Search

BACKGROUND: Traditional recombinant inbred lines (RILs) are generated from repeated self-fertilization or brother-sister mating from the F1 hybrid of two inbred parents. Compared with the F2 population, RILs cumulate more crossovers between loci and thus increase the number of recombinants, resulting in an increased resolution of genetic mapping. Since they are inbred to the isogenic stage, another consequence of the heterozygosity reduction is the increased genetic variance and thus the increased power of QTL detection. Self-fertilization is the primary form of developing RILs in plants. Brother-sister mating is another way to develop RILs but in small laboratory animals. To ensure that the RILs have at least 98% of homozygosity, we need about seven generations of self-fertilization or 20 generations of brother-sister mating. Prior to homozygosity, these lines are called pre-recombinant inbred lines (PRERIL). Phenotypic values of traits in PRERILs are often collected but not used in QTL mapping. To perform QTL mapping in PRERILs, we need the recombination fraction between two markers at generation t for t

Delay discounting refers to the behavioral tendency to devalue rewards as a function of their delay in receipt. Heightened delay discounting has been associated with substance use disorders and multiple co-occurring psychopathologies. Human and animal genetic studies have established that delay discounting is heritable, but only a few associated genes have been identified. We aimed to identify novel genetic loci associated with delay discounting through a genome-wide association study (GWAS) using Heterogeneous Stock (HS) rats, a genetically diverse outbred population derived from eight inbred founder strains. We assessed delay discounting in 650 male and female HS rats using an adjusting amount procedure in which rats chose between smaller immediate sucrose rewards or a larger reward at various delays. Preference switch points were calculated and both exponential and hyperbolic functions were fitted to these indifference points. Area under the curve (AUC) and the discounting parameter k of both functions were used as delay discounting measures. GWAS for AUC, exponential k, and one indifference point identified significant loci on chromosomes 20 and 14. The gene Slc35f1, which encodes a member of the solute carrier family, was the sole gene within the chromosome 20 locus. That locus also contained an eQTL for Slc35f1, suggesting that heritable differences in the expression might be responsible for the association with behavior. Adgrl3, which encodes a latrophilin subfamily G-protein coupled receptor, was the sole gene within the chromosome 14 locus. These findings implicate novel genes in delay discounting and highlight the need for further exploration.

Genome-wide association studies (GWAS) implicate broad genomic loci containing clusters of highly correlated genetic variants. Finemapping techniques can select and prioritize variants within each GWAS locus which are more likely to have a functional influence on the trait. Here, we present a novel method, Finemap-MiXeR, for finemapping causal variants from GWAS summary statistics, controlling for correlation among variants due to linkage disequilibrium. Our method is based on a variational Bayesian approach and direct optimization of the Evidence Lower Bound (ELBO) of the likelihood function derived from the MiXeR model. After obtaining the analytical expression for ELBOs gradient, we apply Adaptive Moment Estimation (ADAM) algorithm for optimization, allowing us to obtain the posterior causal probability of each variant. Using these posterior causal probabilities, we validated Finemap-MiXeR across a wide range of scenarios using both synthetic data, and real data on height from the UK Biobank. Comparison of Finemap-MiXeR with two existing methods, FINEMAP and SuSiE RSS, demonstrated similar or improved accuracy. Furthermore, our method is computationally efficient in several aspects. For example, unlike many other methods in the literature, its computational complexity does not increase with the number of true causal variants in a locus and it does not require any matrix inversion operation. The mathematical framework of Finemap-MiXeR is flexible and may also be applied to other problems including cross-trait and cross-ancestry finemapping.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

Genetic dissection of a QTL from wild emmer wheat, QGpc.huj.uh-5B.2, introgressed into bread wheat, identified candidate genes associated with tolerance to nitrogen deficiency, and potentially useful for improving nitrogen-use efficiency. Nitrogen (N) is an important macronutrient critical to wheat growth and development; its deficiency is one of the main factors causing reductions in grain yield and quality. N availability is significantly affected by drought or flooding, that are dependent on additional factors including soil type or duration and severity of stress. In a previous study, we identified a high grain protein content QTL (QGpc.huj.uh-5B.2) derived from the 5B chromosome of wild emmer wheat, that showed a higher proportion of explained variation under water-stress conditions. We hypothesized that this QTL is associated with tolerance to N deficiency as a possible mechanism underlying the higher effect under stress. To validate this hypothesis, we introgressed the QTL into the elite bread wheat var. Ruta, and showed that under N-deficient field conditions the introgression IL99 had a 33% increase in GPC (p

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p

Populations may adapt to similar environments via parallel or non-parallel genetic changes, but the frequency of these alternative mechanisms and underlying contributing factors are still poorly understood outside model systems. We used QTL mapping to investigate the genetic basis of highly divergent craniofacial traits between the scale-eater (Cyprinodon desquamator) and molluscivore (C. brontotheroides) pupfish adapting to two different hypersaline lake environments on San Salvador Island, Bahamas. We lab-reared F2 scale-eater x molluscivore intercrosses from two different lake populations, estimated linkage maps, scanned for significant QTL for 29 skeletal and craniofacial traits, female mate preference, and sex. We compared the location of QTL between lakes to quantify parallel and non-parallel genetic changes. We detected significant QTL for six craniofacial traits in at least one lake. However, nearly all shared QTL loci were associated with a different craniofacial trait within each lake. Therefore, our estimate of parallel evolution of craniofacial genetic architecture could range from one out of six identical trait QTL (low parallelism) to five out of six integrated trait QTL (high parallelism). We suggest that pleiotropy and trait integration can affect estimates of parallel evolution, particularly within rapid radiations. We also observed increased adaptive introgression in shared QTL regions, suggesting that gene flow contributed to parallel evolution. Overall, our results suggest that the same genomic regions may contribute to parallel adaptation across integrated suites of craniofacial traits, rather than specific traits, and highlight the need for a more expansive definition of parallel evolution.

Cowpea is a highly drought-adapted leguminous crop with great promise for improving agricultural sustainability and food security. Here, we report analyses derived from array-based genotyping of 2,021 accessions constituting a core subset of the worlds largest cowpea collection, held at the International Institute of Tropical Agriculture (IITA) in Ibadan, Nigeria. We used this dataset to examine genetic variation and population structure in worldwide cowpea. We confirm that the primary pattern of population structure is two geographically defined subpopulations originating in West and East Africa, respectively, and that population structure is associated with shifts in phenotypic distribution. Furthermore, we establish the cowpea core collection as a resource for genome-wide association studies by mapping the genetic basis of several phenotypes, with a focus on seed coat pigmentation patterning and color. We anticipate that the genotyped IITA Cowpea Core Collection will serve as a powerful tool for mapping complex traits, facilitating the acceleration of breeding programs to enhance the resilience of this crop in the face of rapid global climate change.

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

Knowing the genes involved in quantitative traits provides an entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six quantitative trait loci (QTLs) by quantitative complementation, and identified six genes. Four genes, Lamp, Ptprd, Nptx2, and Sh3gl, have known roles in synapse function; the fifth, Psip1, was not previously implicated in behavior; and the sixth is a long non-coding RNA, 4933413L06Rik, of unknown function. Variation in transcriptome and epigenetic modalities occurred preferentially in excitatory neurons, suggesting that genetic variation is more permissible in excitatory than inhibitory neuronal circuits. Our results relieve a bottleneck in using genetic mapping of QTLs to uncover biology underlying behavior and prompt a reconsideration of expected relationships between genetic and functional variation.

Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)-an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (β-carotene, β-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside β-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.

Endurance exercise training is known to reduce risk for a range of complex diseases. However, the molecular basis of this effect has been challenging to study and largely restricted to analyses of either few or easily biopsied tissues. Extensive transcriptome data collected across 15 tissues during exercise training in rats as part of the Molecular Transducers of Physical Activity Consortium has provided a unique opportunity to clarify how exercise can affect tissue-specific gene expression and further suggest how exercise adaptation may impact complex disease-associated genes. To build this map, we integrate this multi-tissue atlas of gene expression changes with gene-disease targets, genetic regulation of expression, and trait relationship data in humans. Consensus from multiple approaches prioritizes specific tissues and genes where endurance exercise impacts disease-relevant gene expression. Specifically, we identify a total of 5523 trait-tissue-gene triplets to serve as a valuable starting point for future investigations [Exercise; Transcription; Human Phenotypic Variation].

How human genetic variation contributes to vaccine effectiveness in infants is unclear, and data are limited on these relationships in populations with African ancestries. We undertook genetic analyses of vaccine antibody responses in infants from Uganda (n = 1391), Burkina Faso (n = 353) and South Africa (n = 755), identifying associations between human leukocyte antigen (HLA) and antibody response for five of eight tested antigens spanning pertussis, diphtheria and hepatitis B vaccines. In addition, through HLA typing 1,702 individuals from 11 populations of African ancestry derived predominantly from the 1000 Genomes Project, we constructed an imputation resource, fine-mapping class II HLA-DR and DQ associations explaining up to 10% of antibody response variance in our infant cohorts. We observed differences in the genetic architecture of pertussis antibody response between the cohorts with African ancestries and an independent cohort with European ancestry, but found no in silico evidence of differences in HLA peptide binding affinity or breadth. Using immune cell expression quantitative trait loci datasets derived from African-ancestry samples from the 1000 Genomes Project, we found evidence of differential HLA-DRB1 expression correlating with inferred protection from pertussis following vaccination. This work suggests that HLA-DRB1 expression may play a role in vaccine response and should be considered alongside peptide selection to improve vaccine design.

High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci (QTLs) using QTL mapping. However, most require population structures that fit the models available and a reference genome. Instead, high-throughput short-read sequencing can be combined with BSA of k-mers (BSA-k-mer) to map traits that appear refractory to standard approaches. This method can be applied to any organism and is particularly useful for species with genomes diverged from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and potentially polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we apply the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. Using a mixture of F1 and F2 individuals from a cross between 2 highly heterozygous parents, candidate sequences were identified for each trait using the BSA-k-mer approach. Using parental reads, we were able to determine the parental origin of the loci. Finally, we mapped the identified k-mers to a closely related potato genome to validate the method and determine the genomic loci underlying these sequences. The location identified for the seed spot matches with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both loci are relevant in future breeding toward true seeds in potato.

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1-3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4-7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA-chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an older transcriptomic signature and Alzheimers disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR

Cowpea, Vigna unguiculata L. Walp., is a diploid warm-season legume of critical importance as both food and fodder in sub-Saharan Africa. This species is also grown in Northern Africa, Europe, Latin America, North America, and East to Southeast Asia. To capture the genomic diversity of domesticates of this important legume, de novo genome assemblies were produced for representatives of six subpopulations of cultivated cowpea identified previously from genotyping of several hundred diverse accessions. In the most complete assembly (IT97K-499-35), 26,026 core and 4963 noncore genes were identified, with 35,436 pan genes when considering all seven accessions. GO terms associated with response to stress and defense response were highly enriched among the noncore genes, while core genes were enriched in terms related to transcription factor activity, and transport and metabolic processes. Over 5 million single nucleotide polymorphisms (SNPs) relative to each assembly and over 40 structural variants >1 Mb in size were identified by comparing genomes. Vu10 was the chromosome with the highest frequency of SNPs, and Vu04 had the most structural variants. Noncore genes harbor a larger proportion of potentially disruptive variants than core genes, including missense, stop gain, and frameshift mutations; this suggests that noncore genes substantially contribute to diversity within domesticated cowpea.

Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016-2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma-optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6-6.9%) and stachyose (2.3-8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4-0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.

Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal mechanisms of the link between genetic variation and disease risk is unknown. Expression quantitative trait locus (eQTL) analysis of bulk tissue is a common approach used for deciphering underlying mechanisms, although this can obscure cell-type-specific signals and thus mask trait-relevant mechanisms. Although single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell-type proportions and cell-type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-seq from 1,730 samples derived from whole blood in a cohort ascertained from individuals with BP and SCZ, this study estimated cell-type proportions and their relation with disease status and medication. For each cell type, we found between 2,875 and 4,629 eGenes (genes with an associated eQTL), including 1,211 that are not found on the basis of bulk expression alone. We performed a colocalization test between cell-type eQTLs and various traits and identified hundreds of associations that occur between cell-type eQTLs and GWASs but that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on the regulation of cell-type expression loci and found examples of genes that are differentially regulated according to lithium use. Our study suggests that applying computational methods to large bulk RNA-seq datasets of non-brain tissue can identify disease-relevant, cell-type-specific biology of psychiatric disorders and psychiatric medication.

BackgroundThe accurate identification of the functional elements in the bovine genome is a fundamental requirement for high-quality analysis of data informing both genome biology and genomic selection. Functional annotation of the bovine genome was performed to identify a more complete catalog of transcript isoforms across bovine tissues.ResultsA total of 160,820 unique transcripts (50% protein coding) representing 34,882 unique genes (60% protein coding) were identified across tissues. Among them, 118,563 transcripts (73% of the total) were structurally validated by independent datasets (PacBio isoform sequencing data, Oxford Nanopore Technologies sequencing data, de novo assembled transcripts from RNA sequencing data) and comparison with Ensembl and NCBI gene sets. In addition, all transcripts were supported by extensive data from different technologies such as whole transcriptome termini site sequencing, RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression, chromatin immunoprecipitation sequencing, and assay for transposase-accessible chromatin using sequencing. A large proportion of identified transcripts (69%) were unannotated, of which 86% were produced by annotated genes and 14% by unannotated genes. A median of two 5' untranslated regions were expressed per gene. Around 50% of protein-coding genes in each tissue were bifunctional and transcribed both coding and noncoding isoforms. Furthermore, we identified 3,744 genes that functioned as noncoding genes in fetal tissues but as protein-coding genes in adult tissues. Our new bovine genome annotation extended more than 11,000 annotated gene borders compared to Ensembl or NCBI annotations. The resulting bovine transcriptome was integrated with publicly available quantitative trait loci data to study tissue-tissue interconnection involved in different traits and construct the first bovine trait similarity network.ConclusionsThese validated results show significant improvement over current bovine genome annotations.

Context. Researchers have been accumulating information concerning the locations of genes and quantitative trait loci (QTLs) in cultivated oat (Avena sativa L.) for more than 100 years. Aims. The aim of this work was to create an inventory of genes and QTLs found in cultivated hexaploid oat and produce tools to make this resource more useful. Methods. By using the positions of perfectly matched, single nucleotide polymorphism markers, each centimorgan (cM) location along the consensus map was assigned to a location on the OT3098 v2 physical map found on the GrainGenes database website (https://wheat.pw.usda.gov/jb/?data=/ggds/oat-ot3098v2-pepsico). This information was then used to assign physical locations to the genes and QTLs in the inventory, where possible. Key results. A table comparing the major genetic maps of hexaploid oats to each other, to the 2018 oat consensus map, and to physical chromosomes was produced. Genome browser tracks aligning the consensus map regions and the locations of the genes and QTLs to OT3098 v2 were added to GrainGenes. Conclusions. Many oat genes and QTLs identified using genetic mapping could be assigned positions on physical oat chromosomes. However, many of these assigned regions are quite long, owing to the presence of large areas of reduced recombination. Specific examples of identified patterns of recombination between the genetic and physical maps and validated gene and QTL locations are discussed. Implications. These resources will assist researchers performing comparative genetic and physical mapping in oat.

BackgroundGene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime.ResultsWe demonstrate the analyses using the tool are reproducible, up to 18 × faster using the GPU, and scale linearly with increasing methylation loci.ConclusionsTorch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg .

Safflower oil with high oleic is an important source of oil due to its oxidative stability and nutritional value as well as its industrial benefits. Identification of molecular markers associated with oil quality traits may aid in genotype selection in breeding efforts of safflower. To determine the genetic basis of seed oil, oleic acid, and linoleic acid content in safflower seeds, a recombinant inbred population was developed from a cross between Goldasht (low oleic line) and Mex 22–191 (high oleic line) by individual self-pollinated plants in each generation (from F2 to F9). Fatty acid components were detected by gas chromatography and subsequently analyzed by QTL analysis. The high variability in fatty acid composition was demonstrated and the first high-oleic safflower genotype was generated. A new linkage map with 69 AFLP and 45 ISSR polymorphic markers was made, covering 1472,441 cM of the safflower genome. A total of 63 individual QTLs and 238 epistatic QTLs, related to oil quality, were detected in 14 genomic regions. Some major QTLs with phenotypic variation greater than 10% were identified for the measured traits. These results demonstrate that major QTL may play an important role in increase the oleic acid of the genetic material used. Furthermore, the larger number of minor QTLs and epistatic QTLs, both of which have additive effects, indicates that the expression of these traits is also influenced by interactions between multiple genes. Our results provide additional genetic resources that can be used to precisely breed these traits in the future. [ABSTRACT FROM AUTHOR]

Body conformation traits are linked to the health, longevity, reproductivity, and production performance of cattle. These traits are also crucial for herd selection and developing new breeds. This study utilized pedigree information and phenotypic (1185 records) and genomic (The resequencing of 496 Xinjiang Brown cattle generated approximately 74.9 billion reads.) data of Xinjiang Brown cattle to estimate the genetic parameters, perform factor analysis, and conduct a genome-wide association study (GWAS) for these traits. Our results indicated that most traits exhibit moderate to high heritability. The principal factors, which explained 59.12% of the total variance, effectively represented body frame, muscularity, rump, feet and legs, and mammary system traits. Their heritability estimates range from 0.17 to 0.73, with genetic correlations ranging from −0.53 to 0.33. The GWAS identified 102 significant SNPs associated with 12 body conformation traits. A few of the SNPs were located near previously reported genes and quantitative trait loci (QTLs), while others were novel. The key candidate genes such as LCORL, NCAPG, and FAM184B were annotated within 500 Kb upstream and downstream of the significant SNPs. Therefore, factor analysis can be used to simplify multidimensional conformation traits into new variables, thus reducing the computational burden. The identified candidate genes from GWAS can be incorporated into the genomic selection of Xinjiang Brown cattle, enhancing the reliability of breeding programs. [ABSTRACT FROM AUTHOR]

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins [proximity extension-based (PEA) immunoassays] in a deeply-phenotyped mixed memory clinic cohort [ n = 502, mean age (standard deviation, SD) = 64.1 (8.7) years, 181 female (35.4%)], including patients with Alzheimer's disease (AD, n = 213), dementia with Lewy bodies (DLB, n = 50) and frontotemporal dementia (FTD, n = 93), and controls (n = 146). Validation was assessed in independent cohorts (n = 99 PEA platform, n = 198, mass reaction monitoring-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1 -CR2 (rs3818361, P = 1.65 × 10−8), ZCWPW1 -PILRB (rs1476679, P = 2.73 × 10−32), CTSH -CTSH (rs3784539, P = 2.88 × 10−24) and HESX1 -RETN (rs186108507, P = 8.39 × 10−8), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90 × 10−7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for FTD loci, either for the total sample as for analyses performed within FTD only. Protein QTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia. [ABSTRACT FROM AUTHOR]

Rice root system plays a crucial role in plant adaptation under adverse conditions, particularly drought stress. However, the regulatory gene networks that govern rice root development during stress exposure remain largely unexplored. In this study, we applied a QTL sequencing method to identify QTL/gene controlling the crown root development under Jasmonic acid simulation using the Bulk-segregant analysis. Two rice cultivars with contrasting phenotypes from the Vietnamese traditional rice collection were used as parent pairs for crossing. The single-seed descent method was employed to generate an F2 population of progenies. This F2/3 population was further segregated based on root count under JA stress. Pooled DNA from the two extreme groups in this population was sequenced, and SNP indexes across all loci in these pools were calculated. We detected a significant genomic region on chromosome 10, spanned from 20.39–20.50 Mb, where two rice RLKs were located, OsPUB54 and OsPUB58. Receptor-like kinases (RLKs) are pivotal in regulating various aspects of root development in plants, and the U-box E3 ubiquitination ligase class was generally known for its degradation of some protein complexes. Notably, OsPUB54 was strongly induced by JA treatment, suggesting its involvement in the degradation of the Aux/IAA protein complex, thereby influencing crown root initiation. Besides, the Eukaryotic translation initiation of factor 3 subunit L (eIF3l) and the Mitogen-activated protein kinase kinase kinase 37 (MAPKKK 37) proteins identified from SNPs with high score index which suggests their significant roles in the translation initiation process and cellular signaling pathways, respectively. This information suggests several clues of how these candidates are involved in modifying the rice root system under stress conditions. [ABSTRACT FROM AUTHOR]

Introduction: Owing to advances in high-throughput genome sequencing, QTLSeq mapping of salt tolerance traits is a major platform for identifying soil-salinity tolerance QTLs to accelerate marker-assisted selection for salt-tolerant rice varieties. We performed QTL-BSA-Seq in the seedling stage of rice from a genetic cross of the extreme salt-sensitive variety, IR29, and "Jao Khao" (JK), a Thai salt-tolerant variety. Methods: A total of 462 F2 progeny grown in soil and treated with 160 mM NaCl were used as the QTL mapping population. Two high- and low-bulk sets, based on cell membrane stability (CMS) and tiller number at the recovery stage (TN), were equally sampled. The genomes of each pool were sequenced, and statistical significance of QTL was calculated using QTLseq and G prime (G') analysis, which is based on calculating the allele frequency differences or D(SNP index). Results: Both methods detected the overlapping interval region, wherein CMSbulk was mapped at two loci in the 38.41-38.85 Mb region with 336 SNPs on chromosome 1 (qCMS1) and the 26.13-26.80 Mb region with 1,011 SNPs on chromosome 3 (qCMS3); the D(SNP index) peaks were -0.2709 and 0.3127, respectively. TN-bulk was mapped at only one locus in the overlapping 38.26-38.95 Mb region on chromosome 1 with 575 SNPs (qTN1) and a D(SNP index) peak of -0.3544. These identified QTLs in two different genetic backgrounds of segregating populations derived from JK were validated. The results confirmed the colocalization of the qCMS1 and qTN1 traits on chromosome 1. Based on the CMS trait, qCMS1/qTN1 stably expressed 6%-18% of the phenotypic variance in the two validation populations, while qCMS1/qTN1 accounted for 16%-20% of the phenotypic variance in one validation population based on the TN trait. Conclusion: The findings confirm that the CMS and TN traits are tightly linked to the long arm of chromosome 1 rather than to chromosome 3. The validated qCMS-TN1 QTL can be used for gene/QTL pyramiding in marker-assisted selection to expedite breeding for salt resistance in rice at the seedling stage. [ABSTRACT FROM AUTHOR]

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk postmortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA editing and alternative polyadenylation (APA) within a cell-type-specific population of human neural progenitors and neurons. More RNA editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting that genetically mediated post-transcriptional regulation during brain development leads to differences in brain function. Aygün et al. identify genetic regulation of RNA editing and alternative polyadenylation within a cell-type-specific population of human neural progenitors and neurons. They find more RNA editing and longer polyadenylation sequences in neurons, as well as cell-type-specific editing quantitative trait loci and alternative polyadenylation QTLs, including colocalizations with brain-related traits. [ABSTRACT FROM AUTHOR]

Introduction: Chile pepper (Capsicum annuum L.) mechanization is a promising alternative to traditional hand harvesting due to the costs associated with manual harvest, as well as the increasing unavailability of skilled manual chile harvesters. This study aimed to identify single nucleotide polymorphisms (SNPs) associated with mechanical harvestability (MH) and yield-related traits using multi-locus genome-wide association mapping approaches in a C. annuum association mapping population. Methods: A C. annuum association mapping panel for mechanical harvest was manually direct seeded in an augmented block design in two locations. After filtration, imputation, and quality control 27,291 single nucleotide polymorphism (SNP) markers were used for association analyses. Six multi-locus GWAS models were implemented to identify marker trait association. Results and Discussion: Multi-locus GWAS models identified 12 major SNP markers (R2 > 10) across nine chromosomes associated with plant architecture, easy destemming traits, and yield parameters. The presence of a major QTL in chromosome P2, dstem2.1, identified recently to be associated with destemming force, was confirmed. Mature green and mature red yield shared three SNP markers mapped on chromosome P3, P5, and P6 explaining 11.94% to 25.15% of the phenotypic variation. Candidate gene analysis for the significant loci identified 19 candidate genes regulating different phytohormone biosynthesis/signaling, metabolic processes, transcription, methylation, DNA repair/replication, and RNA splicing, with potential roles in controlling plant architecture and morphology. The diverse positions of the associated SNPs suggest the complex nature of these quantitative traits, involvement of multiple genetic factors, and novel significant marker-trait associations. Results from this study will be relevant for genetic improvement of mechanical harvestability traits in New Mexican chile pepper using molecular markerassisted breeding and selection. [ABSTRACT FROM AUTHOR]

In Asia, where climate change is increasing the damage caused by cold stress, it is crucial to cultivate varieties with enhanced cold tolerance. In this study, the Tongil variety ‘Hanareum2’ was crossed with the Japonica variety ‘Unkwang’ to improve plant growth ability at low temperatures during the seedling stage. This led to the development of 234 recombinant inbred line (RIL) populations, and a linkage map was constructed using 249 single nucleotide polymorphism (SNP) markers. The RIL populations were transplanted to the field one month earlier than the standard transplanting period, and plant height (PH), leaf number (LN), and dry weight (DW) were measured to identify quantitative trait loci (QTL) associated with plant growth ability at low temperatures during the seedling stage. QTLs related to cold tolerance, particularly those carrying the ‘Unkwang’ allele, were identified in the PH and DW traits. For PH, the QTLs qPH1, qPH5, and qPH8 were located on chromosomes 1, 5, and 8, respectively. Regarding DW, the QTLs qDW1, qDW8, and qDW9 were identified on chromosomes 1, 8, and 9. For the LN trait, qLN3 carrying the ‘Hanareum2’ allele was located on chromosome 3. If the identified QTLs are utilized, they can be incorporated into breeding programs for plant growth at low temperatures during the seedling stage. [ABSTRACT FROM AUTHOR]

Rice grain size and grain weight, which have a great influence on rice quality and yield, are complex quantitative traits that are mediated by grain length (GL), grain width (GW), length-to-width ratio (LWR), and grain thickness (GT). In this study, the BC1F2 and BC1F2:3 populations derived from a cross between two indica rice varieties, Guangzhan 63-4S (GZ63-4S) and Dodda, were used to locate quantitative trait loci (QTL) related to grain size. A total of 30 QTL associated with GL, GW and LWR were detected, of which six QTL were scanned repeatedly in both populations. Two QTL, qGL4 and qGL6, were selected for genetic effect validation and were subsequently fine mapped to 2.359 kb and 176 kb, respectively. LOC_Os04g52240 (known as OsKS2/OsKSL2), which encoding an ent-beyerene synthase and as the only gene found in 2.359 kb interval, was proposed to be the candidate for qGL4. Moreover, the grains of qGL4 homozygous mutant plants generated by the CRISPR-Cas9 system became shorter and wider. In addition, the qGL4 allele from GZ63-4S contributes to the increase of yield per plant. Our study not only laid the foundation for further functional study of qGL4 and map-based cloning of qGL6, but also provided genetic resources for the development of high yield and good quality rice varieties. [ABSTRACT FROM AUTHOR]

Twenty-one quantitative trait loci were discovered across six environments, including three (NS), seven (LS) and eleven (VLS) conditions. The linkage groups 1A, 1B, 2A, 2B, 2D, 3B, 4A, 6A, 6B and 7D spanned quantitative trait loci (QTLs). For canopy temperature (CT), a stable QTL (Qct_rpcau_4A) in the environment E6 has shown a phenotypic variance (PVE) up to 17.85%. The QTL, Qspad_rpcau_2D, was found to be stable for SPAD value, explaining the PVE of 15.05%. Whereas, three stable QTLs viz. Qgy_rpcau_3B, Qgy_rpcau_4A and Qgy_rpcau_6A were associated with the chromosomes 3B, 4A and 6B explaining a PVE of 20.85%, 17.43% and 17.37% respectively for the trait GY. The interaction of genotype and environment has been shown to be useful in determining the best lines for heat-stressed environments. In addition, G X E analysis was performed on the population. In the ranking of genotypes for both mean yield and mean vs. stability, GGE biplot across the six environments, DH 146, 195, 60, 202, 65, 155, 124, 5, 201, 169, 15 and 170 were ranked closest to ideal and winning genotype; these were highly adapted and most stable lines. The goal of the current investigation was to find the best suitable double haploid lines which can withstand heat stress and to find those QTLs which are influential to heat stress for the studied traits. [ABSTRACT FROM AUTHOR]

Leaf angle (LA) is closely related to plant architecture, photosynthesis and density tolerance in maize. In the current study, we used a recombinant inbred line population constructed by two maize-inbred lines to detect quantitative trait loci (QTLs) controlling LA. Based on the average LA in three environments, 13 QTLs were detected, with the logarithm of odds ranging from 2.7 to 7.21, and the phenotypic variation explained by a single QTL ranged from 3.93% to 12.64%. A stable QTL, qLA2-3, on chromosome 2 was detected and was considered to be the major QTL controlling the LA. On the basis of verifying the genetic effect of qLA2-3, a fine map was used to narrow the candidate interval, and finally, the target segment was located at a physical distance of approximately 338.46 kb (B73 RefGen_v4 version), containing 16 genes. Re-sequencing and transcriptome results revealed that five candidate genes may be involved in the regulation of LA. The results enrich the information for molecular marker-assisted selection of maize LA and provide genetic resources for the breeding of dense planting varieties. [ABSTRACT FROM AUTHOR]

Wheat is used for making many food products due to its diverse quality profile among different wheat classes. Since laboratory analysis of these end-use quality traits is costly and time-consuming, genetic dissection of the traits is preferential. This study used a genome-wide association study (GWAS) of ten end-use quality traits, including kernel protein, flour protein, flour yield, softness equivalence, solvent's retention capacity, cookie diameter, and top-grain, in soft red winter wheat (SRWW) adapted to US southeast. The GWAS included 266 SRWW genotypes that were evaluated in two locations over two years (2020–2022). A total of 27,466 single nucleotide markers were used, and a total of 80 significant marker-trait associations were identified. There were 13 major-effect quantitative trait loci (QTLs) explaining >10% phenotypic variance, out of which, 12 were considered to be novel. Five of the major-effect QTLs were found to be stably expressed across multiple datasets, and four showed associations with multiple traits. Candidate genes were identified for eight of the major-effect QTLs, including genes associated with starch biosynthesis and nutritional homeostasis in plants. These findings increase genetic comprehension of these end-use quality traits and could potentially be used for improving the quality of SRWW. [ABSTRACT FROM AUTHOR]

Introduction Little is known about the interplay between genetics and epigenetics on antidepressant treatment (1) response and remission, (2) side effects, and (3) serum levels. This study explored the relationship among single nucleotide polymorphisms (SNPs), DNA methylation (DNAm), and mRNA levels of four pharmacokinetic genes, CYP2C19 , CYP2D6 , CYP3A4 , and ABCB1 , and its effect on these outcomes. Methods The Canadian Biomarker Integration Network for Depression-1 dataset consisted of 177 individuals with major depressive disorder treated for 8 weeks with escitalopram (ESC) followed by 8 weeks with ESC monotherapy or augmentation with aripiprazole. DNAm quantitative trait loci (mQTL), identified by SNP-CpG associations between 20 SNPs and 60 CpG sites in whole blood, were tested for associations with our outcomes, followed by causal inference tests (CITs) to identify methylation-mediated genetic effects. Results Eleven cis- SNP-CpG pairs (q<0.05) constituting four unique SNPs were identified. Although no significant associations were observed between mQTLs and response/remission, CYP2C19 rs4244285 was associated with treatment-related weight gain (q =0.027) and serum concentrations of ESCadj (q <0.001). Between weeks 2-4, 6.7% and 14.9% of those with *1/*1 (normal metabolizers) and *1/*2 (intermediate metabolizers) genotypes, respectively, reported ≥2 lbs of weight gain. In contrast, the *2/*2 genotype (poor metabolizers) did not report weight gain during this period and demonstrated the highest ESCadj concentrations. CITs did not indicate that these effects were epigenetically mediated. Discussion These results elucidate functional mechanisms underlying the established associations between CYP2C19 rs4244285 and ESC pharmacokinetics. This mQTL SNP as a marker for antidepressant-related weight gain needs to be further explored. [ABSTRACT FROM AUTHOR]

The high isoflavones content of soybeans is an important breeding goal due to the demonstrated benefits of isoflavones to human health and their association with plant resistance. In this study, quantitative trait loci (QTL) mapping for soybean isoflavone aglycones, including daidzin, glycerin, and genistin, and total isoflavones content was performed in a population of 178 F2:6 recombinant inbred lines (RILs) which was generated from a cross between varieties Jinong 17 and Jinong 18. A genetic linkage map covering 1248 cM was constructed using the simple sequence repeat (SSR) molecular markers. The results revealed 22 isoflavone-related QTLs, 5 for daidzin, 7 for genistin, 6 for glycerin, and 4 for total isoflavone content. Seven of these represented new QTLs. All QTL regions contained 6462 genes, of which 58 have been annotated for flavonoid synthesis. Using public databases, three candidate genes, namely Glyma.11G164400, Glyma.16G158400, and Glyma.19G217700, were subsequently identified. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) demonstrated that the three genes exhibited specific, high expression in soybean seeds and a positive correlation with flavonoid content. These findings might be helpful in the efforts to breed new soybean varieties with improved isoflavone composition and content. [ABSTRACT FROM AUTHOR]

Stripe rust is a serious wheat disease occurring worldwide. At present, the most effective way to control it is to grow resistant cultivars. In this study, a population of 221 recombinant inbred lines (RILs) derived via single-seed descent from a hybrid of a susceptible wheat line, SY95-71, and a resistant line, XK502, was tested in three crop seasons from 2022 to 2024 in five environments. A genetic linkage map was constructed using 12,577 single-nucleotide polymorphisms (SNPs). Based on the phenotypic data of infection severity and the linkage map, five quantitative trait loci (QTL) for adult plant resistance (APR) were detected using the inclusive composite interval mapping (ICIM) method. These five loci are QYrxk502.swust-1BL, QYrxk502.swust-2BL, QYrxk502.swust-3AS, QYrxk502.swust-3BS, and QYrxk502.swust-7BS, explaining 5.67–19.64%, 9.63–36.74%, 9.58–11.30%, 9.76–23.98%, and 8.02–12.41% of the phenotypic variation, respectively. All these QTL originated from the resistant parent XK502. By comparison with the locations of known stripe rust resistance genes, three of the detected QTL, QYrxk502.swust-3AS, QYrxk502.swust-3BS, and QYrxk502.swust-7BS, may harbor new, unidentified genes. From among the tested RILs, 16 lines were selected with good field stripe rust resistance and acceptable agronomic traits for inclusion in breeding programs. [ABSTRACT FROM AUTHOR]

Main conclusion: A genetic linkage map representing the pearl millet genome was constructed with SNP markers. Major and stable QTL associated with flowering, number of productive tillers, ear head length, and test weight were mapped on chromosomes 1 and 3. Pearl millet (Pennisetum glaucum) is a major cereal and fodder crop in arid and semi-arid regions of Asia and Africa. Agronomic traits are important traits in pearl millet breeding and genetic and environmental factors highly influence them. In the present study, an F9 recombinant inbred line (RIL) population derived from a cross between PT6029 and PT6129 was evaluated for agronomic traits in three environments. Utilizing a genotyping by sequencing approach, a dense genetic map with 993 single nucleotide polymorphism markers covering a total genetic distance of 1035.4 cM was constructed. The average interval between the markers was 1.04 cM, and the seven chromosomes varied from 115.39 to 206.72 cM. Quantitative trait loci (QTL) mapping revealed 35 QTL for seven agronomic traits, and they were distributed on all pearl millet chromosomes. These QTL individually explained 11.35 to 26.71% of the phenotypic variation, with LOD values ranging from 2.74 to 5.80. Notably, four QTL (qDFF1.1, qNPT3.1, qEHL3.1, and qTW1.1) associated with days to fifty percent flowering, the number of productive tillers, ear head length, and test weight were found to be major and stable QTL located on chromosomes 1 and 3. Collectively, our results provide an important base for understanding the genetic architecture of agronomic traits in pearl millet, which is useful for accelerating the genetic gain toward crop improvement. [ABSTRACT FROM AUTHOR]

Background: Cannabis sativa is seeing a global resurgence as a food, fiber and medicinal crop for industrial hemp and medicinal Cannabis industries respectively. However, a widespread moratorium on the use and research of C. sativa throughout most of the 20th century has seen the development of improved cultivars for specific end uses lag behind that of conventional crops. While C. sativa research and development has seen significant investments in the recent past, resulting in a suite of publicly available genomic resources and tools, a versatile and cost-effective mid-density genotyping platform for applied purposes in breeding and pre-breeding is lacking. Here we report on a first mid-density fixed-target SNP platform for C. sativa. Results: The High-throughput Amplicon-based SNP-platform for medicinal Cannabis and industrial Hemp (HASCH) was designed using a combination of filtering and Integer Linear Programming on publicly available whole-genome sequencing and RNA sequencing data, supplemented with in-house generated genotyping-by-sequencing (GBS) data. HASCH contains 1,504 genome-wide targets of high call rate (97% mean) and even distribution across the genome, designed to be highly informative (> 0.3 minor allele frequency) across both medicinal cannabis and industrial hemp gene pools. Average numbers of mismatch SNP between any two accessions were 251 for medicinal cannabis (N = 116) and 272 for industrial hemp (N = 87). Comparing HASCH data with corresponding GBS data on a collection of diverse C. sativa accessions demonstrated high concordance and resulted in comparable phylogenies and genetic distance matrices. Using HASCH on a segregating F2 population derived from a cross between a tetrahydrocannabinol (THC)-dominant and a cannabidiol (CBD)-dominant accession resulted in a genetic map consisting of 310 markers, comprising 10 linkage groups and a total size of 582.7 cM. Quantitative Trait Locus (QTL) mapping identified a major QTL for CBD content on chromosome 7, consistent with previous findings. Conclusion: HASCH constitutes a versatile, easy to use and cost-effective genotyping solution for the rapidly growing Cannabis research community. It provides consistent genetic fingerprints of 1504 SNPs with wide applicability genetic resource management, quantitative genetics and breeding. [ABSTRACT FROM AUTHOR]

Direct-seeded rice (DSR) is gaining popularity among farmers due to its environmentally safe and resource-efficient production system. However, managing the rice root-knot nematode (RRKN), Meloidogyne graminicola, remains a major challenge in DSR cultivation. Developing genetic resistance is a pragmatic and effective approach compared to using hazardous pesticides. Pusa Basmati 1121 (PB1121) is the most popular Basmati rice variety, but it is highly susceptible to RRKN. In contrast, Phule Radha (PR) has shown highly resistant reaction to RRKN, as reported in our earlier study. We generated an F2:3 population from the cross of PB1121/PR and evaluated it for RRKN resistance-related traits under artificial inoculation conditions. The distribution pattern of traits in the F2:3 population indicated that resistance may be governed by a few major-effect genes and many minor-effect genes. The molecular markers reported to be associated with QTLs governing RRKN resistance traits were used to test in the current population. Although the simple linear regression identified significant associations between the markers and RRKN resistance-associated traits, these associations were spurious as the LOD score was below the threshold limit. This indicates that PR possesses novel genomic regions for resistance to RRKN as it does not possess any of the earlier reported QTLs. [ABSTRACT FROM AUTHOR]

Introduction: Research has highlighted the role of runt-related transcription factor 2 (Runx2) in the development of osteoarthritis (OA); however, its causal association remains unclear. This study aimed to explore whether Runx2 expression is causally associated with OA and assess its therapeutic potential for OA. Methods: Genetic proxy instruments for Runx2 expression were obtained from gene expression quantitative trait locus (eQTLs) study of eQTLGen Consortium (n = 31,684). Aggregated genome-wide association study (GWAS) data for OA (including all OA [177,517 cases and 649,173 controls], knee OA (KOA) [62,497 cases and 333,557 controls], and hip OA (HOA) [36,445 cases and 316,943 controls]) were extracted from the Genetics of Osteoarthritis Consortium. We integrated eQTLs data with OA GWAS data to estimate their causal association and to estimate the potential of Runx2 as a drug target in the treatment of OA using summary data-based Mendelian randomization (SMR) analysis. Furthermore, different OA GWAS data (including all OA [77,052 cases and 378,169 controls], KOA [24,955 cases and 378,169 controls], and HOA [15,704 cases and 378,169 controls]) derived from the GWAS Catalog database were used for replication study. Results: SMR analysis showed that high expression levels of Runx2 were associated with an increased risk of all OA [odds ratio (OR) 1.044, 95% confidence interval (CI) 1.023–1.067; P = 5.03 × 10−5], KOA (OR 1.040, 95% CI 1.006–1.075; P = 0.021), and HOA (OR 1.067, 95% CI 1.022–1.113; P = 0.003). This suggests that Runx2 inhibitors may have promising potential for the treatment of OA. Notably, the causal effects of Runx2 with all OA (OR 1.053, 95% CI 1.027–1.079; P = 3.95 × 10−5) and KOA (OR 1.043, 95% CI 1.001–1.087; P = 0.045) were repeated in the replication study, but limited evidence supported the association of Runx2 expression levels with HOA (OR 1.045, 95% CI 0.993–1.101; P = 0.094). Conclusions: Our analyses indicate a positive correlation between Runx2 expression and OA risk across all three phenotypes, suggesting the potential of Runx2 inhibitors in the treatment of OA and providing evidence from a genetic perspective. [ABSTRACT FROM AUTHOR]

• This work represents the first-ever detailed multiple marker studies in Stevia. • QTL identification is the novelty of the work that will promote stevia breeding. • The QTL identified could be used in the mapping of genes responsible for rebaudioside-A. • Functional polymorphic markers will be useful in genetic dissection of traits. Stevia rebaudiana Bertoni, belonging to the family Asteraceae, is one of the most important perennial medicinal plants. It is used as a no-calorie sweetener therefore; mining of sweetening genes using molecular markers is a thrust area. In the present study combinations of markers were screened. Out of 170 RAPD, 26 ISSR, and 89 EST-SSR primers, it was observed that 36 RAPD, 10 ISSR, and 33 EST-SSR were found to be polymorphic. Using MAPMAKER/EXP version 3.0 b, four linkage groups were constructed spanning a distance of 927.3 cM with an average distance between loci of 16.29 cM. On QTL identification, a total of 53 locations were found for both trait 1 (rebaudioside-A) and trait 2 (stevioside). Among 53 QTL locations of trait 1, two major QTL were found for rebaudioside-A namely, in the marker interval of L67–L71 (ISSR HB-11)–(IISRS-3-L) in LG1 and the marker interval of L38–L40 (Sigma-5383–027)- (Sigma-5383-029) in LG3 at LOD of 2.5 and 2.7, respectively. The map constructed and QTL identified will greatly facilitate further genetic studies. It is hoped that this work will have a practical impact on the advancement of stevia breeding and genome analysis. [ABSTRACT FROM AUTHOR]

This study evaluated 290 recombinant inbred lines (RILs) from the Nested Association Mapping (NAM) population in the UK, consisting of 24 hybrid families. All genotypes were grown in Southeastern Kazakhstan (Kazakh Research Institute of Agriculture and Plant Growing, Almaty region, 2021–2022) and Northern Kazakhstan (Alexandr Barayev Scientific-Production Center for Grain Farming, Akmola region, 2020). The studied traits included six yield-related characteristics: spike length (SL, cm), number of productive spikes per plant (NPS, pcs), number of kernels per spike (NKS, pcs), weight of kernels per spike (WKS, g), thousand kernel weight (TKW, g), and yield per square meter (YM2, g/m2). The significant phenotypic variability among genotypes was observed, which was suitable for the genome-wide association study of yield-related traits. Pearson's index showed positive correlations among most yield-related traits, although a negative correlation was found between NKS and TKW in southeastern regions, and no correlation was recorded for northern regions. Top-performing RILs, surpassing local checks, were identified for NKS, TKW, and YM2, suggesting their potential for breeding programs. The application of GWAS allowed the identification of 72 quantitative trait loci (QTLs), including 36 QTLs in the southeastern region, 16 QTLs in the northern region, and 19 in both locations. Eleven QTLs matched those reported in previous QTL mapping studies and GWAS for studied traits. The results can be used for further studies related to the adaptation and productivity of wheat in breeding projects for higher grain productivity. [ABSTRACT FROM AUTHOR]

The research reported here was conducted to follow up on observations of durable adult‐plant resistance to net form net blotch in several Australian varieties of barley (Hordeum vulgare L.). Over 11 years, isolates of Pyrenophora teres f. teres were collected and used to inoculate barley varieties. The resistance of five varieties (Clipper, Schooner, Sloop SA, Buloke and Scope) endured until the ninth year. To investigate the genetic control of this durable resistance, doubled haploid lines developed from the F1 generation of a cross between Sloop SA and the susceptible variety Fathom were inoculated with an isolate that appeared fully virulent on Fathom and were evaluated for adult plant resistance. Six quantitative trait loci were mapped: three with resistance from Sloop SA and three with resistance from Fathom. Effects were additive across loci and transgressive segregation provided a few lines with better resistance than Sloop SA. Although the resistance investigated here is no longer effective, insights gained from this research could help guide ongoing efforts in resistance breeding and disease control. [ABSTRACT FROM AUTHOR]

Despite great progress in understanding lipoprotein physiology, there is still much to be learned about the genetic drivers of lipoprotein abundance, composition, and function. We used ion mobility spectrometry to survey 16 plasma lipoprotein subfractions in 500 Diversity Outbred mice maintained on a Western-style diet. We identified 21 quantitative trait loci (QTL) affecting lipoprotein abundance. To refine the QTL and link them to disease risk in humans, we asked if the human homologs of genes located at each QTL were associated with lipid traits in human genome-wide association studies. Integration of mouse QTL with human genome-wide association studies yielded candidate gene drivers for 18 of the 21 QTL. This approach enabled us to nominate the gene encoding the neutral ceramidase, Asah2, as a novel candidate driver at a QTL on chromosome 19 for large HDL particles (HDL-2b). To experimentally validate Asah2, we surveyed lipoproteins in Asah2-/- mice. Compared to wild-type mice, female Asah2-/- mice showed an increase in several lipoproteins, including HDL. Our results provide insights into the genetic regulation of circulating lipoproteins, as well as mechanisms by which lipoprotein subfractions may affect cardiovascular disease risk in humans.

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

Root system architecture plays an essential role in water and nutrient acquisition in plants, and it is significantly involved in plant adaptations to various environmental stresses. In this study, a panel of 242 cotton accessions was collected to investigate six root morphological traits at the seedling stage, including main root length (MRL), root fresh weight (RFW), total root length (TRL), root surface area (RSA), root volume (RV), and root average diameter (AvgD). The correlation analysis of the six root morphological traits revealed strong positive correlations of TRL with RSA, as well as RV with RSA and AvgD, whereas a significant negative correlation was found between TRL and AvgD. Subsequently, a genome-wide association study (GWAS) was performed using the root phenotypic and genotypic data reported previously for the 242 accessions using 56,010 single nucleotide polymorphisms (SNPs) from the CottonSNP80K array. A total of 41 quantitative trait loci (QTLs) were identified, including nine for MRL, six for RFW, nine for TRL, 12 for RSA, 12 for RV and two for AvgD. Among them, eight QTLs were repeatedly detected in two or more traits. Integrating these results with a transcriptome analysis, we identified 17 candidate genes with high transcript values of transcripts per million (TPM)≥30 in the roots. Furthermore, we functionally verified the candidate gene GH_D05G2106, which encodes a WPP domain protein 2 in root development. A virus-induced gene silencing (VIGS) assay showed that knocking down GH_D05G2106 significantly inhibited root development in cotton, indicating its positive role in root system architecture formation. Collectively, these results provide a theoretical basis and candidate genes for future studies on cotton root developmental biology and root-related cotton breeding.