Heritability Research Articles

Morpho-agronomıc varıabılıty, herıtabılıty and genetıc advance studıes ın sesame (sesamum ındıcum L.) In nıgerıa

The study explored morpho-agronomic and biochemical traits to assess variability level and the degree of genetic diversity in 15 Sesame accessions. Data were subjected to analysis of variance, multivariate analyses, and genetic parameters were estimated. Significant differences (P < 0.05) existed among the accessions in all the characters. Four components with a cumulative variation of 85.7% were extracted. Substantial broad sense heritability estimates and high genetic gain were observed in secondary branches (97.8%; 719.4%), primary branches (96.1%;142,5%), capsules per plant (97.8%; 141.1%), single plant seed yield (86.87%; 46.03%), capsule length (99.16%; 32%), and 500 seed weight (95.15%; 34.12%). It may be inferred that a considerable level of variability existed among the accessions studied and charcters like branching habit, capsules per plant, capsule length and single plant seed yield could be considered for selection in breeding for superior genotypes. Bangladesh J. Bot. 53(1): 75-81, 2024 (March)

Genetic variability and character association among maize (Zea mays L.) Inbred lines

Genetic analysis of variability, heritability and character association was studied among 25 maize inbred lines for eleven traits. The ANOVA indicated significant variation existed among the inbred lines chosen for the study for all the traits. Wide range of variability was observed for all the traits among them grain yield varied from 16.03 to 62.52 q/ha with an average mean value of 45.75 q/ha. Phenotypic variance was higher compared to genotypic variance and highest phenotypic variance was observed for plant height followed by grain yield. However, the difference between phenotypic and genotypic variance was very narrow for majority of the traits. Similarly, phenotypic coefficient of variation (PCV) was marginally higher than genotypic coefficient of variation (GCV) and highest GCV and PCV was recorded for grain yield (37.03, 38.12) followed by ear height (24.12, 26.48) indicating that these characters are under genetic control have high potential for selection. The high amount of broad-sense heritability coupled with high genetic advance as a percent mean (GAM) was observed for grain yield (0.94 and 74.12) followed by number of kernels per row (0.90 and 32.88) indicating phenotypic based selection for these traits would be successful. Hundred grain weight had the highest genotypic correlation (0.834) with grain yield followed by number of kernels per row (0.623). Bangladesh J. Bot. 53(1): 57-65, 2024 (March)

Determination of combining ability and heritability for canning quality traits in common bean

Breeding for common bean (Phaseolus vulgaris L.) genotypes with optimal canning quality holds the potential for increased dry bean consumption among middle-class income urban dwellers in sub-Saharan Africa (SSA). Understanding the genetic control of canning quality traits is central for the improvement of common bean genotypes for desired canning quality. The objective of this study was to determine the combining ability and heritability of canning quality traits (CQTs) in common bean; and to establish entry points for effective breeding for these traits. A population from two contrasting parents for canning quality traits was developed and progressed to F2. The F2:F4 seed was evaluated for CQTs at three months post-harvest. Substantial variation was observed among the canning quality traits tested, including the general appearance of the canned beans, seed coat colour retention namely, clumping, free starch, splitting, and hydration coefficient. Canning quality traits encompassed a spectrum of both additive and non-additive effects. Promising combiners for CQTs were identified among the parents, KK8 and MAC 13, suggesting their potential for utilisation in breeding programmes. Moderate to high Baker’s ratio (BR = 0.41-0.94) values were observed for some CQTs and narrow sense heritability (h2 = 0.47-0.66). Canning quality traits exhibited substantial broad sense heritability (H2) values, ranging from 0.6 to 0.92. These findings provide valuable entry points for breeding programmes focused on improving common bean for canning quality.

Genetic diversity and heritability of tomato parental lines assembled for Ralstonia solanacearum resistance

Bacterial wilt is a disease caused by Ralstonia solanacearum, which affects over 450 plant species and causes significant reduction in crop yields including of tomato (Solanum lycopersicum) worldwide. Developing and identifying tomato genotypes with Ralstonia solanacearum tolerance and high yield potential, presents an opportunity for improvement of crop productivity. The objective of this study was to explore the heritability of tomato resistance against bacterial wilt and the genetic variation within the population for breeding purposes. A breeding population was created by crossing two bacterial wilt-resistant (MT56 and BL333) and three commercially desirable susceptible (Assila, Rambo and Heinz) tomato varieties, using North Carolina Design II, in a screen house at the Makerere University Agricultural Research Institute, Kabanyolo (MUARIK). Results showed that the Area Under Disease Progress Curve was significant (P<0.001), indicating that cumulative disease progress was less in resistant genotypes of segregating generations. Disease severity increased with days after inoculation (DAI), with Heinz showing the highest level of susceptibility. The General Combining Ability for male parent (GCAm) was significant (P< 0.01), and Specific Combining Ability (SCAf×m) and GCAf were significant (P<0.01) for the F2 generation. Broad-sense heritability was higher than the narrow-sense heritability in both F1 and F2 generations, suggesting that non-additive gene action predominately controlled tomato resistance to bacterial wilt infestation. The genetic diversity ranged from 0.5 to 0.6759, with a mean value of 0.5787. Polymorphism Information Content (PIC) varied from 0.375 to 0.6357, with a mean of 0.4888, indicating a high degree of variation. SLM 12-2 was the most polymorphic marker, with a PIC of 0.6357. The Unweighted Pair-Group Method with Arithmetic Average (UPGMA) classified all tomato genotypes into six clusters, namely Clusters 1 and 2 (Susceptible parents), Cluster 3 (Resistant parents), Clusters 4 and 5 (New source of resistance), and Cluster 6 (F1P1×P5).

Genetic and Epigenetic Mechanisms Regulating Blood Pressure and Kidney Dysfunction.

The pioneering work of Dr Lewis K. Dahl established a relationship between kidney, salt, and high blood pressure (BP), which led to the major genetic-based experimental model of hypertension. BP, a heritable quantitative trait affected by numerous biological and environmental stimuli, is a major cause of morbidity and mortality worldwide and is considered to be a primary modifiable factor in renal, cardiovascular, and cerebrovascular diseases. Genome-wide association studies have identified monogenic and polygenic variants affecting BP in humans. Single nucleotide polymorphisms identified in genome-wide association studies have quantified the heritability of BP and the effect of genetics on hypertensive phenotype. Changes in the transcriptional program of genes may represent consequential determinants of BP, so understanding the mechanisms of the disease process has become a priority in the field. At the molecular level, the onset of hypertension is associated with reprogramming of gene expression influenced by epigenomics. This review highlights the specific genetic variants, mutations, and epigenetic factors associated with high BP and how these mechanisms affect the regulation of hypertension and kidney dysfunction.

Selective Genotyping and Phenotyping for Optimization of Genomic Prediction Models for Populations with Different Diversity.

To overcome the different challenges to food security caused by a growing population and climate change, soybean (Glycine max (L.) Merr.) breeders are creating novel cultivars that have the potential to improve productivity while maintaining environmental sustainability. Genomic selection (GS) is an advanced approach that may accelerate the rate of genetic gain in breeding using genome-wide molecular markers. The accuracy of genomic selection can be affected by trait architecture and heritability, marker density, linkage disequilibrium, statistical models, and training set. The selection of a minimal and optimal marker set with high prediction accuracy can lower genotyping costs, computational time, and multicollinearity. Selective phenotyping could reduce the number of genotypes tested in the field while preserving the genetic diversity of the initial population. This study aimed to evaluate different methods of selective genotyping and phenotyping on the accuracy of genomic prediction for soybean yield. The evaluation was performed on three populations: recombinant inbred lines, multifamily diverse lines, and germplasm collection. Strategies adopted for marker selection were as follows: SNP (single nucleotide polymorphism) pruning, estimation of marker effects, randomly selected markers, and genome-wide association study. Reduction of the number of genotypes was performed by selecting a core set from the initial population based on marker data, yet maintaining the original population's genetic diversity. Prediction ability using all markers and genotypes was different among examined populations. The subsets obtained by the model-based strategy can be considered the most suitable for marker selection for all populations. The selective phenotyping based on makers in all cases had higher values of prediction ability compared to minimal values of prediction ability of multiple cycles of random selection, with the highest values of prediction obtained using AN approach and 75% population size. The obtained results indicate that selective genotyping and phenotyping hold great potential and can be integrated as tools for improving or retaining selection accuracy by reducing genotyping or phenotyping costs for genomic selection.

The genetic architecture of complete blood counts in lactating Holstein dairy cows.

Complete blood counts (CBCs) measure the abundance of individual immune cells, red blood cells, and related measures such as platelets in circulating blood. These measures can indicate the health status of an animal; thus, baseline circulating levels in a healthy animal may be related to the productive life, resilience, and production efficiency of cattle. The objective of this study is to determine the heritability of CBC traits and identify genomic regions that are associated with CBC measurements in lactating Holstein dairy cattle. The heritability of CBCs was estimated using a Bayes C0 model. The study population consisted of 388 cows with genotypes at roughly 75,000 markers and 16 different CBC phenotypes taken at one to three time points (n = 33, 131, and 224 for 1, 2, and 3 time points, respectively). Heritabilities ranged from 0.00 ± 0.00 (red cell distribution width) to 0.68 ± 0.06 (lymphocytes). A total of 96 different 1-Mb windows were identified that explained more than 1% of the genetic variance for at least one CBC trait, with 10 windows explaining more than 1% of the genetic variance for two or more traits. Multiple genes in the identified regions have functions related to immune response, cell differentiation, anemia, and disease. Positional candidate genes include RAD52 motif-containing protein 1 (RDM1), which is correlated with the degree of immune infiltration of immune cells, and C-X-C motif chemokine ligand 12 (CXCL12), which is critically involved in neutrophil bone marrow storage and release regulation and enhances neutrophil migration. Since animal health directly impacts feed intake, understanding the genetics of CBCs may be useful in identifying more disease-resilient and feed-efficient dairy cattle. Identification of genes responsible for variation in CBCs will also help identify the variability in how dairy cattle defend against illness and injury.

Applying unoccupied aerial systems to assess genetic gain from mass selection for tembotrione tolerance in sorghum (Sorghum bicolor)

AbstractThe post‐emergent herbicide options to control grasses in sorghum have historically been limited. Therefore, a mass selection program was implemented to increase the tolerance of sorghum to the broad‐spectrum herbicide tembotrione. The objectives of this study are to determine (i) which observation timing and vegetative indices are most effective in assessing sorghum injury to tembotrione using unoccupied aerial system imagery and (ii) if mass selection can be used to increase the tolerance of sorghum to tembotrione. Using an unoccupied aerial system, several vegetative indices, collected at either 14 or 21 days after tembotrione application, accurately measured sorghum injury. Over four cycles of selection, tembotrione tolerance increased in a linear and consistent manner. This demonstrates that mass selection can be used as a strategy for developing herbicide tolerance in crops. The modest, but steady genetic gain indicates both the quantitative nature of the trait and sufficient heritability to improve it. Given further development, tembotrione‐resistant sorghum hybrids could provide an effective means of post‐emergent weed control for a range of common weeds.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden).

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

Analysis of Genetic Variability and Heritability in Brinjal (Solanum melongena L.) Genotypes

Analysis on “Study of genetic variability and heritability in brinjal (Solanum melongena L.) genotypes” was carried out at the experimental field of Division of Vegetable Science, FOH, SKUAST, Kashmir Shalimar during kharif season 2021 in Randomised Complete Block Design with three replications. The experimental material comprised of forty genotypes. Analysis of variance revealed that mean sum of squares due to genotypes for all the characters were highly significant, revealing significant variation among all the genotypes for all the traits under study. The phenotypic coefficients of variation were found to be higher than the corresponding genotypic coefficients of variation. The phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) in present experienment were high for the traits; average fruit weight (43.69% and 43.69%), total anthocyanin content (39.10 % and 39.10%), ascorbic acid (31.73 % and 31.73) and dry matter (42.31% and 42.29). Heritability in broad sense was found to be high for all traits under study (greater than 70 per cent). Highest genetic advance as percentage of mean was recorded in average fruit weight (90) followed by dry matter (87.11) and total anthocyanin content (80.55).

Abstract 3425: Genetic predisposition to obesity and survival in women with breast cancer

Abstract Background. Higher body mass index (BMI) is associated with poor survival after breast cancer diagnosis. BMI is a heritable trait. A polygenic risk score (PRS) for BMI has been associated with cardiometabolic traits and found to modify weight loss interventions. Whether BMI genetic scores affect survival in women with breast cancer is unknown. Methods. This analysis was conducted in the Cancer Prevention Study II Nutrition cohort. Women diagnosed with non-metastatic breast cancer between 1992 and 2017 were included in the analysis if they had genotype data. Analyses were restricted to unrelated, postmenopausal women at the time of diagnosis who were of European ancestry (N=3,566). Deaths through 2020 were identified through linkage with the National Death Index. Primary cause of death was based on the International Classification of Disease codes. Pre-diagnosis BMI was self-reported (median 1.3 years from BMI measurement to diagnosis, interquartile range (IQR): 0.6, 1.9). We constructed a PRS using findings from a published meta-analysis of BMI genome wide association studies (GWAS) that included ~700,000 individuals and the PRSice tool.Hazard ratios (HR) and 95% confidence intervals (CI) between the PRS and all-cause mortality were estimated using Cox proportional hazards regression and Fine and Gray models for cause-specific mortality to account for competing risks. Models were adjusted for age and GWAS-specific statistically significant (P<0.05) principal components for population stratification. Mediation was estimated using the mediation R package. Results. The median age at diagnosis was 71.5 years (IQR: 66.3, 76.8). Most women were overweight (33.5%) or obese (18.4%) and were diagnosed with localized stage (63%) and estrogen receptor positive (65%) breast cancer. During a median follow-up of 14.5 years (IQR: 9.7-19.8), there were 1,825 (51.2%) deaths, including 301 breast cancer and 337 cardiovascular disease (CVD) specific deaths. In multivariable models, a 5 Kg/m2 increase in BMI was associated with increased risks of all-cause mortality (HR=1.09, 95% CI: 1.04, 1.15), breast cancer-specific mortality (HR=1.27, 95% CI: 1.13, 1.42), and CVD-specific mortality (HR=1.25, 95% CI: 1.11, 1.41). The PRS was highly predictive of pre-diagnostic BMI (P<0.001). A 1-standard deviation increase in the PRS was associated with statistically increased risk of all-cause mortality (HR=1.06, 95% CI: 1.02, 1.11). Risks of breast cancer (HR=1.07, 95% CI: 0.96, 1.19) or CVD (HR=1.01, 95% CI: 0.90, 1.12) specific mortality did not reach statistical significance. We estimated that 27% of the PRS and all-cause mortality association was mediated by BMI (95% CI: 12%, 91%; P=0.004). Conclusions. Women with breast cancer predisposed to higher BMI were at increased risk of all-cause mortality. A BMI-related PRS may be a useful tool to identify women with breast cancer in need of additional interventions and/or surveillance. Citation Format: Clara Bodelon, Adriana Lori, Mariah Landry, James Hodge, Parichoy Pal Choudhury, Ying Wang, Lauren E. McCullough, Alpa V. Patel, Lauren R. Teras. Genetic predisposition to obesity and survival in women with breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3425.

Variability in seed quality traits in castor germplasm

Castor is an industrial oilseed crop with great potential for biorefineries. However, little is known about the variability in the bioactive compounds in castor germplasm. This study evaluated seed weight, oil content, fatty acid profile, tocopherols, and phytosterols in 160 accessions of the USDA-ARS castor germplasm collection. The accessions were grown in Cordoba, Spain, under three different environmental conditions. Environmental and genotype-by-environment interaction effects were predominant for most traits, resulting in moderate to low broad-sense heritabilities, which ranged from 0.12 for total tocopherol content to 0.88 for hundred-seed weight. The genetic variability in the seed quality traits identified in the collection was lower than that reported previously for the germplasm of wild and semi-wild accessions from Spain, which is attributed to the lower genetic diversity in cultivated than in wild forms. The variation in seed quality traits in castor germplasm can be exploited to improve the concentration of bioactive compounds in castor cultivars.

Genetic diversity and candidate genes for transient waterlogging tolerance in mungbean at the germination and seedling stages.

Mungbean [Vigna radiata var. radiata (L.) Wilczek] production in Asia is detrimentally affected by transient soil waterlogging caused by unseasonal and increasingly frequent extreme precipitation events. While mungbean exhibits sensitivity to waterlogging, there has been insufficient exploration of germplasm for waterlogging tolerance, as well as limited investigation into the genetic basis for tolerance to identify valuable loci. This research investigated the diversity of transient waterlogging tolerance in a mini-core germplasm collection of mungbean and identified candidate genes for adaptive traits of interest using genome-wide association studies (GWAS) at two critical stages of growth: germination and seedling stage (i.e., once the first trifoliate leaf had fully-expanded). In a temperature-controlled glasshouse, 292 genotypes were screened for tolerance after (i) 4 days of waterlogging followed by 7 days of recovery at the germination stage and (ii) 8 days of waterlogging followed by 7 days of recovery at the seedling stage. Tolerance was measured against drained controls. GWAS was conducted using 3,522 high-quality DArTseq-derived SNPs, revealing five significant associations with five phenotypic traits indicating improved tolerance. Waterlogging tolerance was positively correlated with the formation of adventitious roots and higher dry masses. FGGY carbohydrate kinase domain-containing protein was identified as a candidate gene for adventitious rooting and mRNA-uncharacterized LOC111241851, Caffeoyl-CoA O-methyltransferase At4g26220 and MORC family CW-type zinc finger protein 3 and zinc finger protein 2B genes for shoot, root, and total dry matter production. Moderate to high broad-sense heritability was exhibited for all phenotypic traits, including seed emergence (81%), adventitious rooting (56%), shoot dry mass (81%), root dry mass (79%) and SPAD chlorophyll content (70%). The heritability estimates, marker-trait associations, and identification of sources of waterlogging tolerant germplasm from this study demonstrate high potential for marker-assisted selection of tolerance traits to accelerate breeding of climate-resilient mungbean varieties.

Exploring Variability, Character Association and Path Analysis in Chickpea (Cicer arietinum L.) Accessions in the Northwestern Region of India

Assessing genetic variability makes it easier to identify stronger genotypes, allowing to produce high-yielding crops that are climatically resilient and promote efficient crop improvement. The present study aimed to assesses the genetic variability, association study & path analysis of 51 chickpea [Cicer arietinum (L.)] genotypes on 12 characteristics. The experiment utilized Randomized complete block design with three replications conducted in Phagwara, Punjab. The ANOVA recorded significant variance at the 1% level for all traits, indicating considerable variability amongst germplasm. SY expressed comparatively high Genotypic coefficient of variance and heritability with other traits, indicating that it is the most heritable trait and has the highest potential for improvement through selective breeding. Positive correlation with SY was revealed by PH, NPB, NSB, NPP, NFP, TW, BY, HI. Path analysis revealed that NFP had highest positive effect on SY followed by NUFP, HI, BY, NSB, TW, DFF & DM suggesting selection from any of these traits would be beneficial. When selecting traits to improve yield in chickpea through breeding, it is essential to focus on specific characteristics that directly contribute to higher production. This research will help understand yield-influencing factors for resilient chickpea varieties in Punjab environmental conditions.

Abstract P491: Functional Annotations for Improvements in Height and Blood Pressure Polygenic Risk Scores

Background: Genome-wide association studies (GWAS) have advanced our understanding of the polygenic basis of common, complex disorders. However, translating GWAS findings into clinical applications remains challenging. Polygenic risk scores (PRS) hold promise for clinical use with recent methodologies enhancing predictive accuracy. This study compared two PRS (LDpred-funct which incorporates functional annotations into the score and a traditional linear scoring system) for traits with varying heritability in European- (EA) and African-ancestry (AA) populations, addressing a need to evaluate novel approaches across diverse conditions and populations. Hypothesis: This study hypothesized that integrating functional annotations into PRS derivation will enhance performance compared to assessing the genetic load for a trait. The addition will provide improvement for (1) traits with high (height) compared to moderate (systolic blood pressure, SBP) heritability and (2) individuals with EA relative to AA. Methods: This study used multi-ancestry summary statistics representing data from 4,080,687 individuals for height (GIANT consortium) and 436,099 individuals for SBP adjusted for antihypertensive medication use (UK Biobank). Two PRS for these traits were constructed using LDpred-funct: PRS funct which incorporates the functional annotation and PRS raw which is a simple linear scoring system. Optimization was performed in 8,916 AA and 1,716 EA participants from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. PRS predictive performance was evaluated by calculating the proportion of trait variance explained by the PRS (R 2 ) after accounting for age, sex, and genetic ancestry. Results: For height, the PRS funct outperformed PRS raw among both race groups, with a greater improvement among EA (PRS funct R 2 =0.110 versus PRS raw R 2 =0.060, 5% difference) compared to AA (PRS funct R 2 =0.042 versus PRS raw R 2 =0.034, 0.8% difference). Similar findings were observed for medication-adjusted SBP, where PRS funct had better predictive performance than PRS raw , and with greater improvement observed in the EA (PRS funct R 2 =0.042 versus PRS raw R 2 =0.027, 1.5% difference) compared to AA participants (PRS funct R 2 =0.014 versus PRS raw R 2 =0.010, 0.4% difference). Conclusions: Incorporating functional priors into the PRS enhanced the predictive accuracy for both traits. A greater improvement was observed for the higher heritability (height) versus the moderate heritability (SBP) trait, as well as within individuals of EA compared to AA. These findings are currently undergoing validation, using data from the Electronic Medical Records and Genomics (eMERGE) Network, highlighting the potential of incorporating functional annotations into PRS development for broader clinical applications.

Genetic analysis of cassava brown streak disease root necrosis using image analysis and genome-wide association studies.

Cassava brown streak disease (CBSD) poses a substantial threat to food security. To address this challenge, we used PlantCV to extract CBSD root necrosis image traits from 320 clones, with an aim of identifying genomic regions through genome-wide association studies (GWAS) and candidate genes. Results revealed strong correlations among certain root necrosis image traits, such as necrotic area fraction and necrotic width fraction, as well as between the convex hull area of root necrosis and the percentage of necrosis. Low correlations were observed between CBSD scores obtained from the 1-5 scoring method and all root necrosis traits. Broad-sense heritability estimates of root necrosis image traits ranged from low to moderate, with the highest estimate of 0.42 observed for the percentage of necrosis, while narrow-sense heritability consistently remained low, ranging from 0.03 to 0.22. Leveraging data from 30,750 SNPs obtained through DArT genotyping, eight SNPs on chromosomes 1, 7, and 11 were identified and associated with both the ellipse eccentricity of root necrosis and the percentage of necrosis through GWAS. Candidate gene analysis in the 172.2kb region on the chromosome 1 revealed 24 potential genes with diverse functions, including ubiquitin-protein ligase, DNA-binding transcription factors, and RNA metabolism protein, among others. Despite our initial expectation that image analysis objectivity would yield better heritability estimates and stronger genomic associations than the 1-5 scoring method, the results were unexpectedly lower. Further research is needed to comprehensively understand the genetic basis of these traits and their relevance to cassava breeding and disease management.

Integration of genome-wide association and genomic prediction for dissecting seed protein and amino acid in foxtail millet

ContextThe exploitation and utilization of genetic variation in crop germplasm benefit genomics-informed breeding programs. The integration of genome-wide association study (GWAS) and genomic prediction (GP) holds promise for illustrating genetic basis of phenotypic variation. Currently, the use of this integrative approach for dissecting grain protein and amino acid traits remains limited in crop species. ObjectiveThe research objectives were to identify significant single nucleotide polymorphisms (SNPs) associated with seed protein and amino acids and to assess the genomic predictive ability for nutritional traits in natural population of foxtail millet. MethodsIn this study, the concentrations of seed protein and 17 amino acids were assessed in a training population consisting of 238 diverse accessions of foxtail millet. The significant SNPs associated with these phenotypes were identified by GWAS with a mix-linear model. Extensive cross-validation was performed to evaluate the accuracy of genomic prediction of seed nutritional traits. Furthermore, the genomic prediction model was optimized and externally validated in 211 untested materials with the most significant SNPs obtained from GWAS. ResultsA significant genotype variance was detected for seed protein and amino acids and broad-sense heritability (h2) ranged from 0.45 to 0.87 (P < 0.05). The GWAS identified 39 significant SNPs associated with 15 amino acids (p < 1e-06), explaining an average of 12.2% phenotypic variation per locus. The number of significant SNPs ranged from 1 (Asp, Ile, Glu) to 23 for Phe amino acid, including six SNPs associated with one or multiple amino acids. In the training population, the prediction accuracies of protein and amino acids, tested using the 10-fold cross-validation model with whole genome-wide SNPs, ranged from 0.23 (Glu) to 0.60 (Lys) with an average value of 0.44%. Population structure had little effect on the prediction accuracy. In an empirical validation experiment involving 211 untested accessions, the averaged prediction accuracy increased by 12.3% across all traits when using the 1000 top SNPs obtained from GWAS, compared with the same number of randomly selected SNPs from the entire genome. ConclusionsLarge variations of seed protein and amino acids were found in a natural population of foxtail millet. GWAS identified 39 significant SNPs associated with 15 amino acids, and six SNPs were linked to more than one trait. The 10-fold cross-validation model produced the relatively higher prediction accuracies in seed quality traits of diverse accessions. By applying the significant SNPs from GWAS to the untested accessions, the use of 1000 GWAS-top SNPs resulted in more powerful predictions for complex nutritional traits than those using the same number of randomly selected SNPs across the genome. SignificanceThe research highlights the importance and effectiveness of integrative GWAS and genomic prediction in revealing the genetic architecture of seed protein and amino acid variation in foxtail millet. The results provide valuable insights into assessment and improvement of germplasm resources for advancing precision crop phenotyping and enhancing breeding programs for crop nutritional traits.

Prioritization of Kidney Cell Types Highlights Myofibroblast Cells in Regulating Human Blood Pressure

IntroductionBlood pressure (BP) is a highly heritable trait with over two thousand underlying genomic loci identified to date. While the kidney plays a key role, little is known about specific cell types involved in the genetic regulation of BP. MethodsHere, we applied stratified linkage disequilibrium score (LDSC) regression to connect blood pressure GWAS results to specific cell types of the mature human kidney. We used the largest single-stage BP genome-wide analysis to date, including up to 1,028,980 adults of European ancestry, and single-cell transcriptomic data from 14 mature human kidneys, 41 years mean of age. ResultsOur analyses prioritized myofibroblasts and endothelial cells, among the total of 33 annotated cell type, as specifically involved in BP regulation (p-value < 0.05/33 i.e., 0.001515). Enrichment of heritability for systolic BP was observed in myofibroblast cells in mature human kidney cortex, and enrichment of heritability for diastolic BP was observed in descending vasa recta and peritubular capillary endothelial cells as well as stromal myofibroblast cells. The new finding of myofibroblast, the significant cell type for both BP traits, was consistent in eight replication efforts using seven sets of independent data, including in human fetal kidney, in East Asian ancestry, using mouse scRNA-seq data, and when using another prioritization method. ConclusionsOur findings provide a solid basis for follow up studies to further identify genes and mechanisms in myofibroblast cells that underlie the regulation of BP.

Combining GWAS and comparative genomics to fine map candidate genes for days to flowering in mung bean

BackgroundMung bean (Vigna radiata (L.) Wilczek), is an important pulse crop in the global south. Early flowering and maturation are advantageous traits for adaptation to northern and southern latitudes. This study investigates the genetic basis of the Days-to-Flowering trait (DTF) in mung bean, combining genome-wide association studies (GWAS) in mung bean and comparisons with orthologous genes involved with control of DTF responses in soybean (Glycine max (L) Merr) and Arabidopsis (Arabidopsis thaliana).ResultsThe most significant associations for DTF were on mung bean chromosomes 1, 2, and 4. Only the SNPs on chromosomes 1 and 4 were heavily investigated using downstream analysis. The chromosome 1 DTF association is tightly linked with a cluster of locally duplicated FERONIA (FER) receptor-like protein kinase genes, and the SNP occurs within one of the FERONIA genes. In Arabidopsis, an orthologous FERONIA gene (AT3G51550), has been reported to regulate the expression of the FLOWERING LOCUS C (FLC). For the chromosome 4 DTF locus, the strongest candidates are Vradi04g00002773 and Vradi04g00002778, orthologous to the Arabidopsis PhyA and PIF3 genes, encoding phytochrome A (a photoreceptor protein sensitive to red to far-red light) and phytochrome-interacting factor 3, respectively. The soybean PhyA orthologs include the classical loci E3 and E4 (genes GmPhyA3, Glyma.19G224200, and GmPhyA2, Glyma.20G090000). The mung bean PhyA ortholog has been previously reported as a candidate for DTF in studies conducted in South Korea.ConclusionThe top two identified SNPs accounted for a significant proportion (~ 65%) of the phenotypic variability in mung bean DTF by the six significant SNPs (39.61%), with a broad-sense heritability of 0.93. The strong associations of DTF with genes that have orthologs with analogous functions in soybean and Arabidopsis provide strong circumstantial evidence that these genes are causal for this trait. The three reported loci and candidate genes provide useful targets for marker-assisted breeding in mung beans.

Assessment of Genetic Variability, Heritability, Genetic Advance, and Diversity Analysis for Morpho Physiological Traits in Finger Millet [Eleusine coracana (l.) Gaertn.

The study, conducted during the Kharif season of 2022, aimed to evaluate genetic variability, heritability, genetic advance, and diversity for morpho-physiological traits in finger millet (Eleusine coracana (L.) Gaertn.) using 39 genotypes. Significant genetic variation was identified for all studied traits through variance analysis. While moderate to high values of Phenotypic Coefficient of Variation (PCV) and Genotypic Coefficient of Variation (GCV) were observed for most traits, exceptions were noted for days to 50 percent flowering, days to maturity, relative water content in leaves, and chlorophyll stability index. The study revealed high heritability with moderate to high genetic advance as a percent of the mean for most traits, suggesting the prevalence of additive gene effects. However, chlorophyll stability index and relative water content exhibited lower values. D2 analysis indicated the existence of sufficient genetic diversity among the genotypes. The genotypes were categorized into five distinct non-overlapping clusters. Cluster I, the largest cluster with 35 genotypes, displayed maximum intra-cluster distance. Clusters V and III had the highest inter-cluster distances, Days to maturity played a significant role in overall divergence. The findings suggest that a direct selection approach in finger millet landraces could lead to a substantial increase in yield response. This research provides valuable insights into the genetic characteristics of finger millet genotypes, offering a foundation for targeted breeding programs to enhance crop improvement.