Discovery Of Loci Research Articles

Population-specific reference panel improves imputation quality for genome-wide association studies conducted on the Japanese population

To improve imputation quality for genome-wide association studies (GWAS) conducted on the Japanese population, we developed and evaluated four Japanese population-specific reference panels. These panels were constructed through the augmentation of the 1000 Genomes Project (1KG) panel using Japanese whole genome sequencing (WGS) data, with sample sizes ranging from 1 K to 7 K individuals enrolled through the Biobank Japan (BBJ) project, and sequencing depths ranging from 3× to 30×. Among these panels, an augmented reference panel comprising 7472 WGS samples of mixed depth (1KG+7K) exhibit the greatest improvement in imputation quality relative to the Trans-Omics for Precision Medicine (TOPMed) reference panel. Notably, we observe these improvements primarily for rare variants with a minor allele frequency (MAF) <5%. To demonstrate the benefits of improved imputation quality in association analyses of complex traits, we conducted GWAS for serum uric acid and total cholesterol levels following imputation up to the 1KG+7K panel. The analysis reveals several loci reaching genome-wide significance (P < 5 × 10–8) in the 1KG+7K imputation output yet remaining undetected when the same sample set is imputed up to the TOPMed reference panel. In summary, the 1KG+7K panel demonstrates significant advantages in the discovery of trait-associated loci, particularly those influenced by low-frequency association signals.

Chromosome-level genome assemblies and genetic maps reveal heterochiasmy and macrosynteny in endangered Atlantic Acropora

BackgroundOver their evolutionary history, corals have adapted to sea level rise and increasing ocean temperatures, however, it is unclear how quickly they may respond to rapid change. Genome structure and genetic diversity contained within may highlight their adaptive potential.ResultsWe present chromosome-scale genome assemblies and linkage maps of the critically endangered Atlantic acroporids, Acropora palmata and A. cervicornis. Both assemblies and linkage maps were resolved into 14 chromosomes with their gene content and colinearity. Repeats and chromosome arrangements were largely preserved between the species. The family Acroporidae and the genus Acropora exhibited many phylogenetically significant gene family expansions. Macrosynteny decreased with phylogenetic distance. Nevertheless, scleractinians shared six of the 21 cnidarian ancestral linkage groups as well as numerous fission and fusion events compared to other distantly related cnidarians. Genetic linkage maps were constructed from one A. palmata family and 16 A. cervicornis families using a genotyping array. The consensus maps span 1,013.42 cM and 927.36 cM for A. palmata and A. cervicornis, respectively. Both species exhibited high genome-wide recombination rates (3.04 to 3.53 cM/Mb) and pronounced sex-based differences, known as heterochiasmy, with 2 to 2.5X higher recombination rates estimated in the female maps.ConclusionsTogether, the chromosome-scale assemblies and genetic maps we present here are the first detailed look at the genomic landscapes of the critically endangered Atlantic acroporids. These data sets revealed that adaptive capacity of Atlantic acroporids is not limited by their recombination rates. The sister species maintain macrosynteny with few genes with high sequence divergence that may act as reproductive barriers between them. In the Atlantic Acropora, hybridization between the two sister species yields an F1 hybrid with limited fertility despite the high levels of macrosynteny and gene colinearity of their genomes. Together, these resources now enable genome-wide association studies and discovery of quantitative trait loci, two tools that can aid in the conservation of these species.

Analysis of Tandem Repeats in Short-Read Sequencing Data: From Genotyping Known Pathogenic Repeats to Discovering Novel Expansions.

Short tandem repeats (STRs) and variable-number tandem repeats (VNTRs) are repetitive genomic sequences seen widely throughout the genome. These repeat expansions are currently known to cause ∼60 diseases, with expansions in new loci linked to rare diseases continuing to be discovered. Genome sequencing is an important tool for detecting disease-causing variants and several computational tools have been developed to analyze tandem repeats from genomic data, enabling the genotyping and the identification of expanded alleles. However, guidelines for conducting the analysis of these repeats and, more importantly, for assessing the findings are lacking. Understanding the tools and their technical limitations is important for accurately interpreting the results. This article provides detailed, step-by-step instructions for three key use cases in STR analysis from short-read genome sequencing data, which are also applicable to smaller VNTRs. First, it demonstrates an approach for genotyping known pathogenic loci and the identification of clinically significant expansions. Second, we offer guidance on defining tandem repeat loci and conducting genome-wide genotyping studies, which is also applicable to diploid organisms other than humans. Third, instructions are provided on how to find novel expansions at loci not previously known to be associated with disease, aiding in the discovery of new pathogenic loci. Moreover, we introduce the use of newly-developed helper tools that enable a complete and streamlined tandem repeat analysis protocol by addressing the gaps in current methods. All three protocols are compatible with human hg19, hg38, and the latest telomere-to-telomere (hs1) reference genomes. Additionally, this protocol provides an overview and discussion on how to interpret genotyping results. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Genotyping known pathogenic tandem repeat loci Alternate Protocol: Genotyping known pathogenic tandem repeat loci with STRipy Support Protocol 1: Installation of tools and ExpansionHunter catalog modification Basic Protocol 2: Performing genome-wide genotyping of tandem repeats Basic Protocol 3: Discovering de novo tandem repeat expansions Support Protocol 2: Compiling ExpansionHunter Denovo from source code and generating STR profiles.

DINGO: increasing the power of locus discovery in maternal and fetal genome-wide association studies of perinatal traits

Perinatal traits are influenced by fetal and maternal genomes. We investigate the performance of three strategies to detect loci in maternal and fetal genome-wide association studies (GWASs) of the same quantitative trait: (i) the traditional strategy of analysing maternal and fetal GWASs separately; (ii) a two-degree-of-freedom test which combines information from maternal and fetal GWASs; and (iii) a one-degree-of-freedom test where signals from maternal and fetal GWASs are meta-analysed together conditional on estimated sample overlap. We demonstrate that the optimal strategy depends on the extent of sample overlap, correlation between phenotypes, whether loci exhibit fetal and/or maternal effects, and whether these effects are directionally concordant. We apply our methods to summary statistics from a recent GWAS meta-analysis of birth weight. Both the two-degree-of-freedom and meta-analytic approaches increase the number of genetic loci for birth weight relative to separately analysing the scans. Our best strategy identifies an additional 62 loci compared to the most recently published meta-analysis of birth weight. We conclude that whilst the two-degree-of-freedom test may be useful for the analysis of certain perinatal phenotypes, for most phenotypes, a simple meta-analytic strategy is likely to perform best, particularly in situations where maternal and fetal GWASs only partially overlap.

Novel risk loci for COVID-19 hospitalization among admixed American populations.

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

A-167 Hematologic setpoints are a deep physiologic phenotype which enable personalized blood count reference intervals

Abstract Background The complete blood count (CBC) is an important screening tool for healthy adults, commonly ordered at periodic physical exams. However, test results are typically interpreted using one-size-fits-all reference intervals (RIs), which don’t account for the low index-of-individuality of most CBC markers. This undermines the goal of precision medicine - to tailor patient care based on individual characteristics. Methods Here we utilize a database of &amp;gt;50,000 healthy outpatients with yearly CBCs, to investigate the value of patient-specific reference intervals (PRIs) for 9 CBC markers. We use Gaussian mixture modelling to calculate each patient’s setpoints, and to construct associated PRIs. Mechanistic drivers of setpoints were investigated through GWAS and via analysis of excess clinical specimens. Clinical outcomes were analyzed by comparing sensitivity of RIs and PRIs for detection of future cytopenia/cythemia and mortality. Results We found healthy adults had patient-specific setpoints that were stable over decades, and distinctly identifiable from 98% of other patients. Setpoints reflected a deep physiologic phenotype, enabling improved detection of genetic determinants of hematologic regulation (Fig1A), including discovery of multiple novel loci via GWAS analysis. Deviation from PRIs was associated with greater risk of cytopenia/cythemia and mortality (Fig1B) than deviation from the RI for all setpoints except MCHC. Setpoints were significantly correlated with long-term all-cause mortality, even when limited to those within the RI (Fig1C). Conclusions We show that hematologic setpoints reflect a deep, patient-specific phenotype. This phenotype can enhance mechanistic studies, and allow for increased diagnostic sensitivity, through calculation of a personalized reference interval. Setpoints are sufficiently stable and patient-specific to help realize the promise of precision medicine for healthy adults.Fig1A.Significance of GWAS hits using setpoints versus single CBCs. Fig1B. 10yr mortality hazard ratio for tests outside the RI and PRI. Fig1C. Association of WBC setpoint with mortality (limited to WBC setpoints inside the RI).

Reviewing Genetic Testing for Lupus: Implications for Nephritis

Genetic testing has significantly changed our understanding and treatment of systemic lupus erythematosus (SLE), particularly its severe manifestation, lupus nephritis (LN). Nephrology faces great difficulty with LN, which is characterized by severe inflammation and kidney damage. To create individualized treatments, it is essential to identify the genetic variables that influence the LN susceptibility and progression. This review highlights the importance of genetic testing in diagnosing and managing LN, covering genetic predispositions, common markers, the role of ethnicity, specific renal genes, and epigenetic factors. Key genetic markers such as HLA-DRB1, ITGAM, FCGR2A, and IRF5 have been linked to LN, impacting immune regulation and disease progression. Asians, African Americans, and Hispanics have greater prevalence rates of genetic susceptibility than Caucasians, suggesting that ethnicity plays a major role in genetic vulnerability. Genes like APOL1, PDGFRA, and HAS2 play vital roles in renal function and fibrosis, affecting disease outcomes. New treatment targets are provided by epigenetic mechanisms that control gene expression in LN, such as DNA methylation and histone alterations. The progress made in genome-wide association studies (GWAS) has led to the discovery of new genetic loci linked to LN, which has improved our knowledge of its pathogenesis. This review highlights the critical role of genetic testing in LN, emphasizing its potential to improve diagnosis, treatment, and patient outcomes through personalized medicine.

Advancements in Lentil Genomics for Enhanced Crop Breeding: A Review

Lentil (Lens culinaris Medik) is an essential pulse crop that is widely grown for its high nutritional value, notably its high protein content, making it an important dietary component for vegetarians and vegans. Despite being the world's fifth most produced pulse, with large contributions from Canada and India, lentil production confronts obstacles such as poor productivity due to limited genetic improvement against biotic and abiotic stresses under rainfed cultivation conditions. Recent advances in lentil genetics and genomics, such as the discovery of genes related to yield, disease resistance, and nutritional content, have boosted breeding efforts to generate improved lentil varieties. The use of contemporary genomic techniques like molecular markers, marker-assisted selection (MAS), genomic selection (GS), and next-generation sequencing (NGS) technology has sped up the discovery of quantitative trait loci (QTLs) and the production of novel cultivars with superior agronomic characteristics. Databases such as NCBI and ENA, as well as specialized resources like KnowPulse, provide critical genomic data, while the creation of lentil genome assemblies, notably the CDC Redberry variety, has improved our understanding of lentil genetics. These resources help to solve the constraints of traditional breeding, particularly for complex characteristics impacted by genotype-environment interactions, opening the way for more robust and productive lentil varieties. Although the application of advanced tools such as genetic engineering, cisgenesis, and genome editing has moved more slowly in lentils than in other crops, their potential to improve lentil output is encouraging. Recent studies on lentil genomes, together with the creation of increased genetic resources and cutting-edge techniques, offer the ability to overcome production constraints and dramatically increase lentil production and quality throughout the world.

Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy

Insulin resistance causes multiple epidemic metabolic diseases, including type 2 diabetes, cardiovascular disease, and fatty liver, but is not routinely measured in epidemiological studies. To discover novel insulin resistance genes in the general population, we conducted genome-wide association studies in 382,129 individuals for triglyceride to HDL-cholesterol ratio (TG/HDL), a surrogate marker of insulin resistance calculable from commonly measured serum lipid profiles. We identified 251 independent loci, of which 62 were more strongly associated with TG/HDL compared to TG or HDL alone, suggesting them as insulin resistance loci. Candidate causal genes at these loci were prioritized by fine mapping with directions-of-effect and tissue specificity annotated through analysis of protein coding and expression quantitative trait variation. Directions-of-effect were corroborated in an independent cohort of individuals with directly measured insulin resistance. We highlight two phospholipase encoding genes, PLA2G12A and PLA2G6, which liberate arachidonic acid and improve insulin sensitivity, and VGLL3, a transcriptional co-factor that increases insulin resistance partially through enhanced adiposity. Finally, we implicate the anti-apoptotic gene TNFAIP8 as a sex-dimorphic insulin resistance factor, which acts by increasing visceral adiposity, specifically in females. In summary, our study identifies several candidate modulators of insulin resistance that have the potential to serve as biomarkers and pharmacological targets.

Genotype inference from aggregated chromatin accessibility data reveals genetic regulatory mechanisms.

Understanding the genetic causes for variability in chromatin accessibility can shed light on the molecular mechanisms through which genetic variants may affect complex traits. Thousands of ATAC-seq samples have been collected that hold information about chromatin accessibility across diverse cell types and contexts, but most of these are not paired with genetic information and come from diverse distinct projects and laboratories. We report here joint genotyping, chromatin accessibility peak calling, and discovery of quantitative trait loci which influence chromatin accessibility (caQTLs), demonstrating the capability of performing caQTL analysis on a large scale in a diverse sample set without pre-existing genotype information. Using 10,293 profiling samples representing 1,454 unique donor individuals across 653 studies from public databases, we catalog 23,381 caQTLs in total. After joint discovery analysis, we cluster samples based on accessible chromatin profiles to identify context-specific caQTLs. We find that caQTLs are strongly enriched for annotations of gene regulatory elements across diverse cell types and tissues and are often strongly linked with genetic variation associated with changes in expression (eQTLs), indicating that caQTLs can mediate genetic effects on gene expression. We demonstrate sharing of causal variants for chromatin accessibility and diverse complex human traits, enabling a more complete picture of the genetic mechanisms underlying complex human phenotypes. Our work provides a proof of principle for caQTL calling from previously ungenotyped samples, and represents one of the largest, most diverse caQTL resources currently available, informing mechanisms of genetic regulation of gene expression and contribution to disease.

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.

Gene Therapy for Retinitis Pigmentosa: Current Challenges and New Progress.

Retinitis pigmentosa (RP) poses a significant threat to eye health worldwide, with prevalence rates of 1 in 5000 worldwide. This genetically diverse retinopathy is characterized by the loss of photoreceptor cells and atrophy of the retinal pigment epithelium. Despite the involvement of more than 3000 mutations across approximately 90 genes in its onset, finding an effective treatment has been challenging for a considerable time. However, advancements in scientific research, especially in gene therapy, are significantly expanding treatment options for this most prevalent inherited eye disease, with the discovery of new compounds, gene-editing techniques, and gene loci offering hope for more effective treatments. Gene therapy, a promising technology, utilizes viral or non-viral vectors to correct genetic defects by either replacing or silencing disease-causing genes, potentially leading to complete recovery. In this review, we primarily focus on the latest applications of gene editing research in RP. We delve into the most prevalent genes associated with RP and discuss advancements in genome-editing strategies currently employed to correct various disease-causing mutations.

Admixture Mapping of Chronic Kidney Disease and Risk Factors in Hispanic/Latino Individuals From Central America Country of Origin.

Chronic kidney disease (CKD) is highly prevalent in Central America, and genetic factors may contribute to CKD risk. To understand the influences of genetic admixture on CKD susceptibility, we conducted an admixture mapping screening of CKD traits and risk factors in US Hispanic and Latino individuals from Central America country of origin. We analyzed 1023 participants of HCHS/SOL (Hispanic Community Health Study/Study of Latinos) who reported 4 grandparents originating from the same Central America country. Ancestry admixture findings were validated on 8191 African Americans from WHI (Women's Health Initiative), 3141 American Indians from SHS (Strong Heart Study), and over 1.1 million European individuals from a multistudy meta-analysis. We identified 3 novel genomic regions for albuminuria (chromosome 14q24.2), CKD (chromosome 6q25.3), and type 2 diabetes (chromosome 3q22.2). The 14q24.2 locus driven by a Native American ancestry had a protective effect on albuminuria and consisted of 2 nearby regions spanning the RGS6 gene. Variants at this locus were validated in American Indians. The 6q25.3 African ancestry-derived locus, encompassing the ARID1B gene, was associated with increased risk for CKD and replicated in African Americans through admixture mapping. The European ancestry type 2 diabetes locus at 3q22.2, encompassing the EPHB1 and KY genes, was validated in European individuals through variant association. US Hispanic/Latino populations are culturally and genetically diverse. This study focusing on Central America grandparent country of origin provides new loci discovery and insights into the ancestry-of-origin influences on CKD and risk factors in US Hispanic and Latino individuals.

New population of Solanum pimpinellifolium backcross inbred lines as a resource for heat stress tolerance in tomato.

The occurring temperature increase in crop production areas worldwide is generating conditions of heat stress that negatively affect crop productivity. Tomato (Solanum lycopersicum), a major vegetable crop, is highly susceptible to elevated temperatures. Under such conditions, fruit set is dramatically reduced, leading to significant yield losses. Solanum pimpinellifolium, a wild species closely related to the cultivated tomato, was shown to have beneficial attributes under various abiotic stress growth conditions. We have utilized a new population of backcross inbred lines originated from a cross between S. pimpinellifolium and S. lycopersicum, in order to evaluate its potential as a new genetic resource for improvement of reproductive performance of cultivated tomato under heat stress conditions. This population was screened for various heat stress-related traits, under controlled heat stress and non-stress conditions. Our results show that significant variation exists for all the heat stress related traits that were examined and point at individual lines with better reproductive performance under heat stress conditions that share a common introgression from the wild S. pimpinellifolium parent, suggesting several candidate genes as potential drivers of thermotolerance. Thus, our results place this population as a valuable new resource for the discovery of heat stress related genetic loci for the future development of heat stress tolerant tomato cultivars.

Discovery of genomic loci for liver health and steatosis reveals overlap with glutathione redox genetics

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver condition in the United States, encompassing a wide spectrum of liver pathologies including steatosis, steatohepatitis, fibrosis, and cirrhosis. Despite its high prevalence, there are no medications currently approved by the Food and Drug Administration for the treatment of NAFLD. Recent work has suggested that NAFLD has a strong genetic component and identifying causative genes will improve our understanding of the molecular mechanisms contributing to NAFLD and yield targets for future therapeutic investigations. Oxidative stress is known to play an important role in NAFLD pathogenesis, yet the underlying mechanisms accounting for disturbances in redox status are not entirely understood. To better understand the relationship between the glutathione redox system and signs of NAFLD in a genetically-diverse population, we measured liver weight, serum biomarkers aspartate aminotransferase (AST) and alanine aminotransferase (ALT), and graded liver pathology in a large cohort of Diversity Outbred mice. We compared hepatic endpoints to those of the glutathione redox system previously measured in the livers and kidneys of the same mice, and we screened for statistical and genetic associations using the R/qtl2 software. We discovered several novel genetic loci associated with markers of liver health, including loci that were associated with both liver steatosis and glutathione redox status. Candidate genes within each locus point to possible new mechanisms underlying the complex relationship between NAFLD and the glutathione redox system, which could have translational implications for future studies targeting NAFLD pathology.

Characterizing Common and Rare Variations in Nontraditional Glycemic Biomarkers Using Multivariate Approaches on Multiancestry ARIC Study.

Genetic studies of non-traditional glycemic biomarkers, glycated albumin and fructosamine, can shed light on unknown aspects of type 2 diabetes genetics and biology. We performed a multi-phenotype GWAS of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on common variants from genotyped/imputed data. We discovered 2 genome-wide significant loci, one mapping to known type 2 diabetes gene (ARAP1/STARD10) and another mapping to a novel region (UGT1A complex of genes) using multi-omics gene-mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry- and sex-specific (e.g., PRKCA in African ancestry, FCGRT in European ancestry, TEX29 in males). Further, we implemented multi-phenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Ten variant sets annotated to genes across different variant aggregation strategies were exome-wide significant only in multi-ancestry analysis, of which CD1D, EGFL7/AGPAT2 and MIR126 had notable enrichment of rare predicted loss of function variants in African ancestry despite smaller sample sizes. Overall, 8 out of 14 discovered loci and genes were implicated to influence these biomarkers via glycemic pathways, and most of them were not previously implicated in studies of type 2 diabetes. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across the entire allele frequency spectrum in multi-ancestry analysis. Future investigation of the loci and genes potentially acting through glycemic pathways may help us better understand risk of developing type 2 diabetes.

Qfhb.yzu.3B.1 and Qfhb.yzu.6B.3 Are Stable Quantitative Trait Loci for Wheat Resistance to Fusarium Head Blight with Diverse Genetic Backgrounds

Fusarium head blight (FHB) can cause serious yield loss and significant mycotoxin contamination, which seriously threaten global food security and safety. Breeding stable and durable cultivars that are resistant to FHB is one of the most effective approaches to controlling this disease. Fhb1 is a well-known genetic locus for FHB resistance, but its resistance is not always effective across diverse wheat genetic backgrounds. To achieve a high and durable level of resistance, the discovery and use of additional quantitative trait loci (QTL) for FHB resistance are essentially needed in breeding programs. In this study, two independent wheat natural populations of different origins were used for mining resistance QTL with a major and stable effect. Using genome-wide association analysis (GWAS), a total of 58 marker–trait associations (MTAs) on chromosomes 1A, 2B, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A and 7B were found to be significant for type II resistance to FHB. These 58 MTAs represent 24 putative QTL. Among these QTL, Qfhb.yzu.3B.1 and Qfhb.yzu.6B.3 were stably detected in the two natural populations across three consecutive experimental years. The favorable haplotypes at the two QTL could significantly reduce the disease severity, either individually or in combination. These two QTL are also additive to Fhb1 in cultivars with different genetic backgrounds. Breeder-friendly markers were designed to differentiate the contrasting alleles at these two loci, thus proving very useful for improving FHB resistance in wheat by marker-assisted selection.

YQTL Pipeline: A structured computational workflow for large scale quantitative trait loci discovery and downstream visualization.

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. To facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to the association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. The options to run an ANOVA model or testing the interaction with a covariate are also available. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. It can generate Manhattan and Miami plots of phenotype traits, genotype-phenotype boxplots, and trait-QTL connection networks. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTLpipeline.

Skimming genomes for systematics and DNA barcodes of corals.

Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage genome sequencing) is a promising method to not only extract high-copy loci but also 100s to 1000s of phylogenetically informative nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and museum samples. The subphylum Anthozoa, including important ecosystem engineers (e.g., stony corals, black corals, anemones, and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. We conducted genome skimming on 242 anthozoan corals collected from 1886 to 2022. Using existing target-capture baitsets, we bioinformatically obtained UCEs and exons from the genome-skimming data and incorporated them with data from previously published target-capture studies. The mean number of UCE and exon loci extracted from the genome skimming data was 1837 ± 662 SD for octocorals and 1379 ± 476 SD loci for hexacorals. Phylogenetic relationships were well resolved within each class. A mean of 1422 ± 720 loci was obtained from the historical specimens, with 1253 loci recovered from the oldest specimen collected in 1886. We also obtained partial to whole mitogenomes and nuclear rRNA genes from >95% of samples. Bioinformatically pulling UCEs, exons, mitochondrial genomes, and nuclear rRNA genes from genome skimming data is a viable and low-cost option for phylogenetic studies. This approach can be used to review and support taxonomic revisions and reconstruct evolutionary histories, including historical museum and type specimens.

QTL Mapping for Agronomic Important Traits in Well-Adapted Wheat Cultivars

Wheat (Triticum aestivum L.) is one of the most important food crops worldwide and provides the staple food for 40% of the world’s population. Increasing wheat production has become an important goal to ensure global food security. The grain yield of wheat is a complex trait that is usually influenced by multiple agronomically important traits. Thus, the genetic dissection and discovery of quantitative trait loci (QTL) of wheat-yield-related traits are very important to develop high-yield cultivars to improve wheat production. To analyze the genetic basis and discover genes controlling important agronomic traits in wheat, a recombinant inbred lines (RILs) population consisting of 180 RILs derived from a cross between Xinong822 (XN822) and Yannong999 (YN999), two well-adapted cultivars, was used to map QTL for plant height (PH), spike number per spike (SNS), spike length (SL), grain number per spike (GNS), spike number per plant (SN), 1000- grain weight (TGW), grain length (GL), grain width (GW), length/width of grain (GL/GW), perimeter of grain (Peri), and surface area of grains (Sur) in three environments. A total of 64 QTL were detected and distributed on all wheat chromosomes except 3A and 5A. The identified QTL individually explained 2.24–38.24% of the phenotypic variation, with LOD scores ranging from 2.5 to 29. Nine of these QTL were detected in multiple environments, and seven QTL were associated with more than one trait. Additionally, Kompetitive Allele Specific PCR (KASP) assays for five major QTL QSns-1A.2 (PVE = 6.82), QPh-2D.1 (PVE = 37.81), QSl-2D (PVE = 38.24), QTgw-4B (PVE = 8.78), and QGns-4D (PVE = 13.54) were developed and validated in the population. The identified QTL and linked markers are highly valuable in improving wheat yield through marker-assisted breeding, and the large-effect QTL can be fine-mapped for further QTL cloning of yield-related traits in wheat.