Genome-wide Markers Research Articles

Genetic diversity of the Chagas vector Triatoma dimidiata s.l. (Hemiptera: Reduviidae) across geographic scales in a top-priority area for control.

Population genetic structure of arthropod disease vectors provides important information on vector movement and climate or other environmental variables that influence their distribution. This information is critical for data-driven vector control. In the first comprehensive study of the genetic structure of T. dimidiata s.l. (Latreille, 1811) we focus on an area of active transmission designated as a top priority for control. We examined a high number of specimens across a broad geographic area along the border of Guatemala and El Salvador including multiple spatial scales using a high number of genome-wide markers. Measuring admixture, pairwise genetic differentiation, and relatedness, we estimated the specimens represented three genetic clusters. We found evidence of movement (migration/gene flow) across all spatial scales with more admixture among locations in El Salvador than in Guatemala. Although there was significant isolation by distance, the 2 close villages in Guatemala showed either the most or least genetic variation indicating an additional role of environmental variables. Further, we found that social factors may be influencing the genetic structure. We demonstrated the power of genomic studies with a large number of specimens across a broad geographic area. The results suggest that for effective vector control movement must be considered on multiple spatial scales along with its contributing factors.

Enhancing Across-Population Genomic Prediction for Maize Hybrids.

In crop breeding, genomic selection (GS) serves as a powerful tool for predicting unknown phenotypes by using genome-wide markers, aimed at enhancing genetic gain for quantitative traits. However, in practical applications of GS, predictions are not always made within populations or for individuals that are genetically similar to the training population. Therefore, exploring possibilities and effective strategies for across-population prediction becomes an attractive avenue for applying GS technology in breeding practices. In this study, we used an existing maize population of 5820 hybrids as the training population to predict another population of 523 maize hybrids using the GBLUP and BayesB models. We evaluated the impact of optimizing the training population based on the genetic relationship between the training and breeding populations on the accuracy of across-population predictions. The results showed that the prediction accuracy improved to some extent with varying training population sizes. However, the optimal size of the training population differed for various traits. Additionally, we proposed a population structure-based across-population genomic prediction (PSAPGP) strategy, which integrates population structure as a fixed effect in the GS models. Principal component analysis, clustering, and Q-matrix analysis were used to assess the population structure. Notably, when the Q-matrix was used, the across-population prediction exhibited the best performance, with improvements ranging from 8 to 11% for ear weight, ear grain weight and plant height. This is a promising strategy for reducing phenotyping costs and enhancing maize hybrid breeding efficiency.

Genome-Wide Development and Characterization of Microsatellite Markers in the Great Web-Spinning Sawfly Acantholyda posticalis.

The great web-spinning sawfly Acantholyda posticalis is notorious for damaging Pinus forests across the Palearctic region. At present, uncertainties persist regarding its intraspecies variation and presumed subspecies. To use as tools for future studies, herein we developed genome-wide microsatellite markers for A. posticalis. Through searching, rigorous manual screening, and amplification trial, 56 microsatellite markers were obtained from the genome sequences. We characterized these markers across two populations from Shandong province (SD) and Heilongjiang province (HLJ) in China, and carried out cross-amplification in three related species. Out of the 56 markers tested, 10, 31, and 15 were categorized into high, moderate, and low polymorphic levels, respectively, based on their polymorphic information content (PIC) values. Meanwhile, 28, 19, and 4 microsatellite loci were successfully cross-amplified in Cephalcia yanqingensis, C. chuxiongica, and C. infumata, respectively, which could serve as potential molecular markers for their further studies. STRUCTURE and PCoA analyses revealed two distinct clusters corresponding to SD and HLJ, respectively, indicating a high resolution of these markers. Therefore，the 56 microsatellite markers identified here have the potential to serve as efficient tools for unraveling intraspecies variation and evolutionary history of A. posticalis.

Exploring reported population differences in Norway lobster (Nephrops norvegicus) in the Pomo Pits region of the Adriatic Sea using genome-wide markers.

The Norway lobster (Nephrops norvegicus) is one of the most important decapod crustacean seafood species in the Adriatic Sea. Previous research has identified significant differences in growth rates and maturation timing of Nephrops in the Pomo/Jabuka Pits area compared to other subpopulations in Adriatic fishing grounds. Here, we use 1,623 genome-wide single nucleotide polymorphisms (SNPs) to investigate whether the Pomo Pits subpopulation is genetically different from other sites in the Adriatic and neighbouring seas. We found no genetic differentiation among all sampled Adriatic sites, suggesting high gene flow between Pomo Pits Nephrops and those of surrounding areas. We also found genetic homogeneity between the Adriatic sites and single-site samples from the Aegean and Tyrrhenian Seas. However, we detected distinct genetic differentiation between all Mediterranean sites and an Atlantic site in western Scotland, which provides evidence for a phylogenetic break between the Atlantic and the Mediterranean. Our results indicate that Pomo Pits Nephrops are not genetically different from others sampled in the Adriatic and that key biological parameters in Pomo Pits Nephrops could be driven by spatial variation in fishing pressure and/or environmental factors rather than geographic isolation.

A Review on Balancing Genomic Selection Efforts for Allogamous Plant Breeding

Genomic selection (GS) represents a paradigm shift in allogamous plant breeding, leveraging genome-wide marker data to predict the genetic potential of breeding candidates with unprecedented accuracy. This comprehensive review explores the evolution, principles, and applications of GS, highlighting its transformative impact on breeding efficiency and crop improvement. GS uses dense SNP markers to capture the genetic architecture of complex traits, surpassing traditional marker-assisted selection in predictive power. The integration of GS in breeding programs for crops like maize and perennial ryegrass has demonstrated significant gains in traits such as yield, disease resistance, and stress tolerance. Despite its advantages, GS faces challenges including high genotyping costs, the need for large training populations, and the complexity of genetic architectures. Economic constraints and ethical concerns about genetic diversity and data access also pose barriers. Emerging technologies such as AI, machine learning, high-throughput phenotyping, and genome editing hold promise for enhancing GS's accuracy and efficiency. Future strategies should focus on optimizing resource allocation, integrating GS with conventional breeding methods, and fostering collaborative efforts for data sharing and capacity building. The long-term impact of GS is profound, potentially accelerating breeding cycles, enhancing genetic diversity, and developing climate-resilient crops. Collaborative initiatives and open-access genomic resources will be crucial in overcoming current limitations and ensuring that GS benefits global agriculture. As GS continues to evolve, it promises to drive sustainable agricultural practices and improve food security, meeting the challenges posed by climate change and a growing global population. This review underscores the critical role of GS in modern plant breeding and its potential to revolutionize crop improvement.

Under the name of “Lua”: revisiting genetic heterogeneity and population ancestry of Austroasiatic speakers in northern Thailand through genomic analysis

BackgroundAustroasiatic (AA)-speaking populations in northern Thailand are of significant interest due to their status as indigenous descendants and their location at the crossroads of AA prehistoric distribution across Southern China, the Indian Subcontinent, and Mainland Southeast Asia. However, the complexity of ethnic identification can result in inaccuracies regarding the origin and migration history of these populations. To address this, we have conducted a genome-wide SNP analysis of 89 individuals from two Lavue and three Lwa-endonym populations. We then combined our outcomes with previously published data to elucidate the genetic diversity and clustering of AA groups in northern Thailand.ResultsOur findings align with existing linguistic classifications, revealing different genetic compositions among the three branches of the Mon-Khmer subfamily within the AA family: Monic, Khmuic, and Palaungic. Although the term “Lua” ethnicity is confusingly used to identify ethnic groups belonging to both Khmuic and Palaungic branches, our genomic data indicate that the Khmuic-speaking Lua living on the eastern side of the region are relatively distant from the Palaungic-speaking Lavue and Lwa populations living on the western side. The Lavue populations, primarily inhabiting mountainous areas, exhibit a genetic makeup unique to the AA family, with a close genetic relationship to the Karenic subgroup of the Sino-Tibetan language family. Conversely, the Lwa and Blang populations, residing in lowland river valleys, display genetic signatures resulting from admixture with Tai-Kadai-speaking ethnic groups.ConclusionUtilizing genome-wide SNP markers, our findings indicate genetic heterogeneity among the Lua, Lavue, and Lwa ethnic groups. The intricate interplay of genetics, cultural heritage, and historical influences has shaped these ethnic communities. Our study underscores the importance of accurate ethnic classifications, emphasizing the use of self-identified endonyms, names created and used by the ethnic groups themselves. This approach respects the AA communities in northern Thailand and acknowledges their significant contributions to advancing our understanding of genetic anthropology.

Towards the understanding of genetic and morphological variations of a highly abundant seaweed-associated marine invertebrate

Unraveling the patterns of genetic structure and demographic history of marine species, as well as the factors that shape their genetic variations, is fundamental for informing conservation strategies for species and their environments. In this work, we investigate the current population structure and historical demographic patterns of the conspicuous seaweed-associated amphipod Hyale niger at a fine spatial scale in the subtropical SW Atlantic coast, in Brazil, by using both genome-wide and mitochondrial DNA markers. We also investigate how geographic distance, current oceanographic conditions, and variations in a key morphological trait contribute to the genetic variability of the amphipod. We observed an evident population genetic structure, even at a fine spatial scale, although genetic differentiation was lower than our expectations for a benthic direct brooder. Demographic history inferences were consistent across populations and showed two major demographic expansions on interglacial periods during the late Pleiostocene, before and after the last glacial maximum. We also demonstrated that isolation-by-environment (IBE) was the main driver of genetic differentiation, although we could not separate it from the effects of isolation-by-distance (IBD). Among environmental factors, nutrient concentrations in seawater were most relevant for explaining genetic structure. In addition, our data suggest that morphological variation in gnathopod 2 structure of males were not genetic-related and were probably plastic as a response to variations in macroalgae frond size. Our study reinforces the importance of using multiple molecular markers and analytical approaches to unveil patterns and processes generating genetic variation in natural populations.

Analysis of genetic diversity and genetic structure of indigenous chicken populations in Guizhou province based on genome-wide single nucleotide polymorphism markers

Guizhou province in China is rich in indigenous chicken breeds, playing an essential role in the genetic improvement of modern chickens. Genetic diversity has decreased in recent decades due to accelerated breeding processes and changing conservation priorities. To determine the genetic diversity and population structure of Guizhou indigenous chicken breeds, we used 55K genotyping arrays to conduct population genetic analysis on 233 individuals from 8 Guizhou indigenous breeds and 263 individuals from 9 Guizhou indigenous chicken populations. We evaluated the genetic diversity parameter (heterozygosity, proportion of polymorphic markers, and nucleotide diversity), linkage disequilibrium (LD), population structure, and genetic differentiation (FST and genetics distance). Genetic diversity results indicated that the genetic diversity of chicken breeds in Guizhou province is relatively affluent. Among Guizhou breeds, Baiyi black-bone and Guizhou yellow chicken displayed the lowest genetic diversity, as the 2 breeds exhibit lower PN and heterozygosity, the extent of linkage disequilibrium is higher. According to the LD pattern, Guizhou indigenous breeds can be divided into 3 categories. Population structure analysis showed a certain degree of genetic differentiation among local chickens in Guizhou. We argue that Chishui black-bone and Puan black-bone chickens are 2 different geographical regional groups of the same breed. In principal component analysis, individuals from the 2 groups clustered together, and the phylogenetic tree results showed that the 2 groups clustered together to form a branch independent of other breeds, and they displayed an identical pattern of ancestral lineage composition. The research results will provide a reference for protecting local chicken genetic resources in Guizhou Province and promote the protection and utilization of genetic resources.

Integrating targeted genetic markers to genotyping-by-sequencing for an ultimate genotyping tool.

New selection methods, using trait-specific markers (marker-assisted selection (MAS)) and/or genome-wide markers (genomic selection (GS)), are becoming increasingly widespread in breeding programs. This new era requires innovative and cost-efficient solutions for genotyping. Reduction in sequencing cost has enhanced the use of high-throughput low-cost genotyping methods such as genotyping-by-sequencing (GBS) for genome-wide single-nucleotide polymorphism (SNP) profiling in large breeding populations. However, the major weakness of GBS methodologies is their inability to genotype targeted markers. Conversely, targeted methods, such as amplicon sequencing (AmpSeq), often face cost constraints, hindering genome-wide genotyping across a large cohort. Although GBS and AmpSeq data can be generated from the same sample, an efficient method to achieve this is lacking. In this study, we present the Genome-wide & Targeted Amplicon (GTA) genotyping platform, an innovative way to integrate multiplex targeted amplicons into the GBS library preparation to provide an all-in-one cost-effective genotyping solution to breeders and research communities. Custom primers were designed to target 23 and 36 high-value markers associated with key agronomical traits in soybean and barley, respectively. The resulting multiplex amplicons were compatible with the GBS library preparation enabling both GBS and targeted genotyping data to be produced efficiently and cost-effectively. To facilitate data analysis, we have introduced Fast-GBS.v3, a user-friendly bioinformatic pipeline that generates comprehensive outputs from data obtained following sequencing of GTA libraries. This high-throughput low-cost approach will greatly facilitate the application of DNA markers as it provides required markers for both MAS and GS in a single assay.

EZH2 specifically regulates ISL1 during embryonic urinary tract formation

Isl1 has been described as an embryonic master control gene expressed in the pericloacal mesenchyme. Deletion of Isl1 from the genital mesenchyme in mice leads to an ectopic urethral opening and epispadias-like phenotype. Using genome wide association methods, we identified ISL1 as the key susceptibility gene for classic bladder exstrophy (CBE), comprising epispadias and exstrophy of the urinary bladder. The most significant marker (rs6874700) identified in our recent GWAS meta-analysis achieved a p value of 1.48 × 10− 24 within the ISL1 region. In silico analysis of rs6874700 and all other genome-wide significant markers in Linkage Disequilibrium (LD) with rs6874700 (D’ = 1.0; R2 > 0.90) revealed marker rs2303751 (p value 8.12 × 10− 20) as the marker with the highest regulatory effect predicted. Here, we describe a novel 1.2 kb intragenic promoter residing between 6.2 and 7.4 kb downstream of the ISL1 transcription starting site, which is located in the reverse DNA strand and harbors a binding site for EZH2 at the exact region of marker rs2303751. We show, that EZH2 silencing in HEK cells reduces ISL1 expression. We show that ezh2−/− knockout (KO) zebrafish larvae display tissues specificity of ISL1 regulation with reduced expression of Isl1 in the pronephric region of zebrafish larvae. In addition, a shorter and malformed nephric duct is observed in ezh2−/− ko zebrafish Tg(wt1ß:eGFP) reporter lines. Our study shows, that Ezh2 is a key regulator of Isl1 during urinary tract formation and suggests tissue specific ISL1 dysregulation as an underlying mechanism for CBE formation.

Characterization of fine geographic scale population genetics in sugar kelp (Saccharina latissima) using genome-wide markers

BackgroundKelps are not only ecologically important, being primary producers and habitat forming species, they also hold substantial economic potential. Expansion of the kelp cultivation industry raises the interest for genetic improvement of kelp for cultivation, as well as concerns about genetic introgression from cultivated to wild populations. Thus, increased understanding of population genetics in natural kelp populations is crucial. Genotyping-by-sequencing (GBS) is a powerful tool for studying population genetics. Here, using Saccharina latissima (sugar kelp) as our study species, we characterize the population genetics at a fine geographic scale, while also investigating the influence of marker type (biallelic SNPs versus multi-allelic short read-backed haplotypes) and minor allele count (MAC) thresholds on estimated population genetic metrics.ResultsWe examined 150 sporophytes from 10 locations within a small area in Mid-Norway. Employing GBS, we detected 20,710 bi-allelic SNPs and 42,264 haplotype alleles at 20,297 high quality GBS loci. We used both marker types as well as two MAC filtering thresholds (3 and 15) in the analyses. Overall, higher genetic diversity, more outbreeding and stronger substructure was estimated using haplotypes compared to SNPs, and with MAC 15 compared to MAC 3. The population displayed high genetic diversity (HE ranging from 0.18–0.37) and significant outbreeding (FIS ≤ − 0.076). Construction of a genomic relationship matrix, however, revealed a few close relatives within sampling locations. The connectivity between sampling locations was high (FST ≤ 0.09), but subtle, yet significant, genetic substructure was detected, even between sampling locations separated by less than 2 km. Isolation-by-distance was significant and explained 15% of the genetic variation, while incorporation of predicted currents in an “isolation-by-oceanography” model explained a larger proportion (~ 27%).ConclusionThe studied population is diverse, significantly outbred and exhibits high connectivity, partly due to local currents. The use of genome-wide markers combined with permutation testing provides high statistical power to detect subtle population substructure and inbreeding or outbreeding. Short haplotypes extracted from GBS data and removal of rare alleles enhances the resolution. Careful consideration of marker type and filtering thresholds is crucial when comparing independent studies, as they profoundly influence numerical estimates of population genetic metrics.

Genome-wide association study and KASP marker development for starch quality traits in wheat.

Starch is the main component of wheat (Triticum aestivum L.) flour, and its quality directly affects the processing quality of the final product. To investigate the genetic basis of starch, this study assessed the starch quality traits of 341 winter wheat varieties/lines grown in Emin and Qitai during the years 2019-2020 and 2020-2021. A genome-wide association study was conducted with the genotype data obtained from wheat 40K breeding chips using the mixed linear model. Wheat starch quality traits exhibited coefficients of variation ranging from 1.43% to 23.66% and broad-sense heritabilities between 0.37 and 0.87. All traits followed an approximately normal distribution, except for T. There were highly significant correlations among starch quality traits, with the strongest correlation observed between final viscosity (FV) and trough viscosity (TV) (r=0.748), followed by peak viscosity and breakdown (BD) (r=0.679). Thirty-four single-nucleotide polymorphism markers significantly and stably associated with starch quality traits were identified, clustering in 31 genetic loci. These included one locus for TV, six loci for BD, three loci for FV, two loci for peak time (PT), 12 loci for T, five loci for falling number, and two loci for damaged starch. One PT-related block of 410kb was identified in the region of 596 Mb on chromosome 5A, where significant phenotypic differences were observed between different haplotypes. One Kompetitive allele-specific PCR (KASP) marker for T was developed on chromosome 7B, and two KASP markers for BD were developed on chromosome 7A. Four candidate genes possibly affecting BD during grain development were identified on chromosome 7A, including TraesCS7A02G225100.1, TraesCS7A02G225900.1, TraesCS7A02G226400.1, and TraesCS7A02G257100.1. The results have significant implications for utilizing marker-assisted selection in breeding to improve wheat starch quality.

Potential genetic gains from targeted recombination versus recurrent selection for maize yield and moisture

AbstractRecurrent selection is a proven method and targeted recombination is a potential method for achieving genetic gain. Our objectives were to determine the (1) equivalency in predicted gains between cycles of recurrent selection and targeted recombination in maize (Zea mays L.), (2) correspondence between targeted‐recombination positions when gains from nontargeted chromosomes are considered versus ignored, and (3) trade‐offs in predicted gains for yield and moisture in targeted recombination. From genomewide marker effects for 2911 single nucleotide polymorphism loci in 270 biparental populations, we obtained predicted gains from fixed numbers of targeted recombinations and compared these gains to the genotypic‐value distributions of doubled haploids obtained from different cycles of simulated recurrent selection. On average, it took three cycles of single‐trait recurrent selection to obtain at least a few doubled haploid lines with the same performance achieved with nine or 10 targeted recombinations in Cycle 0. Results indicated that when targeting recombinations across the genome, gains from segregation on nontargeted chromosomes do not need to be considered. Predicted increases in yield were associated with increases in moisture. Given the logistics of pyramiding targeted recombinations and the lack of mature technologies for routine targeted recombination, recurrent selection is currently the preferred approach for accumulating favorable recombinations.

Urbanization-associated range expansion genetically homogenizes a butterfly species

Human-induced environmental change and globalization facilitate biological invasions, which can lead to the displacement of native species by non-native ones.1,2,3,4 Analogously, biodiversity loss may occur within species when habitat modifications facilitate the expansion of a specific population's range, leading to genetic admixture with native local populations. We demonstrate such intraspecific loss in population-level diversity in the Southern Small White (Pieris mannii), an originally sedentary butterfly5 that recently expanded its range across Central Europe due to urbanization.6,7,8 Using genome-wide markers from historical museum specimens and contemporary samples, we identify a distinct population initiating this expansion and reveal the genetic homogenization of native local populations by admixture with the expansive one. Our study illustrates how human-made environmental change can simultaneously benefit a species by permitting range expansion and drive cryptic biodiversity loss through the genetic homogenization of conspecific populations.

Identification and Validation of Intra-Species Transferability of Genome-Wide Functional SSR Markers in Glycine max

Identification and Validation of Intra-Species Transferability of Genome-Wide Functional SSR Markers in Glycine max

DNA Methylation signatures underpinning blood neutrophil to lymphocyte ratio during first week of human life

Understanding of newborn immune ontogeny in the first week of life will enable age-appropriate strategies for safeguarding vulnerable newborns against infectious diseases. Here we conducted an observational study exploring the immunological profile of infants longitudinally throughout their first week of life. Our Expanded Program on Immunization - Human Immunology Project Consortium (EPIC-HIPC) studies the epigenetic regulation of systemic immunity using small volumes of peripheral blood samples collected from West African neonates on days of life (DOL) 0, 1, 3, and 7. Genome-wide DNA methylation and single nucleotide polymorphism markers are examined alongside matched transcriptomic and flow cytometric data. Integrative analysis reveals that a core network of transcription factors mediates dynamic shifts in neutrophil-to-lymphocyte ratios (NLR), which are underpinned by cell-type specific methylation patterns in the two cell types. Genetic variants are associated with lower NLRs at birth, and healthy newborns with lower NLRs at birth are more likely to subsequently develop sepsis. These findings provide valuable insights into the early-life determinants of immune system development.

Dense SNP-based analyses complement forensic anthropology biogeographical ancestry assessments

Identification of unidentified human remains (UHRs) is crucial yet challenging, especially with traditional forensic techniques. Forensic anthropological examinations can yield ancestry estimations; however, the utility of these estimates is limited by the data points that can be collected from partial remains, complexities of admixture, and variation of phenotypic expression due to environmental effects. While it is generally known that anthropological estimates can be imprecise, the performance of these methods has not been studied at scale. Genome-wide SNP testing is an orthogonal approach for estimating ancestry and offers a unique opportunity to measure the magnitude of anthropological ancestry misattribution. Genomic ancestry inference leverages principal component analysis (PCA) and model-based clustering approaches. This study compares anthropologically determined ancestry with those estimated using genome-wide SNP markers. A dataset of 611 UHR samples with publicly available ancestry assessments from National Missing and Unidentified Persons System (NamUs) was analyzed. The genetic ancestry approach, validated against reference population samples, offers robust ancestry calculations for major population groups. Inconsistency between anthropological and genomic ancestry assignments were observed, particularly for admixed populations. Although forensic anthropological examinations remain valuable, their limitations emphasize the need for refinement and enhancement through the augmentation of SNP-based analyses. Further validation studies are crucial to define the uncertainty associated with both anthropological and genome-based ancestry estimates to resolve cases and aid law enforcement investigations. Additionally, current policy and practices for reporting ancestry for UHRs should be revisited to reduce potential misinformation.

Multi-Population Analysis for Leaf and Neck Blast Reveals Novel Source of Neck Blast Resistance in Rice.

Rice blast is one of the most devastating biotic stresses that limits rice productivity. The North Eastern Hill (NEH) region of India is considered to be one of the primary centres of diversity for both rice and pathotypes of Magnaporthe grisea. Therefore, the present study was carried out to elucidate the genetic basis of leaf and neck blast resistance under Meghalaya conditions. A set of 80 diverse genotypes (natural population) and 2 F2 populations involving resistant parent, a wildtype landrace, LR 5 (Lal Jangali) and susceptible genotypes Sambha Mahsuri SUB 1 (SMS) and LR 26 (Chakhao Poireiton) were used for association analysis of reported major gene-linked markers with leaf and neck blast resistance to identify major effective genes under local conditions. Genotyping using twenty-five gene-specific markers across diverse genotypes and F2 progenies revealed genes Pi5 and Pi54 to be associated with leaf blast resistance in all three populations. Genes Pib and qPbm showed an association with neck blast resistance in both natural and LR 5 × SMS populations. Additionally, a set of 184 genome-wide polymorphic markers (SSRs and SNPs), when applied to F2-resistant and F2-susceptible DNA bulks derived from LR 5 × LR 26, suggested that Pi20(t) on chromosome 12 is one of the major genes imparting disease resistance. Markers snpOS318, RM1337 and RM7102 and RM247 and snpOS316 were associated with leaf blast and neck blast resistance, respectively. The genotypes, markers and genes will help in marker-assisted selection and development of varieties with durable resistance.

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

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

QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification

QTL-seq is a powerful method that integrates whole-genome sequencing (WGS) with bulk-segregant analysis to rapidly and reliably identify quantitative trait loci (QTLs) associated with specific traits. This approach significantly advances traditional QTL mapping by eliminating the need for genome wide DNA markers such as SSR, RFLP, and INDELs, which are typically used in linkage-based QTL mapping. Instead, QTL-seq leverages WGS to detect all genetic variations such as SNPs, Indels, and Structural Variants across the entire genome, providing a comprehensive resource for marker development in marker-assisted selection. The QTL-seq process begins with the creation of genetically diverse mapping populations, such as F2 or RILs, followed by detailed phenotypic characterization. DNA from plants exhibiting similar phenotypes is pooled into bulk groups and sequenced, allowing for cost-effective and efficient QTL identification. Identified QTLs can be further validated through fine mapping using recombinant screenings and progeny testing, leading to the identification of candidate genes associated with traits of interest. In this study, we outline a user-friendly QTL-seq pipeline, from sequencing to data visualization, using the methodology and data provided by Takagi et al., 2013, to demonstrate its practical application. While the manuscript primarily focuses on describing the pipeline, we also conducted a case study analysis with real data to showcase its effectiveness. Our work contributes to the broader understanding of QTL-seq applications and offers practical recommendations for optimizing this method in future breeding programs.