Massively parallel reporter assay confirms regulatory potential of hQTLs and reveals important variants in lupus and other autoimmune diseases

We designed a massively parallel reporter assay (MPRA) in an Epstein-Barr virus transformed B cell line to directly characterize the potential for histone post-translational modifications, i.e., histone quantitative trait loci (hQTLs), expression QTLs (eQTLs), and variants on systemic lupus erythematosus (SLE) and autoimmune (AI) disease risk haplotypes to modulate regulatory activity in an allele-dependent manner. Our study demonstrates that hQTLs, as a group, are more likely to modulate regulatory activity in an MPRA compared with other variant classes tested, including a set of eQTLs previously shown to interact with hQTLs and tested AI risk variants. In addition, we nominate 17 variants (including 11 previously unreported) as putative causal variants for SLE and another 14 for various other AI diseases, prioritizing these variants for future functional studies in primary and immortalized B cells. Thus, we uncover important insights into the mechanistic relationships among genotype, epigenetics, and gene expression in SLE and AI disease phenotypes.

Liver regulatory mechanisms of noncoding variants at lipid and metabolic trait loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for liver disease and lipid-related metabolic traits, although identifying their target genes and molecular mechanisms remains challenging. We predicted target genes at GWAS signals by integrating them with molecular quantitative trait loci for liver gene expression (eQTL) and liver chromatin accessibility QTL (caQTL). We predicted specific regulatory caQTL variants at four GWAS signals located near EFHD1, LITAF, ZNF329, and GPR180. Using transcriptional reporter assays, we determined that caQTL variants rs13395911, rs11644920, rs34003091, and rs9556404 exhibit allelic differences in regulatory activity. We also performed a protein binding assay for rs13395911 and found that FOXA2 differentially interacts with the alleles of rs13395911. For variants rs13395911 and rs11644920 in putative enhancer regulatory elements, we used CRISPRi to demonstrate that repression of the enhancers altered the expression of the predicted target and/or nearby genes. Repression of the element at rs13395911 reduced the expression of EFHD1, and repression of the element at rs11644920 reduced the expression of LITAF, SNN, and TXNDC11. Finally, we showed that EFHD1 is a metabolically active gene in HepG2 cells. Together, these results provide key steps to connect genetic variants with cellular mechanisms and help elucidate the causes of liver disease.

Shaping immunity: The influence of natural selection on population immune diversity

Humans exhibit considerable variability in their immune responses to the same immune challenges. Such variation is widespread and affects individual and population-level susceptibility to infectious diseases and immune disorders. Although the factors influencing immune response diversity are partially understood, what mechanisms lead to the wide range of immune traits in healthy individuals remain largely unexplained. Here, we discuss the role that natural selection has played in driving phenotypic differences in immune responses across populations and present-day susceptibility to immune-related disorders. Further, we touch on future directions in the field of immunogenomics, highlighting the value of expanding this work to human populations globally, the utility of modeling the immune response as a dynamic process, and the importance of considering the potential polygenic nature of natural selection. Identifying loci acted upon by evolution may further pinpoint variants critically involved in disease etiology, and designing studies to capture these effects will enrich our understanding of the genetic contributions to immunity and immune dysregulation.

Yield-related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton

Salinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield-component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D-value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY-Chr6-2, qBNP-Chr4-1, qBNP-Chr12-1, qBNP-Chr15-5, qLP-Chr19-2) detected in both in E1 and D-value were salt related QTL, and three stable QTL (qLP-Chr5-3, qLP-Chr13-1, qBW-Chr5-5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP-Chr5-3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor-effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP-Chr4-1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.

Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

Quantitative genetic analysis of attractiveness of yeast products to Drosophila

An attractive perfume is a complex mixture of compounds, some of which may be unpleasant on their own. This is also true for the volatile combinations from yeast fermentation products in vineyards and orchards when assessed by Drosophila. Here we used crosses between a yeast strain with an attractive fermentation profile and another strain with a repulsive one and tested flies responses using a T-maze. QTL analysis reveals allelic variation in four yeast genes, PTC6, SAT4, YFL040W, and ARI1, that modulated expression levels of volatile compounds (assessed by GC-MS) and in different combinations, generated various levels of attractiveness. The parent strain that is more attractive to Drosophila has repulsive alleles at two of the loci while the least attractive parent has attractive alleles. Behavioral assays using artificial mixtures mimicking the composition of odors from fermentation validated the results of GC-MS and QTL mapping, thereby directly connecting genetic variation in yeast to attractiveness in flies. This study can be used as a basis for dissecting the combination of olfactory receptors that mediate the attractiveness/repulsion of flies to yeast volatiles and may also serve as a model for testing the attractiveness of pest species such as Drosophila suzukii to their host fruit.

Quantitative Trait Loci Mapping for Bacterial Wilt Resistance and Plant Height in Tomatoes

Bacterial wilt (BW) of tomatoes, caused by Ralstonia solanacearum, is a devastating disease that results in large annual yield losses worldwide. Management of BW of tomatoes is difficult due to the soil-borne nature of the pathogen. One of the best ways to mitigate the losses is through breeding for disease resistance. Moreover, plant height (PH) is a crucial element related to plant architecture, which determines nutrient management and mechanical harvesting in tomatoes. An intraspecific F2 segregating population (NC 11212) of tomatoes was developed by crossing NC 84173 (tall, BW susceptible) × CLN1466EA (short, BW resistant). We performed quantitative trait loci (QTL) mapping using single nucleotide polymorphic (SNP) markers and the NC 11212 F2 segregating population. The QTL analysis for BW resistance revealed a total of three QTLs on chromosomes 1, 2, and 3, explaining phenotypic variation (R2) ranging from 3.6% to 14.9%, whereas the QTL analysis for PH also detected three QTLs on chromosomes 1, 8, and 11, explaining R2 ranging from 7.1% to 11%. This work thus provides information to improve BW resistance and plant architecture-related traits in tomatoes.

Identification of additional body weight QTLs in the Berlin Fat Mouse BFMI861 lines using time series data

The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and metabolic syndrome. The sublines BFMI861-S1 and BFMI861-S2 differ in weight despite high genetic similarity and a shared obesity-related locus. This study focused on identifying additional body weight quantitative trait loci (QTLs) by analyzing weekly weight measurements in a male population of the advanced intercross line BFMI861-S1 x BFMI861-S2. QTL analysis, utilizing 200 selectively genotyped mice (GigaMUGA) and 197 males genotyped for top SNPs, revealed a genome-wide significant QTL on Chr 15 (68.46 to 81.40 Mb) for body weight between weeks 9 to 20. Notably, this QTL disappeared (weeks 21 to 23) and reappeared (weeks 24 and 25) coinciding with a diet change. Additionally, a significant body weight QTL on Chr 16 (3.89 to 22.79 Mb) was identified from weeks 6 to 25. Candidate genes, including Gpt, Cbx6, Apol6, Apol8, Sun2 (Chr 15) and Trap1, Rrn3, Mapk1 (Chr 16), were prioritized. This study unveiled two additional body weight QTLs, one of which is novel and responsive to diet changes. These findings illuminate genomic regions influencing weight in BFMI and emphasize the utility of time series data in uncovering novel genetic factors.

Finding genes and pathways that underlie coral adaptation

Mass coral bleaching is one of the clearest threats of climate change to the persistence of marine biodiversity. Despite the negative impacts of bleaching on coral health and survival, some corals may be able to rapidly adapt to warming ocean temperatures. Thus, a significant focus in coral research is identifying the genes and pathways underlying coral heat adaptation. Here, we review state-of-the-art methods that may enable the discovery of heat-adaptive loci in corals and identify four main knowledge gaps. To fill these gaps, we describe an experimental approach combining seascape genomics with CRISPR/Cas9 gene editing to discover and validate heat-adaptive loci. Finally, we discuss how information on adaptive genotypes could be used in coral reef conservation and management strategies.

A high-density linkage map construction in guava (Psidium guajava L.) using genotyping by sequencing and identification of QTLs for leaf, peel, and pulp color in an intervarietal mapping population

Psidium guajava L. is an important fruit crop in the tropical and subtropical regions of the world. The advanced breeding methods are not employed for important commercial traits like peel and pulp color, seed hardiness, fruit size, etc., due to the scarcity of genome-wide molecular markers and high-density linkage maps. In this study, we employed single-nucleotide polymorphism (SNP) markers and identified quantitative trait loci (QTL) regions that are associated with color traits of leaf, peel, and pulp in the guava intervarietal mapping population. The mapping population was developed from the contrasting genotypes of fruit and leaf color. Variations in color among the segregating hybrids were recorded both visually and using a Color reader. A high-density linkage map of guava was constructed using the SNP markers from genotyping by sequencing (GBS) of 150 hybrid individuals of the cross 'Arka Poorna' (green) x 'Purple Local' (purple). The integrated linkage map consisted of 1426 SNPs mapped on 11 linkage groups (LG), spanning a total distance of around 730 cM with an average of 129.6 markers per LG. Through QTL analysis for color traits, a minor QTL region was identified for visually scored leaf color and peel color on LG1, whereas a major QTL was detected for pulp color in LG4. The Hunter color values (L* and, a*) also had major QTLs with overlapping marker intervals for leaf and peel colors, establishing the association of SNP markers to the trait. The QTLs harbored genes and transcription factors involved in lycopene and anthocyanin pigment biosynthesis. This is the first report of a high-density linkage map based on SNP markers in guava and QTL mapping for color characters in leaf, fruit peel and pulp. The genotyping information generated in this study can aid in genetic engineering and marker-assisted breeding in guava.

Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.)

The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.

A genetic variant in the immune-related gene ERAP1 affects colorectal cancer prognosis

BACKGROUND

Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism.

METHODS

We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments.

RESULTS

The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 ( ERAP1 ) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1 . The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes.

CONCLUSION

The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1 .

TRIAL REGISTRATION

No. NCT00454519 ( https://clinicaltrials.gov/ ).

A landscape of gene expression regulation for synovium in arthritis

The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.

Dissection of the E8 locus in two early maturing Canadian soybean populations

Soybean [Glycine max (L.) Merr.] is a short-day crop for which breeders want to expand the cultivation range to more northern agro-environments by introgressing alleles involved in early reproductive traits. To do so, we investigated quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) regions comprised within the E8 locus, a large undeciphered region (~7.0 Mbp to 44.5 Mbp) associated with early maturity located on chromosome GM04. We used a combination of two mapping algorithms, (i) inclusive composite interval mapping (ICIM) and (ii) genome-wide composite interval mapping (GCIM), to identify major and minor regions in two soybean populations (QS15524F2:F3 and QS15544RIL) having fixed E1, E2, E3, and E4 alleles. Using this approach, we identified three main QTL regions with high logarithm of the odds (LODs), phenotypic variation explained (PVE), and additive effects for maturity and pod-filling within the E8 region: GM04:16,974,874-17,152,230 (E8-r1); GM04:35,168,111-37,664,017 (E8-r2); and GM04:41,808,599-42,376,237 (E8-r3). Using a five-step variant analysis pipeline, we identified Protein far-red elongated hypocotyl 3 (Glyma.04G124300; E8-r1), E1-like-a (Glyma.04G156400; E8-r2), Light-harvesting chlorophyll-protein complex I subunit A4 (Glyma.04G167900; E8-r3), and Cycling dof factor 3 (Glyma.04G168300; E8-r3) as the most promising candidate genes for these regions. A combinatorial eQTL mapping approach identified significant regulatory interactions for 13 expression traits (e-traits), including Glyma.04G050200 (Early flowering 3/E6 locus), with the E8-r3 region. Four other important QTL regions close to or encompassing major flowering genes were also detected on chromosomes GM07, GM08, and GM16. In GM07:5,256,305-5,404,971, a missense polymorphism was detected in the candidate gene Glyma.07G058200 (Protein suppressor of PHYA-105). These findings demonstrate that the locus known as E8 is regulated by at least three distinct genomic regions, all of which comprise major flowering genes.

Dissecting quantitative trait nucleotides by saturation genome editing

Genome editing technologies have the potential to transform our understanding of how genetic variation gives rise to complex traits through the systematic engineering and phenotypic characterization of genetic variants. However, there has yet to be a system with sufficient efficiency, fidelity, and throughput to comprehensively identify causal variants at the genome scale. Here we explored the ability of templated CRISPR editing systems to install natural variants genome-wide in budding yeast. We optimized several approaches to enhance homology-directed repair (HDR) with donor DNA templates, including donor recruitment to target sites, single-stranded donor production by bacterial retrons, and in vivo plasmid assembly. We uncovered unique advantages of each system that we integrated into a single superior system named MAGESTIC 3.0. We used MAGESTIC 3.0 to dissect causal variants residing in 112 quantitative trait loci across 32 environmental conditions, revealing an enrichment for missense variants and loci with multiple causal variants. MAGESTIC 3.0 will facilitate the functional analysis of the genome at single-nucleotide resolution and provides a roadmap for improving template-based genome editing systems in other organisms.

Genome-Wide Association Study Reveals a QTL Region for Ashy Stem Blight Resistance in PRA154 Andean Common Bean

Ashy stem blight (ASB) caused by Macrophomina phaseolina (Tassi) Goidanich affects the common bean (Phaseolus vulgaris L.) at all growing stages. Higher levels of resistance were observed in Andean common beans, but specific resistant quantitative trait loci (QTLs) conferring resistance to this pathogen have not been reported in this gene pool. The objectives of this research were to: (i) conduct a genome-wide association study (GWAS) and QTL mapping for resistance in the Andean breeding line PRA154; and (ii) identify single nucleotide polymorphism (SNP) markers and candidate genes for ASB resistance. Phenotyping was conducted under greenhouse conditions by inoculating the 107 F6:7 recombinant inbred lines (RILs) derived from the cross between the susceptible cultivar 'Verano' and the partial-resistant breeding line PRA154 twice with the M. phaseolina isolate PRI21. Genotyping was performed with 109,040 SNPs distributed across all 11 P. vulgaris chromosomes. A novel major QTL was located between 28,761,668 and 31,263,845 bp, extending 2.5 Mbp on chromosome Pv07, and the highest significant SNP markers were Chr07_28761668_A_G, Chr07_29131720_G_A, and Chr07_31263845_C_T with the highest LOD (more than 10 in most of the cases) and R-squared values, explaining 40% of the phenotypic variance of the PRI21 isolate. The gene Phvul.007G173900 (methylcrotonyl-CoA carboxylase alpha chain and mitochondrial 3-methylcrotonyl-CoA carboxylase 1 [MCCA]) with a size of 10,891 bp, located between 29,131,591 and 29,142,481 bp on Pv07, was identified as one candidate for ASB resistance in PRA154, and it contained Chr07_29131720_G_A. The QTL and genetic marker information could be used to assist common bean breeders to develop germplasm and cultivars with ASB resistance through molecular breeding.

Genomic Regions Associated with Resistance to Gastrointestinal Nematode Parasites in Sheep-A Review

Gastrointestinal nematodes (GINs) can be a major constraint and global challenge to the sheep industry. These nematodes infect the small intestine and abomasum of grazing sheep, causing symptoms such as weight loss, diarrhea, hypoproteinemia, and anemia, which can lead to death. The use of anthelmintics to treat infected animals has led to GIN resistance, and excessive use of these drugs has resulted in residue traced in food and the environment. Resistance to GINs can be measured using multiple traits, including fecal egg count (FEC), Faffa Malan Chart scores, hematocrit, packed cell volume, eosinophilia, immunoglobulin (Ig), and dagginess scores. Genetic variation among animals exists, and understanding these differences can help identify genomic regions associated with resistance to GINs in sheep. Genes playing important roles in the immune system were identified in several studies in this review, such as the CFI and MUC15 genes. Results from several studies showed overlapping quantitative trait loci (QTLs) associated with multiple traits measuring resistance to GINs, mainly FEC. The discovery of genomic regions, positional candidate genes, and QTLs associated with resistance to GINs can help increase and accelerate genetic gains in sheep breeding programs and reveal the genetic basis and biological mechanisms underlying this trait.

Conjunctive Analysis of BSA-Seq and SSR Markers Unveil the Candidate Genes for Resistance to Rice False Smut

Rice false smut (RFS) caused by the fungus Ustilaginoidea virens (Cook) leads to serious yield losses in rice. Identification of the gene or quantitative trait loci (QTLs) is crucial to resistance breeding and mitigation of RFS damage. In this study, we crossed a resistant variety, IR77298-14-1-2::IRGC117374-1, with a susceptible indica cultivar, 9311, and evaluated recombinant inbred lines in a greenhouse. The genetic analysis showed that the RFS resistance of IR77298-14-1-2::IRGC117374-1 was controlled by multiple recessive loci. We identified a novel QTL, qRFS12.01, for RFS resistance in IR77298-14-1-2::IRGC117374-1 by combining bulked segregant analysis with whole genome resequencing (BSA-seq) and simple sequence repeat (SSR) marker mapping approaches. The phenotypic effect of qRFS12.01 on RFS resistance reached 28.74%, suggesting that SSR markers linked to qRFS12.01 are valuable for marker-assisted breeding of RFS resistance in rice. The prediction of putative candidate genes within qRFS12.01 revealed five disease resistance proteins containing NB-ARC domains. In conclusion, our findings provide a new rice chromosome region carrying genes/QTLs for resistance to RFS.

QTL Detection and Candidate Gene Identification for Eating and Cooking Quality Traits in Rice (Oryza sativa L.) via a Genome-Wide Association Study

The eating and cooking quality (ECQ) directly affects the taste of rice, being closely related to factors such as gelatinization temperature (GT), gel consistency (GC) and amylose content (AC). Mining the quantitative trait loci (QTLs), and gene loci controlling ECQ-related traits is vital. A genome-wide association study on ECQ-related traits was conducted, combining 1.2 million single nucleotide polymorphisms (SNPs) with the phenotypic data of 173 rice accessions. Two QTLs for GT, one for GC and five for AC were identified, of which two were found in previously reported genes, and six were newly found. There were 28 positional candidate genes in the region of qAC11. Based on a linkage disequilibrium (LD) analysis, three candidate genes were screened within the LD region associated with AC. There were significant differences between the haplotypes of LOC_Os11g10170, but no significant differences were found for the other two genes. The qRT-PCR results showed that the gene expression levels in the accessions with high ACs were significantly larger than those in the accessions with low ACs at 35d and 42d after flowering. Hap 2 and Hap 3 of LOC_Os11g10170 reduced the AC by 13.09% and 10.77%, respectively. These results provide a theoretical and material basis for improving the ECQ of rice.

The role of gonadal hormones and sex chromosomes in sex-dependent effects of early nutrition on metabolic health

Early-life conditions such as prenatal nutrition can have long-term effects on metabolic health, and these effects may differ between males and females. Understanding the biological mechanisms underlying sex differences in the response to early-life environment will improve interventions, but few such mechanisms have been identified, and there is no overall framework for understanding sex differences. Biological sex differences may be due to chromosomal sex, gonadal sex, or interactions between the two. This review describes approaches to distinguish between the roles of chromosomal and gonadal sex, and summarizes findings regarding sex differences in metabolism. The Four Core Genotypes (FCG) mouse model allows dissociation of the sex chromosome genotype from gonadal type, whereas the XY* mouse model can be used to distinguish effects of X chromosome dosage vs the presence of the Y chromosome. Gonadectomy can be used to distinguish between organizational (permanent) and activational (reversible) effects of sex hormones. Baseline sex differences in a variety of metabolic traits are influenced by both activational and organizational effects of gonadal hormones, as well as sex chromosome complement. Thus far, these approaches have not been widely applied to examine sex-dependent effects of prenatal conditions, although a number of studies have found activational effects of estradiol to be protective against the development of hypertension following early-life adversity. Genes that escape X chromosome inactivation (XCI), such as Kdm5c, contribute to baseline sex-differences in metabolism, while Ogt, another XCI escapee, leads to sex-dependent responses to prenatal maternal stress. Genome-wide approaches to the study of sex differences include mapping genetic loci influencing metabolic traits in a sex-dependent manner. Seeking enrichment for binding sites of hormone receptors among genes showing sexually-dimorphic expression can elucidate the relative roles of hormones. Using the approaches described herein to identify mechanisms underlying sex-dependent effects of early nutrition on metabolic health may enable the identification of fundamental mechanisms and potential interventions.

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants' defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

Integration of genome-wide association study, linkage analysis, and population transcriptome analysis to reveal the TaFMO1-5B modulating seminal root growth in bread wheat

Bread wheat, one of the keystone crops for global food security, is challenged by climate change and resource shortage. The root system plays a vital role in water and nutrient absorption, making it essential for meeting the growing global demand. Here, using an association-mapping population composed of 406 accessions, we identified QTrl.Rs-5B modulating seminal root development with a genome-wide association study and validated its genetic effects with two F5 segregation populations. Transcriptome-wide association study prioritized TaFMO1-5B, a gene encoding the flavin-containing monooxygenases, as the causal gene for QTrl.Rs-5B, whose expression levels correlate negatively with the phenotyping variations among our population. The lines silenced for TaFMO1-5B consistently showed significantly larger seminal roots in different genetic backgrounds. Additionally, the agriculture traits measured in multiple environments showed that QTrl.Rs-5B also affects yield component traits and plant architecture-related traits, and its favorable haplotype modulates these traits toward that of modern cultivars, suggesting the application potential of QTrl.Rs-5B for wheat breeding. Consistently, the frequency of the favorable haplotype of QTrl.Rs-5B increased with habitat expansion and breeding improvement of bread wheat. In conclusion, our findings identified and demonstrated the effects of QTrl.Rs-5B on seminal root development and illustrated that it is a valuable genetic locus for wheat root improvement.

Quantitative Trait Loci Mapping Identified Candidate Genes Involved in Plant Height Regulation in Rice

Rice plant height is an agricultural trait closely related to biomass, lodging tolerance, and yield. Identifying quantitative trait loci (QTL) regions related to plant height regulation and developing strategies to screen potential candidate genes can improve agricultural traits in rice. In this study, a double haploid population (CNDH), derived by crossing 'Cheongcheong' and 'Nagdong' individuals, was used, and a genetic map was constructed with 222 single-sequence repeat markers. In the RM3482-RM212 region on chromosome 1, qPh1, qPh1-1, qPh1-3, qPh1-5, and qPh1-6 were identified for five consecutive years. The phenotypic variance explained ranged from 9.3% to 13.1%, and the LOD score ranged between 3.6 and 17.6. OsPHq1, a candidate gene related to plant height regulation, was screened in RM3482-RM212. OsPHq1 is an ortholog of gibberellin 20 oxidase 2, and its haplotype was distinguished by nine SNPs. Plants were divided into two groups based on their height, and tall and short plants were distinguished and clustered according to the expression level of OsPHq1. QTLs and candidate genes related to plant height regulation, and thus, biomass regulation, were screened and identified in this study, but the molecular mechanism of the regulation remains poorly known. The information obtained in this study will help develop molecular markers for marker-assisted selection and breeding through rice plant height control.

Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize

Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Candidate genes for field resistance to cassava brown streak disease revealed through the analysis of multiple data sources

Cassava (Manihot esculenta Crantz) is a food and industrial storage root crop with substantial potential to contribute to managing risk associated with climate change due to its inherent resilience and in providing a biodegradable option in manufacturing. In Africa, cassava production is challenged by two viral diseases, cassava brown streak disease (CBSD) and cassava mosaic disease. Here we detect quantitative trait loci (QTL) associated with CBSD in a biparental mapping population of a Tanzanian landrace, Nachinyaya and AR37-80, phenotyped in two locations over three years. The purpose was to use the information to ultimately facilitate either marker-assisted selection or adjust weightings in genomic selection to increase the efficiency of breeding. Results from this study were considered in relation to those from four other biparental populations, of similar genetic backgrounds, that were phenotyped and genotyped simultaneously. Further, we investigated the co-localization of QTL for CBSD resistance across populations and the genetic relationships of parents based on whole genome sequence information. Two QTL on chromosome 4 for resistance to CBSD foliar symptoms and one on each of chromosomes 11 and 18 for root necrosis were of interest. Of significance within the candidate genes underlying the QTL on chromosome 4 are Phenylalanine ammonia-lyase (PAL) and Cinnamoyl-CoA reductase (CCR) genes and three PEPR1-related kinases associated with the lignin pathway. In addition, a CCR gene was also underlying the root necrosis-resistant QTL on chromosome 11. Upregulation of key genes in the cassava lignification pathway from an earlier transcriptome study, including PAL and CCR, in a CBSD-resistant landrace compared to a susceptible landrace suggests a higher level of basal lignin deposition in the CBSD-resistant landrace. Earlier RNAscope® in situ hybridisation imaging experiments demonstrate that cassava brown streak virus (CBSV) is restricted to phloem vessels in CBSV-resistant varieties, and phloem unloading for replication in mesophyll cells is prevented. The results provide evidence for the involvement of the lignin pathway. In addition, five eukaryotic initiation factor (eIF) genes associated with plant virus resistance were found within the priority QTL regions.

Alternative SNP weighting for multi-step and single-step genomic BLUP in the presence of causative variants

The accuracy of genetic selection in dairy can be increased by the adoption of new technologies, such as the inclusion of sequence data. In simulation studies, assigning different weights to causative single-nucleotide polymorphism (SNP) markers led to better predictions depending on the genomic prediction method used. However, it is still not clear how the weights should be calculated. Our objective was to evaluate the accuracy of a multi-step method (GBLUP) and single-step GBLUP with simulated data using regular SNP, causatives variants (QTN) and the combination of both. Additionally, we compared the accuracies of all previous scenarios using alternatives for SNP weighting. The data were simulated assuming a single trait with a heritability of 0.3. The effective population size (Ne) was approximately 200. The pedigree contained 440,000 animals, and approximately 16,800 individuals were genotyped. A total of 49,974 SNP markers were evenly placed throughout the genome, and 100, 1000 and 2000 causative QTN were simulated. Both GBLUP and ssGBLUP were used in this study. We evaluated quadratic and nonlinear SNP weights in addition to the unweighted G. The inclusion of QTN to panels led to significant accuracy gains. Nonlinear A was demonstrated to be superior to quadratic weighting and unweighted approaches; however, results from Nonlinear A were dependent on the equation parameters. The unweighted approach was more suitable for less polygenic scenarios. Finally, SNP weighting might help elucidate trait architecture features based on changes in the accuracy of genomic prediction.

Corrigendum: Seed coat pattern QTL and development in cowpea (Vigna unguiculata [L.] Walp.)

[This corrects the article DOI: 10.3389/fpls.2019.01346.].

Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Glycine max (L.) Merr.)

The nutritional value of soybean [Glycine max (L.) Merr.] for animals is influenced by soluble carbohydrates, such as sucrose and stachyose. Although sucrose is nutritionally desirable, stachyose is an antinutrient causing diarrhea and flatulence in non-ruminant animals. We conducted a genome-wide association study of 220 soybean accessions using 21,317 single nucleotide polymorphisms (SNPs) from the SoySNP50K iSelect Beadchip data to identify significant SNPs associated with sucrose and stachyose content. Seven significant SNPs were identified for sucrose content across chromosomes (Chrs.) 2, 8, 12, 17, and 20, while thirteen significant SNPs were identified for stachyose content across Chrs. 2, 5, 8, 9, 10, 13, 14, and 15. Among those significant SNPs, three sucrose-related SNPs on Chrs. 8 and 17 were novel, while twelve stachyose-related SNPs on Chrs. 2, 5, 8, 9, 10, 13, 14, and 15 were novel. Based on Phytozome, STRING, and GO annotation, 17 and 24 candidate genes for sucrose and stachyose content, respectively, were highly associated with the carbohydrate metabolic pathway. Among these, the publicly available RNA-seq Atlas database highlighted four candidate genes associated with sucrose (Glyma.08g361200 and Glyma.17g258100) and stachyose (Glyma.05g025300 and Glyma.13g077900) content, which had higher gene expression levels in developing seed and multiple parts of the soybean plant. The results of this study will extend knowledge of the molecular mechanism and genetic basis underlying sucrose and stachyose content in soybean seed. Furthermore, the novel candidate genes and SNPs can be valuable genetic resources that soybean breeders may utilize to modify carbohydrate profiles for animal and human usage.

A haplotype-resolved chromosome-scale genome for Quercus rubra L. provides insights into the genetics of adaptive traits for red oak species

Northern red oak (Quercus rubra L.) is an ecologically and economically important forest tree native to North America. We present a chromosome-scale genome of Q. rubra generated by the combination of PacBio sequences and chromatin conformation capture (Hi-C) scaffolding. This is the first reference genome from the red oak clade (section Lobatae). The Q. rubra assembly spans 739 Mb with 95.27% of the genome in 12 chromosomes and 33,333 protein-coding genes. Comparisons to the genomes of Quercus lobata and Quercus mongolica revealed high collinearity, with intrachromosomal structural variants present. Orthologous gene family analysis with other tree species revealed that gene families associated with defense response were expanding and contracting simultaneously across the Q. rubra genome. Quercus rubra had the most CC-NBS-LRR and TIR-NBS-LRR resistance genes out of the 9 species analyzed. Terpene synthase gene family comparisons further reveal tandem gene duplications in TPS-b subfamily, similar to Quercus robur. Phylogenetic analysis also identified 4 subfamilies of the IGT/LAZY gene family in Q. rubra important for plant structure. Single major QTL regions were identified for vegetative bud break and marcescence, which contain candidate genes for further research, including a putative ortholog of the circadian clock constituent cryptochrome (CRY2) and 8 tandemly duplicated genes for serine protease inhibitors, respectively. Genome-environment associations across natural populations identified candidate abiotic stress tolerance genes and predicted performance in a common garden. This high-quality red oak genome represents an essential resource to the oak genomic community, which will expedite comparative genomics and biological studies in Quercus species.

Dissecting genomic regions and underlying sheath blight resistance traits in rice (Oryza sativa L.) using a genome-wide association study

The productivity of rice is greatly affected by the infection of the plant pathogenic fungus Rhizoctonia solani, which causes a significant grain yield reduction globally. There exist a limited number of rice accessions that are available to develop sheath blight resistance (ShB). Our objective was to identify a good source of the ShB resistance, understand the heritability, and trait interactions, and identify the genomic regions for ShB resistance traits by genome-wide association studies (GWAS). In the present study, a set of 330 traditional landraces and improved rice varieties were evaluated for ShB resistance and created a core panel of 192 accessions used in the GWAS. This panel provides a more considerable amount of genetic variance and found a significant phenotypic variation among the panel of rice accessions for all the agro-morphological and disease-resistance traits over the seasons. The infection rate of ShB and disease reaction were calculated as percent disease index (PDI) and area under the disease progress curve (AUDPC). The correlation analysis showed a significant positive association between PDIs and AUPDC and a negative association between PDI and plant height, flag leaf length, and grain yield. The panel was genotyped with 133 SSR microsatellite markers, resulting in a genome coverage of 314.83 Mb, and the average distance between markers is 2.53 Mb. By employing GLM and MLM (Q + K) models, 30 marker-trait associations (MTAs) were identified with targeted traits over the seasons. Among these QTLs, eight were found to be novel and located on 2, 4, 8, 10, and 12 chromosomes, which explained the phenotypic variation ranging from 5% to 15%. With the GWAS approach, six candidate genes were identified. Os05t0566400, Os08t0155900, and Os09t0567300 were found to be associated with defense mechanisms against ShB. These findings provided insights into the novel donors of IC283139, IC 277248, Sivappuchithirai Kar, and Bowalia. The promising genomic regions on 10 of 12 chromosomes associated with ShB would be useful in developing rice varieties with durable disease resistance.

Molecular Marker-Assisted Mapping, Candidate Gene Identification, and Breeding in Melon (Cucumis melo L.): A Review

Melon (Cucumis melo L.) is an important crop that is cultivated worldwide for its fleshy fruit. Understanding the genetic basis of a plant's qualitative and quantitative traits is essential for developing consumer-favored varieties. This review presents genetic and molecular advances related to qualitative and quantitative phenotypic traits and biochemical compounds in melons. This information guides trait incorporation and the production of novel varieties with desirable horticultural and economic characteristics and yield performance. This review summarizes the quantitative trait loci, candidate genes, and development of molecular markers related to plant architecture, branching patterns, floral attributes (sex expression and male sterility), fruit attributes (shape, rind and flesh color, yield, biochemical compounds, sugar content, and netting), and seed attributes (seed coat color and size). The findings discussed in this review will enhance demand-driven breeding to produce cultivars that benefit consumers and melon breeders.

QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean

This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9-55.0), contributing 5.5-66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein-including starch, lipid, and fatty acid biosynthesis-related genes-were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content.

Genomics and Physiology of Chlorophyll Fluorescence Parameters in Hordeum vulgare L. under Drought and Salt Stresses

To map the genomic regions and control chlorophyll fluorescence attributes under normal, salinity-, and drought-stress conditions in barley (Hordeum vulgare L.) at the seedling stage, an experiment was conducted in 2019-2020 using 106 F8 lines resulting from the cross between Badia × Kavir. Initially, the different chlorophyll fluorescence parameters were evaluated. Under drought stress, the highest decrease was related to REo/CSm (59.56%), and the highest increase was related to dV/dto (77.17%). Also, under salinity stress, the highest decrease was related to Fv/Fo (59.56%), and the highest increase was related to DIo/RC (77.17%). Linkage maps were prepared using 152 SSR polymorphic markers, 72 ISSR alleles, 7 IRAP alleles, 29 CAAT alleles, 27 Scot alleles, and 15 iPBS alleles. The obtained map accounted for 999.2 centi-Morgans (cM) of the barley genome length (92% of the whole barley genome). The results indicated the importance of chromosomes 3, 2, and 7 in controlling ABS/CSm, Area, ETo/CSm, Fm, Fv, and ETo/RC under drought stress. qEToRCD-7, as a major QTL, controlled 18.3% of ETo/RC phenotypic variation under drought stress. Under salinity stress, the regions of chromosomes 2 and 7 (102 cM and 126 cM) controlled the parameters ABS/CSo, Fm, Fo, Fv, TRo/SCo, Area, ETo/CSm, and ETo/CSo. The results showed that chlorophyll fluorescence is an important parameter in the study of drought and salinity effects on barley. This is the first report of the investigation of changes in the genetic structure of quantitative genes controlling the fluorescence parameters associated with barley response to drought and salinity stresses in the Iranian barley RILs population. According to the obtained results, it is possible to use HVPLASC1B and EBmac0713 in normal conditions, ISSR21-2 and ISSR30-4 in drought conditions, and Bmac0047, Scot5-B, CAAT6-C, and ISSR30iPBS2076-4 in saline stress conditions to select genotypes with higher photosynthetic capacity in marker-assisted selection programs.

Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance

Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.

Identification of genomic loci regulating platelet plasminogen activator inhibitor-1 in mice

BACKGROUND

Plasminogen activator inhibitor-1 (PAI-1, Serpine1) is an important circulating fibrinolysis inhibitor. PAI-1 exists in 2 pools, packaged within platelet α-granules and freely circulating in plasma. Elevated plasma PAI-1 levels are associated with cardiovascular disease. However, little is known about the regulation of platelet PAI-1 (pPAI-1).

OBJECTIVES

We investigated the genetic control of pPAI-1 levels in mice and humans.

METHODS

We measured pPAI-1 antigen levels via enzyme-linked immunosorbent assay in platelets isolated from 10 inbred mouse strains, including LEWES/EiJ (LEWES) and C57BL/6J (B6). LEWES and B6 were crossed to produce the F1 generation, B6LEWESF1. B6LEWESF1 mice were intercrossed to produce B6LEWESF2 mice. These mice were subjected to genome-wide genetic marker genotyping followed by quantitative trait locus analysis to identify pPAI-1 regulatory loci.

RESULTS

We identified differences in pPAI-1 between several laboratory strains, with LEWES having pPAI-1 levels more than 10-fold higher than those in B6. Quantitative trait locus analysis of B6LEWESF2 offspring identified a major pPAI-1 regulatory locus on chromosome 5 from 136.1 to 137.6 Mb (logarithm of the odds score, 16.2). Significant pPAI-1 modifier loci on chromosomes 6 and 13 were also identified.

CONCLUSION

Identification of pPAI-1 genomic regulatory elements provides insights into platelet/megakaryocyte-specific and cell type-specific gene expression. This information can be used to design more precise therapeutic targets for diseases where PAI-1 plays a role.

Plasma proteomic associations with genetics and health in the UK Biobank

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Harnessing the Genetic Basis of Sorghum Biomass-Related Traits to Facilitate Bioenergy Applications

The extensive use of fossil fuels and global climate change have raised ever-increasing attention to sustainable development, global food security and the replacement of fossil fuels by renewable energy. Several C4 monocot grasses have excellent photosynthetic ability, stress tolerance and may rapidly produce biomass in marginal lands with low agronomic inputs, thus representing an important source of bioenergy. Among these grasses, Sorghum bicolor has been recognized as not only a promising bioenergy crop but also a research model due to its diploidy, simple genome, genetic diversity and clear orthologous relationship with other grass genomes, allowing sorghum research to be easily translated to other grasses. Although sorghum molecular genetic studies have lagged far behind those of major crops (e.g., rice and maize), recent advances have been made in a number of biomass-related traits to dissect the genetic loci and candidate genes, and to discover the functions of key genes. However, molecular and/or targeted breeding toward biomass-related traits in sorghum have not fully benefited from these pieces of genetic knowledge. Thus, to facilitate the breeding and bioenergy applications of sorghum, this perspective summarizes the bioenergy applications of different types of sorghum and outlines the genetic control of the biomass-related traits, ranging from flowering/maturity, plant height, internode morphological traits and metabolic compositions. In particular, we describe the dynamic changes of carbohydrate metabolism in sorghum internodes and highlight the molecular regulators involved in the different stages of internode carbohydrate metabolism, which affects the bioenergy utilization of sorghum biomass. We argue the way forward is to further enhance our understanding of the genetic mechanisms of these biomass-related traits with new technologies, which will lead to future directions toward tailored designing sorghum biomass traits suitable for different bioenergy applications.

Mapping QTL for Mineral Accumulation and Shoot Dry Biomass in Barley under Different Levels of Zinc Supply

Zinc (Zn) deficiency is a common limiting factor in agricultural soils, which leads to significant reduction in both the yield and nutritional quality of agricultural produce. Exploring the quantitative trait loci (QTL) for shoot and grain Zn accumulation would help to develop new barley cultivars with greater Zn accumulation efficiency. In this study, two glasshouse experiments were conducted by growing plants under adequate and low Zn supply. From the preliminary screening of ten barley cultivars, Sahara (0.05 mg/pot) and Yerong (0.06 mg/pot) showed the lowest change in shoot Zn accumulation, while Franklin (0.16 mg/pot) had the highest change due to changes in Zn supply for plant growth. Therefore, the double haploid (DH) population derived from Yerong × Franklin was selected to identify QTL for shoot mineral accumulation and biomass production. A major QTL hotspot was detected on chromosome 2H between 31.91 and 73.12 cM encoding genes for regulating shoot mineral accumulations of Zn, Fe, Ca, K and P, and the biomass. Further investigation demonstrated 16 potential candidate genes for mineral accumulation, in addition to a single candidate gene for shoot biomass in the identified QTL region. This study provides a useful resource for enhancing nutritional quality and yield potential in future barley breeding programs.

ex Tan.) and Sweet Orange (C. × sinensis (L.) Osb.) Fruit Essential Oils

Despite their importance in food processing, perfumery and cosmetics, the inheritance of sweet orange aromatic compounds, as well as their yield in the fruit peel, has been little analyzed. In the present study, the segregation of aromatic compounds was studied in an F1 population of 77 hybrids resulting from crosses between clementine and blood sweet orange. Fruit-peel essential oils (PEOs) extracted by hydrodistillation were analyzed by gas chromatography coupled with flame ionization detection. Genotyping by sequencing was performed on the parents and the hybrids. The resulting "clementine × sweet blood orange" genetic map consists of 710 SNP markers distributed in nine linkage groups (LGs), representing the nine citrus chromosomes, and spanning 1054 centimorgans. Twenty quantitative trait loci (QTLs) were identified, explaining between 20.5 and 55.0% of the variance of the major aromatic compounds and PEO yield. The QTLs for monoterpenes and aliphatic aldehydes predominantly colocalized on LGs 5 and 8, as did the two QTLs for PEO yield. The sesquiterpene QTLs were located on LGs 1, 3, 6 and 8. The detection of major QTLs associated with the synthesis of aliphatic aldehydes, known for their strong aromatic properties, open the way for marker-assisted selection.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis

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 post-mortem 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 genetically mediated post-transcriptional regulation during brain development lead to differences in brain function.

Crucial aspects of metabolism and cell biology relating to industrial production and processing of Saccharomyces biomass

The multitude of applications to which Saccharomyces spp. are put makes these yeasts the most prolific of industrial microorganisms. This review considers biological aspects pertaining to the manufacture of industrial yeast biomass. It is proposed that the production of yeast biomass can be considered in two distinct but interdependent phases. Firstly, there is a cell replication phase that involves reproduction of cells by their transitions through multiple budding and metabolic cycles. Secondly, there needs to be a cell conditioning phase that enables the accrued biomass to withstand the physicochemical challenges associated with downstream processing and storage. The production of yeast biomass is not simply a case of providing sugar, nutrients, and other growth conditions to enable multiple budding cycles to occur. In the latter stages of culturing, it is important that all cells are induced to complete their current budding cycle and subsequently enter into a quiescent state engendering robustness. Both the cell replication and conditioning phases need to be optimized and considered in concert to ensure good biomass production economics, and optimum performance of industrial yeasts in food and fermentation applications. Key features of metabolism and cell biology affecting replication and conditioning of industrial Saccharomyces are presented. Alternatives for growth substrates are discussed, along with the challenges and prospects associated with defining the genetic bases of industrially important phenotypes, and the generation of new yeast strains."I must be cruel only to be kind: Thus bad begins, and worse remains behind." William Shakespeare: Hamlet, Act 3, Scene 4.

Skeletal Class II Malocclusion: From Clinical Treatment Strategies to the Roadmap in Identifying the Genetic Bases of Development in Humans with the Support of the Collaborative Cross Mouse Population

Depending on how severe it is, malocclusion, which may involve misaligned teeth, jaws, or a combination of the two, can hurt a person's overall facial aesthetics. The maxillary molar develops before the mandibular molar in class II malocclusion, which affects 15% of the population in the United States. With a retrusive mandible, patients typically have a convex profile. The goal of this study is to classify the skeletal and dental variability present in class II malocclusion, to reduce heterogeneity, present the current clinical treatment strategies, to summarize the previously published findings of genetic analysis, discuss these findings and their constraints, and finally, propose a comprehensive roadmap to facilitate investigations aimed at determining the genetic bases of malocclusion development using a variety of genomic approaches. To further comprehend the hereditary components involved in the onset and progression of class II malocclusion, a novel animal model for class II malocclusion should be developed while considering the variety of the human population. To overcome the constraints of the previous studies, here, we propose to conduct novel research on humans with the support of mouse models to produce contentious findings. We believe that carrying out a genome-wide association study (GWAS) on a large human cohort to search for significant genes and their modifiers; an epigenetics-wide association study (EWAS); RNA-seq analysis; integrating GWAS and the expression of quantitative trait loci (eQTL); and the testing of microRNAs, small RNAs, and long noncoding RNAs in tissues related to the skeletal class II malocclusion (SCIIMO) phenotype, such as mandibular bone, gum, and jaw in humans and the collaborative cross (CC) mouse model, will identify novel genes and genetic factors affecting this phenotype. We anticipate discovering novel genetic elements to advance our knowledge of how this malocclusion phenotype develops and open the venue for the early identification of patients carrying the susceptible genetic factors so that we can offer early prevention treatment strategies.

QTL discovery for resistance to black spot and cercospora leaf spot, and defoliation in two interconnected F1 bi-parental tetraploid garden rose populations

Garden roses are an economically important horticultural crop worldwide, and two major fungal pathogens, black spot (Diplocarpon rosae F.A. Wolf) and cercospora leaf spot of rose (Rosisphaerella rosicola Pass.), affect both the health and ornamental value of the plant. Most studies on black spot disease resistance have focused on diploid germplasm, and little work has been performed on cercospora leaf spot resistance. With the use of newly developed software tools for autopolyploid genetics, two interconnected tetraploid garden rose F1 populations (phenotyped over the course of 3 years) were used for quantitative trait locus (QTL) analysis of black spot and cercospora leaf spot resistance as well as plant defoliation. QTLs for black spot resistance were mapped to linkage groups (LGs) 1-6. QTLs for cercospora resistance and susceptibility were found in LGs 1, 4, and 5 and for defoliation in LGs 1, 3, and 5. The major locus on LG 5 for black spot resistance coincides with the previously discovered Rdr4 locus inherited from Rosa L. 'Radbrite' (Brite Eyes™), the common parent used in these mapping populations. This work is the first report of any QTL for cercospora resistance/susceptibility in tetraploid rose germplasm and the first report of defoliation QTL in roses. A major QTL for cercospora susceptibility coincides with the black spot resistance QTL on LG 5 (Rdr4). A major cercospora resistance QTL was found on LG 1. These populations provide a genetic resource that will further the knowledge base of rose genetics as more traits are studied. Studying more traits from these populations will allow for the stacking of various QTLs for desirable traits.

Intermediate Molecular Phenotypes to Identify Genetic Markers of Anthracycline-Induced Cardiotoxicity Risk

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex trait with a polygenic component that is mainly unidentified. We propose that levels of intermediate molecular phenotypes (IMPs) in the myocardium associated with histopathological damage could explain CDA susceptibility, so variants of genes encoding these IMPs could identify patients susceptible to this complication. Thus, a genetically heterogeneous cohort of mice (n = 165) generated by backcrossing were treated with doxorubicin and docetaxel. We quantified heart fibrosis using an Ariol slide scanner and intramyocardial levels of IMPs using multiplex bead arrays and QPCR. We identified quantitative trait loci linked to IMPs (ipQTLs) and cdaQTLs via linkage analysis. In three cancer patient cohorts, CDA was quantified using echocardiography or Cardiac Magnetic Resonance. CDA behaves as a complex trait in the mouse cohort. IMP levels in the myocardium were associated with CDA. ipQTLs integrated into genetic models with cdaQTLs account for more CDA phenotypic variation than that explained by cda-QTLs alone. Allelic forms of genes encoding IMPs associated with CDA in mice, including AKT1, MAPK14, MAPK8, STAT3, CAS3, and TP53, are genetic determinants of CDA in patients. Two genetic risk scores for pediatric patients (n = 71) and women with breast cancer (n = 420) were generated using machine-learning Least Absolute Shrinkage and Selection Operator (LASSO) regression. Thus, IMPs associated with heart damage identify genetic markers of CDA risk, thereby allowing more personalized patient management.

Genomics for Yield and Yield Components in Durum Wheat

In recent years, many efforts have been conducted to dissect the genetic basis of yield and yield components in durum wheat thanks to linkage mapping and genome-wide association studies. In this review, starting from the analysis of the genetic bases that regulate the expression of yield for developing new durum wheat varieties, we have highlighted how, currently, the reductionist approach, i.e., dissecting the yield into its individual components, does not seem capable of ensuring significant yield increases due to diminishing resources, land loss, and ongoing climate change. However, despite the identification of genes and/or chromosomal regions, controlling the grain yield in durum wheat is still a challenge, mainly due to the polyploidy level of this species. In the review, we underline that the next-generation sequencing (NGS) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms, as well as genome editing technology, will revolutionize plant breeding by providing a great opportunity to capture genetic variation that can be used in breeding programs. To date, genomic selection provides a valuable tool for modeling optimal allelic combinations across the whole genome that maximize the phenotypic potential of an individual under a given environment.

Distinct genetic origins of eumelanin intensity and barring patterns in cichlid fishes

Pigment patterns are incredibly diverse across vertebrates and are shaped by multiple selective pressures from predator avoidance to mate choice. A common pattern across fishes, but for which we know little about the underlying mechanisms, is repeated melanic vertical bars. In order to understand genetic factors that modify the level or pattern of vertical barring, we generated a genetic cross of 322 F2 hybrids between two cichlid species with distinct barring patterns, Aulonocara koningsi and Metriaclima mbenjii. We identify 48 significant quantitative trait loci that underlie a series of seven phenotypes related to the relative pigmentation intensity, and four traits related to patterning of the vertical bars. We find that genomic regions that generate variation in the level of eumelanin produced are largely independent of those that control the spacing of vertical bars. Candidate genes within these intervals include novel genes and those newly-associated with vertical bars, which could affect melanophore survival, fate decisions, pigment biosynthesis, and pigment distribution. Together, this work provides insights into the regulation of pigment diversity, with direct implications for an animal's fitness and the speciation process.