs, such as phenomics data, environmental information, and other omics data. In this study, we sought to evaluate the impact of incorporating environmental information into the modeling process, in addition to genomic and phenomics information. Our evaluation encompassed five data sets of soft white winter wheat, and the results revealed a significant improvement in prediction accuracy, as measured by the normalized root mean square error (NRMSE), through the integration of environmental information. Notably, there was an average gain in prediction accuracy of 49.19% in terms of NRMSE across the data sets. Moreover, the observed prediction accuracy ranged from 5.68% (data set 3) to 60.36% (data set 4), underscoring the substantial effect of integrating environmental information. By including genomic, phenomic, and environmental data in prediction models, plant breeding programs can improve selection efficiency across locations.

Adaptive divergence, historical population dynamics, and simulation of suitable distributions for Picea Meyeri and P. Mongolica at the whole-genome level

The taxonomic classification of Picea meyeri and P. mongolica has long been controversial. To investigate the genetic relatedness, evolutionary history, and population history dynamics of these species, genotyping-by-sequencing (GBS) technology was utilized to acquire whole-genome single nucleotide polymorphism (SNP) markers, which were subsequently used to assess population structure, population dynamics, and adaptive differentiation. Phylogenetic and population structural analyses at the genomic level indicated that although the ancestor of P. mongolica was a hybrid of P. meyeri and P. koraiensis, P. mongolica is an independent Picea species. Additionally, P. mongolica is more closely related to P. meyeri than to P. koraiensis, which is consistent with its geographic distribution. There were up to eight instances of interspecific and intraspecific gene flow between P. meyeri and P. mongolica. The P. meyeri and P. mongolica effective population sizes generally decreased, and Maxent modeling revealed that from the Last Glacial Maximum (LGM) to the present, their habitat areas decreased initially and then increased. However, under future climate scenarios, the habitat areas of both species were projected to decrease, especially under high-emission scenarios, which would place P. mongolica at risk of extinction and in urgent need of protection. Local adaptation has promoted differentiation between P. meyeri and P. mongolica. Genotype‒environment association analysis revealed 96,543 SNPs associated with environmental factors, mainly related to plant adaptations to moisture and temperature. Selective sweeps revealed that the selected genes among P. meyeri, P. mongolica and P. koraiensis are primarily associated in vascular plants with flowering, fruit development, and stress resistance. This research enhances our understanding of Picea species classification and provides a basis for future genetic improvement and species conservation efforts.

Genotyping-by-sequencing and weighted gene co-expression network analysis of genes responsive against Potato virus Y in commercial potato cultivars

Potato is considered a key component of the global food system and plays a vital role in strengthening world food security. A major constraint to potato production worldwide is the Potato Virus Y (PVY), belonging to the genus Potyvirus in the family of Potyviridae. Selective breeding of potato with resistance to PVY pathogens remains the best method to limit the impact of viral infections. Understanding the genetic diversity and population structure of potato germplasm is important for breeders to improve new cultivars for the sustainable use of genetic materials in potato breeding to PVY pathogens. While, genetic diversity improvement in modern potato breeding is facing increasingly narrow genetic basis and the decline of the genetic diversity. In this research, we performed genotyping-by-sequencing (GBS)-based diversity analysis on 10 commercial potato cultivars and weighted gene co-expression network analysis (WGCNA) to identify candidate genes related to PVY-resistance. WGCNA is a system biology technique that uses the WGCNA R software package to describe the correlation patterns between genes in multiple samples. In terms of consumption, these cultivars are a high rate among Iranian people. Using population structure analysis, the 10 cultivars were clustered into three groups based on the 118343 single nucleotide polymorphisms (SNPs) generated by GBS. Read depth ranged between 5 and 18. The average data size and Q30 of the reads were 145.98 Mb and 93.63%, respectively. Based on the WGCNA and gene expression analysis, the StDUF538, StGTF3C5, and StTMEM161A genes were associated with PVY resistance in the potato genome. Further, these three hub genes were significantly involved in defense mechanism where the StTMEM161A was involved in the regulation of alkalization apoplast, the StDUF538 was activated in the chloroplast degradation program, and the StGTF3C5 regulated the proteins increase related to defense in the PVY infected cells. In addition, in the genetic improvement programs, these hub genes can be used as genetic markers for screening commercial cultivars for PVY resistance. Our survey demonstrated that the combination of GBS-based genetic diversity germplasm analysis and WGCNA can assist breeders to select cultivars resistant to PVY as well as help design proper crossing schemes in potato breeding.

Dissection of Common Rust Resistance in Tropical Maize Multiparent Population through GWAS and Linkage Studies

Common rust (CR), caused by Puccina sorghi, is a major foliar disease in maize that leads to quality deterioration and yield losses. To dissect the genetic architecture of CR resistance in maize, this study utilized the susceptible temperate inbred line Ye107 as the male parent crossed with three resistant tropical maize inbred lines (CML312, D39, and Y32) to generate 627 F7 recombinant inbred lines (RILs), with the aim of identifying maize disease-resistant loci and candidate genes for common rust. Phenotypic data showed good segregation between resistance and susceptibility, with varying degrees of resistance observed across different subpopulations. Significant genotype effects and genotype × environment interactions were observed, with heritability ranging from 85.7% to 92.2%. Linkage and genome-wide association analyses across the three environments identified 20 QTLs and 62 significant SNPs. Among these, seven major QTLs explained 66% of the phenotypic variance. Comparison with six SNPs repeatedly identified across different environments revealed overlap between qRUST3-3 and Snp-203,116,453, and Snp-204,202,469. Haplotype analysis indicated two different haplotypes for CR resistance for both the SNPs. Based on LD decay plots, three co-located candidate genes, Zm00001d043536, Zm00001d043566, and Zm00001d043569, were identified within 20 kb upstream and downstream of these two SNPs. Zm00001d043536 regulates hormone regulation, Zm00001d043566 controls stomatal opening and closure, related to trichome, and Zm00001d043569 is associated with plant disease immune responses. Additionally, we performed candidate gene screening for five additional SNPs that were repeatedly detected across different environments, resulting in the identification of five candidate genes. These findings contribute to the development of genetic resources for common rust resistance in maize breeding programs.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Are cereal grasses a single genetic system?

In 1993, a passionate and provocative call to arms urged cereal researchers to consider the taxon they study as a single genetic system and collaborate with each other. Since then, that group of scientists has seen their discipline blossom. In an attempt to understand what unity of genetic systems means and how the notion was borne out by later research, we survey the progress and prospects of cereal genomics: sequence assemblies, population-scale sequencing, resistance gene cloning and domestication genetics. Gene order may not be as extraordinarily well conserved in the grasses as once thought. Still, several recurring themes have emerged. The same ancestral molecular pathways defining plant architecture have been co-opted in the evolution of different cereal crops. Such genetic convergence as much as cross-fertilization of ideas between cereal geneticists has led to a rich harvest of genes that, it is hoped, will lead to improved varieties.

Genome-Wide Association Study of Fungicide Sensitivity in a Fusarium graminearum Population Collected from North Dakota

Fusarium head blight is a destructive disease of small grains. The disease is predominantly caused by the haploid ascomycete fungus Fusarium graminearum in North America. To understand the genetics of quantitative traits for sensitivity to fungicides in this fungal pathogen, we conducted a genome-wide association study of sensitivity to two demethylation inhibition class fungicides, tebuconazole and prothioconazole, using an F. graminearum population of 183 isolates collected between 1981 and 2013 from North Dakota. Baseline sensitivity to tebuconazole and prothioconazole was established using 21 isolates collected between 1981 and 1994. Most fungal isolates were sensitive to both tebuconazole and prothioconazole; however, five isolates showed significantly reduced sensitivity to prothioconazole. The genome-wide association study identified one significant marker-trait association on chromosome 3 for tebuconazole resistance, whereas six significant marker-trait associations, one on chromosome 1, three on chromosome 2, and two on chromosome 4, were detected for prothioconazole resistance. Functional annotation of the marker-trait association for tebuconazole revealed a candidate gene encoding a basic helix-loop-helix domain-containing protein that reinforces sterol in the fungal membrane. Putative genes for prothioconazole resistance were also identified, which are involved in RNA interference, the detoxification by ubiquitin-proteasome pathway, and membrane integrity reinforcement. Considering the potential of the pathogen toward overcoming chemical control, continued monitoring of fungal sensitivities to commercially applied fungicides, especially those containing prothioconazole, is warranted to reduce risks of fungicide resistance in the pathogen populations.

Effects of landscape, resource use, and body size on genetic structure in bee populations

Quantifying genetic structure and levels of genetic variation are fundamentally important to predicting the ability of populations to persist in human-altered landscapes and adapt to future environmental changes. Genetic structure reflects the dispersal of individuals over generations, which can be mediated by species-level traits or environmental factors. Dispersal distances are commonly positively associated with body size and negatively associated with the amount of degraded habitat between sites, motivating the investigation of these potential drivers of dispersal concomitantly. We quantified genetic structure and genetic variability within populations of seven bee species from the genus Euglossa across fragmented landscapes. We genotyped bees at SNP loci and tested the following predictions: (1) deforested areas restrict gene flow; (2) larger species have lower genetic structure; (3) species with greater resource specialization have higher genetic structure; and (4) sites surrounded by more intact habitat have higher genetic diversity. Contrasting with previous work on bees, we found no associations between body size and genetic structure. Genetic structure was higher for species with greater resource specialization, and the amount of intact habitat between or surrounding sites was positively associated with parameters reflecting gene flow and genetic diversity. These results challenge the dominant paradigm that individuals of larger species disperse farther, and they suggest that landscape and resource requirements are important factors mediating dispersal.

Genomic insights on conservation priorities for North Sea houting and European lake whitefish (Coregonus spp.)

Population genomics analysis holds great potential for informing conservation of endangered populations. We focused on a controversial case of European whitefish (Coregonus spp.) populations. The endangered North Sea houting is the only coregonid fish that tolerates oceanic salinities and was previously considered a species (C. oxyrhinchus) distinct from European lake whitefish (C. lavaretus). However, no firm evidence for genetic-based salinity adaptation has been available. Also, studies based on microsatellite and mitogenome data suggested surprisingly recent divergence (c. 2500 years bp) between houting and lake whitefish. These data types furthermore have provided no evidence for possible inbreeding. Finally, a controversial taxonomic revision recently classified all whitefish in the region as C. maraena, calling conservation priorities of houting into question. We used whole-genome and ddRAD sequencing to analyse six lake whitefish populations and the only extant indigenous houting population. Demographic inference indicated post-glacial expansion and divergence between lake whitefish and houting occurring not long after the Last Glaciation, implying deeper population histories than previous analyses. Runs of homozygosity analysis suggested not only high inbreeding (FROH up to 30.6%) in some freshwater populations but also FROH up to 10.6% in the houting prompting conservation concerns. Finally, outlier scans provided evidence for adaptation to high salinities in the houting. Applying a framework for defining conservation units based on current and historical reproductive isolation and adaptive divergence led us to recommend that the houting be treated as a separate conservation unit regardless of species status. In total, the results underscore the potential of genomics to inform conservation practices, in this case clarifying conservation units and highlighting populations of concern.

Characterisation and mapping of a Globodera pallida resistance derived from the wild potato species Solanum spegazzinii

KEY MESSAGE

A new resistance locus acting against the potato cyst nematode Globodera pallida was mapped to chromosome VI in the diploid wild potato species Solanum spegazzinii CPC 7195. The potato cyst nematodes (PCN) Globodera pallida and Globodera rostochiensis are economically important potato pests in almost all regions where potato is grown. One important management strategy involves deployment through introgression breeding into modern cultivars of new sources of naturally occurring resistance from wild potato species. We describe a new source of resistance to G. pallida from wild potato germplasm. The diploid species Solanum spegazzinii Bitter accession CPC 7195 shows resistance to G. pallida pathotypes Pa1 and Pa2/3. A cross and first backcross of S. spegazzinii with Solanum tuberosum Group Phureja cultivar Mayan Gold were performed, and the level of resistance to G. pallida Pa2/3 was determined in progeny clones. Bulk-segregant analysis (BSA) using generic mapping enrichment sequencing (GenSeq) and genotyping-by-sequencing were performed to identify single-nucleotide polymorphisms (SNPs) that are genetically linked to the resistance, using S. tuberosum Group Phureja clone DM1-3 516 R44 as a reference genome. These SNPs were converted into allele-specific PCR assays, and the resistance was mapped to an interval of roughly 118 kb on chromosome VI. This newly identified resistance, which we call Gpa VIlspg, can be used in future efforts to produce modern cultivars with enhanced and broad-spectrum resistances to the major pests and pathogens of potato.

Genetic linkage mapping and quantitative trait locus (QTL) analysis of sweet basil (Ocimum basilicum L.) to identify genomic regions associated with cold tolerance and major volatiles

Chilling sensitivity is one of the greatest challenges affecting the marketability and profitability of sweet basil (Ocimum basilicum L.) in the US and worldwide. Currently, there are no sweet basils commercially available with significant chilling tolerance and traditional aroma profiles. This study was conducted to identify quantitative trait loci (QTLs) responsible for chilling tolerance and aroma compounds in a biparental mapping population, including the Rutgers advanced breeding line that served as a chilling tolerant parent, 'CB15', the chilling sensitive parent, 'Rutgers Obsession DMR' and 200 F2 individuals. Chilling tolerance was assessed by percent necrosis using machine learning and aroma profiling was evaluated using gas chromatography (GC) mass spectrometry (MS). Single nucleotide polymorphism (SNP) markers were generated from genomic sequences derived from double digestion restriction-site associated DNA sequencing (ddRADseq) and converted to genotype data using a reference genome alignment. A genetic linkage map was constructed and five statistically significant QTLs were identified in response to chilling temperatures with possible interactions between QTLs. The QTL on LG24 (qCH24) demonstrated the largest effect for chilling response and was significant in all three replicates. No QTLs were identified for linalool, as the population did not segregate sufficiently to detect this trait. Two significant QTLs were identified for estragole (also known as methyl chavicol) with only qEST1 on LG1 being significant in the multiple-QTL model (MQM). QEUC26 was identified as a significant QTL for eucalyptol (also known as 1,8-cineole) on LG26. These QTLs may represent key mechanisms for chilling tolerance and aroma in basil, providing critical knowledge for future investigation of these phenotypic traits and molecular breeding.

Low Diversity and High Genetic Structure for Platonia insignis Mart., an Endangered Fruit Tree Species

Platonia insignis is a fruit tree native to Brazil of increasing economic importance, with its pulp trading among the highest market values. This study aimed to evaluate the structure and genomic diversity of P. insignis (bacurizeiro) accessions from six locations in the Brazilian States of Roraima, Amazonas, Pará (Amazon biome), and Maranhão (Cerrado biome). A total of 2031 SNP markers were obtained using genotyping-by-sequencing (GBS), from which 625 outlier SNPs were identified. High genetic structure was observed, with most of the genetic variability (59%) concentrated among locations, mainly between biomes (Amazon and Cerrado). A positive and significant correlation (r = 0.85; p < 0.005) was detected between genetic and geographic distances, indicating isolation by distance. The highest genetic diversity was observed for the location in the Cerrado biome (HE = 0.1746; HO = 0.2078). The locations in the Amazon biome showed low genetic diversity indexes with significant levels of inbreeding. The advance of urban areas, events of burning, and expansion of agricultural activities are most probably the main factors for the genetic diversity reduction of P. insignis. Approaches to functional analysis showed that most of the outlier loci found may be related to genes involved in cellular and metabolic processes.

Studies on Candidate Genes Related to Flowering Time in a Multiparent Population of Maize Derived from Tropical and Temperate Germplasm

A comprehensive study on maize flowering traits, focusing on the regulation of flowering time and the elucidation of molecular mechanisms underlying the genes controlling flowering, holds the potential to significantly enhance our understanding of the associated regulatory gene network. In this study, three tropical maize inbreds, CML384, CML171, and CML444, were used, along with a temperate maize variety, Shen137, as parental lines to cross with Ye107. The resulting F1s underwent seven consecutive generations of self-pollination through the single-seed descent (SSD) method to develop a multiparent population. To investigate the regulation of maize flowering time-related traits and to identify loci and candidate genes, a genome-wide association study (GWAS) was conducted. GWAS analysis identified 556 SNPs and 12 candidate genes that were significantly associated with flowering time-related traits. Additionally, an analysis of the effect of the estimated breeding values of the subpopulations on flowering time was conducted to further validate the findings of the present study. Collectively, this study offers valuable insights into novel candidate genes, contributing to an improved understanding of maize flowering time-related traits. This information holds practical significance for future maize breeding programs aimed at developing high-yielding hybrids.

Is there hybridization between 2 species of the same genus in sympatry?-The genetic relationships between Anoplophora glabripennis, Anoplophora chinensis, and putative hybrids

Anoplophora glabripennis (Asian longhorn beetle, ALB) and Anoplophora chinensis (Citrus longhorn beetle, CLB) are native forest pests in China; they have become important international quarantine pests. They are found using the same Salix aureo-pendula host tree of Cixi, Zhejiang province, China. On this host tree, we collected additional beetles that appeared to be morphologically intermediate between ALB and CLB. By using a stereoscope, we observed that there were several bumps on the base of the elytra, which was inconsistent with ALB, which typically has a smooth elytral base, but was more like CLB, which has numerous short tubercles on the elytral base. Given their sympatry and intermediate morphology, we hypothesized that these may represent ALB × CLB hybrids. We studied the genomic profiles for 46 samples (ALB, CLB, and putative hybrids) using genotyping-by-sequencing (GBS) providing a reduced representation of the entire genome. Employing principal component analyses on the 163 GBS-derived single nucleotide polymorphism data, we found putative hybrids tightly clustered with ALB, but genetically distinct from the CLB individuals. Therefore, our initial hybrid hypothesis was not supported by genomic data. Further, while mating experiments between adult ALB and CLB were successful in 4 separate years (2017, 2018, 2020, and 2021), and oviposition behavior was observed, no progeny was produced. Having employed population genomic analysis and biological hybridization experiments, we conclude that the putative hybrids represent newly discovered morphological variants within ALB. Our approach further confirmed the advantage of genome-wide information for Anoplophora species assignment in certain ambiguous classification cases.

Phylogeography, origin and population structure of the self-fertile emerging plant pathogen Phytophthora pseudosyringae

Phytophthora pseudosyringae is a self-fertile pathogen of woody plants, particularly associated with tree species from the genera Fagus, Notholithocarpus, Nothofagus and Quercus, which is found across Europe and in parts of North America and Chile. It can behave as a soil pathogen infecting roots and the stem collar region, as well as an aerial pathogen infecting leaves, twigs and stem barks, causing particular damage in the United Kingdom and western North America. The population structure, migration and potential outcrossing of a worldwide collection of isolates were investigated using genotyping-by-sequencing. Coalescent-based migration analysis revealed that the North American population originated from Europe. Historical gene flow has occurred between the continents in both directions to some extent, yet contemporary migration is overwhelmingly from Europe to North America. Two broad population clusters dominate the global population of the pathogen, with a subgroup derived from one of the main clusters found only in western North America. Index of association and network analyses indicate an influential level of outcrossing has occurred in this preferentially inbreeding, homothallic oomycete. Outcrossing between the two main population clusters has created distinct subgroups of admixed individuals that are, however, less common than the main population clusters. Differences in life history traits between the two main population clusters should be further investigated together with virulence and host range tests to evaluate the risk each population poses to natural environments worldwide.

Population genetics and genomics of Triatoma brasiliensis (Hemiptera, Reduviidae) in an area of high pressure of domiciliary infestation in Northeastern Brazil

Understanding the population dynamics of vectors is crucial for effective control of vector-borne diseases. In the Northeastern Brazilian semi-arid region, Triatoma brasiliensis persists as the most significant Chagas disease vector, frequently displaying recurrent domiciliary infestations. This situation raises relevant public health concerns in the municipality of Currais Novos in the state of Rio Grande do Norte. This area has experienced a high prevalence of peridomiciliary re-infestations by T. brasiliensis, coupled with elevated rates of Trypanosoma cruzi infection. Therefore, we assessed the distribution of genetic variation via mitochondrial Cytochrome b gene (MT-CYB) sequencing (n = 109) and single nucleotide polymorphisms (SNPs, n = 86) to assess the gene flow among distinct populations distributed in varied geographic spots and environments, mainly sylvatic and peridomiciliary. Insects were collected from rural communities at Currais Novos, enclosed within a 16 km radius. Sampling included 13 populations: one intradomiciliary, eight peridomiciliary, and four sylvatic. Furthermore, an external population located 220 km from Currais Novos was also included in the study. The method employed to obtain SNP information relied on ddRAD-seq genotyping-by-sequencing (GBS), enabling a genome-wide analysis to infer genetic variation. Through AMOVA analysis of MT-CYB gene variation, we identified four distinct population groups with statistical significance (FCT= 0.42; p<0.05). We identified a total of 3,013 SNPs through GBS, with 11 loci showing putative signs of being under selection. The variation based on 3,002 neutral loci evidenced low genetic structuration based on low FST values (p>0.05), indicating local panmixia. However, resampling algorithms pointed out that three samples from the external population were assigned (>98 %) in a cluster contrasting from the ones putatively under local panmixia - validating the newly applied genome-wide marker for studies on the population genetics at finer-scale resolution for T. brasiliensis. The presence of population structuring in some of the sampled points, as suggested by the mitochondrial marker, leads us to assume that infestations were probably initiated by small populations of females - demographic event poses a risk for rapid re-infestations. The local panmictic pattern revealed by the GBS marker poses a challenge for vector control measures, as re-infestation foci may be distributed over a wide geographical and ecological range. In such instances, vectors exhibit reduced susceptibility to conventional insecticide spraying operations since sylvatic populations are beyond the reach of these interventions. The pattern of infestation exhibited by T. brasiliensis necessitates integrating innovative strategies into the existing control framework, holding the potential to create a more resilient and adaptive vector control program. In our dataset, the results demonstrated that the genetic signals from both markers were complementary. Therefore, it is essential to consider the nature and inheritance pattern of each marker when inferring the pattern of re-infestations.

Genomic Prediction from Multi-Environment Trials of Wheat Breeding

Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However, the economic value of wheat lines is not only influenced by their additive component but also encompasses a non-additive part (e.g., additive × additive epistasis interaction). In this study, genomic prediction models were implemented in three target populations of environments (TPE) in South Asia. Four models that incorporate genotype × environment interaction (G × E) and genotype × genotype (GG) were tested: Factor Analytic (FA), FA with genomic relationship matrix (FA + G), FA with epistatic relationship matrix (FA + GG), and FA with both genomic and epistatic relationship matrices (FA + G + GG). Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests, leading us to infer that the FA + G model effectively captures certain epistatic effects. The wheat lines tested in sites in different TPE were predicted with different precisions depending on the cross-validation employed. In general, the best prediction accuracy was obtained when some lines were observed in some sites of particular TPEs and the worse genomic prediction was observed when wheat lines were never observed in any site of one TPE.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden)

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

The genetics of Ug99 stem rust resistance in spring wheat variety 'Linkert'

Wheat stem rust caused by Puccinia graminis f. sp. tritici (Pgt) threatens wheat production worldwide. The objective of this study was to characterize wheat stem rust resistance in 'Linkert', a variety with adult plant resistance effective to emerging wheat stem rust pathogen strain Ug99. Two doubled haploid (DH) populations and one recombinant inbred line (RIL) population were developed with 'Linkert' as a stem rust resistant parent. Hard red spring wheat variety 'Forefront' and genetic stock 'LMPG' were used as stem rust susceptible parents of the DH populations. Breeding line 'MN07098-6' was used as a susceptible parent of the RIL population. Both DH and RIL populations with their parents were evaluated both at the seedling stage and in the field against Pgt races. Genotyping data of the DH populations were generated using the wheat iSelect 90k SNP assay. The RIL population was genotyped by genotyping-by-sequencing. We found QTL consistently associated with wheat stem rust resistance on chromosome 2BS for the Linkert/Forefront DH population and the Linkert/MN07098-6 RIL population both in Ethiopia and Kenya. Additional reliable QTL were detected on chromosomes 5BL (125.91 cM) and 4AL (Sr7a) for the Linkert/LMPG population in Ethiopia and Kenya. Different QTL identified in the populations reflect the importance of examining the genetics of resistance in populations derived from adapted germplasm (Forefront and MN07098-6) in addition to a genetic stock (LMPG). The associated markers in this study could be used to track and select for the identified QTL in wheat breeding programs.

Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data

KEY MESSAGE

An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Utilizing Two Populations Derived from Tropical Maize for Genome-Wide Association Analysis of Banded Leaf and Sheath Blight Resistance

Banded leaf and sheath blight (BLSB) in maize is a soil-borne fungal disease caused by Rhizoctonia solani Kühn, resulting in significant yield losses. Investigating the genes responsible for regulating resistance to BLSB is crucial for yield enhancement. In this study, a multiparent maize population was developed, comprising two recombinant inbred line (RIL) populations totaling 442 F8RILs. The populations were generated by crossing two tropical inbred lines, CML444 and NK40-1, known for their BLSB resistance, as female parents, with the high-yielding but BLSB-susceptible inbred line Ye107 serving as the common male parent. Subsequently, we utilized 562,212 high-quality single nucleotide polymorphisms (SNPs) generated through genotyping-by-sequencing (GBS) for a comprehensive genome-wide association study (GWAS) aimed at identifying genes responsible for BLSB resistance. The objectives of this study were to (1) identify SNPs associated with BLSB resistance through genome-wide association analyses, (2) explore candidate genes regulating BLSB resistance in maize, and (3) investigate pathways involved in BLSB resistance and discover key candidate genes through Gene Ontology (GO) analysis. The GWAS analysis revealed nineteen SNPs significantly associated with BLSB that were consistently identified across four environments in the GWAS, with phenotypic variation explained (PVE) ranging from 2.48% to 11.71%. Screening a 40 kb region upstream and downstream of the significant SNPs revealed several potential candidate genes. By integrating information from maize GDB and the NCBI, we identified five novel candidate genes, namely, Zm00001d009723, Zm00001d009975, Zm00001d009566, Zm00001d009567, located on chromosome 8, and Zm00001d026376, on chromosome 10, related to BLSB resistance. These candidate genes exhibit association with various aspects, including maize cell membrane proteins and cell immune proteins, as well as connections to cell metabolism, transport, transcriptional regulation, and structural proteins. These proteins and biochemical processes play crucial roles in maize defense against BLSB. When Rhizoctonia solani invades maize plants, it induces the expression of genes encoding specific proteins and regulates corresponding metabolic pathways to thwart the invasion of this fungus. The present study significantly contributes to our understanding of the genetic basis of BLSB resistance in maize, offering valuable insights into novel candidate genes that could be instrumental in future breeding efforts to develop maize varieties with enhanced BLSB resistance.

MCPtaggR: R package for accurate genotype calling in reduced representation sequencing data by eliminating error-prone markers based on genome comparison

Reduced representation sequencing (RRS) offers cost-effective, high-throughput genotyping platforms such as genotyping-by-sequencing (GBS). RRS reads are typically mapped onto a reference genome. However, mapping reads harbouring mismatches against the reference can potentially result in mismapping and biased mapping, leading to the detection of error-prone markers that provide incorrect genotype information. We established a genotype-calling pipeline named mappable collinear polymorphic tag genotyping (MCPtagg) to achieve accurate genotyping by eliminating error-prone markers. MCPtagg was designed for the RRS-based genotyping of a population derived from a biparental cross. The MCPtagg pipeline filters out error-prone markers prior to genotype calling based on marker collinearity information obtained by comparing the genome sequences of the parents of a population to be genotyped. A performance evaluation on real GBS data from a rice F2 population confirmed its effectiveness. Furthermore, our performance test using a genome assembly that was obtained by genome sequence polishing on an available genome assembly suggests that our pipeline performs well with converted genomes, rather than necessitating de novo assembly. This demonstrates its flexibility and scalability. The R package, MCPtaggR, was developed to provide functions for the pipeline and is available at https://github.com/tomoyukif/MCPtaggR.

Genome-wide genetic architecture for plant maturity and drought tolerance in diploid potatoes

Cultivated potato (Solanum tuberosum) is known to be highly susceptible to drought. With climate change and its frequent episodes of drought, potato growers will face increased challenges to achieving their yield goals. Currently, a high proportion of untapped potato germplasm remains within the diploid potato relatives, and the genetic architecture of the drought tolerance and maturity traits of diploid potatoes is still unknown. As such, a panel of 384 ethyl methanesulfonate-mutagenized diploid potato clones were evaluated for drought tolerance and plant maturity under field conditions. Genome-wide association studies (GWAS) were conducted to dissect the genetic architecture of the traits. The results obtained from the genetic structure analysis of the panel showed five main groups and seven subgroups. Using the Genome Association and Prediction Integrated Tool-mixed linear model GWAS statistical model, 34 and 17 significant quantitative trait nucleotides (QTNs) were found associated with maturity and drought traits, respectively. Chromosome 5 carried most of the QTNs, some of which were also detected by using the restricted two-stage multi-locus multi-allele-GWAS haploblock-based model, and two QTNs were found to be pleiotropic for both maturity and drought traits. Using the non-parametric U-test, one and three QTNs, with 5.13%-7.4% phenotypic variations explained, showed favorable allelic effects that increase the maturity and drought trait values. The quantitaive trait loci (QTLs)/QTNs associated with maturity and drought trait were found co-located in narrow (0.5-1 kb) genomic regions with 56 candidate genes playing roles in plant development and senescence and in abiotic stress responses. A total of 127 potato clones were found to be late maturing and tolerant to drought, while nine were early to moderate-late maturing and tolerant to drought. Taken together, the data show that the studied germplasm panel and the identified candidate genes are prime genetic resources for breeders and biologists in conventional breeding and targeted gene editing as climate adaptation tools.

Genome-Wide Association Study of Preharvest Sprouting in Wheat

Genome-wide association study (GWAS) is widely used to characterize genes or quantitative trait loci (QTLs) associated with preharvest sprouting and seed dormancy. GWAS can identify both previously discovered and novel QTLs across diverse genetic panels. The high-throughput SNP arrays or next-generation sequencing technologies have facilitated the identification of numerous genetic markers, thereby significantly enhancing the resolution of GWAS. Although various methods have been developed, the fundamental principles underlying these techniques remain constant. Here, we provide a basic technological flow to perform seed dormancy assay, followed by GWAS using population structure control, and compared it with previous identified QTLs and genes.

Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits in Urochloa ruziziensis

Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as the main food source for animals in tropical and subtropical regions. The majority of these species are apomictic and tetraploid, highlighting the significance of U. ruziziensis, a sexual diploid species that can be tetraploidized for use in interspecific crosses with apomictic species. As a means to support breeding programs, our study investigates the feasibility of genome-wide family prediction in U. ruziziensis families to predict agronomic traits. Fifty half-sibling families were assessed for green matter yield, dry matter yield, regrowth capacity, leaf dry matter, and stem dry matter across different clippings established in contrasting seasons with varying available water capacity. Genotyping was performed using a genotyping-by-sequencing approach based on DNA samples from family pools. In addition to conventional genomic prediction methods, machine learning and feature selection algorithms were employed to reduce the necessary number of markers for prediction and enhance predictive accuracy across phenotypes. To explore the regulation of agronomic traits, our study evaluated the significance of selected markers for prediction using a tree-based approach, potentially linking these regions to quantitative trait loci (QTLs). In a multiomic approach, genes from the species transcriptome were mapped and correlated to those markers. A gene coexpression network was modeled with gene expression estimates from a diverse set of U. ruziziensis genotypes, enabling a comprehensive investigation of molecular mechanisms associated with these regions. The heritabilities of the evaluated traits ranged from 0.44 to 0.92. A total of 28,106 filtered SNPs were used to predict phenotypic measurements, achieving a mean predictive ability of 0.762. By employing feature selection techniques, we could reduce the dimensionality of SNP datasets, revealing potential genotype-phenotype associations. The functional annotation of genes near these markers revealed associations with auxin transport and biosynthesis of lignin, flavonol, and folic acid. Further exploration with the gene coexpression network uncovered associations with DNA metabolism, stress response, and circadian rhythm. These genes and regions represent important targets for expanding our understanding of the metabolic regulation of agronomic traits and offer valuable insights applicable to species breeding. Our work represents an innovative contribution to molecular breeding techniques for tropical forages, presenting a viable marker-assisted breeding approach and identifying target regions for future molecular studies on these agronomic traits.