Gene Association Studies Research Articles

An association study of clock genes with major depressive disorder

ObjectiveTo study the relationship between clock genes and Major Depressive Disorder (MDD). MethodsGEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD. ResultsSix genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF − beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathways were Toll like receptor signaling pathway, glucolipid metabolism, amino acid metabolism, neuroactive ligand receptor interaction, and so on. The results of immune infiltration analysis showed that NK cells resting and Macrophages M2 were different between MDD and control groups. In MDD, the gene closely related to NK cells resting was HDAC1, and the genes closely related to Macrophages M2 were HDAC1 and NFIL3. The RNA interactions network of clock genes shows that the regulation process is complex, which can provide a reference for subsequent related research. Potential therapeutic drugs predict display, among the 5 clock genes, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. ConclusionAmong all CLOCK genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD. Among them, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs.

Genome wide association study of genes controlling resistance to Didymella rabiei Pathotype IV through genotyping by sequencing in chickpeas (Cicer arietinum)

Ascochyta blight (AB) is a major disease in chickpeas (Cicer arietinum L.) that can cause a yield loss of up to 100%. Chickpea germplasm collections at the center of origin offer great potential to discover novel sources of resistance to pests and diseases. Herein, 189 Cicer arietinum samples were genotyped via genotyping by sequencing. This chickpea collection was phenotyped for resistance to an aggressive Turkish Didymella rabiei Pathotype IV isolate. Genome-wide association studies based on different models revealed 19 single nucleotide polymorphism (SNP) associations on chromosomes 1, 2, 3, 4, 7, and 8. Although eight of these SNPs have been previously reported, to the best of our knowledge, the remaining ten were associated with AB resistance for the first time. The regions identified in this study can be addressed in future studies to reveal the genetic mechanism underlying AB resistance and can also be utilized in chickpea breeding programs to improve AB resistance in new chickpea varieties.

A Large-Scale Candidate-Gene Association Mapping for Drought Tolerance and Agronomic Traits in Sugarcane.

Dissection of the genetic loci controlling drought tolerance traits with a complex genetic inheritance is important for drought-tolerant sugarcane improvement. In this study, we conducted a large-scale candidate gene association study of 649 candidate genes in a sugarcane diversity panel to identify genetic variants underlying agronomic traits and drought tolerance indices evaluated in plant cane and ratoon cane under water-stressed (WS) and non-stressed (NS) environments. We identified 197 significant marker-trait associations (MTAs) in 141 candidate genes associated with 18 evaluated traits with the Bonferroni correction threshold (α = 0.05). Out of the total, 95 MTAs in 78 candidate genes and 62 MTAs in 58 candidate genes were detected under NS and WS conditions, respectively. Most MTAs were found only in specific water regimes and crop seasons. These MTAs explained 7.93-30.52% of phenotypic variation. Association mapping results revealed that 34, 59, and 104 MTAs involved physiological and molecular adaptation, phytohormone metabolism, and drought-inducible genes. They identified 19 pleiotropic genes associated with more than one trait and many genes related to drought tolerance indices. The genetic and genomic resources identified in this study will enable the combining of yield-related traits and sugar-related traits with agronomic value to optimize the yield of sugarcane cultivars grown under drought-stressed and non-stressed environments.

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches toinsights of susceptibility genes.

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Genome-wide Association Studies of REST Gene Associated Neurological Diseases/traits with Related Single Nucleotide Polymorphisms.

Genome-wide association studies (GWAS) have been used to explore the connections between genotypes and phenotypes by comparing the genotype frequencies of genetic changes in individuals with similar origins but distinct traits. The aim is to employ the GWAS catalog to identify and investigate the various correlations between genotypes and phenotypes of the REST gene. In this study, we utilized a large dataset of GWAS comprising 62,218,976 individuals in 112 studies and 122 associations with 122 traits (www.ebi.ac.uk/gwas/genes/REST) from European, Asian, Hispanic, African ancestry up to 28 February 2023. Protein-association network evaluation and gene ontology enrichment study was utilized to evaluate the biological function of the discovered gene modules. We identified several associations for both neurodevelopmental and neurodegenerative disorders linked to REST, as well as its mapped gene modules and their functional relationship networks. This work offers fresh insights into identifying risk loci of neurological disorders caused by REST.

Molecular biology of serotonergic systems in avian brains.

Serotonin (5-hydroxytryptamine, 5-HT) is a phylogenetically conserved neurotransmitter and modulator. Neurons utilizing serotonin have been identified in the central nervous systems of all vertebrates. In the central serotonergic system of vertebrate species examined so far, serotonergic neurons have been confirmed to exist in clusters in the brainstem. Although many serotonin-regulated cognitive, behavioral, and emotional functions have been elucidated in mammals, equivalents remain poorly understood in non-mammalian vertebrates. The purpose of this review is to summarize current knowledge of the anatomical organization and molecular features of the avian central serotonergic system. In addition, selected key functions of serotonin are briefly reviewed. Gene association studies between serotonergic system related genes and behaviors in birds have elucidated that the serotonergic system is involved in the regulation of behavior in birds similar to that observed in mammals. The widespread distribution of serotonergic modulation in the central nervous system and the evolutionary conservation of the serotonergic system provide a strong foundation for understanding and comparing the evolutionary continuity of neural circuits controlling corresponding brain functions within vertebrates. The main focus of this review is the chicken brain, with this type of poultry used as a model bird. The chicken is widely used not only as a model for answering questions in developmental biology and as a model for agriculturally useful breeding, but also in research relating to cognitive, behavioral, and emotional processes. In addition to a wealth of prior research on the projection relationships of avian brain regions, detailed subdivision similarities between avian and mammalian brains have recently been identified. Therefore, identifying the neural circuits modulated by the serotonergic system in avian brains may provide an interesting opportunity for detailed comparative studies of the function of serotonergic systems in mammals.

Candidate Gene Association Studies in Atopic Dermatitis in Participants of European and Asian Ancestry: A Systematic Review and Meta-Analysis.

Atopic dermatitis (AD) has been extensively investigated for genetic associations utilizing both candidate gene approaches and genome-wide scans. Here, we comprehensively evaluated the available literature to determine the association of candidate genes in AD to gain additional insight into the etiopathogenesis of the disease. We systematically screened all studies that explored the association between polymorphisms and AD risks in cases of European and Asian ancestry and synthesized the available evidence through a random-effects meta-analysis. We identified 99 studies that met our inclusion/exclusion criteria that examined 17 candidate loci in Europeans and 14 candidate genes in Asians. We confirmed the significant associations between FLG variants in both European and Asian populations and AD risk, while synthesis of the available data revealed novel loci mapped to IL18 and TGFB1 genes in Europeans and IL12RB1 and MIF in Asians that have not yet been identified by genome-wide association studies. Our findings provide comprehensive evidence for AD risk loci in cases of both European and Asian ancestries, validating previous associations as well as revealing novel loci that could imply previously unexplored biological pathways.

Association of rs35006907 Polymorphism with Risk of Dilated Cardiomyopathy in Han Chinese Population.

Several investigations have demonstrated the association of MTSS1 with left ventricular (LV) structure and function. A recently published study has even revealed that rs35006907 was associated with both MTSS1 expression and the risk of dilated cardiomyopathy (DCM). Our study intended to investigate the relationship between rs35006907 and the risk of DCM in the Han Chinese population. A total of 529 DCM and 600 healthy controls were recruited. We conducted genotyping for rs35006907 in all participants. Gene association studies were performed to assess the association between rs35006907 and the risk of DCM. A series of functional assays including western blot, realtime PCR and firefly luciferase reporter gene assays were conducted to illuminate the underlying mechanism. We found that rs35006907-A allele was significantly associated with reduced risk of DCM in additive (p= 0.004; OR=0.78; 95% CI=0.66-0.93) and recessive models (p= 0.0005; OR=0.56; 95%CI=0.41-0.78) when compared with the rs35006907-C allele. There were significant differences in the left ventricular end-diastolic diameter (LVEDD) and left ventricular ejection fraction (LVEF) between rs35006907-CC/AC and AA genotypes. Furthermore, the variant rs35006907-A allele presented lower reporter gene activity, reduced mRNA and protein expression levels when compared with the C allele. Our findings demonstrated that rs35006907-C allele increased the risk of DCM in Han Chinese population. Besides, rs35006907-C displayed higher reporter gene activity and increased MTSS1 expression in human samples.

Damage effects of bisphenol A against sepsis induced acute lung injury

In addition to oxidative damage, sepsis can cause multiple organ dysfunction and poses a life-threatening threat. In addition to severe tissue damage, hypotension, and multiple organ failure, sepsis can cause high morbidity and mortality. It is the lungs that are most vulnerable in abdominal sepsis, with impaired oxygen and nutrient exchange occurring in the pulmonary microcirculation. However, the etiology of sepsis and the link between sepsis and lung injury has not been elucidated. In this work, by exploring the data from the GEO and CTD database, a gene association study was conducted to determine whether sepsis-induced lung injury is caused by BPA. Further analysis demonstrated that MMP9, CEBPA, CYP1B1, CTSD, FKBP5, DGAT2, HP, TIMP2, ARG1 and MGST1 may play an important role in sepsis-induced lung injury. Finally, the single-cell RNA sequence demonstrated that CEBPA is mainly enriched in lung epithelial cells and epithelial cells, whereas CYP1B1 is closely related to basal cells, macrophages, and interstitial cells. In order to maintain lung function, epithelial and alveolar macrophages as well as other lung cells are important. When the lung epithelium is activated for a prolonged period of time, barrier function may be compromised and tissue damage may result, aggravating the lung injury. By using the animal model, we successfully simulated the model of sepsis lung injury. The HE staining demonstrated the rats with BPA-treated septic lung injury showed more alveolar structure to be disordered, pulmonary interstitial edema to be evident, and red blood cells as well as inflammatory cells. For PCR assay, the results demonstrated that the expression level of CEBPA is higher in the lung samples with sepsis compared with the normal samples of the lung. In order to evaluate the expression level of CEBPA and CYP1B1 in lung tissue, we then performed the PCR assay. For CYP1B1, the results demonstrated that the expression level of CYP1B1 in lung samples with sepsis is lower than in normal lung samples. In total, BPA may be a potential contributing factor to sepsis-induced lung injury.

Candidate gene association study suggests potential role of dopamine beta-hydroxylase in pain heterogeneity in sickle cell disease.

Introduction: Pain is a lifelong companion of individuals with sickle cell disease (SCD) and has a severe impact on their quality of life. Both acute crisis pain and chronic non-crisis pain exhibit high variability between individuals, making it difficult to effectively manage sickle cell-related pain. We investigated the role of dopamine beta-hydroxylase (DBH) gene polymorphisms on pain variability in SCD. DBH is a key enzyme in the catecholamine biosynthesis pathway that catalyzes the conversion of dopamine to norepinephrine, both of which are known mediators of pain and pain-related behaviors. Methods: Acute crisis pain-related utilization and non-crisis chronic pain scores of 131 African Americans with SCD were obtained. Results and discussion: Association analyses revealed that the T allele of upstream variant rs1611115 and downstream variant rs129882 correlated with higher severity of chronic pain in an additive model. On the other hand, the A allele of missense variant rs5324 associated with lower risk of both acute crisis pain and chronic pain. Similarly, the C allele of intronic variant rs2797849 was associated with lower incidence of acute crisis pain in the additive model. In addition, tissue-specific eQTL revealed that the T allele of rs1611115 correlated with decreased expression of DBH in the frontal cortex and anterior cingulate cortex (GTEx), and decreased expression of DBH-AS1 in blood (eQTLGen). Bioinformatic approaches predicted that rs1611115 may be altering a transcription factor binding site, thereby, contributing to its potential effect. Taken together, findings from this study suggest that potential functional polymorphisms of DBH may modulate pain perception in SCD.

Genes and Athletic Performance: The 2023 Update.

Phenotypes of athletic performance and exercise capacity are complex traits influenced by both genetic and environmental factors. This update on the panel of genetic markers (DNA polymorphisms) associated with athlete status summarises recent advances in sports genomics research, including findings from candidate gene and genome-wide association (GWAS) studies, meta-analyses, and findings involving larger-scale initiatives such as the UK Biobank. As of the end of May 2023, a total of 251 DNA polymorphisms have been associated with athlete status, of which 128 genetic markers were positively associated with athlete status in at least two studies (41 endurance-related, 45 power-related, and 42 strength-related). The most promising genetic markers include the AMPD1 rs17602729 C, CDKN1A rs236448 A, HFE rs1799945 G, MYBPC3 rs1052373 G, NFIA-AS2 rs1572312 C, PPARA rs4253778 G, and PPARGC1A rs8192678 G alleles for endurance; ACTN3 rs1815739 C, AMPD1 rs17602729 C, CDKN1A rs236448 C, CPNE5 rs3213537 G, GALNTL6 rs558129 T, IGF2 rs680 G, IGSF3 rs699785 A, NOS3 rs2070744 T, and TRHR rs7832552 T alleles for power; and ACTN3 rs1815739 C, AR ≥21 CAG repeats, LRPPRC rs10186876 A, MMS22L rs9320823 T, PHACTR1 rs6905419 C, and PPARG rs1801282 G alleles for strength. It should be appreciated, however, that elite performance still cannot be predicted well using only genetic testing.

A transcriptome association study of AD risk genes in the pathogenesis of Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) affects millions of people with no effective treatments making it vital to identify potential therapeutic targets. Genome‐wide association studies (GWAS) have consistently identified AD susceptibility loci or ‘hits’. Few of these are differentially expressed in brain transcriptomic studies, meaning that their effects may be manifest via interacting or downstream transcripts. We have recently used machine learning on human brain transcriptomic data to identify and validate an association between lactoferrin and amyloid (1). Here we apply the same method to identify the transcripts associated with AD susceptibility ‘loci’.MethodAnalyses were performed on the disease‐linked genes from our machine learning analyses (LTF, ADAMTS2, PPDPF, PRTN3) and the combined 58 GWAS risk loci from two recent studies (2, 3). Boruta was used to find transcripts associated with each GWAS ‘hit’ and our genes of interest in two pathologically confirmed AD cohorts (Religious Orders Study and Memory and Aging project, Mount Sinai Brain Bank). The GWAS hits and associated transcripts were correlated with disease markers (cognition, plaque number, Braak score, CERAD score) to find direct and indirect effects.ResultsTREM2 was the GWAS ‘hit’ most correlated with disease markers in both cohorts but most GWAS ‘hits’ were either not correlated or negatively correlated with disease markers. Among the GWAS ‘hit’‐associated transcripts, SWAP70, EMP3, and WWTR1 were positively and VGF negatively correlated with disease markers in both cohorts. For our genes of interest, ADAMTS2 and PPDPF shared overlaps between their associated transcripts and that of GWAS ‘hit’ ABCA7. LTF was linked with TREM2 and associated with plaques in both cohorts.ConclusionThis study has teased apart nascent associations between known susceptibility genes and gene expression data from the AD brain, but it also hints that consideration of pathological sub‐phenotypes are required to make greater progress in understanding AD pathogenesis.1. Tsatsanis et al. The acute phase protein lactoferrin is a key feature of AD …. Mol Psychiatry. 2021;26(10):5516‐31.2. Yang et al. A human brain vascular atlas reveals diverse cell mediators of AD risk. BioRxiv [Preprint]. 2021.3. Wightman et al. A GWAS with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease. Nat Genet. 2021;53(9):1276‐82.

Integrating functional scoring and regulatory data to predict the effect of non-coding SNPs in a complex neurological disease.

Most SNPs associated with complex diseases seem to lie in non-coding regions of the genome; however, their contribution to gene expression and disease phenotype remains poorly understood. Here, we established a workflow to provide assistance in prioritising the functional relevance of non-coding SNPs of candidate genes as susceptibility loci in polygenic neurological disorders. To illustrate the applicability of our workflow, we considered the multifactorial disorder migraine as a model to follow our step-by-step approach. We annotated the overlap of selected SNPs with regulatory elements and assessed their potential impact on gene expression based on publicly available prediction algorithms and functional genomics information. Some migraine risk loci have been hypothesised to reside in non-coding regions and to be implicated in the neurotransmission pathway. In this study, we used a set of 22 non-coding SNPs from neurotransmission and synaptic machinery-related genes previously suggested to be involved in migraine susceptibility based on our candidate gene association studies. After prioritising these SNPs, we focused on non-reported ones that demonstrated high regulatory potential: (1) VAMP2_rs1150 (3' UTR) was predicted as a target of hsa-mir-5010-3p miRNA, possibly disrupting its own gene expression; (2) STX1A_rs6951030 (proximal enhancer) may affect the binding affinity of zinc-finger transcription factors (namely ZNF423) and disturb TBL2 gene expression; and (3) SNAP25_rs2327264 (distal enhancer) expected to be in a binding site of ONECUT2 transcription factor. This study demonstrated the applicability of our practical workflow to facilitate the prioritisation of potentially relevant non-coding SNPs and predict their functional impact in multifactorial neurological diseases.

Genome-wide and candidate gene association studies identify BnPAP17 as conferring the utilization of organic phosphorus in oilseed rape

Phosphorus (P) is essential for living plants, and P deficiency is one of the key factors limiting the yield in rapeseed production worldwide. As the most important organ for plants, root morphology traits (RMTs) play a key role in P absorption. To investigate the genetic variability of RMT under low P availability, we dissected the genetic structure of RMTs by genome-wide association studies (GWAS), linkage mapping and candidate gene association studies (CGAS). A total of 52 suggestive loci were associated with RMTs under P stress conditions in 405 oilseed rape accessions. The purple acid phosphatase gene BnPAP17 was found to control the lateral root number (LRN) and root dry weight (RDW) under low P stress. The expression of BnPAP17 was increased in shoot tissue in P-efficient cultivars compared to root tissue and P-inefficient cultivars in response to low P stress. Moreover, the haplotype of BnPAP17Hap3 was detected for the selective breeding of P efficiency in oilseed rape. Over-expression of the BnPAP17Hap3 could promote the shoot and root growth with enhanced tolerance to low P stress and organic phosphorus (Po) utilization in oilseed rape. Collectively, these findings increase our understanding of the mechanisms underlying BnPAP17-mediated low P stress tolerance in oilseed rape.

First genome-wide association study for lymphatic filariasis in a West African population points to a human leukocyte antigen-mediated disease pathophysiology

ObjectivesLymphatic filariasis (LF) represents a parasitic disease caused by filarial nematodes. Although some infected individuals present an asymptomatic course, others suffer severe chronic lymphatic pathology, including lymphedema, hydrocele, and elephantiasis. Several studies have shown that host genetic factors influence LF susceptibility and chronic pathology. The current study aimed to conduct the first genome-wide association study to systematically determine LF susceptibility. MethodsWe analyzed genome-wide single-nucleotide polymorphism data from 1459 LF cases and 1492 asymptomatic controls of West African (Ghanaian) descent. ResultsWe identified two independent genome-wide significant associated genetic variants near the genes HLA-DQB2 (rs7742085) and HLA-DQA1 (rs4959107) contributing to LF and/or lymphedema susceptibility (P <5.0 × 10−8, odds ratios [ORs] >1.30). We also observed suggestive evidence of LF associations (P <1.0 × 10−6) at two non-HLA loci, near the genes ZFHX4-AS1 (rs79562145) and CHP2 (rs12933387). In contrast, we could not replicate any previously reported LF associations drawn from candidate gene association studies. On the polygenic level, we show that our genome-wide association study data explain 24-42% of LF heritability, depending on an assumed population prevalence of 0.5-5.0%. ConclusionOur findings point to an involvement of HLA-mediated immune mechanisms in LF pathophysiology.

The construction and analysis of wax gourd pangenome uncover fruit quality-related and resistance genes

Large-scale resequencing studies in wax gourd have generated a large data resource and mined many selection signals and candidate genes. In this study, we constructed the first pangenome of wax gourd based on resequencing data and obtained 316 Mb novel contigs containing 996 novel genes. A pan-genome-wide gene present/absent variations analysis of 25,188 genes identified 2154 genes as variable genes. Analysis of gene present/absent variations selection between wild accessions, landraces, and cultivar accessions revealed that many genes, including resistance genes, were lost during the process of domestication and improvement. The 22 resistance gene analogs identified in non-reference contigs are complementary to the 642 resistance gene analogs on the reference genome. Genome-wide association studies of gene present/absent variations with fruit weight, fruit length, fruit diameter, and fruit thickness of wax gourd identified five phenotypic-related candidate genes. Pan-genome-wide identification of NAC, WRKY and HSF gene family identified 7 novel genes. In conclusion, this study provides a more complete sequence and genes of the wax gourd genome and identifies new selected genes as well as phenotypically related candidate genes through a series of analyses, as well as provides an abundant resource and research reference for breeding and gene function studies in the wax gourd.

The Identification of a Yield-Related Gene Controlling Multiple Traits Using GWAS in Sorghum (Sorghum bicolor L.).

Sorghum bicolor (L.) is one of the oldest crops cultivated by human beings which has been used in food and wine making. To understand the genetic diversity of sorghum breeding resources and further guide molecular-marker-assisted breeding, six yield-related traits were analyzed for 214 sorghum germplasm from all over the world, and 2,811,016 single-nucleotide polymorphisms (SNPs) markers were produced by resequencing these germplasms. After controlling Q and K, QTLs were found to be related to the traits using three algorisms. Interestingly, an important QTL was found which may affect multiple traits in this study. It was the most likely candidate gene for the gene SORBI_3008G116500, which was a homolog of Arabidopsis thaliana gene-VIP5 found by analyzing the annotation of the gene in the LD block. The haplotype analysis showed that the SORBI_3008G116500hap3 was the elite haplotype, and it only existed in Chinese germplasms. The traits were proven to be more associated with the SNPs of the SORBI_3008G116500 promoter through gene association studies. Overall, the QTLs and the genes identified in this study would benefit molecular-assisted yield breeding in sorghum.

Adaptively Integrative Association between Multivariate Phenotypes and Transcriptomic Data for Complex Diseases.

Phenotype-gene association studies can uncover disease mechanisms for translational research. Association with multiple phenotypes or clinical variables in complex diseases has the advantage of increasing statistical power and offering a holistic view. Existing multi-variate association methods mostly focus on SNP-based genetic associations. In this paper, we extend and evaluate two adaptive Fisher's methods, namely AFp and AFz, from the p-value combination perspective for phenotype-mRNA association analysis. The proposed method effectively aggregates heterogeneous phenotype-gene effects, allows association with different data types of phenotypes, and performs the selection of the associated phenotypes. Variability indices of the phenotype-gene effect selection are calculated by bootstrap analysis, and the resulting co-membership matrix identifies gene modules clustered by phenotype-gene effect. Extensive simulations demonstrate the superior performance of AFp compared to existing methods in terms of type I error control, statistical power and biological interpretation. Finally, the method is separately applied to three sets of transcriptomic and clinical datasets from lung disease, breast cancer, and brain aging and generates intriguing biological findings.

Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes.

Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26-30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done.

GENETIC DISSIMILARITY IN JABUTICABA (Plinia peruviana (poir.) govaerts) IN NORTH OF STATE ESPÍRITO SANTO, BRAZIL

Jabuticaba (Plinia peruviana (Poir.) Govaerts) is a plant rich in compounds that are very useful in industry. Its fruits are the basis for a range of food and pharmaceutical products. Due to the great potential of this species, information about genetic structure of these plants allows us to understand factors linked to quality, in addition to guiding crosses to improve this species for commercial purposes. Thus, we sought to understand the pattern of genetic diversity of jabuticaba found in the northern region of Espírito Santo State, Brazil, using ISSR markers. The results of the dissimilarity values, obtained by the Jaccard index, grouped the 19 accessions studied into five groups. The pair of accessions 10 and 19 showed the highest dissimilarity value, being indicated in crosses aiming at increasing heterozygosity. Accessions 16 and 18 had a lower dissimilarity value, being promising in introgression and gene association studies, due to the narrow genetic basis between the materials. Accessions 1, 4, 12, and 15 are the most divergent and can be indicated for random artificial crossings.