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.

Genetic basis of ecologically relevant body shape variation among four genera of cichlid fishes

Divergence in body shape is one of the most widespread and repeated patterns of morphological variation in fishes and is associated with habitat specification and swimming mechanics. Such ecological diversification is the first stage of the explosive adaptive radiation of cichlid fishes in the East African Rift Lakes. We use two hybrid crosses of cichlids (Metriaclima sp. × Aulonocara sp. and Labidochromis sp. × Labeotropheus sp., >975 animals total) to determine the genetic basis of body shape diversification that is similar to benthic-pelagic divergence across fishes. Using a series of both linear and geometric shape measurements, we identified 34 quantitative trait loci (QTL) that underlie various aspects of body shape variation. These QTL are spread throughout the genome, each explaining 3.2-8.6% of phenotypic variation, and are largely modular. Further, QTL are distinct both between these two crosses of Lake Malawi cichlids and compared to previously identified QTL for body shape in fishes such as sticklebacks. We find that body shape is controlled by many genes of small effect. In all, we find that convergent body shape phenotypes commonly observed across fish clades are most likely due to distinct genetic and molecular mechanisms.

Genetic Analysis and Physical Mapping of Oat Adult Plant Resistance Loci Against Puccinia coronata f. sp. avenae

Six quantitative trait loci (QTLs) for adult plant resistance against oat crown rust (Puccinia coronata f. sp. avenae) were identified from mapping three recombinant inbred populations. Using genotyping-by-sequencing with markers called against the OT3098 v1 reference genome, the QTLs were mapped on six different chromosomes: Chr1D, Chr4D, Chr5A, Chr5D, Chr7A, and Chr7C. Composite interval mapping with marker cofactor selection showed that the phenotypic variance explained by all identified QTLs for coefficient of infection range from 12.2 to 46.9%, whereas heritability estimates ranged from 0.11 to 0.38. The significant regions were narrowed down to intervals of 3.9 to 25 cM, equivalent to physical distances of 11 to 133 Mb. At least two flanking single-nucleotide polymorphism markers were identified within 10 cM of each QTL that could be used in marker-assisted introgression, pyramiding, and selection. The additive effects of the QTLs in each population were determined using single-nucleotide polymorphism haplotype data, which showed a significantly lower coefficient of infection in lines homozygous for the resistant alleles. Analysis of pairwise linkage disequilibrium also revealed high correlation of markers and presence of linkage blocks in the significant regions. To further facilitate marker-assisted breeding, polymerase chain reaction allelic competitive extension (PACE) markers for the adult plant resistance loci were developed. Putative candidate genes were also identified in each of the significant regions, which include resistance gene analogs that encode for kinases, ligases, and predicted receptors of avirulence proteins from pathogens.

Exploiting genetic and genomic resources to enhance productivity and abiotic stress adaptation of underutilized pulses

Underutilized pulses and their wild relatives are typically stress tolerant and their seeds are packed with protein, fibers, minerals, vitamins, and phytochemicals. The consumption of such nutritionally dense legumes together with cereal-based food may promote global food and nutritional security. However, such species are deficient in a few or several desirable domestication traits thereby reducing their agronomic value, requiring further genetic enhancement for developing productive, nutritionally dense, and climate resilient cultivars. This review article considers 13 underutilized pulses and focuses on their germplasm holdings, diversity, crop-wild-crop gene flow, genome sequencing, syntenic relationships, the potential for breeding and transgenic manipulation, and the genetics of agronomic and stress tolerance traits. Recent progress has shown the potential for crop improvement and food security, for example, the genetic basis of stem determinacy and fragrance in moth bean and rice bean, multiple abiotic stress tolerant traits in horse gram and tepary bean, bruchid resistance in lima bean, low neurotoxin in grass pea, and photoperiod induced flowering and anthocyanin accumulation in adzuki bean have been investigated. Advances in introgression breeding to develop elite genetic stocks of grass pea with low β-ODAP (neurotoxin compound), resistance to Mungbean yellow mosaic India virus in black gram using rice bean, and abiotic stress adaptation in common bean, using genes from tepary bean have been carried out. This highlights their potential in wider breeding programs to introduce such traits in locally adapted cultivars. The potential of de-domestication or feralization in the evolution of new variants in these crops are also highlighted.

campestris race 1 identified in Brassica oleracea

The production of Brassica oleracea, an important vegetable crop, is severely affected by black rot disease caused by the bacterial pathogen Xanthomonas campestris pv. campestris. Resistance to race 1, the most virulent and widespread race in B. oleracea, is under quantitative control; therefore, identifying the genes and genetic markers associated with resistance is crucial for developing resistant cultivars. Quantitative trait locus (QTL) analysis of resistance in the F₂ population developed by crossing the resistant parent BR155 with the susceptible parent SC31 was performed. Sequence GBS approach was used to develop a genetic linkage map. The map contained 7,940 single nucleotide polymorphism markers consisting of nine linkage groups spanning 675.64 cM with an average marker distance of 0.66 cM. The F_2:3 population (N = 126) was evaluated for resistance to black rot disease in summer (2020), fall (2020), and spring (2021). QTL analysis, using a genetic map and phenotyping data, identified seven QTLs with LOD values between 2.10 and 4.27. The major QTL, qCaBR1, was an area of overlap between the two QTLs identified in the 2^nd and 3^rd trials located at C06. Among the genes located in the major QTL interval, 96 genes had annotation results, and eight were found to respond to biotic stimuli. We compared the expression patterns of eight candidate genes in susceptible (SC31) and resistant (BR155) lines using qRT-PCR and observed their early and transient increases or suppression in response to Xanthomonas campestris pv. campestris inoculation. These results support the involvement of the eight candidate genes in black rot resistance. The findings of this study will contribute towards marker-assisted selection, additionally the functional analysis of candidate genes may elucidate the molecular mechanisms underlying black rot resistance in B. oleracea.

Identification of Novel QTLs/Defense Genes in Spring Wheat Germplasm Panel for Seedling and Adult Plant Resistance to Stem Rust and Their Validation Through KASP Marker Assays

Stem rust is one of the major diseases threatening wheat production globally. To identify novel resistance quantitative trait loci (QTLs), we performed 35K Axiom Array SNP genotyping assays on an association mapping panel of 400 germplasm accessions, including Indian landraces, in conjunction with phenotyping for stem rust at seedling and adult plant stages. Association analyses using three genome wide association study (GWAS) models (CMLM, MLMM, and FarmCPU) revealed 20 reliable QTLs for seedling and adult plant resistance. Among these 20 QTLs, five QTLs were found consistent with three models, i.e., four QTLs on chromosome 2AL, 2BL, 2DL, and 3BL for seedling resistance and one QTL on chromosome 7DS for adult plant resistance. Further, we identified a total of 21 potential candidate genes underlying QTLs using gene ontology analysis, including a leucine rich repeat receptor (LRR) and P-loop nucleoside triphosphate hydrolase, which have a role in pathogen recognition and disease resistance. Furthermore, four QTLs (Qsr.nbpgr-3B_11, QSr.nbpgr-6AS_11, QSr.nbpgr-2AL_117-6, and QSr.nbpgr-7BS_APR) were validated through KASP located on chromosomes 3B, 6A, 2A, and 7B. Out of these QTLs, QSr.nbpgr-7BS_APR was identified as a novel QTL for stem rust resistance which has been found effective in both seedling as well as the adult plant stages. Identified novel genomic regions and validated QTLs have the potential to be deployed in wheat improvement programs to develop disease resistant varieties for stem rust and can diversify the genetic basis of resistance.

A Comparison of Methods to Estimate Additive-by-Additive-by-Additive of QTL×QTL×QTL Interaction Effects by Monte Carlo Simulation Studies

The goal of the breeding process is to obtain new genotypes with traits improved over the parental forms. Parameters related to the additive effect of genes as well as their interactions (such as epistasis of gene-by-gene interaction effect and additive-by-additive-by-additive of gene-by-gene-by-gene interaction effect) can influence decisions on the suitability of breeding material for this purpose. Understanding the genetic architecture of complex traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-by-QTL interactions and QTL-by-QTL-by-QTL interactions. With regards to the comparing methods for estimating additive-by-additive-by-additive of QTL×QTL×QTL interaction effects by Monte Carlo simulation studies, there are no publications in the open literature. The parameter combinations assumed in the presented simulation studies represented 84 different experimental situations. The use of weighted regression may be the preferred method for estimating additive-by-additive-by-additive of QTL-QTL-QTL triples interaction effects, as it provides results closer to the true values of total additive-by-additive-by-additive interaction effects than using unweighted regression. This is also indicated by the obtained values of the determination coefficients of the proposed models.

Genetic Dissection of Extreme Seed-Flooding Tolerance in a Wild Soybean PI342618B by Linkage Mapping and Candidate Gene Analysis

Seed-flooding stress is one of major abiotic constraints that adversely affects soybean production worldwide. Identifying tolerant germplasms and revealing the genetic basis of seed-flooding tolerance are imperative goals for soybean breeding. In the present study, high-density linkage maps of two inter-specific recombinant inbred line (RIL) populations, named NJIRNP and NJIR4P, were utilized to identify major quantitative trait loci (QTLs) for seed-flooding tolerance using three parameters viz., germination rate (GR), normal seedling rate (NSR), and electrical conductivity (EC). A total of 25 and 18 QTLs were detected by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 12 common QTLs were identified through both methods. All favorable alleles for the tolerance are notably from the wild soybean parent. Moreover, four digenic epistatic QTL pairs were identified, and three of them showed no main effects. In addition, the pigmented soybean genotypes exhibited high seed-flooding tolerance compared with yellow seed coat genotypes in both populations. Moreover, out of five identified QTLs, one major region containing multiple QTLs associated with all three traits was identified on Chromosome 8, and most of the QTLs within this hotspot were major loci (R² > 10) and detectable in both populations and multiple environments. Based on the gene expression and functional annotation information, 10 candidate genes from QTL "hotspot 8-2" were screened for further analysis. Furthermore, the results of qRT-PCR and sequence analysis revealed that only one gene, GmDREB2 (Glyma.08G137600), was significantly induced under flooding stress and displayed a TTC tribasic insertion mutation of the nucleotide sequence in the tolerant wild parent (PI342618B). GmDREB2 encodes an ERF transcription factor, and the subcellular localization analysis using green fluorescent protein (GFP) revealed that GmDREB2 protein was localized in the nucleus and plasma membrane. Furthermore, overexpression of GmDREB2 significantly promoted the growth of soybean hairy roots, which might indicate its critical role in seed-flooding stress. Thus, GmDREB2 was considered as the most possible candidate gene for seed-flooding tolerance.

Fungal effectors versus defense-related genes of B. juncea and the status of resistant transgenics against fungal pathogens

Oilseed brassica has become instrumental in securing global food and nutritional security. B. juncea, colloquially known as Indian mustard, is cultivated across tropics and subtropics including Indian subcontinent. The production of Indian mustard is severely hampered by fungal pathogens which necessitates human interventions. Chemicals are often resorted to as they are quick and effective, but due to their economic and ecological unsustainability, there is a need to explore their alternatives. The B. juncea-fungal pathosystem is quite diverse as it covers broad-host range necrotrophs (Sclerotinia sclerotiorum), narrow-host range necrotrophs (Alternaria brassicae and A. brassicicola) and biotrophic oomycetes (Albugo candida and Hyaloperonospora brassica). Plants ward off fungal pathogens through two-step resistance mechanism; PTI which involves recognition of elicitors and ETI where the resistance gene (R gene) interacts with the fungal effectors. The hormonal signalling is also found to play a vital role in defense as the JA/ET pathway is initiated at the time of necrotroph infection and SA pathway is induced when the biotrophs attack plants. The review discuss the prevalence of fungal pathogens of Indian mustard and the studies conducted on effectoromics. It covers both pathogenicity conferring genes and host-specific toxins (HSTs) that can be used for a variety of purposes such as identifying cognate R genes, understanding pathogenicity and virulence mechanisms, and establishing the phylogeny of fungal pathogens. It further encompasses the studies on identifying resistant sources and characterisation of R genes/quantitative trait loci and defense-related genes identified in Brassicaceae and unrelated species which, upon introgression or overexpression, confer resistance. Finally, the studies conducted on developing resistant transgenics in Brassicaceae have been covered in which chitinase and glucanase genes are mostly used. The knowledge gained from this review can further be used for imparting resistance against major fungal pathogens.

Genome-wide aggregated trans-effects on risk of type 1 diabetes: A test of the "omnigenic" sparse effector hypothesis of complex trait genetics

The "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated through trans-effects on expression of a relatively sparse set of effector ("core") genes. We tested this hypothesis in a study of 4,964 cases of type 1 diabetes (T1D) and 7,497 controls by using summary statistics to calculate aggregated (excluding the HLA region) trans-scores for gene expression in blood. From associations of T1D with aggregated trans-scores, nine putative core genes were identified, of which three-STAT1, CTLA4 and FOXP3-are genes in which variants cause monogenic forms of autoimmune diabetes. Seven of these genes affect the activity of regulatory T cells, and two are involved in immune responses to microbial lipids. Four T1D-associated genomic regions could be identified as master regulators via trans-effects on gene expression. These results support the sparse effector hypothesis and reshape our understanding of the genetic architecture of T1D.

Mutant Tof11 alleles are highly accumulated in early planting-adaptable Japanese summer type soybeans

To avoid crop failure because of climate change, soybean (Glycine max (L.) Merrill) cultivars adaptable to early planting are required in western Japan. Because current Japanese cultivars may not be adaptable, genetic resources with high early-planting adaptability, and their genetic information must be developed. In the present study, summer type (ST) soybeans developed for early planting were used as plant materials. We examined their phenological characteristics and short reproductive period as an indicator of early planting adaptability and performed genetic studies. Biparental quantitative trait loci (QTL) analysis of a representative ST cultivar revealed a principal QTL for the reproductive period duration on chromosome 11. The results of resequencing analysis suggested that circadian clock-related Tof11 (soybean orthologue of PRR3) is a candidate QTL. Additionally, all 25 early planting-adaptable germplasms evaluated in this study possessed mutant alleles in Tof11, whereas 15 conventional cultivars only had wild-type alleles. These results suggest that mutant alleles in Tof11 are important genetic factors in the high adaptability to early planting of these soybeans, and thus, these alleles were acquired and accumulated in the ST soybean population.

Chromosome-scale assembly and quantitative trait locus mapping for major economic traits of the Culter alburnus genome using Illumina and PacBio sequencing with Hi-C mapping information

Topmouth culter (Culter alburnus) is an economically important freshwater fish with high nutritional value. However, its potential genetic advantages have not been fully exploited. Therefore, we aimed to determine the genome sequence of C. alburnus and examine quantitative trait loci (QTLs) related to major economic traits. The results showed that 24 pseudochromosomes were anchored by 914.74 Mb of the C. alburnus genome sequence. De novo sequencing identified 31,279 protein-coding genes with an average length of 8507 bp and average coding sequ ence of 1115 bp. In addition, a high-density genetic linkage map consisting of 24 linkage groups was constructed based on 353,532 high-quality single nucleotide polymorphisms and 4,710 bin markers. A total of 28 QTLs corresponding to 11 genes, 26 QTLs corresponding to 11 genes, and 12 QTLs corresponding to 5 genes were identified for sex, intermuscular spine number and body weight traits, respectively. In this study, we assembled an accurate and nearly complete genome of C. alburnus by combining Illumina, PacBio, and high-throughput Chromosome conformation capture (Hi-C) technologies. In addition, we identified QTLs that explained variances in intermuscular spine number, body weight, and sex differences in C. alburnus. These genetic markers or candidate genes associated with growth traits provide a basis for marker-assisted selection in C. alburnus.

Quantitative and qualitative plant-pathogen interactions call upon similar pathogenicity genes with a spectrum of effects

Septoria leaf blotch is a foliar wheat disease controlled by a combination of plant genetic resistances and fungicides use. R-gene-based qualitative resistance durability is limited due to gene-for-gene interactions with fungal avirulence (Avr) genes. Quantitative resistance is considered more durable but the mechanisms involved are not well documented. We hypothesize that genes involved in quantitative and qualitative plant-pathogen interactions are similar. A bi-parental population of Zymoseptoria tritici was inoculated on wheat cultivar 'Renan' and a linkage analysis performed to map QTL. Three pathogenicity QTL, Qzt-I05-1, Qzt-I05-6 and Qzt-I07-13, were mapped on chromosomes 1, 6 and 13 in Z. tritici, and a candidate pathogenicity gene on chromosome 6 was selected based on its effector-like characteristics. The candidate gene was cloned by Agrobacterium tumefaciens-mediated transformation, and a pathology test assessed the effect of the mutant strains on 'Renan'. This gene was demonstrated to be involved in quantitative pathogenicity. By cloning a newly annotated quantitative-effect gene in Z. tritici that is effector-like, we demonstrated that genes underlying pathogenicity QTL can be similar to Avr genes. This opens up the previously probed possibility that 'gene-for-gene' underlies not only qualitative but also quantitative plant-pathogen interactions in this pathosystem.

High-density genetic mapping of Fusarium head blight resistance and agronomic traits in spring wheat

Fusarium head blight (FHB) has rapidly become a major challenge to successful wheat production and competitive end-use quality in western Canada. Continuous effort is required to develop germplasm with improved FHB resistance and understand how to incorporate the material into crossing schemes for marker-assisted selection and genomic selection. The aim of this study was to map quantitative trait loci (QTL) responsible for the expression of FHB resistance in two adapted cultivars and to evaluate their co-localization with plant height, days to maturity, days to heading, and awnedness. A large doubled haploid population of 775 lines developed from cultivars Carberry and AC Cadillac was assessed for FHB incidence and severity in nurseries near Portage la Prairie, Brandon, and Morden in different years, and for plant height, awnedness, days to heading, and days to maturity near Swift Current. An initial linkage map using a subset of 261 lines was constructed using 634 polymorphic DArT and SSR markers. QTL analysis revealed five resistance QTL on chromosomes 2A, 3B (two loci), 4B, and 5A. A second genetic map with increased marker density was constructed using the Infinium iSelect 90k SNP wheat array in addition to the previous DArT and SSR markers, which revealed two additional QTL on 6A and 6D. The complete population was genotyped, and a total of 6,806 Infinium iSelect 90k SNP polymorphic markers were used to identify 17 putative resistance QTL on 14 different chromosomes. As with the smaller population size and fewer markers, large-effect QTL were detected on 3B, 4B, and 5A that were consistently expressed across environments. FHB resistance QTL were co-localized with plant height QTL on chromosomes 4B, 6D, and 7D; days to heading on 2B, 3A, 4A, 4B, and 5A; and maturity on 3A, 4B, and 7D. A major QTL for awnedness was identified as being associated with FHB resistance on chromosome 5A. Nine small-effect QTL were not associated with any of the agronomic traits, whereas 13 QTL that were associated with agronomic traits did not co-localize with any of the FHB traits. There is an opportunity to select for improved FHB resistance within adapted cultivars by using markers associated with complementary QTL.

The trouble with triples: Examining the impact of measurement error in mediation analysis

Mediation analysis is used in genetic mapping studies to identify candidate gene mediators of quantitative trait loci (QTL). We consider genetic mediation analysis of triplets-sets of three variables consisting of a target trait, the genotype at a QTL for the target trait, and a candidate mediator that is the abundance of a transcript or protein whose coding gene co-locates with the QTL. We show that, in the presence of measurement error, mediation analysis can infer partial mediation even in the absence of a causal relationship between the candidate mediator and the target. We describe a measurement error model and a corresponding latent variable model with estimable parameters that are combinations of the causal effects and measurement errors across all three variables. The relative magnitudes of the latent variable correlations determine whether or not mediation analysis will tend to infer the correct causal relationship in large samples. We examine case studies that illustrate the common failure modes of genetic mediation analysis and demonstrate how to evaluate the effects of measurement error. While genetic mediation analysis is a powerful tool for identifying candidate genes, we recommend caution when interpreting mediation analysis findings.

Interactions of Different Species of Phytophthora with Cacao Induce Genetic, Biochemical, and Morphological Plant Alterations

Diseases associated with Phytophthora cause considerable losses in cocoa production worldwide. Analyzing genes, proteins, and metabolites involved in Theobroma cacao's interaction with Phytophthora species is essential to explaining the molecular aspects of plant defense. Through a systematic literature review, this study aims to identify reports of genes, proteins, metabolites, morphological characteristics, and molecular and physiological processes of T. cacao involved in its interaction with species of Phytophthora. After the searches, 35 papers were selected for the data extraction stage, according to pre-established inclusion and exclusion criteria. In these studies, 657 genes and 32 metabolites, among other elements (molecules and molecular processes), were found to be involved in the interaction. The integration of this information resulted in the following conclusions: the expression patterns of pattern recognition receptors (PRRs) and a possible gene-to-gene interaction participate in cocoa resistance to Phytophthora spp.; the expression pattern of genes that encode pathogenesis-related (PRs) proteins is different between resistant and susceptible genotypes; phenolic compounds play an important role in preformed defenses; and proline accumulation may be involved in cell wall integrity. Only one proteomics study of T. cacao-Phytophthora spp. was found, and some genes proposed via QTL analysis were confirmed in transcriptomic studies.

A Combination of QTL Mapping and GradedPool-Seq to Dissect Genetic Complexity for Gibberella Ear Rot Resistance in Maize Using an IBM Syn10 DH Population

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most devastating maize diseases that reduces grain yield and quality worldwide. Utilization of host genetic resistance has become one of the most suitable strategies to control GER. In this study, a set of 246 diverse inbred lines derived from the intermated B 73 × Mo 17 doubled haploid population (IBM Syn10 DH) were used to detect quantitative trait loci (QTL) associated with resistance to GER. Meanwhile, a GradedPool-Seq (GPS) approach was performed to identify genomic variations involved in GER resistance. Using artificial inoculation across multiple environments, GER severity of the population was observed with wide phenotypic variation. Based on the linkage mapping, a total of 14 resistant QTLs were detected, accounting for 5.11 to 14.87% of the phenotypic variation, respectively. In GPS analysis, five significant single nucleotide polymorphisms (SNPs) associated with GER resistance were identified. Combining QTL mapping and GPS analysis, a peak-value SNP on chromosome 4 from GPS was overlapped with the QTL qGER4.2, suggesting that the colocalized region could be the most possible target location conferring resistance to GER. Subsequently, seven candidate genes were identified within the peak SNP, linking them to GER resistance. These findings are useful for exploring the complicated genetic variations in maize GER resistance. The genomic regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the combined strategy that can be used for quantitative traits in plant species.

Polygenic sex determination in vertebrates - is there any such thing?

Genetic sex determination (SD) in most vertebrates is controlled by a single master sex gene, which ensures a 1:1 sex ratio. However, more complex systems abound, and several have been ascribed to polygenic SD (PSD), in which many genes at different loci interact to produce the sexual phenotype. Here we examine claims for PSD in vertebrates, finding that most constitute transient states during sex chromosome turnover, or aberrant systems in species hybrids. To avoid confusion about terminology, we propose a consistent nomenclature for genetic SD systems.

Identification of QTL controlling volatile terpene contents in tea plant (Camellia sinensis) using a high-aroma 'Huangdan' x 'Jinxuan' F1 population

Aroma is an important factor affecting the character and quality of tea. The improvement of aroma trait is a crucial research direction of tea plant breeding. Volatile terpenes, as the major contributors to the floral odors of tea products, also play critical roles in the defense responses of plants to multiple stresses. However, previous studies have largely focused on the aroma formation during the manufacture of tea or the comparison of raw tea samples. The mechanisms causing different aroma profiles between tea cultivars have remained underexplored. In the current study, a high-density genetic linkage map of tea plant was constructed based on an F₁ population of 'Huangdan' × 'Jinxuan' using genotyping by sequencing. This linkage map covered 1754.57 cM and contained 15 linkage groups with a low inter-marker distance of 0.47 cM. A total of 42 QTLs associated with eight monoterpene contents and 12 QTLs associated with four sesquiterpenes contents were identified with the average PVE of 12.6% and 11.7% respectively. Furthermore, six candidate genes related to volatile terpene contents were found in QTL cluster on chromosome 5 by RNA-seq analysis. This work will enrich our understanding of the molecular mechanism of volatile terpene biosynthesis and provide a theoretical basis for tea plant breeding programs for aroma quality improvement.

Analysis of Systemic Epigenetic Alterations in Inflammatory Bowel Disease: Defining Geographical, Genetic and Immune-Inflammatory influences on the Circulating Methylome

BACKGROUND

Epigenetic alterations may provide valuable insights into gene-environment interactions in the pathogenesis of inflammatory bowel disease [IBD].

METHODS

Genome-wide methylation was measured from peripheral blood using the Illumina 450k platform in a case-control study in an inception cohort (295 controls, 154 Crohn's disease [CD], 161 ulcerative colitis [UC], 28 IBD unclassified [IBD-U)] with covariates of age, sex and cell counts, deconvoluted by the Houseman method. Genotyping was performed using Illumina HumanOmniExpressExome-8 BeadChips and gene expression using the Ion AmpliSeq Human Gene Expression Core Panel. Treatment escalation was characterized by the need for biological agents or surgery after initial disease remission.

RESULTS

A total of 137 differentially methylated positions [DMPs] were identified in IBD, including VMP1/MIR21 [p = 9.11 × 10-15] and RPS6KA2 [6.43 × 10-13], with consistency seen across Scandinavia and the UK. Dysregulated loci demonstrate strong genetic influence, notably VMP1 [p = 1.53 × 10-15]. Age acceleration is seen in IBD [coefficient 0.94, p < 2.2 × 10-16]. Several immuno-active genes demonstrated highly significant correlations between methylation and gene expression in IBD, in particular OSM: IBD r = -0.32, p = 3.64 × 10-7 vs non-IBD r = -0.14, p = 0.77]. Multi-omic integration of the methylome, genome and transcriptome also implicated specific pathways that associate with immune activation, response and regulation at disease inception. At follow-up, a signature of three DMPs [TAP1, TESPA1, RPTOR] were associated with treatment escalation to biological agents or surgery (hazard ratio of 5.19 [CI: 2.14-12.56], logrank p = 9.70 × 10-4).

CONCLUSION

These data demonstrate consistent epigenetic alterations at diagnosis in European patients with IBD, providing insights into the pathogenetic importance and translational potential of epigenetic mapping in complex disease.

Associations among the genome, rumen metabolome, ruminal bacteria, and milk production in early-lactation Holsteins

A multicenter observational study to evaluate genome-wide association was conducted in early-lactation Holstein cows (n = 293) from 36 herds in Canada, the USA, and Australia. Phenotypic observations included rumen metabolome, acidosis risk, ruminal bacterial taxa, and milk composition and yield measures. Diets ranged from pasture supplemented with concentrates to total mixed rations (nonfiber carbohydrates = 17 to 47, and neutral detergent fiber = 27 to 58% of dry matter). Rumen samples were collected <3 h after feeding and analyzed for pH, ammonia, d- and l-lactate, volatile fatty acid (VFA) concentrations, and abundance of bacterial phyla and families. Eigenvectors were produced using cluster and discriminant analyses from a combination of pH and ammonia, d-lactate, and VFA concentrations, and were used to estimate the probability of the risk of ruminal acidosis based on proximity to the centroid of 3 clusters, termed high (24.0% of cows), medium (24.2%), and low risk (51.8%) for acidosis. DNA of sufficient quality was successfully extracted from whole blood (218 cows) or hair (65 cows) collected simultaneously with the rumen samples and sequenced using the Geneseek Genomic Profiler Bovine 150K Illumina SNPchip. Genome-wide association used an additive model and linear regression with principal component analysis (PCA) population stratification and a Bonferroni correction for multiple comparisons. Population structure was visualized using PCA plots. Single genomic markers were associated with milk protein percent and the center logged ratio abundance of the phyla Chloroflexi, SR1, and Spirochaetes, and tended to be associated with milk fat yield, rumen acetate, butyrate, and isovalerate concentrations and with the probability of being in the low-risk acidosis group. More than one genomic marker was associated or tended to be associated with rumen isobutyrate and caproate concentrations, and the center log ratio of the phyla Bacteroidetes and Firmicutes and center log ratio of the families Prevotellaceae, BS11, S24-7, Acidaminococcaceae, Carnobacteriaceae, Lactobacillaceae, Leuconostocaceae, and Streptococcaceae. The provisional NTN4 gene, involved in several functions, had pleiotropy with 10 bacterial families, the phyla Bacteroidetes and Firmicutes, and butyrate. The ATP2CA1 gene, involved in the ATPase secretory pathway for Ca²⁺ transport, overlapped for the families Prevotellaceae, S24-7, and Streptococcaceae, the phylum Bacteroidetes, and isobutyrate. No genomic markers were associated with milk yield, fat percentage, protein yield, total solids, energy-corrected milk, somatic cell count, rumen pH, ammonia, propionate, valerate, total VFA, and d-, l-, or total lactate concentrations, or probability of being in the high- or medium-risk acidosis groups. Genome-wide associations with the rumen metabolome, microbial taxa, and milk composition were present across a wide geographical and management range of herds, suggesting the existence of markers for the rumen environment but not for acidosis susceptibility. The variation in pathogenesis of ruminal acidosis in the small population of cattle in the high risk for acidosis group and the dynamic nature of the rumen as cows cycle through a bout of acidosis may have precluded the identification of markers for acidosis susceptibility. Despite a limited sample size, this study provides evidence of interactions between the mammalian genome, the rumen metabolome, ruminal bacteria, and milk protein percentage.

Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping

Cotton leaf curl virus (CLCuV) causes devastating losses to fiber production in Central Asia. Viral spread across Asia in the last decade is causing concern that the virus will spread further before resistant varieties can be bred. Current development depends on screening each generation under disease pressure in a country where the disease is endemic. We utilized quantitative trait loci (QTL) mapping in four crosses with different sources of resistance to identify single nucleotide polymorphism (SNP) markers associated with the resistance trait to allow development of varieties without the need for field screening every generation. To assist in the analysis of multiple populations, a new publicly available R/Shiny App was developed to streamline genetic mapping using SNP arrays and to also provide an easy method to convert and deposit genetic data into the CottonGen database. Results identified several QTL from each cross, indicating possible multiple modes of resistance. Multiple sources of resistance would provide several genetic routes to combat the virus as it evolves over time. Kompetitive allele specific PCR (KASP) markers were developed and validated for a subset of QTL, which can be used in further development of CLCuV-resistant cotton lines.

Using QTL to Identify Genes and Pathways Underlying the Regulation and Production of Milk Components in Cattle

Milk is a complex liquid, and the concentrations of many of its components are under genetic control. Many genes and pathways are known to regulate milk composition, and the purpose of this review is to highlight how the discoveries of quantitative trait loci (QTL) for milk phenotypes can elucidate these pathways. The main body of this review focuses primarily on QTL discovered in cattle (Bos taurus) as a model species for the biology of lactation, and there are occasional references to sheep genetics. The following section describes a range of techniques that can be used to help identify the causative genes underlying QTL when the underlying mechanism involves the regulation of gene expression. As genotype and phenotype databases continue to grow and diversify, new QTL will continue to be discovered, and although proving the causality of underlying genes and variants remains difficult, these new data sets will further enhance our understanding of the biology of lactation.

Image-based assessment of plant disease progression identifies new genetic loci for resistance to Ralstonia solanacearum in tomato

A major challenge in global crop production is mitigating yield loss due to plant diseases. One of the best strategies to control these losses is through breeding for disease resistance. One barrier to the identification of resistance genes is the quantification of disease severity, which is typically based on the determination of a subjective score by a human observer. We hypothesized that image-based, non-destructive measurements of plant morphology over an extended period after pathogen infection would capture subtle quantitative differences between genotypes, and thus enable identification of new disease resistance loci. To test this, we inoculated a genetically diverse biparental mapping population of tomato (Solanum lycopersicum) with Ralstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease. We acquired over 40 000 time-series images of disease progression in this population, and developed an image analysis pipeline providing a suite of 10 traits to quantify bacterial wilt disease based on plant shape and size. Quantitative trait locus (QTL) analyses using image-based phenotyping for single and multi-traits identified QTLs that were both unique and shared compared with those identified by human assessment of wilting, and could detect QTLs earlier than human assessment. Expanding the phenotypic space of disease with image-based, non-destructive phenotyping both allowed earlier detection and identified new genetic components of resistance.

Quantitative Trait Loci (QTL) Analysis of Seed Protein and Oil Content in Wild Soybean (Glycine soja)

Soybean seeds consist of approximately 40% protein and 20% oil, making them one of the world's most important cultivated legumes. However, the levels of these compounds are negatively correlated with each other and regulated by quantitative trait loci (QTL) that are controlled by several genes. In this study, a total of 190 F₂ and 90 BC₁F₂ plants derived from a cross of Daepung (Glycine max) with GWS-1887 (G. soja, a source of high protein), were used for the QTL analysis of protein and oil content. In the F_2:3 populations, the average protein and oil content was 45.52% and 11.59%, respectively. A QTL associated with protein levels was detected at Gm20_29512680 on chr. 20 with a likelihood of odds (LOD) of 9.57 and an R² of 17.2%. A QTL associated with oil levels was also detected at Gm15_3621773 on chr. 15 (LOD: 5.80; R²: 12.2%). In the BC₁F_2:3 populations, the average protein and oil content was 44.25% and 12.14%, respectively. A QTL associated with both protein and oil content was detected at Gm20_27578013 on chr. 20 (LOD: 3.77 and 3.06; R² 15.8% and 10.7%, respectively). The crossover to the protein content of BC₁F_3:4 population was identified by SNP marker Gm20_32603292. Based on these results, two genes, Glyma.20g088000 (S-adenosyl-l-methionine-dependent methyltransferases) and Glyma.20g088400 (oxidoreductase, 2-oxoglutarate-Fe(II) oxygenase family protein), in which the amino acid sequence had changed and a stop codon was generated due to an InDel in the exon region, were identified.

Identification of Drought Tolerant Rice (Oryza Sativa L.) Genotypes with Asian and African Backgrounds

Drought is among the major abiotic stresses on rice production that can cause yield losses of up to 100% under severe drought conditions. Neither of the rice varieties currently grown in Burundi can withstand very low and irregular precipitation. This study identified genotypes that have putative quantitative trait loci (QTLs) associated with drought tolerance and determined their performance in the field. Two hundred and fifteen genotypes were grown in the field under both drought and irrigated conditions. Genomic deoxyribonucleic acid (DNA) was extracted from rice leaves for further genotypic screening. The results revealed the presence of the QTLs qDTY12.1, qDTY3.1, qDTY2-2_1, and qDTY1.1 in 90%, 85%, 53%, and 22% of the evaluated genotypes, respectively. The results of the phenotypic evaluation showed a significant yield reduction due to drought stress. Yield components and other agronomic traits were also negatively affected by drought. Genotypes having high yield best linear unbiased predictions (BLUPs) with two or more major QTLs for drought tolerance, including IR 108044-B-B-B-3-B-B, IR 92522-45-3-1-4, and BRRI DHAN 55 are of great interest for breeding programs to improve the drought tolerance of lines or varieties with other preferred traits.

A new allele PEL9 GG identified by genome-wide association study increases panicle elongation length in rice (Oryza sativa L.)

Considering the male sterile line has the phenomenon of panicle enclosure, panicle elongation length (PEL) plays an important role in hybrid rice seed production. However, the molecular mechanism underlying this process is poorly understood. In this study, we investigated the PEL phenotypic values of 353 rice accessions across six environments, which shows abundant phenotypic variation. Combining the 1.3 million single-nucleotide polymorphisms, we performed a genome-wide association study on PEL. Three quantitative trait loci (QTL) qPEL4, qPEL6, and qPEL9 were identified as significantly associated with PEL, of which qPEL4 and qPEL6 were previously reported QTLs and qPEL9 was novel. One causal gene locus, PEL9, was identified and validated. The PEL of accessions carrying allele PEL9 ^GG was significantly longer than that of those carrying allele PEL9 ^TT. We also demonstrated that the outcrossing rate of female parents carrying allele PEL9 ^GG increased by 14.81% compared with that of the isogenic line carrying allele PEL9 ^TT in an F₁ hybrid seed production field. The allele frequency of PEL9^GG increased gradually with an increase in latitude in the Northern Hemisphere. Our results should facilitate the improvement of the PEL of the female parent of hybrid rice.

Genome wide association study of thyroid hormone levels following challenge with porcine reproductive and respiratory syndrome virus

Introduction: Porcine reproductive and respiratory syndrome virus (PRRSV) causes respiratory disease in piglets and reproductive disease in sows. Piglet and fetal serum thyroid hormone (i.e., T3 and T4) levels decrease rapidly in response to Porcine reproductive and respiratory syndrome virus infection. However, the genetic control of T3 and T4 levels during infection is not completely understood. Our objective was to estimate genetic parameters and identify quantitative trait loci (QTL) for absolute T3 and/or T4 levels of piglets and fetuses challenged with Porcine reproductive and respiratory syndrome virus. Methods: Sera from 5-week-old pigs (N = 1792) at 11 days post inoculation (DPI) with Porcine reproductive and respiratory syndrome virus were assayed for T3 levels (piglet_T3). Sera from fetuses (N = 1,267) at 12 or 21 days post maternal inoculation (DPMI) with Porcine reproductive and respiratory syndrome virus of sows (N = 145) in late gestation were assayed for T3 (fetal_T3) and T4 (fetal_T4) levels. Animals were genotyped using 60 K Illumina or 650 K Affymetrix single nucleotide polymorphism (SNP) panels. Heritabilities, phenotypic correlations, and genetic correlations were estimated using ASREML; genome wide association studies were performed for each trait separately using Julia for Whole-genome Analysis Software (JWAS). Results: All three traits were low to moderately heritable (10%-16%). Phenotypic and genetic correlations of piglet_T3 levels with weight gain (0-42 DPI) were 0.26 ± 0.03 and 0.67 ± 0.14, respectively. Nine significant quantitative trait loci were identified for piglet_T3, on Sus scrofa chromosomes (SSC) 3, 4, 5, 6, 7, 14, 15, and 17, and collectively explaining 30% of the genetic variation (GV), with the largest quantitative trait loci identified on SSC5, explaining 15% of the genetic variation. Three significant quantitative trait loci were identified for fetal_T3 on SSC1 and SSC4, which collectively explained 10% of the genetic variation. Five significant quantitative trait loci were identified for fetal_T4 on SSC1, 6, 10, 13, and 15, which collectively explained 14% of the genetic variation. Several putative immune-related candidate genes were identified, including CD247, IRF8, and MAPK8. Discussion: Thyroid hormone levels following Porcine reproductive and respiratory syndrome virus infection were heritable and had positive genetic correlations with growth rate. Multiple quantitative trait loci with moderate effects were identified for T3 and T4 levels during challenge with Porcine reproductive and respiratory syndrome virus and candidate genes were identified, including several immune-related genes. These results advance our understanding of growth effects of both piglet and fetal response to Porcine reproductive and respiratory syndrome virus infection, revealing factors associated with genomic control of host resilience.

Cardiac copper content and its relationship with heart physiology: Insights based on quantitative genetic and functional analyses using BXD family mice

Background

Copper (Cu) is essential for the functioning of various enzymes involved in important cellular and physiological processes. Although critical for normal cardiac function, excessive accumulation, or deficiency of Cu in the myocardium is detrimental to the heart. Fluctuations in cardiac Cu content have been shown to cause cardiac pathologies and imbalance in systemic Cu metabolism. However, the genetic basis underlying cardiac Cu levels and their effects on heart traits remain to be understood. Representing the largest murine genetic reference population, BXD strains have been widely used to explore genotype-phenotype associations and identify quantitative trait loci (QTL) and candidate genes.

Methods

Cardiac Cu concentration and heart function in BXD strains were measured, followed by QTL mapping. The candidate genes modulating Cu homeostasis in mice hearts were identified using a multi-criteria scoring/filtering approach.

Results

Significant correlations were identified between cardiac Cu concentration and left ventricular (LV) internal diameter and volumes at end-diastole and end-systole, demonstrating that the BXDs with higher cardiac Cu levels have larger LV chamber. Conversely, cardiac Cu levels negatively correlated with LV posterior wall thickness, suggesting that lower Cu concentration in the heart is associated with LV hypertrophy. Genetic mapping identified six QTLs containing a total of 217 genes, which were further narrowed down to 21 genes that showed a significant association with cardiac Cu content in mice. Among those, Prex1 and Irx3 are the strongest candidates involved in cardiac Cu modulation.

Conclusion

Cardiac Cu level is significantly correlated with heart chamber size and hypertrophy phenotypes in BXD mice, while being regulated by multiple genes in several QTLs. Prex1 and Irx3 may be involved in modulating Cu metabolism and its downstream effects and warrant further experimental and functional validations.

Chromatin modules and their implication in genomic organization and gene regulation

Regulation of gene expression is a complex but highly guided process. While genomic technologies and computational approaches have allowed high-throughput mapping of cis-regulatory elements (CREs) and their interactions in 3D, their precise role in regulating gene expression remains obscure. Recent complementary observations revealed that interactions between CREs frequently result in the formation of small-scale functional modules within topologically associating domains. Such chromatin modules likely emerge from a complex interplay between regulatory machineries assembled at CREs, including site-specific binding of transcription factors. Here, we review the methods that allow identifying chromatin modules, summarize possible mechanisms that steer CRE interactions within these modules, and discuss outstanding challenges to uncover how chromatin modules fit in our current understanding of the functional 3D genome.

Combining genome-wide association study based on low-coverage whole genome sequencing and transcriptome analysis to reveal the key candidate genes affecting meat color in pigs

Meat color is an attractive trait that influences consumers' purchase decisions at the point of sale. To decipher the genetic basis of meat color traits, we performed a genome-wide association study based on low-coverage whole-genome sequencing. In total, 669 (Pietrain × Duroc) × (Landrace × Yorkshire) pigs were genotyped using low-coverage whole-genome sequencing. Single nucleotide polymorphism (SNP) calling and genotype imputation were performed using the BaseVar + STITCH channel. Six individuals with an average depth of 12.05× whole-genome resequencing were randomly selected to assess the accuracy of imputation. Heritability evaluation and genome-wide association study for meat color traits were conducted. Functional enrichment analysis of the candidate genes from genome-wide association study and integration analysis with our previous transcriptome data were conducted. The imputation accuracy parameters, allele frequency R² , concordance rate, and dosage R² were 0.959, 0.952, and 0.933, respectively. The heritability values of a*_45 min , b*_45 min , L*_45 min , C*, and H⁰ were 0.19, 0.11, 0.06, 0.16, and 0.26, respectively. In total, 3884 significant SNPs and 15 QTL, corresponding to 382 genes, were associated with meat color traits. Functional enrichment analysis revealed that 10 genes were the potential candidates for regulating meat color. Moreover, integration analysis revealed that DMRT2, EFNA5, FGF10, and COL11A2 were the most promising candidates affecting meat color. In summary, this study provides new insights into the molecular basis of meat color traits, and provides a new theoretical basis for the molecular breeding of meat color traits in pigs.

From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels.

Analysis of transcriptional changes in the immune system associated with pubertal development in a longitudinal cohort of children with asthma

Puberty is an important developmental period marked by hormonal, metabolic and immune changes. Puberty also marks a shift in sex differences in susceptibility to asthma. Yet, little is known about the gene expression changes in immune cells that occur during pubertal development. Here we assess pubertal development and leukocyte gene expression in a longitudinal cohort of 251 children with asthma. We identify substantial gene expression changes associated with age and pubertal development. Gene expression changes between pre- and post-menarcheal females suggest a shift from predominantly innate to adaptive immunity. We show that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.

Thorough Characterization of ETHQB3.5, a QTL Involved in Melon Fruit Climacteric Behavior and Aroma Volatile Composition

The effect of the QTL involved in climacteric ripening ETHQB3.5 on the fruit VOC composition was studied using a set of Near-Isogenic Lines (NILs) containing overlapping introgressions from the Korean accession PI 16375 on the chromosome 3 in the climacteric 'Piel de Sapo' (PS) genetic background. ETHQB3.5 was mapped in an interval of 1.24 Mb that contained a NAC transcription factor. NIL fruits also showed differences in VOC composition belonging to acetate esters, non-acetate esters, and sulfur-derived families. Cosegregation of VOC composition (23 out of 48 total QTLs were mapped) and climacteric ripening was observed, suggesting a pleiotropic effect of ETHQB3.5. On the other hand, other VOCs (mainly alkanes, aldehydes, and ketones) showed a pattern of variation independent of ETHQB3.5 effects, indicating the presence of other genes controlling non-climacteric ripening VOCs. Network correlation analysis and hierarchical clustering found groups of highly correlated compounds and confirmed the involvement of the climacteric differences in compound classes and VOC differences. The modification of melon VOCs may be achieved with or without interfering with its physiological behavior, but it is likely that high relative concentrations of some type of ethylene-dependent esters could be achieved in climacteric cultivars.

Effect of all-but-one conditional analysis for eQTL isolation in peripheral blood

Expression quantitative trait locus detection has become increasingly important for understanding how noncoding variants contribute to disease susceptibility and complex traits. The major challenges in expression quantitative trait locus fine-mapping and causal variant discovery relate to the impact of linkage disequilibrium on signals due to one or multiple functional variants that lie within a credible set. We perform expression quantitative trait locus fine-mapping using the all-but-one approach, conditioning each signal on all others detected in an interval, on the Consortium for the Architecture of Gene Expression cohorts of microarray-based peripheral blood gene expression in 2,138 European-ancestry human adults. We contrast these results with traditional forward stepwise conditional analysis and a Bayesian localization method. All-but-one conditioning significantly modifies effect-size estimates for 51% of 2,351 expression quantitative trait locus peaks, but only modestly affects credible set size and location. On the other hand, both conditioning approaches result in unexpectedly low overlap with Bayesian credible sets, with just 57% peak concordance and between 50% and 70% SNP sharing, leading us to caution against the assumption that any one localization method is superior to another. We also cross reference our results with ATAC-seq data, cell-type-specific expression quantitative trait locus, and activity-by-contact-enhancers, leading to the proposal of a 5-tier approach to further reduce credible set sizes and prioritize likely causal variants for all known inflammatory bowel disease risk loci active in immune cells.

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 disease whose polygenic component is mainly unidentified. We propose that levels of intermediate molecular phenotypes in the myocardium associated with histopathological damage could explain CDA susceptibility; so that variants of genes encoding these intermediate molecular phenotypes could identify patients susceptible to this complication. A genetically heterogeneous cohort of mice generated by backcrossing (N = 165) was treated with doxorubicin and docetaxel. Cardiac histopathological damage was measured by fibrosis and cardiomyocyte size by an Ariol slide scanner. We determine intramyocardial levels of intermediate molecular phenotypes of CDA associated with histopathological damage and quantitative trait loci (ipQTLs) linked to them. These ipQTLs seem to contribute to the missing heritability of CDA because they improve the heritability explained by QTL directly linked to CDA (cda-QTLs) through genetic models. Genes encoding these molecular subphenotypes were evaluated as genetic markers of CDA in three cancer patient cohorts (N = 517) whose cardiac damage was quantified by echocardiography or Cardiac Magnetic Resonance. Many SNPs associated with CDA were found using genetic models. LASSO multivariate regression identified two risk score models, one for pediatric cancer patients and the other for women with breast cancer. Molecular intermediate phenotypes associated with heart damage can identify genetic markers of CDA risk, thereby allowing a more personalized patient management. A similar strategy could be applied to identify genetic markers of other complex trait diseases.

Rare variant analyses across multiethnic cohorts identify novel genes for refractive error

Refractive error, measured here as mean spherical equivalent (SER), is a complex eye condition caused by both genetic and environmental factors. Individuals with strong positive or negative values of SER require spectacles or other approaches for vision correction. Common genetic risk factors have been identified by genome-wide association studies (GWAS), but a great part of the refractive error heritability is still missing. Some of this heritability may be explained by rare variants (minor allele frequency [MAF] ≤ 0.01.). We performed multiple gene-based association tests of mean Spherical Equivalent with rare variants in exome array data from the Consortium for Refractive Error and Myopia (CREAM). The dataset consisted of over 27,000 total subjects from five cohorts of Indo-European and Eastern Asian ethnicity. We identified 129 unique genes associated with refractive error, many of which were replicated in multiple cohorts. Our best novel candidates included the retina expressed PDCD6IP, the circadian rhythm gene PER3, and P4HTM, which affects eye morphology. Future work will include functional studies and validation. Identification of genes contributing to refractive error and future understanding of their function may lead to better treatment and prevention of refractive errors, which themselves are important risk factors for various blinding conditions.

Genome-wide association study for grain zinc concentration in bread wheat (Triticum aestivum L.)

Introduction

Zinc (Zn) deficiency causes serious diseases in people who rely on cereals as their main food source. However, the grain zinc concentration (GZnC) in wheat is low. Biofortification is a sustainable strategy for reducing human Zn deficiency.

Methods

In this study, we constructed a population of 382 wheat accessions and determined their GZnC in three field environments. Phenotype data was used for a genome-wide association study (GWAS) using a 660K single nucleotide polymorphism (SNP) array, and haplotype analysis identified an important candidate gene for GZnC.

Results

We found that GZnC of the wheat accessions showed an increasing trend with their released years, indicating that the dominant allele of GZnC was not lost during the breeding process. Nine stable quantitative trait loci (QTLs) for GZnC were identified on chromosomes 3A, 4A, 5B, 6D, and 7A. And an important candidate gene for GZnC, namely, TraesCS6D01G234600, and GZnC between the haplotypes of this gene showed, significant difference (P ≤ 0.05) in three environments.

Discussion

A novel QTL was first identified on chromosome 6D, this finding enriches our understanding of the genetic basis of GZnC in wheat. This study provides new insights into valuable markers and candidate genes for wheat biofortification to improve GZnC.

The Wistar Kyoto Rat: A Model of Depression Traits

There is an ongoing debate about the value of animal research in psychiatry with valid lines of reasoning stating the limits of individual animal models compared to human psychiatric illnesses. Human depression is not a homogenous disorder; therefore, one cannot expect a single animal model to reflect depression heterogeneity. This limited review presents arguments that the Wistar Kyoto (WKY) rats show intrinsic depression traits. The phenotypes of WKY do not completely mirror those of human depression but clearly indicate characteristics that are common with it. WKYs present despair- like behavior, passive coping with stress, comorbid anxiety, and enhanced drug use compared to other routinely used inbred or outbred strains of rats. The commonly used tests identifying these phenotypes reflect exploratory, escape-oriented, and withdrawal-like behaviors. The WKYs consistently choose withdrawal or avoidance in novel environments and freezing behaviors in response to a challenge in these tests. The physiological response to a stressful environment is exaggerated in WKYs. Selective breeding generated two WKY substrains that are nearly isogenic but show clear behavioral differences, including that of depression-like behavior. WKY and its substrains may share characteristics of subgroups of depressed individuals with social withdrawal, low energy, weight loss, sleep disturbances, and specific cognitive dysfunction. The genomes of the WKY and WKY substrains contain variations that impact the function of many genes identified in recent human genetic studies of depression. Thus, these strains of rats share characteristics of human depression at both phenotypic and genetic levels, making them a model of depression traits.

Fruit growth and development in apple: a molecular, genomics and epigenetics perspective

Fruit growth and development are physiological processes controlled by several internal and external factors. This complex regulatory mechanism comprises a series of events occurring in a chronological order over a growing season. Understanding the underlying mechanism of fruit development events, however, requires consideration of the events occurring prior to fruit development such as flowering, pollination, fertilization, and fruit set. Such events are interrelated and occur in a sequential order. Recent advances in high-throughput sequencing technology in conjunction with improved statistical and computational methods have empowered science to identify some of the major molecular components and mechanisms involved in the regulation of fruit growth and have supplied encouraging successes in associating genotypic differentiation with phenotypic observations. As a result, multiple approaches have been developed to dissect such complex regulatory machinery and understand the genetic basis controlling these processes. These methods include transcriptomic analysis, quantitative trait loci (QTLs) mapping, whole-genome approach, and epigenetics analyses. This review offers a comprehensive overview of the molecular, genomic and epigenetics perspective of apple fruit growth and development that defines the final fruit size and provides a detailed analysis of the mechanisms by which fruit growth and development are controlled. Though the main emphasis of this article is on the molecular, genomic and epigenetics aspects of fruit growth and development, we will also deliver a brief overview on events occurring prior to fruit growth.

Hunting for Genes Underlying Emotionality in the Laboratory Rat: Maps, Tools and Traps

Scientists have systematically investigated the hereditary bases of behaviors since the 19th century, moved by either evolutionary questions or clinically-motivated purposes. The pioneer studies on the genetic selection of laboratory animals had already indicated, one hundred years ago, the immense complexity of analyzing behaviors that were influenced by a large number of small-effect genes and an incalculable amount of environmental factors. Merging Mendelian, quantitative and molecular approaches in the 1990s made it possible to map specific rodent behaviors to known chromosome regions. From that point on, Quantitative Trait Locus (QTL) analyses coupled with behavioral and molecular techniques, which involved in vivo isolation of relevant blocks of genes, opened new avenues for gene mapping and characterization. This review examines the QTL strategy applied to the behavioral study of emotionality, with a focus on the laboratory rat. We discuss the challenges, advances and limitations of the search for Quantitative Trait Genes (QTG) playing a role in regulating emotionality. For the past 25 years, we have marched the long journey from emotionality-related behaviors to genes. In this context, our experiences are used to illustrate why and how one should move forward in the molecular understanding of complex psychiatric illnesses. The promise of exploring genetic links between immunological and emotional responses are also discussed. New strategies based on humans, rodents and other animals (such as zebrafish) are also acknowledged, as they are likely to allow substantial progress to be made in the near future.

Identification of Genomic Regions Associated with High Grain Zn Content in Polished Rice Using Genotyping-by-Sequencing (GBS)

Globally, micronutrient (iron and zinc) enriched rice has been a sustainable and cost-effective solution to overcome malnutrition or hidden hunger. Understanding the genetic basis and identifying the genomic regions for grain zinc (Zn) across diverse genetic backgrounds is an important step to develop biofortified rice varieties. In this case, an RIL population (306 RILs) obtained from a cross between the high-yielding rice variety MTU1010 and the high-zinc rice variety Ranbir Basmati was utilized to pinpoint the genomic region(s) and QTL(s) responsible for grain zinc (Zn) content. A total of 2746 SNP markers spanning a genetic distance of 2445 cM were employed for quantitative trait loci (QTL) analysis, which resulted in the identification of 47 QTLs for mineral (Zn and Fe) and agronomic traits with 3.5-36.0% phenotypic variance explained (PVE) over the seasons. On Chr02, consistent QTLs for grain Zn polished (qZnPR.2.1) and Zn brown (qZnBR.2.2) were identified. On Chr09, two additional reliable QTLs for grain Zn brown (qZnBR.9.1 and qZnBR.9.2) were identified. The major-effect QTLs identified in this study were associated with few key genes related to Zn and Fe transporter activity. The genomic regions, candidate genes, and molecular markers associated with these major QTLs will be useful for genomic-assisted breeding for developing Zn-biofortified varieties.

Pinpointing Genomic Regions and Candidate Genes Associated with Seed Oil and Protein Content in Soybean through an Integrative Transcriptomic and QTL Meta-Analysis

Soybean with enriched nutrients has emerged as a prominent source of edible oil and protein. In the present study, a meta-analysis was performed by integrating quantitative trait loci (QTLs) information, region-specific association and transcriptomic analysis. Analysis of about a thousand QTLs previously identified in soybean helped to pinpoint 14 meta-QTLs for oil and 16 meta-QTLs for protein content. Similarly, region-specific association analysis using whole genome re-sequenced data was performed for the most promising meta-QTL on chromosomes 6 and 20. Only 94 out of 468 genes related to fatty acid and protein metabolic pathways identified within the meta-QTL region were found to be expressed in seeds. Allele mining and haplotyping of these selected genes were performed using whole genome resequencing data. Interestingly, a significant haplotypic association of some genes with oil and protein content was observed, for instance, in the case of FAD2-1B gene, an average seed oil content of 20.22% for haplotype 1 compared to 15.52% for haplotype 5 was observed. In addition, the mutation S86F in the FAD2-1B gene produces a destabilizing effect of (ΔΔG Stability) -0.31 kcal/mol. Transcriptomic analysis revealed the tissue-specific expression of candidate genes. Based on their higher expression in seed developmental stages, genes such as sugar transporter, fatty acid desaturase (FAD), lipid transporter, major facilitator protein and amino acid transporter can be targeted for functional validation. The approach and information generated in the present study will be helpful in the map-based cloning of regulatory genes, as well as for marker-assisted breeding in soybean.

Genetic basis of maize kernel protein content revealed by high-density bin mapping using recombinant inbred lines

Maize with a high kernel protein content (PC) is desirable for human food and livestock fodder. However, improvements in its PC have been hampered by a lack of desirable molecular markers. To identify quantitative trait loci (QTL) and candidate genes for kernel PC, we employed a genotyping-by-sequencing strategy to construct a high-resolution linkage map with 6,433 bin markers for 275 recombinant inbred lines (RILs) derived from a high-PC female Ji846 and low-PC male Ye3189. The total genetic distance covered by the linkage map was 2180.93 cM, and the average distance between adjacent markers was 0.32 cM, with a physical distance of approximately 0.37 Mb. Using this linkage map, 11 QTLs affecting kernel PC were identified, including qPC7 and qPC2-2, which were identified in at least two environments. For the qPC2-2 locus, a marker named IndelPC2-2 was developed with closely linked polymorphisms in both parents, and when tested in 30 high and 30 low PC inbred lines, it showed significant differences (P = 1.9E-03). To identify the candidate genes for this locus, transcriptome sequencing data and PC best linear unbiased estimates (BLUE) for 348 inbred lines were combined, and the expression levels of the four genes were correlated with PC. Among the four genes, Zm00001d002625, which encodes an S-adenosyl-L-methionine-dependent methyltransferase superfamily protein, showed significantly different expression levels between two RIL parents in the endosperm and is speculated to be a potential candidate gene for qPC2-2. This study will contribute to further research on the mechanisms underlying the regulation of maize PC, while also providing a genetic basis for marker-assisted selection in the future.

Genetic Dissection of Alkalinity Tolerance at the Seedling Stage in Rice (Oryza sativa) Using a High-Resolution Linkage Map

Although both salinity and alkalinity result from accumulation of soluble salts in soil, high pH and ionic imbalance make alkaline stress more harmful to plants. This study aimed to provide molecular insights into the alkalinity tolerance using a recombinant inbred line (RIL) population developed from a cross between Cocodrie and Dular with contrasting response to alkalinity stress. Forty-six additive QTLs for nine morpho-physiological traits were mapped on to a linkage map of 4679 SNPs under alkalinity stress at the seedling stage and seven major-effect QTLs were for alkalinity tolerance scoring, Na⁺ and K⁺ concentrations and Na⁺:K⁺ ratio. The candidate genes were identified based on the comparison of the impacts of variants of genes present in five QTL intervals using the whole genome sequences of both parents. Differential expression of no apical meristem protein, cysteine protease precursor, retrotransposon protein, OsWAK28, MYB transcription factor, protein kinase, ubiquitin-carboxyl protein, and NAD binding protein genes in parents indicated their role in response to alkali stress. Our study suggests that the genetic basis of tolerance to alkalinity stress is most likely different from that of salinity stress. Introgression and validation of the QTLs and genes can be useful for improving alkalinity tolerance in rice at the seedling stage and advancing understanding of the molecular genetic basis of alkalinity stress adaptation.

Genetic determinants of polygenic prediction accuracy within a population

Genomic risk prediction is on the emerging path toward personalized medicine. However, the accuracy of polygenic prediction varies strongly in different individuals. Based on up to 352,277 European ancestry participants in the UK Biobank, we constructed polygenic risk scores for 15 physiological and biochemical quantitative traits. We identified a total of 185 polygenic prediction variability quantitative trait loci for 11 traits by Levene's test among 254,376 unrelated individuals. We validated the effects of prediction variability quantitative trait loci using an independent test set of 58,927 individuals. For instance, a score aggregating 51 prediction variability quantitative trait locus variants for triglycerides had the strongest Spearman correlation of 0.185 (P-value <1.0 × 10-300) with the squared prediction errors. We found a strong enrichment of complex genetic effects conferred by prediction variability quantitative trait loci compared to risk loci identified in genome-wide association studies, including 89 prediction variability quantitative trait loci exhibiting dominance effects. Incorporation of dominance effects into polygenic risk scores significantly improved polygenic prediction for triglycerides, low-density lipoprotein cholesterol, vitamin D, and platelet. In conclusion, we have discovered and profiled genetic determinants of polygenic prediction variability for 11 quantitative biomarkers. These findings may assist interpretation of genomic risk prediction in various contexts and encourage novel approaches for constructing polygenic risk scores with complex genetic effects.

Genotyping by Sequencing (GBS)-Based QTL Mapping for Bacterial Fruit Blotch (BFB) in Watermelon

Watermelon (Citrullus lanatus), an economically important and nutritionally rich Cucurbitaceous crop grown worldwide, is severely affected by bacterial fruit blotch (BFB). Development of resistant cultivar is the most eco-friendly, cost-effective, and sustainable way to tackle this disease. This requires wider understanding of the genetics of resistance to BFB. In this study, we identified quantitative trait loci (QTLs) associated with BFB resistance in an F₂ mapping population developed from BFB-resistant 'PI 189225' (Citrullus amarus) and -susceptible 'SW 26' (C. lanatus) genotypes based on the polymorphic markers identified by genotyping by sequencing (GSB). A linkage map covering a total genetic distance of 3377.1 cM was constructed. Two QTLs for BFB resistance, namely, ClBFB10.1 and ClBFB10.2, both located on chromosome 10 explaining 18.84 and 15.41% of the phenotypic variations, respectively, were identified. Two SNP-based high-resolution melting (HRM) markers WmBFB10.1 and WmBFB10.2 having high positive correlation with resistance vs. susceptible alleles were developed. The efficacy of the markers was validated in another F₂ population derived from SW34 × PI 189225. The highest phenotypic variation was found in the locus ClBFB10.2, which also contains three putative candidate genes for resistance to BFB. These findings will accelerate the development of BFB-resistant watermelon varieties via molecular breeding.

Identification of a QTL region for ashy stem blight resistance using genome-wide association and linage analysis in common bean recombinant inbred lines derived from BAT 477 and NY6020-4

Ashy stem blight (ASB), caused by the fungus Macrophomina phaseolina (Tassi) Goidanich is an important disease of the common bean (Phaseolus vulgaris L.). It is important to identify quantitative trait loci (QTL) for ASB resistance and introgress into susceptible cultivars of the common bean. The objective of this research was to identify QTL and single nucleotide polymorphism (SNP) markers associated with ASB resistance in recombinant inbred lines (RIL) derived from a cross between BAT 477 and NY6020-4 common bean. One hundred and twenty-six F_6:7 RIL were phenotyped for ASB in the greenhouse. Disease severity was scored on a scale of 1-9. Genotyping was performed using whole genome resequencing with 2x common bean genome size coverage, and over six million SNPs were obtained. After being filtered, 72,017 SNPs distributed on 11 chromosomes were used to conduct the genome-wide association study (GWAS) and QTL mapping. A novel QTL region of ~4.28 Mbp from 35,546,329 bp to 39,826,434 bp on chromosome Pv03 was identified for ASB resistance. The two SNPs, Chr03_39824257 and Chr03_39824268 located at 39,824,257 bp and 39,824,268 bp on Pv03, respectively, were identified as the strongest markers associated with ASB resistance. The gene Phvul.003G175900 (drought sensitive, WD repeat-containing protein 76) located at 39,822,021 - 39,824,655 bp on Pv03 was recognized as one candidate for ASB resistance in the RIL, and the gene contained the two SNP markers. QTL and SNP markers may be used to select plants and lines for ASB resistance through marker-assisted selection (MAS) in common bean breeding.

Machine learning assisted dynamic phenotypes and genomic variants help understand the ecotype divergence in rapeseed

Three ecotypes of rapeseed, winter, spring, and semi-winter, have been formed to enable the plant to adapt to different geographic areas. Although several major loci had been found to contribute to the flowering divergence, the genomic footprints and associated dynamic plant architecture in the vegetative growth stage underlying the ecotype divergence remain largely unknown in rapeseed. Here, a set of 41 dynamic i-traits and 30 growth-related traits were obtained by high-throughput phenotyping of 171 diverse rapeseed accessions. Large phenotypic variation and high broad-sense heritability were observed for these i-traits across all developmental stages. Of these, 19 i-traits were identified to contribute to the divergence of three ecotypes using random forest model of machine learning approach, and could serve as biomarkers to predict the ecotype. Furthermore, we analyzed genomic variations of the population, QTL information of all dynamic i-traits, and genomic basis of the ecotype differentiation. It was found that 213, 237, and 184 QTLs responsible for the differentiated i-traits overlapped with the signals of ecotype divergence between winter and spring, winter and semi-winter, and spring and semi-winter, respectively. Of which, there were four common divergent regions between winter and spring/semi-winter and the strongest divergent regions between spring and semi-winter were found to overlap with the dynamic QTLs responsible for the differentiated i-traits at multiple growth stages. Our study provides important insights into the divergence of plant architecture in the vegetative growth stage among the three ecotypes, which was contributed to by the genetic differentiation, and might contribute to environmental adaption and yield improvement.