Trait Associations Research Articles

Unraveling Promising Genetic Variability Associated with Strong Culm and Yield Parameters in Inter Sub-Specific Cross Derived Recombinant Inbred Lines in Rice (Oryza sativa L.)

Strengthening the rice culm through genetic improvement has been an important target in breeding to abate the lodging problem in rice. The present investigation was attempted to study the variability, genetic parameters and trait association in recombinant inbred lines (RILs) derived from inter sub-specific cross of elite indica mega variety ‘Swarna’ and Tropical japonica strong culm accession ‘IRGC 39111’. Analysis of Variance (ANOVA) displayed significant variation in RILs for all the traits studied. The investigation revealed high estimates of GCV and PCV along with high heritability and genetic advance as percent of mean (GAM) for all culm strength (CS) traits revealing the role of additive gene effect and selection of these traits shall be effective in rice improvement. Correlation studies revealed that the internode breaking weight (IBW) and bending moment at breaking(M) had a high significant positive correlation with all the CS traits, panicle weight and grain yield. Thus, the direct selection of positively associated traits can improve the lodging resistance in rice. The principal component analysis (PCA) showed that, seven principal components (PCs) out of 23 traits attributed approximately 92.9% of the total cumulative variability. The traits culm thickness (CT), Internode breaking weight (IBW), section modulus (SM), bending stress (BS), Bending moment at breaking (M) contributed maximum to the total diversity and the lines with higher trait values for the aforementioned traits could be utilized as donors to improve the culm strength and its attributing traits in future breeding programs. From this study, it is evident that tropical japonica lines can be a great source of genetic diversification for rice improvement.

Major depression recurrence is associated with differences in obesity-related traits in women, but not in men.

Obesity-related cardiometabolic comorbidity is common in major depressive disorder (MDD). However, sex differences and MDD recurrence may modify the MDD-obesity-link. Sex-specific associations of MDD recurrence (single [MDDS] or recurrent episodes [MDDR]) and obesity-related traits were analyzed in 4.100 adults (51.6% women) from a cross-sectional population-based cohort in Germany (SHIP-Trend-0). DSM-IV-based lifetime MDD diagnoses and MDD recurrence status were obtained through diagnostic interviews. Obesity-related outcomes included anthropometrics (weight, body mass index, waist- and hip-circumference, waist-to-hip ratio, waist-to-height ratio), bioelectrical impedance analysis of body fat mass and fat-free mass, and subcutaneous (SAT) and visceral adipose tissue (VAT) from abdominal magnetic resonance imaging. Sex-stratified linear regression models predicting obesity-related traits from MDD recurrence status were adjusted for age, education, and current depressive symptoms. 790 participants (19.3%) fulfilled lifetime MDD criteria (23.8% women vs. 14.5% men, p<0.001). In women, MDDS was inversely associated with anthropometric indicators of general and central obesity, while MDDR was positively associated with all obesity-related traits, except waist-to-hip ratio and fat-free mass. In women, MDDR versus MDDS was associated with higher levels of obesity across all outcomes except fat-free mass. In men, MDD was positively associated with SAT regardless of MDD recurrence. Additionally, lifetime MDD was positively associated with VAT in men. Results remained significant in sensitivity analyses after exclusion of participants with current use of antidepressants. The MDD-obesity association is modified by MDD recurrence and sex independent of current depressive symptoms. Accounting for sex and MDD recurrence may identify individuals with MDD at increased cardiometabolic risk.

Genome-wide assessment of population structure and association mapping for agronomic and grain nutritional traits in proso millet (Panicum miliaceum L.)

Proso millet is an important but under-researched and underutilized crop with the potential to become a future smart crop because of its climate-resilient features and high nutrient content. Assessing diversity and marker-trait associations are essential to support the genomics-assisted improvement of proso millet. This study aimed to assess the population structure and diversity of a proso millet diversity panel and identify marker-trait associations for agronomic and grain nutrient traits. In this study, genome-wide single nucleotide polymorphisms (SNPs) were identified by mapping raw genotyping-by-sequencing (GBS) data onto the proso millet genome, resulting in 5621 quality-filtered SNPs in 160 diverse accessions. The modified Roger's Distance assessment indicated an average distance of 0.268 among accessions, with the race miliaceum exhibiting the highest diversity and ovatum the lowest. Proso millet germplasm diversity was structured according to geographic centers of origin and domestication. Genome-wide association mapping identified 40 marker-trait associations (MTAs), including 34 MTAs for agronomic traits and 6 for grain nutrients; 20 of these MTAs were located within genes. Favourable alleles and phenotypic values were estimated for all MTAs. This study provides valuable insights into the population structure and diversity of proso millet, identified marker-trait associations, and reported favourable alleles and their phenotypic values for supporting genomics-assisted improvement efforts in proso millet.

Biochemical Defense Arsenal, Genes/QTLs and Transcripts for Imparting Anthracnose Resistance in Common bean (Phaseolus vulgaris L.)

Anthracnose (ANT), caused by Colletotrichum lindemuthianum, is the most devastating disease affecting common bean (Phaseolus vulgaris L.), leading to significant yield losses in the Western Himalayas. The study provides a comprehensive understanding of ANT resistance via trait phenotyping, biochemical profiling, genome-wide association studies (GWASs), and RNA sequencing. The assessment of bean association mapping panel in different environments revealed a diverse spectrum of resistance levels. Biochemical analysis revealed distinctive defense responses against ANT infection among different genotypes. GWAS approach identified 24 significant marker‒trait associations (MTAs) distributed across all 11 bean chromosomes. Notably, 03 MTAs (BMr205, BMr269 and BMr244) present on chromosome Pv07 were validated for ANT, and the remaining MTAs were novel MTAs for ANT. Transcriptome sequencing of resistant (PBG-3) and susceptible (PBG-26) genotypes under mock and 120-hour post inoculation conditions revealed key differentially expressed genes, such as leucine-rich repeat domain-containing protein (PHAVU_007G087700g), NB-ARC domain-containing protein (PHAVU_003G002500g) and transcription factors pivotal for disease resistance. The expression patterns of four genes (PHAVU_007G087700g, PHAVU_003G002500g, PHAVU_007G056100g and PHAVU_003G003000g) were validated through quantitative reverse transcription polymerase chain reaction (qRT‒PCR). Furthermore, the integration of GWAS-identified candidate genes with transcriptomics and cross-referencing with previous studies validated overlapping regions and common candidate genes, enriching our understanding of the genetic basis of ANT resistance. Therefore, the results offer a holistic perspective on ANT resistance in common bean, providing a foundation for targeted breeding efforts. The identified potential candidate genes and associated pathways will contribute valuable insights into the development of ANT resistant common bean varieties.

Complex trait associations in rare diseases and impacts on Mendelian variant interpretation

Emerging evidence implicates common genetic variation - aggregated into polygenic scores (PGS) - in the onset and phenotypic presentation of rare diseases. Here, we comprehensively map individual polygenic liability for 1102 open-source PGS in a cohort of 3059 probands enrolled in the Genomic Answers for Kids (GA4K) rare disease study, revealing widespread associations between rare disease phenotypes and PGSs for common complex diseases and traits, blood protein levels, and brain and other organ morphological measurements. Using this resource, we demonstrate increased polygenic liability in probands with an inherited candidate disease variant (VUS) compared to unaffected carrier parents. Further, we show an enrichment for large-effect rare variants in putative core PGS genes for associated complex traits. Overall, our study supports and expands on previous findings of complex trait associations in rare diseases, implicates polygenic liability as a potential mechanism underlying variable penetrance of candidate causal variants, and provides a framework for identifying novel candidate rare disease genes.

Nutrient responsiveness and correlation analysis of cashew (Anacardium occidentale L.) cv. Balabhadra for vegetative, reproductive traits and nut yield under coastal Odisha condition

Aim: The aim of the present study was to investigate the effect of nutrient management approaches on vegetative, reproductive growth and yield of cashew, Anacardium occidentale L. cv. Balabhadra. Methodology: Trial was conducted during 2021-22 to 2022-23 to study the foliar application of different macro, secondary and micro- nutrients of cashew plant. The experiment was designed in RBD with six treatments and four replications. Foliar spraying was done at three stages viz., pre-flowering, flowering and nut set stages. Results: Treatment schedules i.e., 100% RDF+10 kg FYM/plant /year+ foliar spray of major nutrients (3% urea+0.5% MAP+1% K2SO4)+ foliar spray of secondary and micro-nutrients (0.5 % ZnSO4 + 0.1 % Solubor + 0.5 % MgSO4) witnessed better performance of cashew for most of the vegetative and reproductive traits under study. Multivariate analysis showed formation of five principal components, where PC1 contributed maximum (97.80 %) towards total variance. Pearson correlation coefficient analysis revealed positive association of yield relevant traits (P &lt; 0.001) and negative correlation for number of flowering laterals and nut drop (%). Interpretation: Foliar spraying of macro, secondary and micronutrients in combination significantly influenced the vegetative and reproductive traits which may influence the nut yield of cashew. Key words: Cashew, Foliar spray, Nutrients

Trait association and prediction through integrative k-meranalysis.

Genome-wide association study (GWAS) with single nucleotide polymorphisms (SNPs) has been widely used to explore genetic controls of phenotypic traits. Alternatively, GWAS can use counts of substrings of length k from longer sequencing reads, k-mers, as genotyping data. Using maize cob and kernel color traits, we demonstrated that k-mer GWAS can effectively identify associated k-mers. Co-expression analysis of kernel color k-mers and genes directly found k-mers from known causal genes. Analyzing complex traits of kernel oil and leaf angle resulted in k-mers from both known and candidate genes. A gene encoding a MADS transcription factor was functionally validated by showing that ectopic expression of the gene led to less upright leaves. Evolution analysis revealed most k-mers positively correlated with kernel oil were strongly selected against in maize populations, while most k-mers for upright leaf angle were positively selected. In addition, genomic prediction of kernel oil, leaf angle, and flowering time using k-mer data resulted in a similarly high prediction accuracy to the standard SNP-based method. Collectively, we showed k-mer GWAS is a powerful approach for identifying trait-associated genetic elements. Further, our results demonstrated the bridging role of k-mers for data integration and functional gene discovery.

Y and mitochondrial chromosomes in the heterogeneous stock rat population.

Genome-wide association studies typically evaluate the autosomes and sometimes the X Chromosome, but seldom consider the Y or mitochondrial (MT) Chromosomes. We genotyped the Y and MT Chromosomes in heterogeneous stock (HS) rats (Rattus norvegicus), an outbred population created from 8 inbred strains. We identified 8 distinct Y and 4 distinct MT Chromosomes among the 8 founders. However, only 2 types of each nonrecombinant chromosome were observed in our modern HS rat population (generations 81-97). Despite the relatively large sample size, there were virtually no significant associations for behavioral, physiological, metabolome, or microbiome traits after correcting for multiple comparisons. However, both Y and MT Chromosomes were strongly associated with the expression of a few genes located on those chromosomes, which provided a positive control. Our results suggest that within modern HS rats there are no Y and MT Chromosomes differences that strongly influence behavioral or physiological traits. These results do not address other ancestral Y and MT Chromosomes that do not appear in modern HS rats, nor do they address effects that may exist in other rat populations, or in other species.

Unraveling genotypic interactions in sugar beet for enhanced yield stability and trait associations

The interaction between genotype and environment (GEI) significantly influences plant performance, crucial for breeding programs and ultimately boosting crop productivity. Alongside GEI, breeders encounter another hurdle in their quest for yield improvement, notably adverse and negative correlations among pivotal traits. This study delved into the stability of white sugar yield (WSY), root yield (RY), sugar content (SC), extraction coefficient of sugar (ECS), and the interplay among essential traits including RY, SC, alpha amino nitrogen (N), sodium (Na+), and potassium (K+) across 15 sugar beet hybrids and three control varieties. The investigation spanned two locations over two consecutive years (2022–2023), employing a randomized complete block design with four replications to comprehensively analyze these factors. The analysis of variance highlighted the significant effects of environment, genotype, and GEI at the 1% probability level. Notably, the AMMI analysis of GEI revealed the significance of the first component for WSY, RY, and SC, with the first two components proving significant for ECS. Within the linear mixed model (LMM), WSY, RY, SC, and ECS demonstrated significant effects from both genotype and GEI. In the WAASB biplot, genotypes 10, 8, 17, 6, 13, 14, 15, 7, 12, and 16 exhibited stability in WSY, while genotypes 9, 10, 6, 14, 7, 8, 13, 12, 18, and 15 displayed stability in RY. Additionally, genotypes 10, 15, 12, 13, 16, 17, 6, and 14 were stable for SC, and genotypes 8, 10, 7, 6, 13, 12, 16, 17, 15, 14, and 18 showcased stability in ECS, boasting above-average yield values. In the genotype by yield × trait (GYT) biplot, genotypes 15, 18, and 16 emerged as top performers when combining RY with SC, Na+, N, and K+, suggesting their potential for inclusion in breeding programs.

Lipidomics profiling and circulating triglyceride concentrations in sub-Saharan African individuals

Elevated triglycerides (TG) are a risk factor for cardiometabolic disorders. There are limited data on lipidomics profiles associated with serum triglycerides concentrations, although these could advance our understanding of the mechanisms underlying these associations. We conducted a lipidomics study of 308 Nigerians with replication in 199 Kenyans. Regression models were used to assess the association of TG with 480 lipid metabolites. Association and mediation analyses were conducted to determine the relationship among TG, metabolites, and several cardiometabolic traits. Ninety-nine metabolites were significantly associated with TG, and 91% of these associations replicated. Overrepresentation analysis identified enrichment of diacylglycerols, monoacylglycerols, diacylglycerophosphoethanolamines, monoacylglycerophosphocholines, ceramide phosphocholines, and diacylglycerophosphocholines. TG-cardiometabolic trait associations were largely mediated by TG-associated metabolites. Associations with type 2 diabetes, waist circumference, body mass index, total cholesterol, and low-density lipoprotein cholesterol concentration were independently mediated by metabolites in multiple subpathways. This lipidomics study in sub-Saharan Africans demonstrated that TG is associated with several non-TG lipids classes, including phosphatidylethanolamines, phosphatidylcholines, lysophospholipids, and plasmalogens, some of which may mediate the effect of TG as a risk factor for cardiometabolic disorders. The study identifies metabolites that are more proximal to cardiometabolic traits, which may be useful for understanding the underlying biology as well as differences in TG-trait associations across ancestries.

Investigating the network ties between affect, attachment, and psychopathology

ObjectivesRecent years have seen an increased interest regarding theoretical and empirical associations of adult attachment security and primary affective traits concerning psychiatric disorders. In this study, network analysis technique is applied to dissect the links between both psychodynamic personality constructs and an array of psychopathological symptoms. MethodsA total sample of 921 (69.9 % female) participants from the general population was investigated. A regularized cross-sectional partial correlation network between attachment (Experiences in Close Relationships-Revised [ECR-RD8]), primary affective traits (Brief Affective Neuroscience Personality Scales [BANPS-GL]) and psychopathological symptoms (ICD-10-Symptom-Rating Questionnaire [ISR]) was estimated via the EBICglasso algorithm. Node centrality, predictability and bridge centrality were analyzed. To evaluate the stability of the network and evaluate the significance of differences, we employed bootstrap techniques. ResultsThe network was found to be stable, allowing reliable interpretations. We observed SADNESS, as well as depressive, PTSD and anxiety symptoms as the most influential nodes within the investigated network. Attachment AV and SADNESS were observed as nodes with the highest bridge centrality. ConclusionsThe results provide a data-driven in-depth look into the complex dynamics between psychopathological symptoms, attachment security and basic affective traits. Results underscore the critical interconnections between affect, attachment, and psychopathology, advocating for a psychodynamically informed systems approach in psychological research that considers the affective dimensions underlying human mental health.

Integrating genome-and transcriptome-wide association studies to uncover the host-microbiome interactions in bovine rumen methanogenesis.

The ruminal microbiota generates biogenic methane in ruminants. However, the role of host genetics in modifying ruminal microbiota-mediated methane emissions remains mysterious, which has severely hindered the emission control of this notorious greenhouse gas. Here, we uncover the host genetic basis of rumen microorganisms by genome-and transcriptome-wide association studies with matched genome, rumen transcriptome, and microbiome data from a cohort of 574 Holstein cattle. Heritability estimation revealed that approximately 70% of microbial taxa had significant heritability, but only 43 genetic variants with significant association with 22 microbial taxa were identified through a genome-wide association study (GWAS). In contrast, the transcriptome-wide association study (TWAS) of rumen microbiota detected 28,260 significant gene-microbe associations, involving 210 taxa and 4652 unique genes. On average, host genetic factors explained approximately 28% of the microbial abundance variance, while rumen gene expression explained 43%. In addition, we highlighted that TWAS exhibits a strong advantage in detecting gene expression and phenotypic trait associations in direct effector organs. For methanogenic archaea, only one significant signal was detected by GWAS, whereas the TWAS obtained 1703 significant associated host genes. By combining multiple correlation analyses based on these host TWAS genes, rumen microbiota, and volatile fatty acids, we observed that substrate hydrogen metabolism is an essential factor linking host-microbe interactions in methanogenesis. Overall, these findings provide valuable guidelines for mitigating methane emissions through genetic regulation and microbial management strategies in ruminants.

Association of Personality Traits of Alcohol-dependent Patients with Their Psychiatric Comorbidities: A Cross-sectional Study from Central Rural India

Introduction: Alcohol dependence syndrome (ADS) is a significant health problem all over the world. Alcohol-dependent individuals have a high prevalence of psychiatric comorbidities and nonadaptive personality traits that may influence the pathogenesis, treatment outcome, clinical course, and relapse of ADS. Aim: The aim of this study was to assess the personality traits and psychiatric comorbidities of alcohol-dependent patients and to determine the association of personality traits with psychiatric comorbidities in ADS. Methodology: An observational study was conducted on 100 patients of ADS from Acharya Vinoba Bhave Rural Hospital, Sawangi Wardha, Maharashtra. They were assessed through semi-structured sociodemographic pro forma, Mini-International Neuropsychiatric Interview PLUS, and 16 Personality Factor Inventory. Results: Most of the patients scored high on personality traits such as dominance (67%), warmth (56%), sensitivity (70%), social boldness (56%), openness to change (65%), vigilance (77%), and perfectionism (52%) while they scored low on factors privateness (50%) and liveliness (35%). The prevalence of psychiatric comorbidity was found to be 49%, with mood disorders (21%) being the most common diagnosis. Personality factors dominance (0.0001) and social boldness (0.042) were significantly associated with psychiatric comorbidities with P &lt; 0.05. Conclusion: The personality traits and psychiatric comorbidity need to be addressed at the time of management to improve outcome.

Association between Inflammatory Dietary Pattern and Mammographic Features

BackgroundThe empirical dietary inflammation pattern score (EDIP), which measures the ability of the diet to regulate chronic inflammation, is associated with both higher adiposity and breast cancer (BC) risk. Mammographic density (MD) is an important risk factor for BC. ObjectiveWe examined the associations between EDIP and mammographic features overall and stratified by menopausal status, and assessed the extent to which these associations are mediated by adiposity. MethodsWe included 4145 participants without BC in the Nurses’ Health Study (NHS) and NHSII. Cumulative average EDIP was assessed by food frequency questionnaires every 4–6 y. We assessed MD parameters (percent MD, dense area, and nondense area) and V (measure of grayscale variation). MD parameters were square-root transformed. Multivariable-adjusted linear regression models were used to analyze the associations between EDIP score and MD parameters. Baron and Kenny’s regression method was used to assess the extent to which the associations of EDIP and mammographic traits were mediated by BMI. ResultsIn multivariable-adjusted models, EDIP was significantly inversely associated with percent MD [top compared with bottom quartile, β = –0.57; 95% confidence interval (CI): –0.78, –0.36]. Additional adjustment for BMI attenuated the association (β = –0.15; 95% CI: –0.34, 0.03), with 68% (β = 0.68, 20; 95% CI: 0.54, 0.86) mediation via BMI. In addition, EDIP was positively associated with nondense area after adjusting for BMI and other covariates. No associations were observed for dense area and V measure. Results were similar when stratified by menopausal status. ConclusionsEDIP score was inversely associated with percent MD and positively associated with nondense area, and these associations were largely mediated by BMI.

Identifying the physiological traits associated with DNA marker using genome wide association in wheat under heat stress

Heat stress poses a significant environmental challenge that profoundly impacts wheat productivity. It disrupts vital physiological processes such as photosynthesis, by impeding the functionality of the photosynthetic apparatus and compromising plasma membrane stability, thereby detrimentally affecting grain development in wheat. The scarcity of identified marker trait associations pertinent to thermotolerance presents a formidable obstacle in the development of marker-assisted selection strategies against heat stress. To address this, wheat accessions were systematically exposed to both normal and heat stress conditions and phenotypic data were collected on physiological traits including proline content, canopy temperature depression, cell membrane injury, photosynthetic rate, transpiration rate (at vegetative and reproductive stage and ‘stay-green’. Principal component analysis elucidated the most significant contributors being proline content, transpiration rate, and canopy temperature depression, which exhibited a synergistic relationship with grain yield. Remarkably, cluster analysis delineated the wheat accessions into four discrete groups based on physiological attributes. Moreover, to explore the relationship between physiological traits and DNA markers, 158 wheat accessions were genotyped with 186 SSRs. Allelic frequency and polymorphic information content value were found to be highest on genome A (4.94 and 0.688), chromosome 1A (5.00 and 0.712), and marker Xgwm44 (13.0 and 0.916). Population structure, principal coordinate analysis and cluster analysis also partitioned the wheat accessions into four subpopulations based on genotypic data, highlighting their genetic homogeneity. Population diversity and presence of linkage disequilibrium established the suitability of population for association mapping. Additionally, linkage disequilibrium decay was most pronounced within a 15–20 cM region on chromosome 1A. Association mapping revealed highly significant marker trait associations at Bonferroni correction P < 0.00027. Markers Xwmc418 (located on chromosome 3D) and Xgwm233 (chromosome 7A) demonstrated associations with transpiration rate, while marker Xgwm494 (chromosome 3A) exhibited an association with photosynthetic rates at both vegetative and reproductive stages under heat stress conditions. Additionally, markers Xwmc201 (chromosome 6A) and Xcfa2129 (chromosome 1A) displayed robust associations with canopy temperature depression, while markers Xbarc163 (chromosome 4B) and Xbarc49 (chromosome 5A) were strongly associated with cell membrane injury at both stages. Notably, marker Xbarc49 (chromosome 5A) exhibited a significant association with the 'stay-green' trait under heat stress conditions. These results offers the potential utility in marker-assisted selection, gene pyramiding and genomic selection models to predict performance of wheat accession under heat stress conditions.

Genomics‐based plant disease resistance prediction using machine learning

AbstractPlant disease outbreaks continuously challenge food security and sustainability. Traditional chemical methods used to treat diseases have environmental and health concerns, raising the need to enhance inherent plant disease resistance mechanisms. Traits, including disease resistance, can be linked to specific loci in the genome and identifying these markers facilitates targeted breeding approaches. Several methods, including genome‐wide association studies and genomic selection, have been used to identify important markers and select varieties with desirable traits. However, these traditional approaches may not fully capture the non‐linear characteristics of the effect of genomic variation on traits. Machine learning, known for its data‐mining abilities, offers an opportunity to enhance the accuracy of the existing trait association approaches. It has found applications in predicting various agronomic traits across several species. However, its use in disease resistance prediction remains limited. This review highlights the potential of machine learning as a complementary tool for predicting the genetic loci contributing to pathogen resistance. We provide an overview of traditional trait prediction methods, summarize machine‐learning applications, and address the challenges and opportunities associated with machine learning‐based crop disease resistance prediction.

Uncovering Fusarium Species Associated with Fusarium Wilt in Chickpeas (Cicer arietinum L.) and the Identification of Significant Marker–Trait Associations for Resistance in the International Center for Agricultural Research in the Dry Areas’ Chickpea Collection Using SSR Markers

Enhancing plants’ resistance against FW is crucial for ensuring a sustainable global chickpea production. The present study focuses on the identification of fungal pathogens and the assessment of ninety-six chickpea samples for Fusarium wilt from the International Center for Agricultural Research in the Dry Areas (ICARDA)’s collection. Eight fungal isolates were recovered from the symptomatic chickpeas. Polyphasic identification was conducted by comparing the internal transcribed spacer region (ITS), the elongation factor 1-α (tef1-α), and beta-tubulin (tub2). Among them, Neocosmospora solani, N. nelsonii, N. falciformis, N. brevis, Fusarium brachygibbosum, and F. gossypinum were identified. An analysis of the genetic diversity of chickpeas, using 69 polymorphic simple sequence repeat (SSR) markers, revealed a total of 191 alleles across all markers, with, on average, each SSR marker detecting approximately 2.8 alleles. A STRUCTURE analysis delineated lines into two distinct sub-groups (K = 2). Association mapping, using the generalized linear model (GLM) and mixed linear model (MLM) approaches, identified six and five marker–trait associations (MTAs) for FW resistance, respectively. Notably, these TA42, TA125 (A) and TA125 (B), TA37, and TAASH MTAs, commonly found in both models, emerge as potential candidates for the targeted enhancement of FW resistance in chickpeas. To our knowledge, this study represents an inaugural report on the association mapping of genomic loci governing FW resistance in chickpeas from the ICARDA’s accessions.

Genome wide association study of antioxidant activity in pigeonpea germplasm

Pigeonpea (Cajanus cajan L.) is a nutritious crop with antioxidant potential, making it valuable for health supplements and medicinal products. Pigeonpea seed coat possess a rich source of antioxidant properties, particularly in dark colour seed coat varieties. Recently, antioxidant-based drugs for the prevention and treatment of complex diseases have evoked a great deal of research interest in natural antioxidants. We resolved genomic regions by conducted a genome-wide association study (GWAS) using a high-throughput 62 K SNP “CcSNPnks” genic chip to identify SNP markers associated with antioxidant properties in 287 diverse panel of pigeonpea genotypes. Evaluated their antioxidant activity using a spectrophotometric technique based on ferric ion-reducing antioxidant potential (FRAP) and calculated the gallic acid equivalents (GAE) per 100 g of extract. Significant differences in antioxidant activities were found among genotypes, ranging from 3.27 mg in ICPL-13271 to 16.85 mg in UP 9-I for ferric iron-reducing activity. The GWAS identified four distinct marker trait association (MTA) that exhibit a strong correlation with antioxidant properties. We identified significant marker trait associations with chr 2 (AX-165372487), chr 6 (AX-165348296) code for RGA1 protein, chr 10 (AX-165367685) codes for alkaline ceramidase (transcript variant), and chr 11 (AX-165411944) codes for (DL)-glycerol-3-phosphatase 2. The identified protein, RGA1, is involved in reducing ROS accumulation in response to stress by up-regulating the transcription of superoxide dismutases. It suppresses GA-induced vegetative growth and floral initiation. Rapidly degraded in response to GA and involved in fruit and flower development. Furthermore, the population structure analysis identified four distinct sub-populations with admixture types, effectively grouping all genotypes based on their ancestry. Our findings advance the understanding of the genetic underpinning antioxidant concentrations, holding potential for applications in crop breeding and aligning with consumer preferences. This study provides a cornerstone for future research into exploiting marker-assisted breeding to produce pigeonpea cultivars.

Genome‐Wide Association Studies Predicted Drought Stress Occuring at Anthesis and Post‐Anthesis Stages in Novel Diverse Germplasm of Bread Wheat (Triticum aestivum)

ABSTRACTThis study employed genome‐wide association studies (GWAS) to identify the crucial marker–trait associations (MTAs) for agronomic and physiological traits in bread wheat grown under full irrigation and 40% reduced irrigation. One hundred twenty‐four genotypes derived from three‐way crosses of landraces and synthetic bread wheat were evaluated for 2 years in the field conditions of CIMMYT Obregon, Mexico. Irrigation was not provided at anthesis and post‐anthesis stage for the drought treatment, and data of 12 traits were recorded. Most of the traits were reduced significantly under drought conditions except for vigour, wax and spike length (SL); genotypes were significantly different for the eight traits except for days to heading (DTH), number of grains spike−1 (NGS), normalized difference in vegetation index (NDVI) and canopy temperature depression (CTD); and differences were also significant for five traits between the years. Moreover, GY was significantly and negatively correlated with wax and CTD. Our GWAS results indicated 117 significant (p ≤ 0.001) MTAs distributed on all the wheat chromosomes except chromosomes 4B and 4D explaining 10%–21.5% of the phenotypic variation of the corresponding traits. Moreover, 22 MTAs were recorded for grain yield and explaining the phenotypic variations up to 14.7% with one common association under both irrigated and drought conditions. Additionally, we also identified the associations for NDVI, CTD and SL at chromosome 1B, suggesting that genotypes are sustaining superior grain yield through better values of traits like NDVI, CTD, and SL under the challenging conditions of anthesis and post‐anthesis drought stress.

Study of variability, combining ability, genetics and association of different yield related traits in rice (Oryza sativa L.) genotypes

Study of variability, combining ability, genetics and association of different yield related traits in rice (Oryza sativa L.) genotypes