Genetic Background Research Articles

Polygenic risk score of metabolic dysfunction-associated steatotic liver disease amplifies the health impact on severe liver disease and metabolism-related outcomes

BackgroundAlthough the inherited risk factors associated with fatty liver disease are well understood, little is known about the genetic background of metabolic dysfunction-associated steatotic liver disease (MASLD) and its related health impacts. Compared to non-alcoholic fatty liver disease (NAFLD), MASLD presents significantly distinct diagnostic criteria, and epidemiological and clinical features, but the related genetic variants are yet to be investigated. Therefore, we conducted this study to assess the genetic background of MASLD and interactions between MASLD-related genetic variants and metabolism-related outcomes.MethodsParticipants from the UK Biobank were grouped into discovery and replication cohorts for an MASLD genome-wide association study (GWAS), and base and target cohorts for polygenic risk score (PRS) analysis. Autosomal genetic variants associated with NAFLD were compared with the MASLD GWAS results. Kaplan–Meier and Cox regression analyses were used to assess associations between MASLD and metabolism-related outcomes.ResultsSixteen single-nucleotide polymorphisms (SNPs) were identified at genome-wide significance levels for MASLD and duplicated in the replication cohort. Differences were found after comparing these SNPs with the results of NAFLD-related genetic variants. MASLD cases with high PRS had a multivariate-adjusted hazard ratio of 3.15 (95% confidence interval, 2.54–3.90) for severe liver disease (SLD), and 2.81 (2.60–3.03) for type 2 diabetes mellitus. The high PRS amplified the impact of MASLD on SLD and extrahepatic outcomes.ConclusionsHigh PRS of MASLD GWAS amplified the impact of MASLD on SLD and metabolism-related outcomes, thereby refining the process of identification of individuals at high risk of MASLD. Supplementation of this process with relevant genetic backgrounds may lead to more effective MASLD prevention and management.

Ancestral origins and admixture history of Kazakhs.

Kazakh people, like many other populations that settled in Central Asia, demonstrate an array of mixed anthropological features of East Eurasian (EEA) and West Eurasian (WEA) populations, indicating a possible scenario of biological admixture between already differentiated EEA and WEA populations. However, their complex biological origin and genomic makeup, as well as their genetic interaction with surrounding populations, are not well understood. In an attempt to decipher their genetic structure and population history, we conducted, to our knowledge, the first whole-genome sequencing study of Kazakhs residing in Xinjiang (KZK). We demonstrated that KZK derived their ancestries from four ancestral source populations: East Asian (∼39.7%), West Asian (∼28.6%), Siberian (∼23.6%), and South Asian (∼8.1%). The recognizable interactions of EEA and WEA ancestries in Kazakhs were dated back to the 15th century BCE. Kazakhs were genetically distinctive from Uyghurs in terms of their overall genomic makeup, although the two populations were closely related in genetics, and both showed a substantial admixture of EEA and WEA ancestries. Notably, we identified a considerable sex-biased admixture, with an excess of western males and eastern females contributing to the KZK gene pool. We further identified a set of genes that showed remarkable differentiation in KZK from the surrounding populations, including those associated with skin color (SLC24A5, OCA2), essential hypertension (HLA-DQB1), hypertension (MTHFR, SLC35F3), and neuron development (CNTNAP2). These results advance our understanding of the complex history of contacts between Western and Eastern Eurasians, especially those situated along the old Silk Road.

Genetic parameters and genome-wide association analyses for lifetime productivity in Chinese Holstein cattle

Lifetime productivity is a trait of great importance to dairy cattle populations as it combines information from production and longevity variables. Therefore, we investigated the genetic background of lifetime productivity in high-producing dairy cattle by integrating genomics and transcriptomics data sets. A total of 3,365,612 test-day milk yield records from 134,029 Chinese Holstein cows were used to define 6 lifetime productivity traits, including lifetime milk yield covering full lifespan and 5 cumulative milk yield traits covering partial lifespan. Genetic parameters were estimated based on univariate and bivariate linear animal models and the Restricted Maximum Likelihood (REML) method. Genome-wide association studies (GWAS) and weighted gene co-expression network analyses (WGCNA) were performed to identify candidate genes associated with lifetime productivity based on genomic data from 3,424 cows and peripheral blood RNA-seq data from 23 cows, respectively. Lifetime milk yield averaged 24,800.8 ± 14,396.6 kg (mean ± SD) across an average of 2.4 parities in Chinese Holstein population. The heritability estimates for lifetime productivity traits ranged from 0.05 (±0.01 for SE) to 0.10 (±0.02 for SE). The estimate of genetic correlation between lifetime milk yield and productive life is 0.88 (±0.3 for SE) while the genetic correlation with 305d milk yield in the first lactation was 0.49 (±0.08 for SE). Absolute values for most genetic correlation estimates between lifetime productivity and type traits were lower than 0.30. Moderate genetic correlations were found between udder related traits and lifetime productivity, such as with udder depth (0.33), rear udder attachment height (0.33), and udder system (0.34). Some single nucleotide polymorphisms and gene co-expression modules significantly associated with lifetime milk yield were identified based on GWAS and WGCNA analyses, respectively. Functional enrichment analyses of the candidate genes identified revealed important pathways related to immune system, longevity, energy utilization and metabolism, and FoxO signaling. The genes NTMT1, FNBP1, and S1PR1 were considered to be the most important candidate genes influencing lifetime productivity in Holstein cows. Overall, our findings indicate that lifetime productivity is heritable in Chinese Holstein cattle and important candidate genes were identified by integrating genomic and transcriptomic data sets.

Associations between Serum Metabolites and Female Cancers: a Bidirectional Two-sample Mendelian Randomization Study

Female cancers, especially breast, ovarian, cervical and endometrial cancers, constitute a major threat to women's health worldwide. In view of the complex genetic background of cancers cannot be fully explained with current genetic information, we used a bidirectional two-sample mendelian randomization approach to explore the causal associations between serum metabolites and four major female cancers—breast, ovarian, cervical and endometrial cancers. We analyzed the metabolites dataset from the Canadian Longitudinal Study of Aging and cancer datasets from the 10th round of the Finngen project. Replication analyses was performed with Cancer Association Consortium and Leo’s studies. Instrumental variables were analyzed using methods including the Wald ratio, inverse-variance weighted, MR-Egger, and weighted median. To ensure robustness, sensitivity analyses were performed using Cochrane’s Q, Egger’s intercept, MR-PRESSO, and leave-one-out methods. After meticulous analysis, we obtained levels of 3-hydroxyoleoylcarnitine, hexadecanedioate, tetradecanedioate and carnitine C14 with robust causal associations with breast cancer, levels of 5alpha-androstan-3alpha,17beta-diol monosulfate (1), androstenediol (3beta,17beta) monosulfate (1), androsterone sulfate, and 5alpha-androstan-3beta,17beta-diol disulfate causal associations with endometrial cancer. The reverse analysis showed that breast, ovarian, and endometrial cancer and survival of breast and ovarian cancer were found to have causal relationships with 8, 5, 2, 6, and 3 metabolites, respectively. These insights underscore the potential roles of specific metabolites in the etiology of female cancers, providing new biomarkers for early detection, risk stratification, and disease progression monitoring. Further research could elucidate how these metabolites influence specific pathways in cancer development, offering theoretical foundations for prevention and treatment strategies.

Genetic Variations in TrkB.T1 Isoform and Their Association with Somatic and Psychological Symptoms in Individuals with IBS

Irritable bowel syndrome (IBS), a disorder of gut-brain interaction, is often comorbid with somatic pain and psychological disorders. Dysregulated signaling of brain-derived neurotrophic factor (BDNF) and its receptor, tropomyosin-related kinase B (TrkB), has been implicated in somatic-psychological symptoms in individuals with IBS. We investigated the association of 10 single nucleotide polymorphisms (SNPs) in the regulatory 3' untranslated region (UTR) of NTRK2 (TrkB) kinase domain-deficient truncated isoform (TrkB.T1) and BDNF Val66Met SNP with somatic and psychological symptoms and quality of life in a cohort from the United States (U.S.) (IBS n=464; healthy controls n=156). We found that the homozygous recessive genotype (G/G) of rs2013566 in individuals with IBS is associated with worsened somatic symptoms, including headache, back pain, joint pain, muscle pain, and somatization as well as diminished sleep quality, energy level and overall quality of life. Validation using United Kingdom BioBank (UKBB) data confirmed the association of rs2013566 with increased likelihood of headache. Several SNPs (rs1627784, rs1624327, rs1147198) showed significant associations with muscle pain in our U.S. cohort. These 4 SNPs are predominantly located in H3K4Me1-enriched regions, suggesting their enhancer and/or transcription regulation potential. Our findings suggest that genetic variation within the 3'UTR region of the TrkB.T1 isoform may contribute to comorbid conditions in individuals with IBS, resulting in a spectrum of somatic and psychological symptoms impacting their quality of life. These findings advance our understanding of the genetic interaction between BDNF/TrkB pathways and somatic-psychological symptoms in IBS, highlighting the importance of further exploring this interaction for potential clinical applications. PerspectiveThis study aims to understand the genetic effects on IBS-related symptoms across somatic, psychological, and quality of life domains, validated by UKBB data. The rs2013566 homozygous recessive genotype correlates with worsened somatic symptoms and reduced quality of life, emphasizing its clinical significance.

Combination of dual JAK/HDAC inhibitor with regorafenib synergistically reduces tumor growth, metastasis, and regorafenib-induced toxicity in colorectal cancer

BackgroundTreatment with regorafenib, a multiple-kinase inhibitor, to manage metastatic colorectal cancers (mCRCs) shows a modest improvement in overall survival but is associated with severe toxicities. Thus, to reduce regorafenib-induced toxicity, we used regorafenib at low concentration along with a dual JAK/HDAC small-molecule inhibitor (JAK/HDACi) to leverage the advantages of both JAK and HDAC inhibition to enhance antitumor activity. The therapeutic efficacy and safety of the combination treatment was evaluated with CRC models.MethodsThe cytotoxicity of JAK/HDACi, regorafenib, and their combination were tested with normal colonic and CRC cells exhibiting various genetic backgrounds. Kinomic, ATAC-seq, RNA-seq, cell cycle, and apoptosis analyses were performed to evaluate the cellular functions/molecular alterations affected by the combination. Efficacy of the combination was assessed using patient-derived xenograft (PDX) and experimental metastasis models of CRC. To evaluate the interplay between tumor, its microenvironment, and modulation of immune response, MC38 syngeneic mice were utilized.ResultsThe combination therapy decreased cell viability; phosphorylation of JAKs, STAT3, EGFR, and other key kinases; and inhibited deacetylation of histone H3K9, H4K8, and alpha tubulin proteins. It induced cell cycle arrest at G0-G1 phase and apoptosis of CRC cells. Whole transcriptomic analysis showed that combination treatment modulated molecules involved in apoptosis, extracellular matrix-receptor interaction, and focal adhesion pathways. It synergistically reduces PDX tumor growth and experimental metastasis, and, in a syngeneic mouse model, the treatment enhances the antitumor immune response as evidenced by higher infiltration of CD45 and cytotoxic cells. Pharmacokinetic studies showed that combination increased the bioavailability of regorafenib.ConclusionsThe combination treatment was more effective than with regorafenib or JAK/HDACi alone, and had minimal toxicity. A clinical trial to evaluate this combination for treatment of mCRCs is warranted.

Association study of Plasmodium falciparum Acetyl-CoA Synthetase Mutations S868G and V949I with antimalarial drugs.

Plasmodium falciparum acetyl-CoA synthetase (PfACAS) protein is an important source of acetyl-CoA. We detected the mutations S868G and V949I in PfACAS by whole-genome sequencing analysis in some recrudescent parasites after antimalarial treatment with artesunate and dihydroartemisinin-piperaquine, suggesting that they may confer drug resistance. Using CRISPR/Cas9 technology, we engineered parasite lines carrying the PfACAS S868G and V949I mutations in two genetic backgrounds and evaluated their susceptibility to antimalarial drugs in vitro. The results demonstrated that PfACAS S868G and V949I mutations alone or in combination were not enough to provide resistance to antimalarial drugs.

Unraveling schizophrenia's genetic complexity through advanced causal inference and chromatin 3D conformation

Schizophrenia is a polygenic complex disease with a heritability as high as 80 %, yet the mechanism of polygenic interaction in its pathogenesis remains unclear. Studying the interaction and regulation of schizophrenia susceptibility genes is crucial for unraveling the pathogenesis of schizophrenia and developing antipsychotic drugs. Therefore, we developed a bioinformatics method named GRACI (Gene Regulation Analysis based on Causal Inference) based on the principles of information theory, a causal inference model, and high order chromatin 3D conformation. GRACI captures the interaction and regulatory relationships between schizophrenia susceptibility genes by analyzing genotyping data. Two datasets, comprising 1459 and 2065 samples respectively, were analyzed, and the gene networks from both datasets were constructed. GRACI showcased superior accuracy when compared to widely adopted methods for detecting gene-gene interactions and intergenic regulation. This alignment was further substantiated by its correlation with chromatin high-order conformation patterns. Using GRACI, we identified three potential genes—KCNN3, KCNH1, and KCND3—that are directly associated with schizophrenia pathogenesis. Furthermore, the results of GRACI on the standalone dataset illustrated the method's applicability to other complex diseases. GRACI download: https://github.com/liuliangjie19/GRACI

In Vivo Mouse Models for Adult Brain Tumors: Exploring Tumorigenesis and Advancing Immunotherapy Development.

Brain tumors, particularly glioblastoma (GBM), are devastating and challenging to treat, with a low 5-year survival rate of only 6.6%. Mouse models are established to understand tumorigenesis and develop new therapeutic strategies. Large-scale genomic studies have facilitated the identification of genetic alterations driving human brain tumor development and progression. Genetically engineered mouse models (GEMMs) with clinically relevant genetic alterations are widely used to investigate tumor origin. Additionally, syngeneic implantation models, utilizing cell lines derived from GEMMs or other sources, are popular for their consistent and relatively short latency period, addressing various brain cancer research questions. In recent years, the success of immunotherapy in specific cancer types has led to a surge in cancer immunology-related research which specifically necessitates the utilization of immunocompetent mouse models. In this review, we provide a comprehensive summary of GEMMs and syngeneic mouse models for adult brain tumors, emphasizing key features such as model origin, genetic alteration background, oncogenic mechanisms, and immune-related characteristics. Our review serves as a valuable resource for the brain tumor research community, aiding in the selection of appropriate models to study cancer immunology.

Role of female reproductive hormones and genetics in temporomandibular joint disorders.

The disorders of temporomandibular joint manifest clinically with disruptions in its movement and facial pain. Women exhibit athree-fold higher propensity for developing temporomandibular joint disorders compared to men. There are several studies describing the effects of female reproductive hormones on temporomandibular joint structures and pain perception, shedding light on the genetic influence underlying these conditions. Several polymorphisms have been studied and documented in the literature, shedding light on the genetic background of temporomandibular joint disorders.This review aims to propose anovel approach to the complex diagnosis and treatment of this type of disorders. Specifically, we advocate for heightening the emphasis on young women diagnosed with temporomandibular joint disorders during their reproductive years, as such manifestation could potentially serve as early indicators of other underlying health conditions linked to the reproductive system. We posit that genetic studies hold promise as acornerstone for tailoring personalized treatment strategies for TMJD in the future (Tab. 1, Ref. 46). Text in PDF www.elis.sk Keywords: temporomandibular joint disorders, infertility, female reproductive hormones, genetic polymorphism.

Evidence of 14-3-3 proteins contributing to kinetochore integrity and chromosome congression during mitosis.

The 14-3-3 family of proteins are conserved across eukaryotes and serve myriad important regulatory functions of the cell. Homo/heterodimers of these protein homologs, majorly recognize their ligands via conserved motifs to modulate the localization and functions of those effector ligands. In most of the genetic backgrounds of Saccharomyces cerevisiae, disruption of both 14-3-3 homologs (Bmh1 and Bmh2) are either lethal or survive with severe growth defects showing gross chromosomal missegregation and prolonged cell cycle arrest. To elucidate their contributions to chromosome segregation, in this work we investigated their centromere/kinetochore-related functions. Analysis of appropriate deletion mutants shows that Bmh isoforms have cumulative and unshared isoform-specific contributions in maintaining the proper integrity of the kinetochore ensemble. Consequently, bmh mutant cells exhibited perturbations in kinetochore-microtubule (KT-MT) dynamics, characterized by kinetochore declustering, mis-localization of kinetochore proteins, and Mad2-mediated transient G2/M arrest. These defects also caused an asynchronous chromosome congression in bmh mutants during metaphase. In summary, this report advances the knowledge on contributions of budding yeast 14-3-3 proteins in chromosome segregation by demonstrating their roles in kinetochore integrity and chromosome congression.

Smooth muscle expression of RNA editing enzyme ADAR1 controls vascular integrity and progression of atherosclerosis.

Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 ( IFIH1 ) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing to be an important mechanism of coronary artery disease (CAD) risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque, we implicate the vascular smooth muscle cell (SMC) to have a unique requirement for RNA editing, and that ISG induction occurs in SMC phenotypic modulation, implicating MDA5 activation. Through culture of human coronary artery SMCs, generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background, and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality.

Large Language Models and Genomics for Summarizing the Role of microRNA in Regulating mRNA Expression

microRNA (miRNA)–messenger RNA (mRNA or gene) interactions are pivotal in various biological processes, including the regulation of gene expression, cellular differentiation, proliferation, apoptosis, and development, as well as the maintenance of cellular homeostasis and pathogenesis of numerous diseases, such as cancer, cardiovascular diseases, neurological disorders, and metabolic conditions. Understanding the mechanisms of miRNA–mRNA interactions can provide insights into disease mechanisms and potential therapeutic targets. However, extracting these interactions efficiently from a huge collection of published articles in PubMed is challenging. In the current study, we annotated a miRNA–mRNA Interaction Corpus (MMIC) and used it for evaluating the performance of a variety of machine learning (ML) models, deep learning-based transformer (DLT) models, and large language models (LLMs) in extracting the miRNA–mRNA interactions mentioned in PubMed. We used the genomics approaches for validating the extracted miRNA–mRNA interactions. Among the ML, DLT, and LLM models, PubMedBERT showed the highest precision, recall, and F-score, with all equal to 0.783. Among the LLM models, the performance of Llama-2 is better when compared to others. Llama 2 achieved 0.56 precision, 0.86 recall, and 0.68 F-score in a zero-shot experiment and 0.56 precision, 0.87 recall, and 0.68 F-score in a three-shot experiment. Our study shows that Llama 2 achieves better recall than ML and DLT models and leaves space for further improvement in terms of precision and F-score.

EIF6 Promotes Gastric Cancer Proliferation and Invasion by Regulating Cell Cycle.

To investigate the role and function of eIF6 in gastric cancer (GC). The expression level of eIF6 in GC tissues and normal tissues was detected in different high-throughput sequencing cohorts. Survival analysis, gene differential analysis, and enrichment analysis were performed in the TCGA cohort. Biological networks centered on eIF6 were constructed through two different databases. Immunohistochemistry (IHC) and Western blot were used to detect protein expression of eIF6, and qRT-PCR was used to detect eIF6 mRNA expression. The correlation between the expression of eIF6 in GC tissues and clinicopathological parameters of GC was analyzed. siRNA knockout of eIF6 was used to study the proliferation, migration, and invasion. The effects of eIF6 on cell cycle and Cyclin B1 were detected by flow cytometry and Western blot. eIF6 was significantly overexpressed in GC tissues and predicted poor prognosis. In addition, 113 differentially expressed genes were detected in cancer-related biological pathways and functions by differential analysis. Biological networks revealed interactions of genes and proteins with eIF6. The expression intensity of eIF6 in cancer tissues was higher than that in adjacent tissues (P = 0.0001), confirming the up-regulation of eIF6 expression in GC tissues. The expression level of eIF6 was statistically significant with pTNM stage (P = 0.006). siRNA knockout of eIF6 significantly reduced the proliferation, colony formation, migration, and invasion ability of GC cells. Silencing of eIF6 also inhibited the cell cycle of GC cells in G2/M phase and decreased the expression level of CyclinB1. Our study suggests that eIF6 is up-regulated in GC and may promote the proliferation, migration, and invasion of GC by regulating cell cycle.

Systemic therapy for differentiated thyroid cancer with distant metastasis

Background: Thyroid cancer is a slow-growing tumor with excellent oncological outcomes. However, few patients with unexpectedly severe outcomes are usually ignored.Current Concepts: Radioactive iodine therapy is the mainstay treatment for differentiated thyroid cancer with distant metastasis. The refractoriness to radioactive iodine therapy has been overcome by the emergence of targeted agents. First, multikinase inhibitors (sorafenib and lenvatinib) targeting the growth factor pathway were developed and approved as anticancer agents for patients with advanced differentiated thyroid cancer, regardless of their genetic features. With progress in sequencing techniques, the genetic backgrounds of tumors have unveiled new targets, including rearrangements during transformation and tropomyosin receptor kinase. Special attention should be paid to the national health insurance coverage of systemic therapeutics and genetic studies.Discussion and Conclusion: New drugs were introduced to treat previously untreatable advanced thyroid cancers. However, the cost of these drugs has increased with new developments, and only first-line drugs for thyroid cancer are still covered by insurance. These medical advances will remain an illusion for clinics and patients if improvements in healthcare policies do not accompany them.

Variability and Correlation-coefficient Analysis for Some Proximate Components of Lablab purpureus (L.) Sweet Genotypes of Assam

Background: Lablab purpureus (L.) Sweet is an important and primarily consumed vegetable crop in Assam. Large number of genotypes of Lablab purpureus (L.) Sweet are available in Assam, India, which are prosperous source of the gene pool. However, there has been limited understanding of the genetic background of the various proximate components of Lablab, although we primarily use the crop for these proximate components. The present study helps us understand the genetic background of the various proximate components so that they can be efficiently utilized to further improve the genotypes. Methods: Sixteen (16) genotypes of Lablab purpureus (L.) Sweet of Assam were collected from the 6 (six) Agro-climatic zones of Assam, their genetic variability were assessed and correlation analysis with respect to their proximate components during the period 2020-2023. The various proximate components that were analyzed includes moisture, ash, fibre, fat, crude protein content and total carbohydrate content. Various genetic parametres were also determined which included heritability, genotypic and phenotypic coefficient of variance (GCV and PCV) and genetic advance percentage of mean (GAPM). Result: Significant differences were found among the genotypes in all studied traits in the study. GCV and PCV revealed variability and less influence of the environment that supports the influence of heritable components on traits. High heritability and genetic advance for all the traits indicated action of additive genes. Heritability along with GAPM is a positive indicator of expected progress through selection. The study will help us in understanding the genetic parameters associated with the various proximate components.

From Chaos Comes Order: Genetics and Genome Biology of Arbuscular Mycorrhizal Fungi.

Arbuscular mycorrhizal fungi (AMF) are obligate mutualists that can enhance nutrition and growth of their plant hosts while providing protection against pathogens. AMF produce spores and hyphal networks that can carry thousands of nuclei in a continuous cytoplasm, with no evidence of sexual reproduction. This review examines the impact of genomic technologies on our view of AMF genetics and evolution. We highlight how the genetics, nuclear dynamics, and epigenetics of these prominent symbionts follow trends preserved in distant multinucleate fungal relatives. We also propose new avenues of research to improve our understanding of their nuclear biology and their intricate genetic interactions with plant hosts.

From Chaos Comes Order: Genetics and Genome Biology of Arbuscular Mycorrhizal Fungi.

Arbuscular mycorrhizal fungi (AMF) are obligate mutualists that can enhance nutrition and growth of their plant hosts while providing protection against pathogens. AMF produce spores and hyphal networks that can carry thousands of nuclei in a continuous cytoplasm, with no evidence of sexual reproduction. This review examines the impact of genomic technologies on our view of AMF genetics and evolution. We highlight how the genetics, nuclear dynamics, and epigenetics of these prominent symbionts follow trends preserved in distant multinucleate fungal relatives. We also propose new avenues of research to improve our understanding of their nuclear biology and their intricate genetic interactions with plant hosts.

Transcription factor OsbZIP10 modulates rice grain quality by regulating OsGIF1.

Understanding and optimizing the process of grain filling helps the quest to maximize rice (Oryza sativa L.) seed yield and quality, yet the intricate mechanisms at play remain fragmented. Transcription factors (TFs) are major players in the gene networks underlying the grain filling process. Here, we employed grain incomplete filling (OsGIF1)/cell wall invertase 2, a key gene involved in grain filling, to explore its upstream TFs and identified a bZIP family TF, OsbZIP10, to be a transcriptional activator of OsGIF1. Rice grains of the knockouts of OsbZIP10 showed increased white-core rates but lower amylose content (AC), leading to better eating and cooking qualities in all genetic backgrounds investigated, though the impact of mutations in OsbZIP10 on grain weight depended on genetic background. Multi-omics analyses suggested that, in addition to OsGIF1, multiple genes involved in different biological processes contributing to grain filling were targeted by OsbZIP10, including OsAGPS1, a gene encoding the ADP-Glc pyrophosphorylase (AGPase) small subunit, and genes contributing to homeostasis of reactive oxygen species. Distinct genetic make-up was observed in OsbZIP10 between japonica and indica rice varieties, with the majority varieties of each subspecies belonging to two different haplotypes that were closely associated with AC. Overexpressing the haplotype linked to high-AC in the low-AC genetic background increased AC. Overall, this study sheds crucial light on the significance of the OsbZIP10-OsGIF1 module in the determination of rice grain quality, offering a potential avenue for genetic engineering of rice to produce seeds with tailored attributes.

A complete chromosome substitution mapping panel reveals genome-wide epistasis in Arabidopsis.

Chromosome substitution lines (CSLs) are tentatively supreme resources to investigate non-allelic genetic interactions. However, the difficulty of generating such lines in most species largely yielded imperfect CSL panels, prohibiting a systematic dissection of epistasis. Here, we present the development and use of a unique and complete panel of CSLs in Arabidopsis thaliana, allowing the full factorial analysis of epistatic interactions. A first comparison of reciprocal single chromosome substitutions revealed a dependency of QTL detection on different genetic backgrounds. The subsequent analysis of the complete panel of CSLs enabled the mapping of the genetic interactors and identified multiple two- and three-way interactions for different traits. Some of the detected epistatic effects were as large as any observed main effect, illustrating the impact of epistasis on quantitative trait variation. We, therefore, have demonstrated the high power of detection and mapping of genome-wide epistasis, confirming the assumed supremacy of comprehensive CSL sets.