Exploring SoySNP50K and USDA Germplasm Collection Data to Find New QTLs Associated with Protein and Oil Content in Brazilian Genotypes.

Genetic diversity within a germplasm collection plays a vital role in the success of breeding programs. However, comprehending this diversity and identifying accessions with desirable traits pose significant challenges. This study utilized publicly available data to investigate SNP markers associated with protein and oil content in Brazilian soybeans. Through this research, twenty-two new QTLs (Quantitative Trait Loci) were identified, and we highlighted the substantial influence of Roanoke, Lee and Bragg ancestor on the genetic makeup of Brazilian soybean varieties. Our findings demonstrate that certain markers are being lost in modern cultivars, while others maintain or even increase their frequency. These observations indicate genomic regions that have undergone selection during soybean introduction in Brazil and could be valuable in breeding programs aimed at enhancing protein or oil content.

Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs.

BACKGROUND: Mapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in the Longissimus lumborum tissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs. RESULTS: The number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the "Meat and Carcass" type QTL. The scenarios with the highest number of cis- (n = 304) and trans- (n = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes. CONCLUSIONS: After LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.

The chromosome-scale genome and the genetic resistance machinery against insect herbivores of the Mexican toloache, Datura stramonium.

Plant resistance refers to the heritable ability of plants to reduce damage caused by natural enemies, such as herbivores and pathogens, either through constitutive or induced traits like chemical compounds or trichomes. However, the genetic architecture-the number and genome location of genes that affect plant defense and the magnitude of their effects-of plant resistance to arthropod herbivores in natural populations remains poorly understood. In this study, we aimed to unveil the genetic architecture of plant resistance to insect herbivores in the annual herb Datura stramonium (Solanaceae) through quantitative trait loci mapping. We achieved this by assembling the species' genome and constructing a linkage map using an F2 progeny transplanted into natural habitats. Furthermore, we conducted differential gene expression analysis between undamaged and damaged plants caused by the primary folivore, Lema daturaphila larvae. Our genome assembly resulted in 6,109 scaffolds distributed across 12 haploid chromosomes. A single quantitative trait loci region on chromosome 3 was associated with plant resistance, spanning 0 to 5.17 cM. The explained variance by the quantitative trait loci was 8.44%. Our findings imply that the resistance mechanisms of D. stramonium are shaped by the complex interplay of multiple genes with minor effects. Protein-protein interaction networks involving genes within the quantitative trait loci region and overexpressed genes uncovered the key role of receptor-like cytoplasmic kinases in signaling and regulating tropane alkaloids and terpenoids, which serve as powerful chemical defenses against D. stramonium herbivores. The data generated in our study constitute important resources for delving into the evolution and ecology of secondary compounds mediating plant-insect interactions.

Genome-wide association study for growth traits in Blanco Orejinegro and Romosinuano cattle.

Growth traits are economically important characteristics for the genetic improvement of local cattle breeds. Genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to perform a GWAS to identify genomic regions and genes associated to birth weight, weaning weight adjusted for 240 days, 16 months, and 24 months weight in Romosinuano (ROMO) and Blanco Orejinegro (BON) cattle. A single-step genomic-BLUP was implemented using 596 BON and 569 ROMO individuals that were genotyped with an Illumina BovineSNP50 BeadChip. There were 25 regions of interest identified on different chromosomes, with few of them simultaneously associated with two or more growth traits and some were common to both breeds. The gene mapping allowed to find 173 annotations on these regions, from which 49 represent potential candidate genes with known growth-related functions in cattle and other species. Among the regions that were associated with several growth traits, that at 24 - 27 MB of BTA14, has important candidate genes such as LYPLA1, XKR4, TMEM68 and PLAG1. Another region of interest at 0.40-0.77 Mb of BTA23 was identified in both breeds, containing KHDRBS2 as a potential candidate gene influencing body weight. Future studies targeting these regions could provide more knowledge to uncover the genetic architecture underlying growth traits in BON and ROMO cattle. The genomic regions and genes identified in this study could be used to improve the prediction of genetic merit for growth traits in these creole cattle breeds.

Genetic mapping of craniofacial traits in the Mexican tetra reveals loci associated with bite differences between cave and surface fish.

BACKGROUND: The Mexican tetra, Astyanax mexicanus, includes interfertile surface-dwelling and cave-dwelling morphs, enabling powerful studies aimed at uncovering genes involved in the evolution of cave-associated traits. Compared to surface fish, cavefish harbor several extreme traits within their skull, such as a protruding lower jaw, a wider gape, and an increase in tooth number. These features are highly variable between individual cavefish and even across different cavefish populations. RESULTS: To investigate these traits, we created a novel feeding behavior assay wherein bite impressions could be obtained. We determined that fish with an underbite leave larger bite impressions with an increase in the number of tooth marks. Capitalizing on the ability to produce hybrids from surface and cavefish crosses, we investigated genes underlying these segregating orofacial traits by performing Quantitative Trait Loci (QTL) analysis with F2 hybrids. We discovered significant QTL for bite (underbite vs. overbite) that mapped to a single region of the Astyanax genome. Within this genomic region, multiple genes exhibit coding region mutations, some with known roles in bone development. Further, we determined that there is evidence that this genomic region is under natural selection. CONCLUSIONS: This work highlights cavefish as a valuable genetic model for orofacial patterning and will provide insight into the genetic regulators of jaw and tooth development.

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.

Mating success at elevated temperature is associated to thermal adaptation in a set of recombinant inbred lines of Drosophila melanogaster.

In insects, mating ability at elevated temperature can be relevant for adaptation to heat-stressed environments and global warming. Here, we examined copulation latency (T1), copulation duration (T2), and mating frequency (T3, an index of mating success) in two related sets of recombinant inbred lines (RIL) in Drosophila melanogaster at both elevated (33 °C) and benign (25 °C) temperatures. One of these RIL sets (RIL-SH2) was shown to be consistently more resistant in both heat knockdown and heat-shock survival assays than its related set (RIL-D48) in previous studies. Negative correlations across RILs were found between T1 and T3 in this study. Flies from the heat-resistant set of RIL (RIL-SH2) were better able to mate at elevated temperature than flies from the heat-susceptible set (RIL-D48). Quantitative trait locus (QTL) mapping identified temperature-dependent QTLs for all traits (T1, T2 and T3) on all the three major chromosomes. Mating success at elevated temperature was found to be influenced by multiple QTLs. At elevated temperature, several QTLs for mating traits co-localized with QTLs that were previously associated with thermotolerance. The genetic basis for T1, T2 and T3 at the elevated temperature was found to be largely different from the genetic basis controlling the variation for mating success at benign temperature, as there was only a very low (or even null) number of QTLs overlapping across temperatures.

Genetic mapping of maize metabolites using high-throughput mass profiling.

Plant metabolites are the basis of human nutrition and have biological relevance in ecology. Farmers selected plants with favorable characteristics since prehistoric times and improved the cultivars, but without knowledge of underlying mechanisms. Understanding the genetic basis of metabolite production can facilitate the successful breeding of plants with augmented nutritional value. To identify genetic factors related to the metabolic composition in maize, we generated mass profiles of 198 recombinant inbred lines (RILs) and their parents (B73 and Mo17) using direct-injection electrospray ionization mass spectrometry (DLI-ESI MS). Mass profiling allowed the correct clustering of samples according to genotype. We quantified 71 mass features from grains and 236 mass features from leaf extracts. For the corresponding ions, we identified tissue-specific metabolic 'Quantitative Trait Loci' (mQTLs) distributed across the maize genome. These genetic regions could regulate multiple metabolite biosynthesis pathways. Our findings demonstrate that DLI-ESI MS has sufficient analytical resolution to map mQTLs. These identified genetic loci will be helpful in metabolite-focused maize breeding. Mass profiling is a powerful tool for detecting mQTLs in maize and enables the high-throughput screening of loci responsible for metabolite biosynthesis.

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.

Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness.

Understanding the architecture of gene expression is fundamental to unravel the molecular mechanisms regulating complex traits in bovine, such as intramuscular fat content (IMF) and backfat thickness (BFT). These traits are economically important for the beef industry since they affect carcass and meat quality. Our main goal was to identify gene expression regulatory polymorphisms within genomic regions (QTL) associated with IMF and BFT in Nellore cattle. For that, we used RNA-Seq data from 193 Nellore steers to perform SNP calling analysis. Then, we combined the RNA-Seq SNP and a high-density SNP panel to obtain a new dataset for further genome-wide association analysis (GWAS), totaling 534,928 SNPs. GWAS was performed using the Bayes B model. Twenty-one relevant QTL were associated with our target traits. The expression quantitative trait loci (eQTL) analysis was performed using Matrix eQTL with the complete SNP dataset and 12,991 genes, revealing a total of 71,033 cis and 36,497 trans-eQTL (FDR < 0.05). Intersecting with QTL for IMF, we found 231 eQTL regulating the expression levels of 117 genes. Within those eQTL, three predicted deleterious SNPs were identified. We also identified 109 eQTL associated with BFT and affecting the expression of 54 genes. This study revealed genomic regions and regulatory SNPs associated with fat deposition in Nellore cattle. We highlight the transcription factors FOXP4, FOXO3, ZSCAN2, and EBF4, involved in lipid metabolism-related pathways. These results helped us to improve our knowledge about the genetic architecture behind important traits in cattle.

Genome-Wide Analysis of Disordered Eating Behavior in the Mexican Population.

Alterations in eating behavior characterized eating disorders (ED). The genetic factors shared between ED diagnoses have been underexplored. The present study performed a genome-wide association study in individuals with disordered eating behaviors in the Mexican population, blood methylation quantitative trait loci (blood-meQTL), summary data-based Mendelian randomization (SMR) analysis, and in silico function prediction by different algorithms. The analysis included a total of 1803 individuals. We performed a genome-wide association study and blood-meQTL analysis by logistic and linear regression. In addition, we analyzed in silico functional variant prediction, phenome-wide, and multi-tissue expression quantitative trait loci. The genome-wide association study identified 44 single-nucleotide polymorphisms (SNP) associated at a nominal value and seven blood-meQTL at a genome-wide threshold. The SNPs show enrichment in genome-wide associations of the metabolic and immunologic domains. In the in silico analysis, the SNP rs10419198 (p-value = 4.85 × 10-5) located on an enhancer mark could change the expression of PRR12 in blood, adipocytes, and brain areas that regulate food intake. Additionally, we found an association of DNA methylation levels of SETBP1 (p-value = 6.76 × 10-4) and SEMG1 (p-value = 5.73 × 10-4) by SMR analysis. The present study supports the previous associations of genetic variation in the metabolic domain with ED.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean.

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Genome-wide association mapping for heading date in oats under subtropical environments

Selection for heading date has been a decisive factor to increase areas cropped with oats in Brazil. Although important to oat breeders, genomic regions controlling heading date have not been completely identified. The objective of this study was to identify genomic regions controlling oat heading date in subtropical environments. A set of 412 oat genotypes, developed from 1974 to 2015, was assessed for heading date in contrasting environments and genotyped using genotyping-by-sequencing (GBS). Phenotypic and genotypic data were used in single and multi-environment association models. Quantitative trait loci (QTL) associated to heading date were identified on oat consensus groups Mrg02, Mrg05, Mrg06, Mrg12, and Mrg21. Some of the findings confirmed the association of genomic regions with heading date, while others emerge as new candidate regions associated to the trait. The genomic regions identified on Mrg02 and Mrg12 were associated to Vernalization 3 (Vrn3), while the genomic region identified on Mrg21 is associated with Vernalization 1 (Vrn1). The Vrn1 region was detected in Londrina, an environment with reduced vernalization condition, and in the multi-environment model. The results reveal that some genotypes of the panel are responsive to vernalization, increasing the days to heading without this environmental stimulus. Our results provide important contribution for a better understanding of heading date in subtropical environments and a strong basis for marker-assisted selection in oats.

Discovering of Genomic Variations Associated to Growth Traits by GWAS in Braunvieh Cattle.

A genome-wide association study (GWAS) was performed to elucidate genetic architecture of growth traits in Braunvieh cattle. Methods: The study included 300 genotyped animals by the GeneSeek® Genomic Profiler Bovine LDv.4 panel; after quality control, 22,734 SNP and 276 animals were maintained in the analysis. The examined phenotypic data considered birth (BW), weaning (WW), and yearling weights. The association analysis was performed using the principal components method via the egscore function of the GenABEL version 1.8-0 package in the R environment. The marker rs133262280 located in BTA 22 was associated with BW, and two SNPs were associated with WW, rs43668789 (BTA 11) and rs136155567 (BTA 27). New QTL associated with these liveweight traits and four positional and functional candidate genes potentially involved in variations of the analyzed traits were identified. The most important genes in these genomic regions were MCM2 (minichromosome maintenance complex component 2), TPRA1 (transmembrane protein adipocyte associated 1), GALM (galactose mutarotase), and NRG1 (neuregulin 1), related to embryonic cleavage, bone and tissue growth, cell adhesion, and organic development. This study is the first to present a GWAS conducted in Braunvieh cattle in Mexico providing evidence for genetic architecture of assessed growth traits. Further specific analysis of found associated genes and regions will clarify its contribution to the genetic basis of growth-related traits.

QTL mapping for bioenergy traits in sweet sorghum recombinant inbred lines.

During the past decade, sweet sorghum (Sorghum bicolor Moench L.) has shown great potential for bioenergy production, especially biofuels. In this study, 223 recombinant inbred lines (RILs) derived from a cross between two sweet sorghum lines (Brandes × Wray) were evaluated in three trials. Single-nucleotide polymorphisms (SNPs) derived from genotyping by sequencing of 272 RILs were used to build a high-density genetic map comprising 3,767 SNPs spanning 1,368.83 cM. Multitrait multiple interval mapping (MT-MIM) was carried out to map quantitative trait loci (QTL) for eight bioenergy traits. A total of 33 QTLs were identified for flowering time, plant height, total soluble solids and sucrose (five QTLs each), fibers (four QTLs), and fresh biomass yield, juice extraction yield, and reducing sugars (three QTLs each). QTL hotspots were found on chromosomes 1, 3, 6, 9, and 10, in addition to other QTLs detected on chromosomes 4 and 8. We observed that 14 out of the 33 mapped QTLs were found in all three trials. Upon further development and validation in other crosses, the results provided by the present study have a great potential to be used in marker-assisted selection in sorghum breeding programs for biofuel production.

Genetic Mapping for Agronomic Traits in IAPAR 81/LP97-28 Population of Common Bean (Phaseolus vulgaris L.) under Drought Conditions.

One of the significant challenges of common bean breeding is developing cultivars with high yields under drought conditions. The present study attempted to map quantitative trait loci (QTLs) and identify molecular markers that are linked to drought tolerance in the common bean. We evaluated 160 recombinant inbred lines (RILs), derived from the cross between the carioca cultivars IAPAR 81 (drought tolerant) and LP97-28 (susceptible to drought). In 2014 and 2015, two experiments were conducted (DS-drought stress, and NS-no drought stress). In the DS experiment, water suppression was performed at the flowering stages R5 to R6. The results of our experiments showed that drought conditions play an essential role in reducing most of the traits that were evaluated. RILs under drought conditions reduced the grain yield by 62.03% and 24% in 2014 and 2015, respectively. We identified 15 quantitative trait loci distributed on the chromosomes Pv01, Pv02, Pv03, Pv07, Pv08, Pv09, Pv10, and Pv11, related to grain yield, seed yield per day, 100-seed weight, number of pods per plant, plant height, number of days for flowering, and number of days to maturity. The characteristics of seed yield per day, 100-seed weight, and number of days to maturity showed that QTLs colocalized on Pv07. Identifying QTLs that are linked to drought tolerance in the RIL population IAPAR 81 × LP97-28 is of particular importance for common bean breeding programs seeking to improve carioca beans that are cultivated in regions with drought conditions, such as Brazil.

Detection of Quantitative Trait Loci Controlling the Content of Phenolic Compounds in an Asian Plum (Prunus salicina L.) F1 Population.

Consumption of fresh fruit is known to protect against non-communicable diseases due to the fruit's content in compounds with an antioxidant capacity, among them is polyphenols. Asian plums (Prunus salicina L.) accumulate more than 40 phenolic compounds, with a remarkable diversity in their profiles, depending on the variety and environmental conditions. Although candidate genes have been indicated to control this trait, the loci controlling its phenotypic variation have not yet been defined in this species. The aim of this work was to identify the quantitative trait Loci (QTL) controlling the phenolic compounds content in the Asian plum skin and flesh. Using UHPLC-DAD-Orbitrap-MS, we determined that cyanidin-3-glucoside and cyanidin-3-rutinoside are the main anthocyanins in Asian plums. Other anthocyanins found to a lesser extent were tentatively identified as cyanidin bound to different sugar and procyanidin moieties. Then we phenotyped fruits of 92 and 80 F1 seedlings from the cross < "98.99" × "Angeleno"> (98 Ang) for two harvest seasons. We used HPLC-DAD to quantify single anthocyanin and spectrophotometric techniques to determine the total content of phenols, flavonoids, procyanidins, and antioxidant activity (DPPH and FRAP). To determine the phenotype-genotype association of phenolic compounds content, phenotypic values (adjusted by linear mixed-effects models), genotypic data and linkage maps were analyzed with the multiple QTL model (MQM) approach. We found a total of 21 significant trait-marker associations: 13 QTLs segregating from "98.99" and 8 QTLs from "Angeleno." From these associations, 8 corresponded to phenolic compound content in the flesh and 13 in the skin. Phenotype variance was explained by the detected loci, ranging from 12.4 to 27.1%. The identified loci are related to the content of cyanidin-3-glucoside (LG4), cyanidin-3-rutinoside (LG4), total flavonoids and procyanidins (LG5 and LG8), and minor anthocyanin compounds (LG3 and LG4). These results will help improve the efficiency of breeding programs for the generation of Asian plum varieties with high phenolic compound content.

Genetic mapping of metabolic traits in the blind Mexican cavefish reveals sex-dependent quantitative trait loci associated with cave adaptation.

BACKGROUND: Despite a longstanding interest in understanding how animals adapt to environments with limited nutrients, we have incomplete knowledge of the genetic basis of metabolic evolution. The Mexican tetra, Astyanax mexicanus, is a species of fish that consists of two morphotypes; eyeless cavefish that have adapted to a low-nutrient cave environment, and ancestral river-dwelling surface fish with abundant access to nutrients. Cavefish have evolved altered blood sugar regulation, starvation tolerance, increased fat accumulation, and superior body condition. To investigate the genetic basis of cavefish metabolic evolution we carried out a quantitative trait loci (QTL) analysis in surface/cave F2 hybrids. We genetically mapped seven metabolism-associated traits in hybrids that were challenged with a nutrient restricted diet. RESULTS: We found that female F2 hybrids are bigger than males and have a longer hindgut, bigger liver, and heavier gonad, even after correcting for fish size. Although there is no difference between male and female blood sugar level, we found that high blood sugar is associated with weight gain in females and lower body weight and fat level in males. We identified a significant QTL associated with 24-h-fasting blood glucose level with the same effect in males and females. Differently, we identified sex-independent and sex-dependent QTL associated with fish length, body condition, liver size, hindgut length, and gonad weight. We found that some of the genes within the metabolism QTL display evidence of non-neutral evolution and are likely to be under selection. Furthermore, we report predicted nonsynonymous changes to the cavefish coding sequence of these genes. CONCLUSIONS: Our study reveals previously unappreciated genomic regions associated with blood glucose regulation, body condition, gonad size, and internal organ morphology. In addition, we find an interaction between sex and metabolism-related traits in A. mexicanus. We reveal coding changes in genes that are likely under selection in the low-nutrient cave environment, leading to a better understanding of the genetic basis of metabolic evolution.

Genetic dissection of flowering time in flax (Linum usitatissimum L.) through single- and multi-locus genome-wide association studies.

In a rapidly changing climate, flowering time (FL) adaptation is important to maximize seed yield in flax (Linum usitatissimum L.). However, our understanding of the genetic mechanism underlying FL in this multipurpose crop remains limited. With the aim of dissecting the genetic architecture of FL in flax, a genome-wide association study (GWAS) was performed on 200 accessions of the flax core collection evaluated in four environments. Two single-locus and six multi-locus models were applied using 70,935 curated single nucleotide polymorphism (SNP) markers. A total of 40 quantitative trait nucleotides (QTNs) associated with 27 quantitative trait loci (QTL) were identified in at least two environments. The number of QTL with positive-effect alleles in accessions was significantly correlated with FL (r = 0.77 to 0.82), indicating principally additive gene actions. Nine QTL were significant in at least three of the four environments accounting for 3.06-14.71% of FL variation. These stable QTL spanned regions that harbored 27 Arabidopsis thaliana and Oryza sativa FL-related orthologous genes including FLOWERING LOCUS T (Lus10013532), FLOWERING LOCUS D (Lus10028817), transcriptional regulator SUPERMAN (Lus10021215), and gibberellin 2-beta-dioxygenase 2 (Lus10037816). In silico gene expression analysis of the 27 FL candidate gene orthologous suggested that they might play roles in the transition from vegetative to reproductive phase, flower development and fertilization. Our results provide new insights into the QTL architecture of flowering time in flax, identify potential candidate genes for further studies, and demonstrate the effectiveness of combining different GWAS models for the genetic dissection of complex traits.

Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia.

BACKGROUND: Body traits are generally controlled by several genes in vertebrates (i.e. polygenes), which in turn make them difficult to identify through association mapping. Increasing the power of association studies by combining approaches such as genotype imputation and multi-trait analysis improves the ability to detect quantitative trait loci associated with polygenic traits, such as body traits. RESULTS: A multi-trait genome-wide association study (mtGWAS) was performed to identify quantitative trait loci (QTL) and genes associated with body traits in Nile tilapia (Oreochromis niloticus) using genotypes imputed to whole-genome sequences (WGS). To increase the statistical power of mtGWAS for the detection of genetic associations, summary statistics from single-trait genome-wide association studies (stGWAS) for eight different body traits recorded in 1309 animals were used. The mtGWAS increased the statistical power from the original sample size from 13 to 44%, depending on the trait analyzed. The better resolution of the WGS data, combined with the increased power of the mtGWAS approach, allowed the detection of significant markers which were not previously found in the stGWAS. Some of the lead single nucleotide polymorphisms (SNPs) were found within important functional candidate genes previously associated with growth-related traits in other terrestrial species. For instance, we identified SNP within the α1,6-fucosyltransferase (FUT8), solute carrier family 4 member 2 (SLC4A2), A disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and heart development protein with EGF like domains 1 (HEG1) genes, which have been associated with average daily gain in sheep, osteopetrosis in cattle, chest size in goats, and growth and meat quality in sheep, respectively. CONCLUSIONS: The high-resolution mtGWAS presented here allowed the identification of significant SNPs, linked to strong functional candidate genes, associated with body traits in Nile tilapia. These results provide further insights about the genetic variants and genes underlying body trait variation in cichlid fish with high accuracy and strong statistical support.