A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species

Multiple Origins or Widespread Gene Flow in Agricultural Fields? Regional Population Genomics of Herbicide Resistance in Bromus tectorum

The repeated evolution of herbicide resistance in agriculture provides an unprecedented opportunity to understand how organisms rapidly respond to strong anthropogenic-driven selection pressure. We recently identified agricultural populations of the grass species Bromus tectorum L. with resistance to multiple herbicides. To understand the evolutionary origins and spread of resistance, we investigated the resistance mechanisms to acetolactate synthase (ALS) inhibitors and photosystem II inhibitors, two widely used herbicide modes of action, in 49 B. tectorum populations. We assessed the genetic diversity, structure and relatedness in a subset of 21 populations. Resistance to ALS inhibitors was associated with multiple nonsynonymous mutations in ALS, the target site gene, despite the relatively small geographic region where populations originated, suggesting ALS inhibitor resistance evolution occurred multiple times in the region. We also found evidence that mechanisms not related to the target site evolved and were common in the populations studied. Resistance to photosystem II inhibitors was confirmed in two populations and was conferred by nonsynonymous mutations in the plastid gene psbA. Population genomics analyses suggested that ALS resistance in most populations, at the nucleotide level, spread via gene flow, except for one population where we found evidence that Pro-197-His mutations may have evolved in three separate events. Our results suggest that both gene flow via pollen and/or seed dispersal and multiple local evolutionary events were involved in the spread of herbicide-resistant B. tectorum. Our results provide an empirical example of the rapid repeated evolution of a trait under strong anthropogenic selection and elucidate the evolutionary origins of herbicide resistance in a plant species of agricultural importance.

Environmental data provide marginal benefit for predicting climate adaptation

Climate change poses a major challenge for both natural and cultivated species. Genomic tools are increasingly used in both conservation and breeding to identify adaptive loci that can be used to guide management in future climates. Here, we study the utility of climate and genomic data for identifying promising alleles using common gardens of a large, geographically diverse sample of traditional maize varieties to evaluate multiple approaches. First, we used genotype data to predict environmental characteristics of germplasm collections to identify varieties that may be pre-adapted to target environments. Second, we used environmental GWAS (envGWAS) to identify loci associated with historical divergence along climatic gradients. Finally, we compared the value of environmental data and envGWAS-prioritized loci to genomic data for prioritizing traditional varieties. We find that maize yield traits are best predicted by genome-wide relatedness and population structure, and that incorporating envGWAS-identified variants or environment-of-origin data provide little additional predictive information. While our results suggest that environmental data provide limited benefit in predicting fitness-related phenotypes, environmental GWAS is nonetheless a potentially powerful approach to identify individual novel loci associated with adaptation, especially when coupled with high density genotyping.

Genotyping-by-sequencing elucidates the species limits of Ukrainian taxa within Veronica subg. Pseudolysimachium

The subgenus Veronica subg. Pseudolysimachium contains mostly species occurring in natural and seminatural grasslands throughout Eurasia and is characterized by one of the highest diversification rates within Veronica, making it difficult to outline species boundaries, especially in taxa from its diversity hotspots. To resolve species limits among its Ukrainian members, the European diversity hotspot of the group, we combine evidence from GBS, niche modeling, palynology and morphometrics and compare the climatic niches of three closely related species. We confirm that Veronica maeotica and V.steppacea are distinct species. Both taxa, even though previously largely ignored, represent independent lineages in the phylogeny and are characterized each by a unique combination of morphological traits. Veronica steppacea is adapted to a drier, more continental climate than its closest relative, V.barrelieri, highlighting the importance of the zonality of the Eurasian steppe belt in shaping the diversity of the subgenus. Veronicaincana is split into two geographically distinct clades, providing evidence that plants with a cobwebby indumentum arose twice within the subgenus. Two other Ukrainian taxa, V.gryniana and V.incana subsp.hololeuca, may be of hybrid origin.

A divergent haplotype with a large deletion at the berry color locus causes a white-skinned phenotype in grapevine

The current genetic model explaining berry skin color in Vitis vinifera is incomplete and fails to predict berry skin color phenotypes for one allele of VvMybA1, referred to as VvMybA1_SUB. Our study focuses on this specific allele, revealing that the haplotype containing VvMybA1_SUB (haplotype F) represents an ancient lineage of the berry color locus. Within haplotype F, we identified two functional subhaplotypes, HapF1 and HapF2, associated with black-skinned phenotype, and one non-functional subhaplotype, HapFDEL, responsible for white-skinned phenotype. HapF1 likely originated from wild populations domesticated in the Near East and subsequently spread globally with the expansion of viticulture. In contrast, HapF2 has a more restricted distribution and may have emerged from hybridization events between cultivated grapevines and local wild populations as viticulture migrated to the Italian peninsula. Furthermore, we found that in white-skinned berry cultivar, HapF has undergone a large deletion at the berry color locus, removing the majority of the VvMybA genes. Previous works suggested a single common origin for white-skinned varieties during grapevine domestication. Our results challenge this notion, instead proposing that white-skinned grape cultivars arose at least twice during grapevine domestication history. Alongside the major haplotype A, some white-skinned cultivars, such as cv. ‘Sultanina’ harbor HapFDEL. Since HapFDEL is present only in table grape varieties, we suggest that it likely arose from a recent mutational event and dispersed along the ancient Silk Road into East Asia. These findings enhance our understanding of the genetic diversity and evolutionary trajectory of grapevine cultivars, offering insights into their domestication and spread across different geographical regions.

Genomic selection of maize test-cross hybrids leveraged by marker sampling

Maize (Zea mays L.) is a staple crop and the most cultivated cereal worldwide. The expansion of this crop was possible due to efforts in management and breeding. From the breeding standpoint, advances were achieved through field experimental design and analyses, establishing heterotic patterns, and releasing heterotic hybrids. Over the last decade, data analyses have benefited from the surge of genome-based approaches. However, it lacks optimization regarding marker dimensionality, proper selection of tested lines and/or environments, and an indication of promising inbred lines for crosses. This study aimed to convert a high-density single nucleotide polymorphism marker dataset into a low-density dataset and perform genomic selection of maize hybrids tested in drought stress and well-watered environments for grain yield and secondary traits. Single nucleotide polymorphism markers were ranked and selected based on effects from a genome-wide association study. For genomic selection, methods containing general and specific combining abilities (GCA and SCA, respectively) and interaction effects were compared in cross-validation schemes. Accuracies using selected markers were similar to complete marker dataset for all traits under drought nand well-watered conditions. For genomic selection, the model containing the main effects of GCA for inbred lines and testers, SCA for hybrids, and the interaction of GCA and SCA with environments (Model 7) performed better for all traits when information about all environments was included. The model without interaction effects (Model 6) performed better when information about environments was missing.

Individual plant genetics reveal the control of local adaptation in European maize landraces

BACKGROUND

European maize landraces encompass a large amount of genetic diversity, allowing them to be well-adapted to their local environments. This diversity can be exploited to improve the fitness of elite material in the face of a changing climate.

RESULTS

We characterized the genetic diversity of 333 individual plants from 40 European maize landrace populations (EMLPs). We identified five genetic groups that mirrored the proximities of their geographical origins. Fixation indices showed moderate differentiation among genetic groups (0.034 to 0.093). More than half of the genetic variance was observed to be partitioned among individuals. Nucleotide diversity of EMLPs decreased significantly as latitude increased (from 0.16 to 0.04), suggesting serial founder events during maize expansion in Europe. GWAS with latitude, longitude, and elevation as response variables identified 28, 347, and 68 significant SNP positions, respectively. We pinpointed significant SNPs near dwarf8, tb1, ZCN7, ZCN8, and ZmMADS69 and identified 126 candidate genes with ontology terms indicative of local adaptation in maize, regulating adaptation to diverse abiotic and biotic environmental stresses.

CONCLUSIONS

This study suggests a quick and cost-efficient approach to identifying genes involved in local adaptation without requiring field data. The EMLPs used in this study have been assembled to serve as a continuing resource of genetic diversity for further research aimed at improving agronomically relevant adaptation traits.

Integrating Genetic Diversity and Agronomic Innovations for Climate-Resilient Maize Systems

Maize is a vital staple crop significantly affected by climate change, necessitating urgent efforts to enhance its resilience. This review analyzes advanced methodologies for maize improvement, focusing on the identification of genetic determinants through QTL mapping, candidate gene mining, and GWAS. We highlight the transformative potential of CRISPR gene editing for identifying key regulators in maize development and the utility of virus-induced gene silencing (VIGS) for functional genomics. Additionally, we discuss breeding strategies leveraging the genetic diversity of maize wild relatives and innovations such as speed breeding and genomic selection (GS), which accelerate breeding cycles. Marker-assisted selection (MAS) plays a critical role in developing superior maize varieties. The review also encompasses agronomic practices and technological innovations, including GS, aimed at climate mitigation. High-throughput phenotyping and omics-based approaches, including transcriptomics and metabolomics, are essential tools for developing climate-resilient maize. Climate changes have a significant impact on maize production and pose unprecedented challenges to its cultivation.

Harnessing Genomics for Breeding Lantana camara L.: Genotyping and Ploidy Testing of Clonal Lines Through ddRADseq Applications

Lantana camara L. is sold worldwide for ornamental purposes, although it is also characterized by high invasiveness potential. Genetic and molecular data available for L. camara are still poor, and breeding is performed through conventional methods. This study focused on a molecular genotyping analysis through the ddRADseq method on an experimental collection of lantana clonal lines to evaluate the potential of molecular techniques in performing marker-assisted breeding, in favour of variety registration and in guaranteeing plant variety protection for the species. Although high genetic uniformity was observed in the population, a unique molecular profile was assigned to every line, indicating the effectiveness of the approach used. Interestingly, low degrees of heterozygosity were observed. In addition, the possibility of inferring ploidy levels through SNP profiles was assessed since it would avoid the necessity of previous biological knowledge and the use of fresh materials. Ploidy analysis is of high interest for lantana breeding to obtain less invasive triploids. Flow cytometry and chromosome counting were used for inference assessment. An nQuack framework provided correct results for the majority of the clonal lines, confirming its effectiveness. These findings encourage the adoption of molecular systems to help breed minor species such as L. camara.

The integration of quantitative trait locus mapping and transcriptome studies reveals candidate genes for water stress response in St. Augustinegrass

BACKGROUND

Drought resistance is an increasingly important trait for many plants-including St. Augustinegrass, a major warm-season turfgrass-as more municipalities impose restrictions on frequency and amount of irrigation. Breeding efforts have focused on breeding for drought resistance, and several drought-related quantitative trait loci (QTL) have been identified for St. Augustinegrass in previous studies. However, the molecular basis of this trait remains poorly understood, posing a significant roadblock to the genetic improvement of the species.

RESULTS

This study sought to validate those QTL regions in an independent biparental population developed from two sibling lines, XSA10098 and XSA10127. The drought evaluation in two greenhouse trials showed significant genotype variation for drought stress traits including leaf wilting, percent green cover, relative water content, percent recovery, and the area under the leaf wilting-, percent green cover-, and percent recovery- curves. A linkage map was constructed using 12,269 SNPs, representing the densest St. Augustinegrass linkage map to date. A multiple QTL mapping approach identified 24 QTL including overlapping regions on linkage groups 3, 4, 6, and 9 between this study and previous St. Augustinegrass drought resistance studies. At the transcriptome level, 1965 and 1005 differentially expressed genes were identified in the drought sensitive and tolerant genotypes, respectively. Gene Ontology and KEGG analysis found different mechanisms adopted by the two genotypes in response to drought stress. Integrating QTL and transcriptomics analyses revealed several candidate genes which are involved in processes including cell wall organization, photorespiration, zinc ion transport, regulation of reactive oxygen species, channel activity, and regulation in response to abiotic stress.

CONCLUSIONS

By innovatively integrating QTL and transcriptomics, our study advances the understanding of the genetic control of water stress response in St. Augustinegrass, providing a foundation for targeted drought resistance breeding.

How transdisciplinarity can help biotech-driven biodiversity research

The Kunming-Montreal Global Biodiversity Framework marks a significant step toward conserving genetic diversity on a global scale. Sequencing advancements have broadened biodiversity studies by enabling the mapping of species distributions, increasing understanding of ecological interactions, and monitoring genetic diversity. However, these tools are hindered by inequalities and biases, particularly in biodiversity-rich developing countries. To navigate these challenges, we propose strategies using the existing biotechnological toolbox to make biodiversity data more accessible and useful for research and development. This includes increasing funding for database curation, improving metadata standards, addressing inequalities in technological capacity, and supporting holistic capacity-building programmes. Implementing these strategies can unlock new opportunities for biodiversity research aligned with sustainable development principles and can contribute to improved conservation outcomes.

Multiple source locations and long-distance dispersal explain the rapid spread of a recent amphibian invasion

Rapid range expansions are characteristic for non-native invasive species when introduced outside their native range. Understanding the dynamics and mechanisms of expanding non-native invasive species is key for regional management. While population genetics and long-term occurrence records are often used in this context, each provides only partial insights, highlighting the need for a combined approach. We demonstrate this synergy using the American bullfrog (Lithobates catesbeianus) invasion in the Grote Nete river valley (Belgium) as a case study. It is commonly believed that this invasion constitutes a single metapopulation established by one primary introduction followed by downstream dispersal. However, recent evidence suggests a more complex scenario, involving introduction at multiple locations and bidirectional dispersal. To differentiate between both scenarios, we analysed nearly three decades of occurrence records and 8592 single nucleotide polymorphisms across 372 individuals from 31 localities, and determined the number of source locations, the range expansion rate, the population genetic structure, and the magnitude and direction of gene flow. We found that invasive spread originated from up to six source locations followed by bidirectional dispersal and downstream long-distance dispersal (LDD) events. Our results suggest that at least two source locations were founded by primary introductions, two from LDD events, while the remaining resulted from secondary introductions. A canal crossing the river was identified as a dispersal barrier, leading to different invasion dynamics on both sides. Our study shows how asynchronous introductions at multiple locations, dispersal barriers, and environmental heterogeneity can lead to distinct spread dynamics within a seemingly continuous and interconnected metapopulation.

Genetic diversity and population structure of ALS-resistant Amaranthus hybridus across Brazil's primary soybean-growing regions

BACKGROUND

Resistance to acetolactate synthase (ALS)-inhibiting herbicides has emerged in Amaranthus hybridus populations across Brazil's soybean-growing regions. To gain insights into the evolutionary origins and spread of resistance, this study (1) investigated the ALS inhibitor resistance mechanisms in nine A. hybridus populations and (2) assessed their genetic diversity, structure, and relatedness.

RESULTS

Resistance to the ALS inhibitor chlorimuron in A. hybridus was associated with two distinct target-site mutations: Trp-574-Leu and Asp-376-Glu. Population genetics revealed low levels of genetic diversity (HE = 0.00117 to 0.16019; π = 0.00126 to 0.17421) and inbreeding (FIS = 0.0015 to 0.13157). Principal component analysis differentiated A. hybridus by geographical region, while ADMIXTURE analysis revealed population structure with evidence of admixture between genetic clusters in three groups of populations.

CONCLUSION

The results suggest multiple local and independent evolutionary origins of resistance. The spread of resistance is primarily driven by local herbicide selection pressure and gene flow through seed dispersal. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Prediction of biomass sorghum hybrids using environmental feature-enriched genomic combining ability models in tropical environments

KEY MESSAGE

Incorporating environmental features improved the predictive ability of genomic prediction models under multi-environment trials in tropical conditions. Gathering environmental and genomic information can benefit the breeding of sorghum hybrids by overcoming complications imposed by the genotype-by-environment interaction (GEI). In this study, we explored the value of combining environmental features (EFs) and genomic data to enhance predictions for biomass sorghum hybrid breeding, addressing GEI complexities. We also investigated if considering specific time windows for EFs improves the prediction. We used a historical dataset from a tropical biomass sorghum breeding program featuring 253 genotypes across 64 trials. Initially, a first-stage analysis was performed to obtain the adjusted means (EBLUEs) and scrutinize the impact of 29 EFs (geographic, climatic, and soil-related EFs) on GEI. Subsequently, in the second-stage analysis, we used data from 221 hybrids that had both parents genotyped to evaluate the predictive ability and assertiveness of 12 models with different effects. The most relevant EFs included soil organic carbon, insolation on a horizontal surface, longitude, temperature at dew point, and nitrogen content. Across three cross-validation scenarios (CV1, CV0, and CV00), the most effective model encompassed main combining ability effects, GEI, and G ω I (genotype-by-specific environmental effects interaction), utilizing an environmental kinship matrix ( Ω ) derived from mean EF values. Only in CV2, a model with a similar structure but utilizing Ω from specific time windows outperformed others. Our findings highlight the potential of integrating environmental and genomic data to refine predictive models for optimizing biomass sorghum hybrid breeding strategies.

Machine learning solutions for integrating partially overlapping genetic datasets and modelling host-endophyte effects in ryegrass (Lolium) dry matter yield estimation

Plant genetic evaluation often faces challenges due to complex genetic structures. Ryegrass (Lolium), a valuable species for pasture-based agriculture, exhibits heterogeneous genetic diversities among base breeding populations. Partially overlapping datasets from incompatible studies and commercial restrictions further impede outcome integration across studies, complicating the evaluation of key agricultural traits such as dry matter yield (DMY). To address these challenges: (1) we implemented a population genotyping approach to capture the genetic diversity in ryegrass base cultivars; (2) we introduced a machine learning-based strategy to integrate genetic distance matrices (GDMs) from incompatible genotyping approaches, including alignments using multidimensional scaling (MDS) and Procrustes transformation, as well as a novel evaluation strategy (BESMI) for the imputation of structural missing data. Endophytes complicate genetic evaluation by introducing additional variation in phenotypic expression. (3) We modelled the impacts of nine commercial endophytes on ryegrass DMY, enabling a more balanced estimation of untested cultivar-endophyte combinations. (4) Phylogenetic analysis provided a pseudo-pedigree relationship of the 113 ryegrass populations and revealed its associations with DMY variations. Overall, this research offers practical insights for integrating partially overlapping GDMs with structural missing data patterns and facilitates the identification of high-performing ryegrass clades. The methodological advancements-including population sequencing, MDS alignment via Procrustes transformation, and BESMI-extend beyond ryegrass applications.

Genome wide association study of Fusarium wilt resistance in Spinacia turkestanica

Fusarium wilt of spinach, caused by Fusarium oxysporum f. sp. spinaciae (Fos), leads to substantial losses in spinach (Spinacia oleracea) seed production in the only region of the USA suitable for growing spinach seed crops, the maritime Pacific Northwest. Accessions of wild spinach, S. turkestanica, serve as a major source of resistance to multiple spinach diseases. In this study, 84 Spinacia genotypes (all 68 S. turkestanica accessions available publicly and 16 S. oleracea) were evaluated for reactions to Fos at medium and high densities of inoculum comprising a mix of isolates of races 1 and 2, using a factorial experimental design of genotypes (n = 84) and Fos inoculum density (0, 12,500, and 37,500 CFU/ml potting medium) with two replicates. The area under the disease progress curve (AUDPC) calculated for wilt severity 28, 35, and 42 days after planting (DAP) ranged from 0.0 to 11.0 and 1.5 to 13.3 at medium and high inoculum densities, respectively. Of the 68 S. turkestanica accessions, 17 and 8 showed high levels of resistance at medium and high inoculum densities, respectively. Single nucleotide polymorphism (SNP) markers (n = 7,065) identified with genotyping-by-sequencing (GBS) were used for genome wide association studies (GWAS) using multiple models tested with GAPIT and TASSEL software. Twelve SNPs were associated significantly with Fusarium wilt resistance in 10 QTL regions located on chromosomes 1, 3, 4, and 6. SNP S6_38110665 on chromosome 6 was validated across multiple GWAS models and demonstrated a major effect (-2.48 to -2.79) at reducing Fusarium wilt severity. SNP S6_38110665 can be used to introduce Fusarium wilt resistance QTL into cultivated spinach (S. oleracea) using marker-assisted selection, thereby enhancing breeding programs for improved disease resistance.

Dairy Cattle Reproduction, Production, and Disease Resistance in the Omics Era: Genome-Wide Selection Signatures Identify Candidate Genes in Sahiwal Cattle

Climate emergency and ecological sustainability call for new ways of thinking livestock health, including the dairy cattle. This study unpacks the genetic diversity and selection sweeps of Sahiwal cattle in relation to adaptability, production, and disease resistance. Using nucleotide diversity (π) calculated from 10 kb windows across the genome with VCFtools, 716 regions of genetic diversity were identified across 29 chromosomes, and importantly, with chromosome 15 showing the highest density. A total of 92 quantitative trait loci (QTL) linked genes were analyzed, with chromosome 1 harboring the highest number. Trait association analysis using the Cattle QTL database showed that 14 genes were linked to production traits, 10 to reproduction traits, and 8 to disease susceptibility. Notable genes included CSMD2 and EFNA1, which influence milk production traits such as fat percentage and yield, and PCBP3 and SGCD, which affect reproductive traits. Additionally, the genes TBXAS1 and ASTN2 were associated with disease traits such as bovine respiratory disease and sole ulcers. Selection sweeps, identified using Tajima's D, revealed 728 sweeps across the genome, with chromosomes 6 and 8 showing the highest frequencies. These sweeps indicate regions under strong selective pressure, likely due to the breed's adaptation to arid environments and specific trait selection. The present study highlights how genetic diversity and selection sweeps contribute to Sahiwal cattle's adaptability, production efficiency, and disease resistance. The insights reported here provide a foundation for livestock health and targeted breeding strategies in the case of Sahiwal cattle under diverse ecological conditions such as tropical climate.

Rapid Colonisation of Synanthropic Stone Martens in a Highly Urbanised Region: Insights From Temporal and Spatial Analysis

Medium-sized carnivores, including the synanthropic stone marten (Martes foina Erxleben, 1777), have shown remarkable adaptability to urbanised and fragmented landscapes, facilitating their spread across mainland Europe. This study investigates the recolonisation of a highly urbanised region by stone martens within two decades, examining spatial and temporal genome-wide data (using genotyping by sequencing) to reveal colonisation dynamics, sources, and barriers influencing their expansion. Using genotypes from 5536 SNPs across 376 stone martens collected between 1995 and 2013, our findings indicate that stone martens successfully expanded through urban environments, yet dispersal was neither entirely random nor strictly distance-dependent. The initial southeastern stronghold (E1) showed the lowest genetic diversity and limited spatial expansion, while other population sources contributed to recolonisation, highlighting a complex, multi-source expansion. Gene flow in the early stages was largely confined to E1, progressing northward and eventually enabling exchange with a second eastern lineage (E2). Meanwhile, the western lineage displayed higher connectivity, occasionally crossing barriers like motorways. Motorways, however, significantly shaped recolonisation patterns, reducing gene flow, while other elements such as built-up areas, secondary roads or waterways showed an additional though very small effect. Over the study period, genetic patch size increased, indicating longer dispersal distances. Gene flow strengthened within both eastern (E1 and E2) and western populations. Still, the western population diverged into two subclusters (W1 and W2) of which one became more differentiated. This suggests limited genetic homogenisation in the near future. This study provides insights into the genetic and ecological dynamics of carnivore recolonisation in highly fragmented landscapes.

What Are We Learning from Plant Pangenomes?

A single reference genome does not fully capture species diversity. By contrast, a pangenome incorporates multiple genomes to capture the entire set of nonredundant genes in a given species, along with its genome diversity. New sequencing technologies enable researchers to produce multiple high-quality genome sequences and catalog diverse genetic variations with better precision. Pangenomic studies have detected structural variants in plant genomes, dissected the genetic architecture of agronomic traits, and helped unravel molecular underpinnings and evolutionary origins of plant phenotypes. The pangenome concept has further evolved into a so-called super-pangenome that includes wild relatives within a genus or clade and shifted to graph-based reference systems. Nevertheless, building pangenomes and representing complex structural variants remain challenging in many crops. Standardized computing pipelines and common data structures are needed to compare and interpret pangenomes. The growing body of plant pangenomics data requires new algorithms, huge data storage capacity, and training to help researchers and breeders take advantage of newly discovered genes and genetic variants.

Litchi40K v1.0: a cost-effective, flexible, and versatile liquid SNP chip for genetic analysis and digitalization of germplasm resources in litchi

Genetic breeding and molecular identification in varieties depend on high-performance genotyping tools. The high heterozygosity of the litchi genome contributes to increased resequencing costs and elevated error rates in hybridization-based genotyping methods. In this study, a liquid chip named Litchi40K v1.0 was developed with high-depth resequencing data from 875 litchi samples, and its efficacy was validated across three different populations. In the L. chinensis var. fulvosus population, three subpopulations characterized by spatial distribution, and a total of 1110 genes were identified in the genomic regions with subpopulation differentiation. Additionally, a total of 30 significant signals associated with diverse agronomic traits were identified. The H002 haplotype of LITCHI02696, dominant in the Sub2 subgroup, significantly increased the soluble solid content in the L. chinensis var. fulvosus population. In a hybrid F1 population, a high-density genetic map was constructed and 79 dwarfing-related QTLs were identified with the liquid chip. An NAC transcription factor was identified as a candidate gene with a heterozygous frameshift variant in the male parent. To facilitate the digitization of germplasm resources, 384 SNPs were selected, and the DNA fingerprint map revealed clear genetic relationships and a total of 10 potential synonym groups or instances of bud mutations were identified in 164 main cultivated litchi varieties. This study provides cost-effective, flexible, and versatile liquid chip for genetic analysis and digitalization of germplasm resources in litchi.

Large Inversions Shape Diversification and Genome Evolution in Common Quails

Chromosomal inversions, by suppressing recombination, can profoundly shape genome evolution and drive adaptation. In the common quail (Coturnix coturnix), a highly mobile bird with a vast Palearctic breeding range, we previously identified a massive inversion on chromosome 1 associated with distinct phenotypes and restricted geographic distribution. Here, using a new de novo genome assembly, we characterise this inversion and uncover additional, ancient structural variation on chromosome 2 that segregates across the species' range: either two putatively linked inversions or a single, large inversion that appears as two due to scaffolding limitations. Together, the inversions encompass a remarkable 15.6% of the quail genome (153.6 Mbp), creating highly divergent haplotypes that diverged over a million years ago. While the chromosome 1 inversion is linked to phenotypic differences, including morphology and migratory behaviour, the chromosome 2 inversion(s) show no such association. Notably, all inversion regions exhibit reduced effective population size and a relaxation of purifying selection, evidenced by elevated nonsynonymous-to-synonymous substitution ratios (N/S). This suggests that inversions, particularly the geographically restricted one on chromosome 1, may act as engines of diversification, accelerating the accumulation of functional variation and potentially contributing to local adaptation, especially within isolated island populations. Our findings demonstrate how large-scale chromosomal rearrangements can compartmentalise a genome, fostering distinct evolutionary trajectories within a single, highly mobile species.

Fitness and Morphology Support Genetic Differentiation Across Different Geographic Scales in a Native Insect Utilising Native vs. Invasive Host Plants

Native species can evolve rapidly in response to utilising invasive species as novel resources. We investigated the genetic and trait differentiation of the Australian soapberry bug Leptocoris tagalicus across three biotypes: those feeding on invasive Cardiospermum grandiflorum in New South Wales (NSW) and Queensland (Qld), invasive C. halicacabum in the Northern Territory (NT), and on the native host Alectryon tomentosus (in Qld). Genetic analyses revealed moderate differentiation between NT insects and those from NSW and Qld (F ST = 0.033). Conversely, insects from NSW and Qld had low genetic differentiation, irrespective of their host plant associations (F ST = 0.008). Field data and data from a multi-generation experiment indicated ongoing adaptation in proboscis length in insects feeding on the two invasive host plant species, likely in response to the sizes of their fruits. Multi-generation hybridisation experiments demonstrated high narrow sense heritability in insect proboscis length and body size (H2 = 0.48 and 0.4, respectively). Crosses involving F1 hybrids of insect biotypes generally outperformed inter-biotype and control crosses. Taken together, these findings support ongoing genetic differentiation among L. tagalicus biotypes across different spatial scales, even in instances of high gene flow.

Identification of single nucleotide polymorphisms and candidate genes associated with fiber content in sweetpotato (Ipomoea batatas (L.) Lam.) through a genome-wide association study

BACKGROUND

Sweetpotato (Ipomoea batatas (L.) Lam.) is an essential root crop with several nutritional benefits, including high dietary fiber content. While fiber contributes positively to human health by reducing the risk of metabolic and gastrointestinal diseases, excessive fiber accumulation can negatively impact texture and consumer preference. Despite its importance, the genetic mechanisms underlying fiber content in sweetpotato remain largely unexplored. Therefore, this study aimed to identify the genomic regions and candidate genes associated with fiber content through a genome-wide association study (GWAS).

RESULTS

Significant phenotypic variation in fiber content were observed among 140 sweetpotato genotypes. The GWAS analysis identified seven significant single nucleotide polymorphisms (SNPs), with Iba_chr07a_20294133 and Iba_chr12a_38616338 consistently detected across the FarmCPU and BLINK models. Notably, three SNPs (Iba_chr01a_17621178, Iba_chr10a_773882, and Iba_chr12a_38616338) showed significant phenotypic differentiation between homozygous alleles, making them promising candidates for marker development. Candidate gene analysis identified four genes with significantly upregulated expression in high-fiber genotypes: IbANT1 (adenine nucleotide transporter BT1), IbCYP86B1 (cytochrome P450 86B1), IbSCR3 (scarecrow-like protein 3), and IbFER (FERONIA receptor-like kinase). These genes are involved in suberin biosynthesis, cell wall remodeling, and metabolic regulation, suggesting their crucial roles in fiber accumulation.

CONCLUSION

This study provides novel insights into the genetic regulation of fiber content in sweetpotato. The identification of significant SNPs and candidate genes offers valuable resources for breeding programs targeting fiber optimization. Further validation is essential for the effective application of these SNPs and genes into marker-assisted selection strategies.

Progress and innovations of gene cloning in wheat and its close relatives

KEY MESSAGE

Wheat and its close relatives have large and complex genomes, making gene cloning difficult. Nevertheless, developments in genomics over the past decade have made it more feasible. The large and complex genomes of cereals, especially bread wheat, have always been a challenge for gene mapping and cloning. Nevertheless, recent advances in genomics have led to significant progress in this field. Currently, high-quality reference sequences are available for major wheat species and their relatives. New high-throughput genotyping platforms and next-generation sequencing technologies combined with genome complexity reduction techniques and mutagenesis have opened new avenues for gene cloning. In this review, we provide a comprehensive overview of the genes cloned in wheat so far and discuss the strategies used for cloning these genes. We highlight the advantages and drawbacks of individual approaches and show how particular genomic progress contributed to wheat gene cloning. A wide range of new resources and approaches have led to a significant increase in the number of successful cloning projects over the past decade, demonstrating that it is now feasible to perform rapid gene cloning of agronomically important genes, even in a genome as large and complex as that of wheat.

Genetic diversity analysis and conservation strategy recommendations for ex situ conservation of Cupressus chengiana

BACKGROUND

Cupressus chengiana is mainly distributed in the Hengduan Mountains area in China. It is one of the Class II endangered plants, ex situ conservation is often used to the affected C. chengiana population due to the construction of the power station. However, population fragmentation and inbreeding in the ex situ conservation have led to decline in genetic diversity. It is therefore important to clarify the differences in genetic diversity between native populations and ex situ population.

RESULTS

In this study, we used Genotyping-by-Sequencing to assess the genetic diversity of 30 C. chengiana trees from four populations in the Dadu River Basin, southwest China, including one ex situ conserved population (DK) and three native populations (BW, SA, RJ). The results showed that compared with the native populations, the DK population showed higher genetic diversity. Among the three native populations, SA population may experience inbreeding and has low genetic diversity. The population structure analysis further revealed that the DK population had higher gene flow and lower differentiation than other three populations. For ex situ populations, the primary determinant of genetic diversity is the genetic variation present in the seedlings sourced from natural populations.

CONCLUSION

These findings support the feasibility of ex situ conservation for C. chengiana conservation. This study provides a scientific foundation for the preservation, management, and restoration of C. chengiana, and would offer valuable insights for the conservation of other endangered plants.

Genome-wide identification and association analysis of informative SNPs of various nutri-nutraceutical traits in Buckwheat (Fagopyrum spp.)

Buckwheat (Fagopyrum spp.) is a pseudocereal with nutraceutical properties that offer several nutritional and health benefits. Buckwheat proteins are gluten-free and have balanced quantities of amino acids and micronutrients, with a higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. In the present study, we conducted a genome-wide association study (GWAS) to investigate the genetic basis of nutraceutical traits in buckwheat. Using 132 diverse genotypes, we evaluated 10 key nutritional and nutraceutical traits: phenol, flavonoids, antioxidants, methionine, lysine, protein content, nitrogen, iron, zinc, and ascorbic acid. Fagopyrum tartaricum displayed higher levels of phenols, flavonoids, antioxidants, iron, zinc, and nitrogen, while Fagopyrum esculentum exhibited elevated methionine, lysine, protein, and ascorbic acid levels. Genotyping by sequencing identified 3,728,028 single-nucleotide polymorphisms (SNPs), with the highest density on chromosome 1. GWAS detected 46 significant SNPs associated with the studied traits, including an SNP on chromosome 6 linked to lysine with aphenotypic contribution of 49.62%. Candidate gene analysis identified 138 genes within 100 kb of significant quantitative trait loci (QTLs), involved in metabolic and biosynthetic pathways such as amino acid and carbohydrate metabolism. Population structure analysis grouped the genotypes into three populations, enhancing the reliability of marker-trait associations. Gene Ontology analysis highlighted key biological processes, including lipid transport, tryptophan metabolism, and protein phosphorylation, providing insights into the molecular mechanisms governing these traits. The present study emphasizes the potential of molecular breeding to enhance the nutritional quality of buckwheat and its role in addressing global malnutrition. The identified SNP markers and candidate genes offer a valuable foundation for developing high-yield, nutrient-rich buckwheat varieties through genome editing and marker-assisted selection.

Evolutionary History and Rhizosphere Microbial Community Composition in Domesticated Hops (Humulus lupulus L.)

Humulus lupulus L., commonly known as hop, is a perennial crop grown worldwide and is well known for its pharmacological, commercial, and most importantly brewing applications. For hundreds of years, hop has undergone intense artificial selection, with over 250 cultivated varieties being developed worldwide, all displaying differences in key characteristics such as bitter acid concentrations, flavour and aroma profiles, changes in photoperiod, growth, and pathogen/pest resistances. Previous studies have individually explored differences between cultivars, aiming to identify markers that can quickly and cost-effectively differentiate between cultivars. However, little is known about their evolutionary history and the variability in their associated rhizospheric microbial communities. Coupling phenotypic, genomic, and soil metagenomic data, our study explores the global population structure and domestication history of 98 hop cultivars. We assessed differences in growth rates, rates of viral infection, usage of dissolvable nitrogen, and soil microbial community compositions between US and non-US based cultivars. Our study revealed that worldwide hop cultivars cluster into four subpopulations: Central European, English, and American ancestry as previously reported, and one new group, the Nobles, revealing further substructure amongst Central European cultivars. Modelling the evolutionary history of domesticated hop reveals divergence of the common ancestors of modern US cultivars around 2800 years before present (ybp), and more recent divergences with gene flow across English, Central European, and Noble cultivars, reconciled with key events in human history and migrations. Furthermore, cultivars of US origin were shown to overall outperform non-US cultivars in both growth rates and usage of dissolvable nitrogen and display novel microbial composition under common-garden settings in the United States.

Gaining insights into genomic regions associated with Chilo partellus resistance in teosinte-derived maize population

Introduction

Maize stem borer (Chilo partellus) is an important primary pest of the maize crop that feeds on leaves, cobs, and pith, leading to complete damage of the plant and hence lower productivity of maize. Teosinte is a wild progenitor of maize and an important source of genetic variability that possesses diverse alleles for resistance against biotic and abiotic stresses. Therefore, teosinte is a promising candidate for introducing genetic diversity into cultivated maize germplasm by domesticating its wild alleles.

Methods

In this study, we investigated the genomic regions in F6 Teosinte derived maize mapping population (recombinant inbred lines) by crossing LM13 with Teosinte (Zea mays sps. parviglumis) during 2020 -2023. The F6 mapping population (89 lines) thus developed was subjected to genotyping by sequencing (GBS), and the polymorphic simple sequence repeat (SSR) markers were found. This population was screened against C. partellus {leaf injury rating (LIR) and % dead heart} during the Kharif seasons of 2023 and 2024 (June to September).

Results

The C. partellus infestations showed significant differences among the F6 lines with respect to the measured LIR and % dead heart, where the LIR ranged from 1.7 to 7.7 in the population. The phenotypic and molecular data from the SSR and single-nucleotide polymorphism (SNP) markers were used to map the quantitative trait loci (QTLs). A total of four putative QTLs (qLIR_4.1, qLIR_9.1, qDH_1.1, and qDH_2.1) were identified on chromosomes 4, 9, 1, and 2 respectively for both the traits.

Conclusion

These QTLs can be used in marker-assisted breeding to develop hybrids resistant to C. partellus. Based on a literature review, we believe that our study offers a pioneering report on identifying the QTLs associated with C. partellus resistance in maize varieties in Asia. The findings of this study are expected to be of use in the future for fine mapping, expression analyses, and marker tag development for marker-assisted selection aimed at improving maize resistance to pests.

Identification of favorable alleles from exotic Upland cotton lines for fiber quality improvement using multiple association models

Upland cotton (Gossypium hirsutum) faces the challenge of limited genetic diversity in the elite or improved gene pool. To address this issue, we explored alleles contributed by five 'converted' exotic lines sampling most of the undomesticated botanical races of G. hirsutum, in BC1F2 and F3 populations. Joint analysis of all populations along with population-specific analyses identified 38 unique QTL for six different fiber quality traits. At 15 of these loci, DES56 or the elite allele improved upon all the exotics. For another 15, only a single of the five exotics improved upon the elite allele, suggesting the rare alleles that may not have been sampled in the cotton domestication or improvement. At the remaining 8 QTL, multiple exotic lines contributed the superior allele, suggesting that DES56 (and by extension the elite gene pool) has chronically poor alleles at these loci. Converted strains T1046, T326, and T063 showed the highest potential for contributions to cotton fiber quality breeding programs. Upper Half Mean Length and Fiber Strength showed multiple QTL regions affecting both traits simultaneously, while the Uniformity Index showed the smallest heritability values. The estimation of pairwise genetic distances for six parental lines indicates that DES56 has a higher genetic similarity with each exotic line than the exotic lines have with each other. Most of the detected QTL were 'minor' (explaining less than 10% of variance) supporting the implementation of genomic selection techniques to utilize the cumulative effects of most of these QTL distributed genome-wide. Finally, some regions were consistently unfavorable for exotic introgression such as on chromosomes A13 and D09, indicating the possible genome-wide haplotypes that may combine the benefits of a history of scientific breeding of the elite gene pool.

Identification of late blight resistance QTLs in an interspecific RIL population of tomato via genotyping-by-sequencing

Late blight (LB), caused by Phytophthora infestans, is a destructive disease of the cultivated tomato, Solanum lycopersicum. Environmental concerns and pathogen resistance have propelled research towards developing host resistance. The current LB-resistant cultivars of tomato exhibit susceptibility under severe disease pressure, necessitating the identification, characterization, and incorporation of additional resistance genes into new tomato cultivars. Recently, we identified Solanum pimpinellifolium accession PI 270443 with strong resistance to LB and developed a RIL population from its cross with an LB-susceptible tomato breeding line. In the present study, we constructed a high-density genetic map of the RIL population, using 8,470 SNP markers set into 1,195 genomic bins, with a total genetic distance of 1232 cM and an average bin size of 1 cM. We identified 2 major adjoining LB-resistance QTLs on chromosome 10 and a few minor QTLs on chromosomes 1 and 12 of PI 270443. While one of the QTLs on chromosome 10 colocalized with the known LB-resistance gene Ph- 2 and a LB-resistance QTL previously identified in an F2 population of the same cross, the present study allowed marker saturation of the region, fine mapping of the QTL, and identification of candidate resistance genes in the region. One of the 2 major QTLs on chromosome 10 and the 3 QTLs on chromosomes 1 and 12 were not previously reported in S. pimpinellifolium for LB resistance. These results will expedite transferring of LB resistance from PI 270443 into the tomato cultigen via MAS and discovering the underpinning LB-resistance genes in PI 270443.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-025-01560-6.

Genetic Differentiation of Chinese Fir Populations From Mainland China and Taiwan as Revealed by Genotyping-By-Sequencing Analysis, With Implication for Taxonomic Position of the Species

Climate change and strait isolation during the glacial period had a profound effect on the differentiation of gymnosperms on both sides of the Taiwan Strait. The taxonomic status and population structure of Cunninghamia konishii (Taiwan) and C. lanceolata (mainland China) remain contentious due to conflicting morphological and molecular evidence. Thus, we sampled 92 accessions from seven natural populations, six from mainland China and one from Taiwan, and conducted high-throughput genotyping-by-sequencing (GBS) analysis. The northern marginal population exhibited the lowest genetic diversity (θπ = 4.828 × 10-3), while the Taiwan population had the highest (θπ = 5.821 × 10-3), reflecting its role as a glacial refugium, while mainland populations retained lower diversity due to post-glacial bottlenecks. There was little difference in Tajima's D values of selection pressure between mainland China and Taiwan. However, significant gene flow (Nm = 2.839) was observed, combined with low F ST values (0.072-0.122), which indicate low genetic differentiation among C. lanceolata and C. konishii. Migration analysis indicated a high probability of unidirectional gene flow from mainland China to Taiwan, with the Dongshan Land Bridge facilitating pre-glacial gene flow. We conclude that C. konishii represents an ecotype of C. lanceolata , shaped by environmental plasticity and incomplete isolation. This study enhances our understanding of the gene flow and evolutionary processes shaping the species and offers new insights into their taxonomic classification.

Integrative mapping in large inbred and hybrid association panels along with an F2 population advanced a novel understanding of general combining ability for plant height in maize

KEY MESSAGE

We identified 44 QTL for PH-related traits evaluated for inbreds per se and GCA effects in large inbred and hybrid association panels and seven QTL for EH/PH in an F2 population coupled with BSA-seq. Among four co-localized QTL, seven novel potential candidate genes were significantly associated with PH-related traits, shedding new light on understanding the genetics of GCA for PH. Breeding optimal plant height (PH) is essential for improving maize (Zea mays L.) plant architecture, yield, lodging resistance, and density tolerance, yet there is limited genetic loci available regarding the general combining ability (GCA) for PH-related traits. In the current study, an inbred association panel of 312 inbred lines (IAP) along with a hybrid association panel (HAP) of 764 hybrid combinations were utilized to dissect the genetics of PH-related traits and their GCA effects across three environments. We found 44 quantitative trait loci (QTL) with 76 significant single-nucleotide polymorphisms (SNPs) for PH-related traits evaluated for inbreds per se and GCA effects; however, no overlapping loci were identified across inbreds per se and GCA effects, indicating conspicuous discrepancies in their genetics. In addition, GCA effects with complex genetic basis differed for diverse testers, which highlighted the specificity and complexity among heterotic groups. Correspondingly, we evaluated an F2 population derived from two parental lines LY-02 and LH513 with the contrasting EH/PH coupled with bulked segregant analysis by sequencing (BSA-seq) and found seven QTL for EH/PH. Among four co-localized loci across the association and QTL mapping, seven novel candidate genes were found to differently express among LY-02, LH513, and their F1 and were potentially associated with PH-related traits. The current study with combined mapping in diverse mapping populations provided a novel understanding of GCA for PH-related traits in maize.

Reduced-Representation Sequencing Detects Trans-Arctic Connectivity and Local Adaptation in Polar Cod (Boreogadus saida)

Information on connectivity and genetic structure of marine organisms remains sparse in frontier ecosystems such as the Arctic Ocean. Filling these knowledge gaps becomes increasingly urgent, as the Arctic is undergoing rapid physical, ecological and socio-economic changes. The abundant and widely distributed polar cod (Boreogadus saida) is highly adapted to Arctic waters, and its larvae and juveniles live in close association with sea ice. Through a reduced-representation sequencing approach, this study explored the spatial genetic structure of polar cod at a circum-Arctic scale. Genomic variation was partitioned into neutral and adaptive components to respectively investigate genetic connectivity and local adaptation. Based on 922 high-quality single nucleotide polymorphism (SNP) markers genotyped in 611 polar cod, broad-scale differentiation was detected among three groups: (i) Beaufort -Chukchi seas, (ii) all regions connected by the Transpolar Drift, ranging from the Laptev Sea to Iceland, including the European Arctic and (iii) West Greenland. Patterns of neutral genetic structure suggested broadscale oceanographic and sea ice drift features (i.e., Beaufort Gyre and Transpolar Drift) as important drivers of connectivity. Genomic variation at 35 outlier loci indicated adaptive divergence of the West Greenland and the Beaufort-Chukchi Seas populations, possibly driven by environmental conditions. Sea ice decline and changing ocean currents can alter or disrupt connectivity between polar cod from the three genetic groups, potentially undermining their resilience to climate change, even in putative refugia, such as the Central Arctic Ocean and the Arctic Archipelago.

A Sorghum BAK1/SERK4 Homolog Functions in Pathogen-Associated Molecular Patterns-Triggered Immunity and Cell Death in Response to Colletotrichum sublineola Infection

Sorghum bicolor is the fifth most important cereal crop and expected to gain prominence due to its versatility, low input requirements, and tolerance to hot and dry conditions. In warm and humid environments, the productivity of sorghum is severely limited by the hemibiotrophic fungal pathogen Colletotrichum sublineola, the causal agent of anthracnose. Cultivating anthracnose-resistant accessions is the most effective and environmentally benign way to safeguard yield. A previous genome-wide association study for anthracnose resistance in the Sorghum Association Panel uncovered single-nucleotide polymorphisms on chromosome 5 associated with resistance to anthracnose, including one located within the coding region of gene Sobic.005G182400. In this study, we investigated the molecular function of Sobic.005G182400 in response to C. sublineola infection. Conserved domain, phylogenetic, and structural analyses revealed that the protein encoded by Sobic.005G182400 shares significant structural similarity with the Arabidopsis BRASSINOSTEROID INSENSITIVE1-ASSOCIATED RECEPTOR KINASE1 (BAK1)/SOMATIC EMBRYOGENESIS RECEPTOR-LIKE KINASE4 (SERK4). Although sequence analysis of four sorghum accessions showed no substantial variation in the coding region, accession SC1330, which carries the resistance allele, exhibited significantly higher expression of Sobic.005G182400 during early infection (≤24 h). Co-expression network analysis identified that the module associated with Sobic.005G182400 was enriched in genes involved in endocytosis, autophagy, and vesicle transport. Gene regulatory network analysis further suggested that Sobic.005G182400 regulates genes required for BAK1/SERK4-mediated cell death via protein glycosylation. Together, these findings indicate that Sobic.005G182400 encodes a protein with similarity to Arabidopsis BAK1/SERK4 that enables pathogen-associated molecular patterns-triggered immunity and regulates cell death.

The Relative Roles of Selection and Drift in the Chaffinch Radiation (Aves: Fringilla) Across the Atlantic Archipelagos of Macaronesia

Island populations diverge from the mainland and from each other by both natural selection and neutral forces such as founder effects and genetic drift. In this work, we aim to determine the relative roles of selection and drift in the diversification of chaffinches (Fringilla spp.) in Macaronesia. We tested the hypothesis that taxa inhabiting Macaronesian archipelagos, which exhibit significant differences in habitat and climate compared with the mainland, should experience distinct ecological pressures, leading to divergence at loci under selection related to environmental variables. To determine the role of local adaptation in the differentiation of these taxa, we performed genotype-environment association (GEA) analyses using ten environmental variables and 52,306 single nucleotide polymorphism markers obtained from genotyping-by-sequencing (GBS) in 79 chaffinches. Redundancy analysis (RDA) revealed that genomic variation is associated with environmental variables and identified candidate genes related to phenotypic traits and environmental variables. Variables associated with habitat type and precipitation, together with drift, played an important role in the genomic differentiation between chaffinches from Macaronesia and the mainland, as well as within the Canarian archipelago. Genetic drift was identified as the main factor in the differentiation of North African chaffinches from Macaronesia and mainland Europe, as well as Madeira chaffinches from those in the Canary Islands. Finally, chaffinches from the Canary Islands show an incipient diversification process at the genetic and phenotypic level driven by both selection and neutral processes. Our results suggest that both habitat-driven local adaptation and drift have played a role in the radiation of chaffinch taxa in Macaronesia.

Speciation with gene flow in an island endemic hummingbird

We examined speciation in streamertail hummingbirds (Trochilus polytmus and Trochilus scitulus), Jamaican endemic taxa that challenge the rule that bird speciation cannot progress in situ on small islands. Our analysis shows that divergent selection acting on male bill color, a sexual ornament that is red in polytmus and black in scitulus, acts as a key reproductive barrier. We conducted a population-level analysis of genomic and phenotypic patterns to determine the traits that contribute the most to speciation despite ongoing gene flow across a narrow hybrid zone. We characterized genomic patterns using 6,451 single-nucleotide polymorphisms and a segment of the mitochondrial control region. Our analyses revealed high diversity within species, and low divergence between them, consistent with a recent speciation event or extensive gene flow following secondary contact. We observed narrow clines in two phenotypic traits and several SNP loci. The cline width for male bill color is only 2.3 km, marking it as one of the narrowest phenotypic clines documented in an avian hybrid zone. The coincidence of estimated cline centers with the Rio Grande Valley suggests that this landscape feature may contribute to hybrid zone stability. However, given that streamertails are highly mobile, it is unlikely that such a narrow river acts as a physical barrier to dispersal. The limited genomic divergence across scanned regions of the genome offers little support for postmating reproductive barriers. Instead, our findings point to strong premating selection acting on bill color as the primary driver of streamertail speciation.

Optimising Exome Captures in Species With Large Genomes Using Species-Specific Repetitive DNA Blocker

Large and highly repetitive genomes are common. However, research interests usually lie within the non-repetitive parts of the genome, as they are more likely functional, and can be used to answer questions related to adaptation, selection and evolutionary history. Exome capture is a cost-effective method for providing sequencing data from protein-coding parts of the genes. C0t-1 DNA blockers consist of repetitive DNA and are used in exome captures to prevent the hybridisation of repetitive DNA sequences to capture baits or bait-bound genomic DNA. Universal blockers target repetitive regions shared by many species, while species-specific c0t-1 DNA is prepared from the DNA of the studied species, thus perfectly matching the repetitive DNA contents of the species. So far, the use of species-specific c0t-1 DNA has been limited to a few model species. Here, we evaluated the performance of blocker treatments in exome captures of Pinus sylvestris, a widely distributed conifer species with a large (> 20 Gbp) and highly repetitive genome. We compared treatment with a commercial universal blocker to treatments with species-specific c0t-1 (30,000 and 60,000 ng). Species-specific c0t-1 captured more unique exons than the initial set of targets leading to increased SNP discovery and reduced sequencing of tandem repeats compared to the universal blocker. Based on our results, we recommend optimising exome captures using at least 60,000 ng of species-specific c0t-1 DNA. It is relatively easy and fast to prepare and can also be used with existing bait set designs.

Missing genotype imputation in non-model species using self-organizing maps

Current methodologies of genome-wide single-nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well-studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non-model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self-organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM-derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open-source application programmed in Python3 and with a user-friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.

Transcriptional Reprogramming and Allelic Variation in Pleiotropic QTL Regulates Days to Flowering and Growth Habit in Pigeonpea

The present study investigated the linkage between days to flowering (DTF) and growth habit (GH) in pigeonpea using QTL mapping, QTL-seq, and GWAS approaches. The linkage map developed here is the largest to date, spanning 1825.56 cM with 7987 SNP markers. In total, eight and four QTLs were mapped for DTF and GH, respectively, harbouring 78 pigeonpea orthologs of Arabidopsis flowering time genes. Corroboratively, QTL-seq analysis identified a single linked QTL for both traits on chromosome 3, possessing 15 genes bearing genic variants. Together, these 91 genes were clustered primarily into autonomous, photoperiod, and epigenetic pathways. Further, we identified 39 associations for DTF and 111 associations for GH through GWAS in the QTL regions. Of these, nine associations were consistent and constituted nine haplotypes (five late, two early, one each for super-early and medium duration). The involvement of multiple genes explained the range of allelic effects and the presence of multiple LD blocks. Further, the linked QTL on chromosome 3 was fine-mapped to the 0.24-Mb region with an LOD score of 8.56, explaining 36.47% of the phenotypic variance. We identified a 10-bp deletion in the first exon of TFL1 gene of the ICPL 20338 variety, which may affect its interaction with the Apetala1 and Leafy genes, resulting in determinate GH and early flowering. Further, the genic marker developed for the deletion in the TFL1 gene could be utilized as a foreground marker in marker-assisted breeding programmes to develop early-flowering pigeonpea varieties.

Anthropogenic Landscape Alteration, but Not Urbanization, Influences Non-Adaptive Evolution in Common Milkweed (Asclepias syriaca L.)

Urbanization can alter mating and dispersal, with consequences for non-adaptive evolution in populations. Potential outcomes vary widely due to the heterogeneity of urban landscapes and the diverse life history strategies of taxa. Furthermore, it is unclear how plants, which are significantly understudied in this context, are impacted. To better understand how urbanization influences non-adaptive evolution in a native plant of conservation importance, we analyzed patterns of neutral genetic variation in common milkweed (Asclepias syriaca). From 256 individuals sampled across 122 locations throughout the Greater Toronto Area, Canada, we created two datasets of 2,835 and 972 single nucleotide polymorphisms through genotype-by-sequencing. Genetic diversity and effective population size N e were mostly consistent between urban and rural habitats. Genetic differentiation between urban and rural habitats was low, and samples originated from a single genetic population. Demographic analysis indicated that N e decreased by > 99% within the past 800 years, with the rate of loss accelerating over time. These findings suggest that this A. syriaca population was little affected by the transition from rural to urban habitat; rather, anthropogenic activity prior to urbanization, such as precontact Indigenous inhabitation and colonial settlement, had observable effects on population demography. This study demonstrates how anthropogenic factors can modify the degree to which urbanization impacts evolution and emphasizes the importance of contextualizing results with demographic, ecological, and cultural histories.

Multi-locus genome-wide association mapping for major agronomic and yield-related traits in sorghum (Sorghum bicolor (L.) moench) landraces

BACKGROUND

Sorghum is a vital cereal crop for over 750 million people, ranking 5th globally. It has multiple purposes, including food, feed, and biofuels, and is essential in Ethiopia, which has a rich genetic diversity of various agroecological zones.

OBJECTIVE

Explore marker-trait associations (MTAs) to identify quantitative trait nucleotides (QTNs) and new candidate genes associated with agronomic and yield contributing traits in Ethiopian sorghum landraces using multi-locus GWAS models to assist the genomic-assisted breeding strategies.

METHOD

This study investigates the genetic basis of agronomic traits in Ethiopian sorghum landraces through multi-locus Genome-Wide Association Studies (ML-GWAS). 216 landraces, improved varieties, and check cultivars were obtained from the Ethiopian Biodiversity Institute and the National Sorghum Improvement Program for this study. The experiment was conducted over two cropping seasons, employing an α-lattice design for phenotyping key traits such as days to flowering, days to maturity, plant height, seed number per plant, grain yield, and thousand seed weight. A mixed linear model (MLM) was used to analyze the phenotypic data and estimate the genetic parameters including variances and the broad sense heritability. GBS with the ApeKI restriction enzyme provided 50,165 high-quality SNP markers. The six ML-GWAS models identified significant QTNs with a LOD score threshold value of ≥ 4.0. The analysis revealed major QTNs associated with traits across multiple chromosomes, supported by a stringent filtering criterion that ensured reliability. Co-localization with known QTLs was explored using the Sorghum QTL Atlas database and candidate genes within significant QTN regions, providing the genetic architecture influencing agronomic performance were identified via the Phytozome platform using the biomaRt package.

RESULT

Pearson correlation analysis revealed significant associations among most traits, with p-values less than 0.0001, except for grain yield per plant which showed lower correlations with other traits. Genetic variability analysis indicated that days to flowering exhibited high heritability (0.7) and genetic advance (19.6%) as percent of mean, suggesting strong genetic control, while grain yield displayed extremely low h2 (0.003). A total of 351,692 SNP markers were identified across 10 sorghum chromosomes from 216 Ethiopian sorghum landraces, and we have been refining this to 50,165 filtered SNPs. Manhattan plots indicated significant marker-trait associations (MTAs) across multiple chromosomes, particularly for days to flowering and plant height. Significant QTNs were associated with key traits including flowering time, plant height, and grain yield. ML-GWAS identified 176 QTNs with varying LOD scores and phenotypic effects. Multiple genes linked to these QTNs highlight the complexity of genetic interactions of studied traits with 36 unique and 12 major QTNs. Notable SNP markers were concentrated on chromosomes 1, 2, and 3, reinforcing the importance of these regions for breeding efforts. Candidate gene analysis revealed key genes regulating flowering time, stress response, and yield traits, which could serve as targets for genetic enhancement. In our study, key candidate genes have been successfully identified, these are regulating flowering time, maturity, and stress resilience. Genes such as Sobic.001G196700 and Sobic.002G183400 are identified as critical regulators of floral development. The stress-responsive gene Sobic.005G176100 (a mannose-6-phosphate isomerase), emphasizes the importance of resilience in sorghum cultivation under adverse conditions. Additionally, Sobic.003G324400 and Sobic.004G178300 are essential for regulating plant height and seed weight, making them valuable for yield enhancement breeding programs.

CONCLUSION

This study enhances our understanding of the genetic diversity of Ethiopian sorghum landraces, crucial for breeding programs. It identifies key QTNs and candidate genes associated with important agronomic traits, offering insights for marker-assisted and genomic-assisted breeding. The ML-GWAS models highlight the genetic complexity of flowering time and grain yield traits, emphasizing the need for targeted breeding efforts to maximize sorghum productivity.

Genomic Selection for Pea Grain Yield and Protein Content in Italian Environments for Target and Non-Target Genetic Bases

Enhanced pea cultivation, which can increase the sustainability of European agriculture, requires better-performing cultivars. This study investigated the genomic selection (GS) ability to predict grain yield, protein content, and protein yield on the same or a different genetic base (target/non-target GB) relative to that employed for model training. GS models were developed on 276 lines from three Recombinant Inbred Line (RIL) populations evaluated in three Italian autumn-sown environments using 5537 SNPs from genotyping by sequencing. Validation in two cropping years concerned 108 independent lines from five RIL populations, of which two belonged to the GS training set, and three shared one parent each with training populations. A genome-wide association study performed on the GS training set using 18,674 SNPs highlighted the polygenic control of protein content and grain yield, with several environment-dependent QTLs for yield. Intermediate/high predictive ability within or across populations emerged for all traits in the target GB (0.359-0.675), with some variation depending on the population. Predictive ability in the non-target GB was modest/intermediate for protein content, and null/poor for the other traits. No inverse correlation emerged between grain yield and protein content. GS proved useful for all traits in the target GB and for protein content in a non-target GB.

Genetic Dissection of Triple Rust Resistance (Leaf, Yellow, and Stem Rust) in Kenyan Wheat Cultivar, "Kasuku"

Climate change is driving the spread of transboundary wheat diseases, necessitating the development of resilient wheat varieties for sustainable agriculture. Wheat rusts, including leaf rust (LR), yellow rust (YR), and stem rust (SR), remain among the most economically significant diseases, causing substantial yield losses worldwide. Enhancing genetic diversity by identifying and deploying rust resistance genes is crucial for durable resistance in wheat breeding programs. This study aimed to identify quantitative trait loci (QTL) associated with rust resistance in the CIMMYT wheat line Kasuku, released in Kenya in 2018. A recombinant inbred line (RIL) population (181 lines) derived from Kasuku (triple rust-resistant) and Apav#1 (triple rust-susceptible) was evaluated under artificial LR and YR epidemics in Mexico and YR and SR in Kenya. QTL mapping using genotyping-by-sequencing (DArTSeq) and phenotypic data identified four major loci: QLrYrSr.cim-1BL (Lr46/Yr29/Sr58) on 1BL, conferring resistance to LR, YR, and SR; QLrYr.cim-2AS (Yr17/Lr37) on 2AS, providing LR and YR resistance; QLrYr.cim-3AL on 3AL; and QLrYrSr.cim-6AL on 6AL, representing novel loci associated with multiple rust resistances. Additionally, minor QTL were also identified: for LR (QLr.cim-2DS on 2DS, QLr.cim-6DS on 6DS), for YR (QYrKen.cim-3DS on 3DS, QYrKen.cim-6BS on 6BS), and for SR (QSr.cim-2BS on 2BS, QSr.cim-5AL on 5AL, QSr.cim-6AS on 6AS). RILs carrying these QTL combinations exhibited significant reductions in rust severity. Flanking markers for these loci are being used to develop Kompetitive Allele-Specific PCR (KASP) markers for fine mapping and marker-assisted selection (MAS). These findings contribute to the strategic deployment of rust resistance genes in wheat breeding programs, facilitating durable resistance to multiple rust pathogens.

GWAS-assisted and multitrait genomic prediction for improvement of seed yield and canning quality traits in a black bean breeding panel

In recent years, black beans (Phaseolus vulgaris L.) have gained popularity in the United States, with improved seed yield and canning quality being critical traits for new cultivars. Achieving genetic gains in these traits is often challenging due to negative trait associations and the need for specialized equipment and trained sensory panels for evaluation. This study investigates the integration of genomics and phenomics to enhance selection accuracy for these complex traits. We evaluated the prediction accuracy of single-trait (ST) and multitrait (MT) genomic prediction (GP) models, incorporating near-infrared spectroscopy (NIRS) data and markers identified through genome-wide association studies (GWAS). The models demonstrated moderate prediction accuracies for yield and canning appearance (App) and high accuracies for color retention. No significant differences were found between ST and MT models within the same breeding cycle. However, across breeding cycles, MT models outperformed ST models by up to 45 and 63% for canning App and seed yield, respectively. Interestingly, incorporating significant SNP markers identified by GWAS and NIRS data into the models tended to decrease prediction accuracy both within and between breeding cycles. As genotypes from the new breeding cycle were included, the models' prediction accuracy generally increased. Our findings underscore the potential of MT models to enhance the prediction of complex traits such as seed yield and canning quality in dry beans and highlight the importance of continually updating the training dataset for effective GP implementation in dry bean breeding.

Experimental evolution in maize with replicated divergent selection identifies two plant-height-associated regions

Experimental evolution studies are common in agricultural research, where they are often deemed "long-term selection." These are often used to perform selection mapping, which involves identifying markers that were putatively under selection based on finding signals of selection left in the genome. A challenge of previous selection mapping studies, especially in agricultural research, has been the specification of robust significance thresholds. This is in large part because long-term selection studies in crops have rarely included replication. Usually, significance thresholds in long-term selection experiments are based on outliers from an empirical distribution. This approach is prone to missing true positives or including false positives. Under laboratory conditions with model species, replicated selection has been shown to be a powerful tool, especially for the specification of significance thresholds. Another challenge is that commonly used single-marker-based statistics may identify neutral linked loci which have hitchhiked along with regions that are actually under selection. In this study, we conducted divergent, replicated selection for short and tall plant height in a random-mating maize population under real field conditions. Selection of the 5% tallest and shortest plants was conducted for 3 generations. Significance thresholds were specified using the false discovery rate for selection (FDRfS) based on a window-based statistic applied to a statistic leveraging replicated selection (FSTSum). Overall, we found 2 significant regions putatively under selection. One region was located on chromosome 3 close to the plant-height genes Dwarf1 and iAA8. We applied a haplotype block analysis to further dissect the pattern of selection in significant regions of the genome. We observed patterns of strong selection in the subpopulations selected for short plant height on chromosome 3.

The Distribution and Dispersal of Large Haploblocks in a Superspecies

Haploblocks are regions of the genome that coalesce to an ancestor as a single unit. Differentiated haplotypes in these regions can result from the accumulation of mutational differences in low-recombination chromosomal regions, especially when selective sweeps occur within geographically structured populations. We introduce a method to identify large well-differentiated haploblock regions (LHBRs), based on the variance in standardised heterozygosity (ViSHet) of single nucleotide polymorphism (SNP) genotypes among individuals, calculated across a genomic region (500 SNPs in our case). We apply this method to the greenish warbler (Phylloscopus trochiloides) ring species, using a newly assembled reference genome and genotypes at more than 1 million SNPs among 257 individuals. Most chromosomes carry a single distinctive LHBR, containing 4-6 distinct haplotypes that are associated with geography, enabling detection of hybridisation events and transition zones between differentiated populations. LHBRs have exceptionally low within-haplotype nucleotide variation and moderately low between-haplotype nucleotide distance, suggesting their establishment through recurrent selective sweeps at varying geographic scales. Meiotic drive is potentially a powerful mechanism of producing such selective sweeps, and the LHBRs are likely to often represent centromeric regions where recombination is restricted. Links between populations enable introgression of favoured haplotypes and we identify one haploblock showing a highly discordant distribution compared to most of the genome, being present in two distantly separated geographic regions that are at similar latitudes in both east and central Asia. Our results set the stage for detailed studies of haploblocks, including their genomic location, gene content and contribution to reproductive isolation.

A comprehensive catalog of single nucleotide polymorphisms (SNPs) from the black pepper (Piper nigrum L.) genome

BACKGROUND

Single nucleotide polymorphisms (SNPs) have emerged as the marker of choice in breeding and genetics, particularly in non-model organisms such as black pepper (Piper nigrum L.), a globally recognized spice crop. This study presents a comprehensive catalog of SNPs in the black pepper genome using data from 30 samples obtained from RNA sequencing and restriction site-associated DNA sequencing, retrieved from the Sequence Read Archive, and their consequences at the sequence level.

RESULTS

Three SNP calling and filtering pipelines, namely BCFtools, Genome Analysis Toolkit (GATK)-soft filtering, and GATK-hard filtering, were employed. Results revealed 498,128, 396,003, and 312,153 SNPs respectively identified by these pipelines, with 260,026 SNPs commonly detected across all methods. Analysis of SNP distribution across the 45 scaffolds of the black pepper genome showed varying densities, with pseudo-chromosomes Pn25 (0.86 SNPs/kb), Pn8 (0.74 SNPs/kb), and Pn7 (0.72 SNPs/kb) exhibiting the highest densities. Conversely, scaffolds Pn27 to Pn43 exhibited minimal SNP distribution, except Pn45. Approximately 34.80% of SNPs exhibited stronger genetic linkage (r2 > 0.7). Moreover, SNPs predominately mapped to downstream (≈ 32.54%), upstream (≈ 22.52%), and exonic (≈ 16.20%) regions of genes. Transition substitution accounted for the majority (≈ 57.42%) of identified SNPs, resulting in an average transition-to-transversion ratio of 1.36. Notably, 56.09% of SNPs were non-synonymous, with a significant proportion (≈ 53.59%) being missense mutations. Additionally, 12,491 SNPs with high or moderate impacts were identified, particularly in genes associated with secondary metabolism and alkaloid biosynthesis pathways. Furthermore, the expression of 675 genes was potentially influenced by local (cis-acting) SNPs, while 554 genes were affected by distal (trans-acting) SNPs.

CONCLUSION

The findings of the present study underscore the utility of identified SNPs and their targets, especially those impacting important pathways, for future genetic investigations and crop improvement efforts in black pepper. The characterization of SNPs in genes related to secondary metabolism and alkaloid biosynthesis highlights their potential for targeted breeding aimed at enhancing the yield, quality, and resilience of this economically important crop in diverse environmental conditions.

Genomic selection, gene editing, and reproductive biotechnology: a triad for the improvement of native buffalo breeds in a developing country perspective like Pakistan

Pakistan is the 2nd largest country in buffalo population in the world. The current population of buffalo in Pakistan is 45.0 million heads whereas the current world buffalo population is 200 million heads. Pakistan is home to one of the best buffalo breeds in the world i.e., Nili, Ravi, Nili-Ravi, Kundi, and Azi Khaili. Moreover, Pakistan is ranked 2nd largest buffalo-milk-producing country in the world. Keeping in consideration, the tremendous role and importance of buffalo, the current study aims to provide a comprehensive overview of the important genetic studies conducted up till now and the need to apply the latest genomic tools, gene editing, and reproductive biotechnologies for the improvement of these native buffalo breeds. The current research is limited to a few diversity studies, basic phylogenetics, evolution, and genetic characterization using only a few loci and phenotypic studies of limited productive traits. The current picture is gloomy as proper genetic characterization and diversity study of these breeds has never been made using reliable, accurate, and advanced genomic techniques. In a developing country like Pakistan where there is no comprehensive data collection coupled with scattered farming without any organized breeding system; genomic selection, gene editing, and application of advanced reproductive biotechnology techniques are the most promising techniques for rapid and sustainable development in the productive and reproductive potential of our Black Gold. Advancement in the methods of genotyping using commercially available SNP Chips at affordable prices along with improvements in reproductive biotechnology and genome editing techniques will provide the framework for the true genetic exploration and optimal utilization of precious native buffalo breeds potential. Conclusively, these techniques have great potential to revolutionize the world's buffalo population.

Genome-wide differentiation by geography not species in taxonomically complex eyebrights (Euphrasia)

Most studies investigating the genomic nature of species differences anticipate monophyletic species with genome-wide differentiation. However, this may not be the case at the earliest stages of speciation where reproductive isolation is weak and homogenizing gene flow blurs species boundaries. We investigate genomic differences between species in a postglacial radiation of eyebrights (Euphrasia), a taxonomically complex plant group with variation in ploidy and mating system. We use genotyping-by-sequencing and spatially aware clustering methods to investigate genetic structure across 378 populations from 18 British and Irish Euphrasia species. We find only northern Scottish populations of the selfing heathland specialist E. micrantha demonstrate genome-wide divergence from other species. Instead of genetic clusters corresponding to species, all other clusters align with geographic regions, such as a genetic cluster on Shetland that includes 10 tetraploid species. Recent divergence and extensive gene flow between putative species are supported by a lack of species-specific single-nucleotide polymorphisms or clear outlier loci. We anticipate a similar lack of association between genomic clusters and species identities may occur in other recent postglacial groups. Where new species emerge this is associated with a transition in mating system or novel ecological preferences.

Association study of crude seed protein and fat concentration in a USDA pea diversity panel

Pea (Pisum sativum L.) is a key rotational crop and is increasingly important in the food processing sector for its protein. This study focused on identifying diverse high seed protein concentration (SPC) lines in pea plant genetic resources. Objectives included identifying high-protein pea lines, exploring genetic architecture across environments, pinpointing genes and metabolic pathways associated with high protein, and documenting information for single nucleotide polymorphism (SNP)-based marker-assisted selection. From 2019 to 2021, a 487-accession pea diversity panel, More protein, More pea, More profit, was evaluated in a randomized complete block design. DNA was extracted for genomic analysis via genotype-by-sequencing. Phenotypic analysis included protein and fat measurements in seeds and flower color. Genome-wide association study (GWAS) used multiple models, and the Pathways Association Study Tool was used for metabolic pathway analysis. Significant associations were found between SNPs and pea seed protein and fat concentration. Gene Psat7g216440 on chromosome 7, which targets proteins to cellular destinations, including seed storage proteins, was identified as associated with SPC. Genes Psat4g009200, Psat1g199800, Psat1g199960, and Psat1g033960, all involved in lipid metabolism, were associated with fat concentration. GWAS also identified genes annotated for storage proteins associated with fat concentration, indicating a complex relationship between fat and protein. Metabolic pathway analysis identified 20 pathways related to fat and seven to protein concentration, involving fatty acids, amino acid and protein metabolism, and the tricarboxylic acid cycle. These findings will assist in breeding of high-protein, diverse pea cultivars, and SNPs that can be converted to breeder-friendly molecular marker assays are identified for genes associated with high protein.

Molecular markers enhance substantially the distinctness of alfalfa varieties for registration and protection

Plant varieties must satisfy distinctness, uniformity, and stability (DUS) requirements for registration. Morphophysiological trait-based distinctness may be challenging for cultivars of major perennial forages. Our study focused on alfalfa (Medicago sativa L. subsp. sativa) with the aims of (a) comparing morphophysiological distinctness with molecular distinctness based on genotyping-by-sequencing (GBS) or the alfalfa DArTag panel, envisaging different statistical criteria for molecular distinctness, and (b) assessing the consistency of morphophysiological and molecular cultivar diversity. The 18 most grown Italian varieties were jointly reevaluated morphophysiologically and were characterized molecularly using three bulked DNA samples of 200 independent genotypes per cultivar. Morphophysiological distinctness was limited by correlations between traits and resulted in 39 non-distinct cultivars in 153 paired comparisons and three cultivars distinct from any other. Best configurations for molecular distinctness featured about 10-fold more polymorphic markers and 10-fold lower average read depth per marker for GBS compared to DArTag. DArTag markers allowed for somewhat better variety distinction than GBS. They reduced to 11 the non-distinct cultivars in paired comparisons and increased to 11 the completely distinct cultivars, based on a principal components analysis of allele frequencies followed by analyses of variance on cultivar principal component scores. This criterion achieved greater variety distinctness than cluster analysis with bootstrap values, discriminant analysis, or analysis of molecular variance. Morphophysiologically distinct cultivars were generally distinct molecularly, but not the reverse. Mantel's test revealed a modest consistency across morphophysiological and DArTag (r = 0.39) or GBS-based (r = 0.46) measures of cultivar Euclidean distance. Our results and other considerations strongly encourage the adoption of molecular distinctness for alfalfa DUS.