Gene-environment Interactions Research Articles

Gene-environment interactions and colorectal cancer risk: A case-control study on xenobiotic metabolizing enzyme polymorphisms in the Jammu& Kashmir, India population

BackgroundCancer remains a significant global health concern, with colorectal cancer (CRC) showing a rising incidence, particularly among younger populations. Most CRC cases are linked to a complex interplay of genetic and environmental factors. The cytochrome P450 (CYP) superfamily, including enzymes like CYP2A13 and CYP2A6, plays a vital role in metabolizing environmental carcinogens such as polycyclic aromatic hydrocarbons (PAHs) and nitrosamines. Polymorphisms in these genes, alongside phase II glutathione-S-transferases (GSTs) involved in detoxification, can influence individual cancer risk. This study focuses on the association between these genetic polymorphisms and CRC risk in the Jammu & Kashmir, population, a region with high exposure to dietary and lifestyle-related carcinogens. MethodologyThis hospital-based case-control study was conducted at the Sher-I-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, J&K, India between March 2019 and March 2022. The study included 246 histopathologically confirmed colorectal cancer (CRC) cases, and an equal number of matched controls based on age (±5 years), gender, and place of residence. Blood samples were collected for DNA extraction, followed by genotyping of xenobiotic-metabolizing enzyme (XME) genes, including CYP2A13, CYP2A6, and GSTs using standard PCR-RFLP and multiplex PCR methods. Statistical analyses were performed using STATA software to assess the association between gene polymorphisms and CRC risk. ResultsThe study revealed key associations between genetic and environmental factors and CRC risk. The analysis demonstrated that cases had significantly lower education levels than controls. Family history of cancer, smoking, and dietary factors like red meat and salt tea consumption were more prevalent among cases. Genetic analysis identified significant interactions between various CYP and GST genotypes, and environmental factors such as smoking, pesticide exposure, and diet, with varying effects on CRC risk. ConclusionThe research underscores the influence of genetic and environmental factors on colorectal cancer (CRC) risk. Lower educational was associated with a heightened risk of CRC. Certain genotype variants of xenobiotic metabolizing enzymes (XME) were found to increase CRC risk, particularly in conjunction with smoking, pesticide exposure, and sun-dried vegetable consumption. A family history of cancer, especially CRC, further amplified the risk. These findings emphasize the importance of developing personalized CRC prevention and screening strategies that account for gene-environment interactions.

Understanding species limits through the formation of phylogeographic lineages.

The outcomes of speciation across organismal dimensions (e.g., ecological, genetic, phenotypic) are often assessed using phylogeographic methods. At one extreme, reproductively isolated lineages represent easily delimitable species differing in many or all dimensions, and at the other, geographically distinct genetic segments introgress across broad environmental gradients with limited phenotypic disparity. In the ambiguous gray zone of speciation, where lineages are genetically delimitable but still interacting ecologically, it is expected that these lineages represent species in the context of ontology and the evolutionary species concept when they are maintained over time with geographically well-defined hybrid zones, particularly at the intersection of distinct environments. As a result, genetic structure is correlated with environmental differences and not space alone, and a subset of genes fail to introgress across these zones as underlying genomic differences accumulate. We present a set of tests that synthesize species delimitation with the speciation process. We can thereby assess historical demographics and diversification processes while understanding how lineages are maintained through space and time by exploring spatial and genome clines, genotype-environment interactions, and genome scans for selected loci. Employing these tests in eight lineage-pairs of snakes in North America, we show that six pairs represent 12 "good" species and that two pairs represent local adaptation and regional population structure. The distinct species pairs all have the signature of divergence before or near the mid-Pleistocene, often with low migration, stable hybrid zones of varying size, and a subset of loci showing selection on alleles at the hybrid zone corresponding to transitions between distinct ecoregions. Locally adapted populations are younger, exhibit higher migration, and less ecological differentiation. Our results demonstrate that interacting lineages can be delimited using phylogeographic and population genetic methods that properly integrate spatial, temporal, and environmental data.

Identification of high-yielding and stable cultivars of wheat under different sowing dates: Comparison of AMMI and GGE-biplot analyses

Evaluating the adaptability and yield stability of wheat varieties across different sowing dates is crucial for the success of breeding programs. In this study, we used Additive Main Effects and Multiplicative Interactions (AMMI) and Genotype × Genotype–Environment (GGE) biplot analyses to evaluate the performance of 13 wheat varieties across eight sowing dates. The main objective was to compare varieties and sowing dates to identify the most stable varieties for cultivation. Both AMMI and GGE biplot analyses showed significant effects of genotype, environment and genotype-environment (GE) interaction on grain yield. The interaction patterns identified by AMMI and GGE-biplots categorized Mihan, Oroom and Pishgam as the most stable, high yielding and early maturing wheat varieties. Furthermore, while the GGE biplot method proved to be more efficient than the AMMI model for stability analysis, our results indicate considerable overlap between the results of these two approaches. These results provide a valuable basis for optimizing genetic improvement strategies in wheat breeding programs.

An adaptive dynamical system model for development of schizophrenia: Epigenetics and false memories

This paper introduces a fifth-order adaptive dynamical system model represented as a self-modelling network model to understand the role of epigenetic factors in developing schizophrenia, particularly about the occurrence of false memories. Schizophrenia, affecting a significant portion of the global population, presents complex challenges due to its symptoms across cognitive, emotional, and social domains. Central to this paper is the exploration of epigenetic influences on the development of schizophrenia, with a focus on how these epigenetic factors contribute to the generation of false memories, a notable symptom of the disorder. The model assumes that early adverse experiences significantly affect hippocampal development, which is crucial for memory processes. By employing a fifth-order adaptive dynamical system model represented as a self-modelling network, this paper examines the intricate dynamics between genetic predispositions, environmental factors, and epigenetic modifications in schizophrenia. The model’s sophistication allows for a nuanced understanding of the gene-environment interactions, particularly highlighting the role of early-life trauma in shaping lifelong cognitive outcomes. This approach offers a comprehensive framework for analyzing the multifaceted nature of schizophrenia, contributing to a deeper understanding of its etiology and progression.

How is Excitotoxicity Being Modelled in iPSC-Derived Neurons?

Excitotoxicity linked either to environmental causes (pesticide and cyanotoxin exposure), excitatory neurotransmitter imbalance, or to intrinsic neuronal hyperexcitability, is a pathological mechanism central to neurodegeneration in amyotrophic lateral sclerosis (ALS). Investigation of excitotoxic mechanisms using in vitro and in vivo animal models has been central to understanding ALS mechanisms of disease. In particular, advances in induced pluripotent stem cell (iPSC) technologies now provide human cell-based models that are readily amenable to environmental and network-based excitotoxic manipulations. The cell-type specific differentiation of iPSC, combined with approaches to modelling excitotoxicity that include editing of disease-associated gene variants, chemogenetics, and environmental risk-associated exposures make iPSC primed to examine gene-environment interactions and disease-associated excitotoxic mechanisms. Critical to this is knowledge of which neurotransmitter receptor subunits are expressed by iPSC-derived neuronal cultures being studied, how their activity responds to antagonists and agonists of these receptors, and how to interpret data derived from multi-parameter electrophysiological recordings. This review explores how iPSC-based studies have contributed to our understanding of ALS-linked excitotoxicity and highlights novel approaches to inducing excitotoxicity in iPSC-derived neurons to further our understanding of its pathological pathways.

Associations of classical HLA alleles with sleep behaviours.

Immune dysregulation has been observed in individuals with sleep disturbance, with HLA molecules play a crucial role in the immune response. This study aimed to investigate the associations between HLA alleles and sleep behaviours, considering several environmental factors. Data were sourced from the UK Biobank. Logistic regression analyses were performed to explore the associations between 359 HLA alleles and 4 sleep behaviours, including chronotype (n = 204,636), insomnia (n = 227,553), snoring (n = 214,350) and daytime dozing (n = 227,197). Furthermore, gene-environmental interaction studies (GEIS) were conducted to evaluate the interactions of HLA alleles with environmental factors on sleep behaviours. This study analysed a total sample and subgroups stratified by sex to elucidate the impact of HLA alleles on sleep behaviours. Our findings revealed several associations between specific HLA alleles and sleep behaviours. Notably, HLA-A*23:01 was associated with evening chronotype in the total sample (OR = 0.918, 95%CI: 0.872-0.965), while HLA-A*32:01 was associated with evening chronotype in males (OR = 1.089, 95%CI: 1.037-1.144). Furthermore, GEIS identified multiple sets of interactions associated with sleep behaviours. For example, the interaction of HLA-DPA1*01:04 with alcohol consumption was associated with daytime dozing in the total sample (OR = 1.993, 95%CI: 1.351-2.941), while the interaction of HLA-DQB1*05:04 with ever suffered mental distress preventing usual activities was associated with insomnia in males (OR = 0.409, 95%CI: 0.254-0.658). Our findings highlight the involvement of HLA in sleep regulation and underscore the potential interactions between HLA alleles and environmental factors in modulating susceptibility to sleep behaviours.

A genome-wide gene-environmental interaction study identified novel loci for the relationship between ambient air pollution exposure and depression, anxiety

BackgroundGenetic factors and environmental exposures, including air pollution, contribute to the risk of depression and anxiety. While the association between air pollution and depression and anxiety has been established in the UK Biobank, there has been limited research exploring this relationship from a genetic perspective. MethodsBased on individual genotypic and phenotypic data from a cohort of 104,385 participants in the UK Biobank, a polygenic risk score for depression and anxiety was constructed to explore the joint effects of nitric oxide (NO), nitrogen dioxide (NO2), particulate matter (PM) with a diameter of ⩽2.5 μm (PM2.5) and 2.5–10 μm (PMcoarse) with depression and anxiety by linear and logistic regression models. Subsequently, a genome-wide gene-environmental interaction study (GWEIS) was performed using PLINK 2.0 to identify the genes interacting with air pollution for depression and anxiety. ResultsA substantial risk of depression and anxiety development was detected in participants exposed to the high air pollution concomitantly with high genetic risk. GWEIS identified 166, 23, 18, and 164 significant candidate loci interacting with NO, NO2, PM2.5, and PMcoarse for Patient Health Questionnaire-9 (PHQ-9) score, and detected 44, 10, 10, and 114 candidate loci associated with NO, NO2, PM2.5, and PMcoarse for General Anxiety Disorder (GAD-7) score, respectively. And some significant genes overlapped among four air pollutants, like TSN (rs184699498, PNO2 = 3.47 × 10−9; rs139212326, PPM2.5 = 1.51 × 10−8) and HSP90AB7P(rs150987455, PNO2 = 1.63 × 10−11; rs150987455, PPM2.5 = 7.64 × 10−11), which were common genes affecting PHQ-9 score for both NO2 and PM2.5. ConclusionOur study identified the joint effects of air pollution with genetic susceptibility on the risk of depression and anxiety, and provided several novel candidate genes for the interaction, contributing to an understanding of the genetic architecture of depression and anxiety.

Связь полиморфизма rs11546155 гена GGT7 с риском развития ишемического инсульта

Background: Since oxidative stress plays a role in the pathogenesis of ischemic stroke (IS), it is important to investigate the molecular mechanisms contributing to redox homeostasis and glutathione metabolism. The aim of the study: To analyze the association of the rs11546155 polymorphism of gamma-glutamyltransferase 7 (GGT7) gene with the risk of ischemic stroke. Materials and methods: DNA samples from 600 patients with IS and 688 controls were used for genotyping SNP rs11546155 by real-time PCR with allele discrimination using TaqMan probes. Results: It was found that genotypes G/A and A/A are associated with an increased risk of IS in females (OR=1.54, 95%CI 1.02–2.32, Pperm=0.04), while no associations between rs11546155 genotypes were observed in males. In patients with hypodynamia, the rs11546155 polymorphism was associated with an increased risk of IS (OR=1.59, 95%CI 1.01–2.00, Pperm=0.04), while in individuals with normal and increased physical activity, the SNP did not influence disease risk. Moreover, the carriers of allele rs11546155G who did not abuse alcohol possess a decreased risk of IS (OR = 1.59, 95%CI 1.012.00, Pperm = 0.04), while the protective effect of the allele against disease risk was not seen in alcohol abusers. Functional SNP annotation showed that the IS-related rs11546155A allele is associated with decreased expression of the GGT7 gene, as well as genes involved in autophagy and proteasomal protein degradation. Conclusion: This study was the first to establish the association of the rs11546155 polymorphism with the risk of IS. Further studies are needed to clarify the nature of the sex-specific SNP association and gene-environment interactions.

New developments in the diagnosis and management of motor neuron disease.

Motor neuron disease (MND) is a devastating neurodegenerative disease characterized by progressive muscle weakness. PubMed, MEDLINE, and Cochrane databases were searched for articles to March 2024. Searches involved the terms 'motor neuron disease' or 'amyotrophic lateral sclerosis' and 'epidemiology', 'diagnosis', 'clinical', 'genetic', 'management', 'treatment', or 'trial'. Evidence-based management involves riluzole, multidisciplinary care, provision of noninvasive ventilation and gastrostomy, and symptomatic treatments. Tofersen should be offered to treat SOD1-MND. Edaravone and Relyvrio are approved treatments in the USA, but insufficient evidence was found to support approval in the UK and Europe. The discovery of neurofilaments as MND biomarkers, growth of platform trials and development of novel therapies provide optimism for more powerful neuroprotective therapies. Further work should focus on the elucidation of environmental causes of MND, gene-environment interactions, and advanced cellular models of disease.

Influence of different environmental challenges on the expression of reproductive traits in Holstein cattle in Southern Brazil.

The aim of this study was to assess the impact of genotype-environment interaction (GEI) on the manifestation of traits such as age at first calving (AFC), age at first service (AFS), and calving interval (CI) through the application of the reaction norm model in Holstein cattle raised in Paraná state, Brazil. Utilizing data from the milk testing service of the Paraná Association of Holstein Cattle Breeders (APCBRH), this study analyzed records from 179,492 animals undergoing their first, second, and third lactations from the years 2012 to 2022. These animals were part of 513 herds spread across 72 municipalities in Paraná. The environmental gradient was established by normalizing contemporary group solutions, derived from the animal model, with the 305-day-corrected milk yield serving as the dependent variable. Subsequently, reaction norms were determined utilizing a Random Regression Model. Spearman's correlation was then applied to compare the estimates of breeding values across different environmental gradients for the studied traits. The highest EG (+ 4) indicates the least challenging environments, where animals experience better environmental conditions. Conversely, lower EG (-4) values represent the most challenging environments, where animals endure worse conditions. The only trait that exhibited a moderate heritability magnitude was AFC (0.23) in the least challenging environmental condition. The other traits were classified as having low heritability magnitudes regardless of the evaluated environmental gradient. While minimal evidence was found for the influence of GEI on CI, a clear GEI effect was observed for AFC and AFS across all environmental gradients examined. A reversal in genotype ranking occurred under extreme environmental conditions. The findings suggest that the best-performing genotype under one environmental gradient may not necessarily excel under another.

Pathogenesis of HIV associated nephropathy in children and adolescents: taking a hard look 40 years later in the era of gene-environmental interaction.

HIV-associated nephropathy (HIVAN) is a kidney disease that affects mainly people of African ancestry with a high HIV-1 viral load. New antiretroviral therapies (ART) have been highly efficient preventing and improving the outcome of HIVAN. However, providing chronic ART to children and adolescents living with HIV (CALWH) remains a significant challenge all over the world. More that 2.5 million CALWH, including those living in Sub-Saharan Africa, continue to be at high risk of developing HIVAN. Much of our understanding of the pathogenesis of HIVAN is based on studies conducted in transgenic mice and adults with HIVAN. However, CALWH may experience different health outcomes, risk factors, and susceptibilities to HIVAN in comparison to adults. This article reviews the progress made over the last 40 years in understanding the pathogenesis of HIVAN in CALWH, focusing on how the HIV virus, alongside genetic and environmental factors, contributes to the development of this disease. The landmark discovery that two risks alleles of the Apolipoprotein-1 (APOL1) gene play a critical role in HIVAN has significantly advanced our understanding of the disease's pathogenesis. However, we still need to understand why renal inflammation persists despite ART and determine whether the kidney may harbor HIV reservoirs that need to be eliminated to cure HIV permanently. For these reasons, we emphasize reviewing how HIV-1 infects renal cells, affects their growth and regeneration, and discussing how inflammatory cytokines and APOL1 affect the outcome of childhood HIVAN.

Ethical, Legal, and Social Implications of Gene-Environment Interaction Research.

Many complex disorders are impacted by the interplay of genetic and environmental factors. In gene-environment interactions (GxE), an individual's genetic and epigenetic makeup impacts the response to environmental exposures. Understanding GxE can impact health at the individual, community, and population levels. The rapid expansion of GxE research in biomedical studies for complex diseases raises many unique ethical, legal, and social implications (ELSIs) that have not been extensively explored and addressed. This review article builds on discussions originating from a workshop held by the National Institute of Environmental Health Sciences (NIEHS) and the National Human Genome Research Institute (NHGRI) in January 2022, entitled: "Ethical, Legal, and Social Implications of Gene-Environment Interaction Research." We expand upon multiple key themes to inform broad recommendations and general guidance for addressing some of the most unique and challenging ELSI in GxE research. Key takeaways include strategies and approaches for establishing sustainable community partnerships, incorporating social determinants of health and environmental justice considerations into GxE research, effectively communicating and translating GxE findings, and addressing privacy and discrimination concerns in all GxE research going forward. Additional guidelines, resources, approaches, training, and capacity building are required to further support innovative GxE research and multidisciplinary GxE research teams.

Progeny Selection and Genetic Diversity in a Pinus taeda Clonal Seed Orchard

The present article describes the development of an improved Pinus taeda clonal seed orchard adapted to the edaphoclimatic conditions of Uruguay. Initially, 2068 hectares distributed in nine companies were prospected, and 124 plus trees were identified based on growth, straightness, and health traits. These trees were clonally propagated via grafting to establish a clonal seed orchard. For the genetic evaluation of the orchard, two progeny tests were carried out in the Rivera and Paysandú municipalities. Quantitative genetic analyses allowed us to identify a simple genotype–environment interaction and an expected genetic gain for volumes of 17%, 13%, and 8% for selection intensities of 12%, 25%, and 50%, respectively. Moreover, the genetic diversity of the 124 clones of the orchard was assessed using 10 microsatellite markers. The fingerprinting profiles allowed us to identify a total of 224 alleles. The polymorphism information content of the different markers was in the range of 0.594 to 0.895. The combined probability of identity and probability of identity among siblings had a discrimination power of 8.26 × 10–14 and 5.91 × 10–5, respectively. Analysis of the genetic structure demonstrated that the seed orchard population was not structured by the supplier.

The role of gene–environment interaction in the formation of risk attitudes

Understanding the formation of risk preferences is crucial for elucidating the roots of economic, social, and health inequalities. However, this area remains inadequately explored. This study employs a risk preference measure directly linked to the labor market to examine whether previous experiences with high unemployment rates influence current risk decision-making among the elderly, and whether this impact varies by genotype. The findings indicate that individuals with low genetic predispositions for risk tolerance are more significantly influenced by historical fluctuations in unemployment rates than those with high genetic predispositions for risk tolerance. Consequently, this paper identifies genetic endowment as a crucial moderating factor that shapes how past experiences impact current decision-making processes. This disparity in how past experiences shape risk preferences based on genetic predisposition may further amplify inequalities in health, wealth, income, and other outcomes associated with risk preferences.

Case of familial interstitial lung disease attributedto ATP-binding cassette transporter 3 gene mutationin identical twins.

Mutations in ABCA3 can result in surfactant deficiency, leading to respiratory distress syndrome in term neonates, and interstitial lung disease (ILD) in children. Here, we report an extremely rare case of ILD in an identical twin with novel ABCA3 germline mutations. Interestingly, they showed mostly similar, but slightly different, clinical features. Our cases suggest that, in addition to genetic factors, non-genetic factors are involved in the severity of the disease and its clinical course. Studies of gene-environment interactions, especially with twins, are needed, as they may contribute to the understanding of the clinical heterogeneity of ILD and its association with various underlying conditions as well as rare variant mutations.

Genotypic and environmental influences on colour and curcuminoids of turmeric (Curcuma longa L.) genotypes across contrasting production environments

Abstract Turmeric (Curcuma longa L.) is rich in curcuminoids, which are polyphenolic pigments make it one of the most valuable spice and medicinal plant. The rising need for natural colours and the numerous health advantages of curcuminoids are driving up the demand of turmeric. In this study, the effects of genotype and genotype × environment on the colour characteristics of 21 turmeric genotypes were examined in three different production environments namely vertical farming, greenhouse, and field conditions. The pooled analysis of variance revealed highly significant (P < 0.05) differences among genotypes (G), environments (E), and G × E interaction for three colour parameters [L* (lightness index), A* (redness index), B* (yellowness index)]. Among the genotypes, the values ranged from 41.80 to 54.76, 13.92 to 24.83 and 31.72 to 47.67 for L*, A*, B*, respectively. Erode Local (22.34), IISR Pragati (24.56) and IISR Prathiba (26.55) recorded maximum A* value under vertical farming, greenhouse, and field conditions, respectively. Correlation analysis between colour values and curcuminoids revealed a significant positive correlation (r = 0.608–0.735, P < 0.001) between A* value and curcuminoids. Furthermore, stability analysis for A* value revealed 78.87% genotype × environment interaction (GEI) from the first two principal components of GGE biplot. IISR Pragati and Waigon Turmeric are best was most stable for A* value across environments. Our study revealed that colour traits among genotypes vary widely and are strongly impacted by genetic and environmental factors. These findings are crucial for future breeding programs to enhance turmeric's colour, ensuring high-quality, stable products for producers and consumers.

Alcohol Use Among American Youth: Differential Susceptibility to Peer Influence on Substance Use Tied to Genetic Risk

ABSTRACT The behavior of peers is one of the most robust correlates of deviance and arguably the strongest influence on substance use; however, not all youth mirror their peers’ behavior. Understanding how youth may be differentially susceptible to peer influence has implications for both theory and substance use policy. The potential moderation of the peer behavior-youth substance use relationship by genetic risk is explored to determine if differential susceptibility to peer influence is partially tied to biological factors. A subsample of data from the first two waves of the National Longitudinal Study of Adolescent to Adult Health (Add Health) is utilized (n = 1,495). Evidence of a gene-environment interaction emerges whereby genetic risk conditions the relationship between peer substance use and early onset of alcohol use in models controlling for several risk and protective factors (e.g. poverty, self-control, victimization, social support, neighborhood dissatisfaction, religiosity). Genotype appears particularly salient when youth report a moderate degree of peer substance use (when peer substance use exceeds the mean but does not reach the extreme). This finding has implications for Burgess and Akers’ Social Learning Theory and other peer-based theories of behavior. It suggests that interventions to insulate youth from substance-using peers will be particularly impactful for those at enhanced genetic risk for early alcohol use. The identified gene-environment interaction partially explains why some youth are differentially susceptible to peer influence.

A case study of actual versus desired inclusion of community-derived core concepts into neuroscience courses in different disciplines at a large university

Neuroscience is an inherently interdisciplinary and rapidly evolving field. While many universities have neuroscience or related majors, they are highly heterogeneous, and it is unclear how their content aligns with a recent proposal of what ideas make up the field of neuroscience. It is therefore important to document and assess the alignment of neuroscience curricula with core concepts in the field. Recently, a large effort by some members of the neuroscience education community described eight core concepts for undergraduate neuroscience curricula. In this paper, we focus primarily on courses in biology, cognitive science, and psychology at a large university, surveying the recent and current course instructors of these courses to ask them (1) to what extent these community-derived core concepts are incorporated into their classes and (2) to what extent these concepts should be incorporated into their classes. In addition, we map core concepts onto course syllabi. We found that core concepts are well-represented across disciplines, and identified differences between departments' inclusion of core concepts. We found that instructors cover fewer core concepts than they desire, and that two core concepts, “Evolution” and “Gene-environment interactions”, were less frequently addressed across disciplines. We consider barriers to instructors' ability to align course content with core concepts, both within and across disciplines. In this effort, we provide an example of how departments can evaluate their alignment of major requirements with the neuroscience core concepts.

Advancements in Lentil Genomics for Enhanced Crop Breeding: A Review

Lentil (Lens culinaris Medik) is an essential pulse crop that is widely grown for its high nutritional value, notably its high protein content, making it an important dietary component for vegetarians and vegans. Despite being the world's fifth most produced pulse, with large contributions from Canada and India, lentil production confronts obstacles such as poor productivity due to limited genetic improvement against biotic and abiotic stresses under rainfed cultivation conditions. Recent advances in lentil genetics and genomics, such as the discovery of genes related to yield, disease resistance, and nutritional content, have boosted breeding efforts to generate improved lentil varieties. The use of contemporary genomic techniques like molecular markers, marker-assisted selection (MAS), genomic selection (GS), and next-generation sequencing (NGS) technology has sped up the discovery of quantitative trait loci (QTLs) and the production of novel cultivars with superior agronomic characteristics. Databases such as NCBI and ENA, as well as specialized resources like KnowPulse, provide critical genomic data, while the creation of lentil genome assemblies, notably the CDC Redberry variety, has improved our understanding of lentil genetics. These resources help to solve the constraints of traditional breeding, particularly for complex characteristics impacted by genotype-environment interactions, opening the way for more robust and productive lentil varieties. Although the application of advanced tools such as genetic engineering, cisgenesis, and genome editing has moved more slowly in lentils than in other crops, their potential to improve lentil output is encouraging. Recent studies on lentil genomes, together with the creation of increased genetic resources and cutting-edge techniques, offer the ability to overcome production constraints and dramatically increase lentil production and quality throughout the world.

Genotype x environment interaction and yield stability of soybean (Glycine max l.) genotypes in multi-environment trials (METs) in Nigeria

Genotype × environment interaction (GEI) poses a critical challenge to plant breeders by complicating the identification of stable variety (ies) for performance across diverse environments. GGE biplot and AMMI analyses have been identified as the most effective and appropriate statistical techniques for identifying stable and high-performing genotypes across diverse environments. The objective of this study was to identify widely adapted and high-yielding soybean genotypes from Multi-Locational Trials (MLTs) using GGE and AMMI biplot analyses. Fifteen IITA-bred elite soybean lines and three standard checks were evaluated for stability of performance in a 3 × 6 alpha lattice design with three replications across seven locations in Nigeria. Significant (p < 0.001) differences were detected among genotypes, environments, and GEI for grain yield, which ranged between 979.8 kg ha−1 and 3645 kg ha−1 with a mean of 2324 kg ha−1. To assess the stability of genotypes, analyses were conducted using the general linear method, GGE, and the Additive Main Effect and Multiplicative Interaction (AMMI) approach, as well as WAAS and ASV rank indices. In the GGE biplot model, the first two principal components accounted for 67.4 % of the total variation, while in the AMMI model, the first two Interaction Principal Component Axes (IPCA1 and IPCA2) explained 73.20 % and 11.40 % of the variation attributed to genotype by environment interaction, respectively. GGE biplot identified G10 and G16 as the most stable and productive genotypes, while WAASB index revealed G16, G10, G9, G4 and G2 as the most adaptive, stable and productive genotypes across locations, and ASV identified G9, G13, G4, G14 and G10 as the most stable and productive.Consequently, genotypes G2, G4, G9, G10 and G16 displayed outstanding and stable grain yield performance across the test locations and are, therefore, recommended for release as new soybean varieties suitable for cultivation in the respective mega environment where they performed best. More importantly, the two genotypes are recommended for recycling as sources of high-yield and yield stability genes, and as parental lines for high-yield and stable performance for future breeding and genomic selection.