RESUMO
Despite being developed from one zygote, heterokaryotypic monozygotic (MZ) co-twins exhibit discordant karyotypes. Epigenomic studies in biological samples from heterokaryotypic MZ co-twins are of the most significant value for assessing the effects on gene- and allele-specific expression of an extranumerary chromosomal copy or structural chromosomal disparities in otherwise nearly identical germline genetic contributions. Here, we use RNA-Seq data from existing repositories to establish within-pair correlations for the breadth and magnitude of allele-specific expression (ASE) in heterokaryotypic MZ co-twins discordant for trisomy 21 and maternal 21q inheritance, as well as homokaryotypic co-twins. We show that there is a genome-wide disparity at ASE sites between the heterokaryotypic MZ co-twins. Although most of the disparity corresponds to changes in the magnitude of biallelic imbalance, ASE sites switching from either strictly monoallelic to biallelic imbalance or the reverse occur in few genes that are known or predicted to be imprinted, subject to X-chromosome inactivation or A-to-I(G) RNA edited. We also uncovered comparable ASE differences between homokaryotypic MZ twins. The extent of ASE discordance in MZ twins (2.7%) was about 10-fold lower than the expected between pairs of unrelated, non-twin males or females. The results indicate that the observed within-pair dissimilarities in breadth and magnitude of ASE sites in the heterokaryotypic MZ co-twins could not solely be attributable to the aneuploidy and the missing allelic heritability at 21q.
RESUMO
Diploid organisms have two copies of each gene, called alleles, that can be separately transcribed. The RNA abundance associated to any particular allele is known as allele-specific expression (ASE). When two alleles have polymorphisms in transcribed regions, ASE can be studied using RNA-seq read count data. ASE has characteristics different from the regular RNA-seq expression: ASE cannot be assessed for every gene, measures of ASE can be biased towards one of the alleles (reference allele), and ASE provides two measures of expression for a single gene for each biological samples with leads to additional complications for single-gene models. We present statistical methods for modeling ASE and detecting genes with differential allelic expression. We propose a hierarchical, overdispersed, count regression model to deal with ASE counts. The model accommodates gene-specific overdispersion, has an internal measure of the reference allele bias, and uses random effects to model the gene-specific regression parameters. Fully Bayesian inference is obtained using the fbseq package that implements a parallel strategy to make the computational times reasonable. Simulation and real data analysis suggest the proposed model is a practical and powerful tool for the study of differential ASE.
Assuntos
Teorema de Bayes , RNA-Seq , Zea mays/genética , Algoritmos , Alelos , Gráficos por Computador , Simulação por Computador , Biblioteca Gênica , Heterozigoto , Cadeias de Markov , Modelos Estatísticos , Método de Monte Carlo , RNA de Plantas/genética , Curva ROC , Análise de Regressão , Software , Zea mays/fisiologiaRESUMO
Cardiovascular disease (CVD) is a broad definition for diseases of the heart and blood vessels with high mortality and morbidity worldwide. Atherosclerosis and hypertension are the most common causes of CVD, and multiple factors confer the susceptibility. Some of the predisposing factors are modifiable such as diet, smoking, and exercise, whereas others, including age, sex, and individual's genetic variations contributing to the CVD composition traits, are non-modifiable. This latter group includes serum lipid traits. High serum lipid levels, specifically high levels of serum low-density lipoprotein cholesterol and triglycerides, are well-established key risk factors of atherosclerosis. This review will discuss genomics and systems biology approaches in the study of common dyslipidemias. The non-Mendelian forms of dyslipidemias are highly complex, and the molecular mechanisms underlying these polygenic lipid disorders are estimated to involve hundreds of genes. Interactions between the different genes and environmental factors also contribute to the clinical outcomes; however, very little is known about these interactions and their molecular mechanisms. To better address the complex genetic architecture and multiple properties leading to high serum lipid levels, networks and systems approach combining information at genomic, transcriptomics, methylomics, proteomics, metabolomics, and phenome level are being developed, with the ultimate goal to elucidate the cascade of dynamic changes leading to CVD in humans. (REV INVEST CLIN. 2018;70:217-23).
Assuntos
Dislipidemias/terapia , Genômica/métodos , Biologia de Sistemas/métodos , Aterosclerose/complicações , Doenças Cardiovasculares/etiologia , Doenças Cardiovasculares/prevenção & controle , Dislipidemias/complicações , Humanos , Hipertensão/complicações , Lipídeos/sangue , Fatores de RiscoRESUMO
BACKGROUND: Gene regulatory variation has been proposed to play an important role in the adaptation of plants to environmental stress. In the central highlands of Mexico, farmer selection has generated a unique group of maize landraces adapted to the challenges of the highland niche. In this study, gene expression in Mexican highland maize and a reference maize breeding line were compared to identify evidence of regulatory variation in stress-related genes. It was hypothesised that local adaptation in Mexican highland maize would be associated with a transcriptional signature observable even under benign conditions. METHODS: Allele specific expression analysis was performed using the seedling-leaf transcriptome of an F1 individual generated from the cross between the highland adapted Mexican landrace Palomero Toluqueño and the reference line B73, grown under benign conditions. Results were compared with a published dataset describing the transcriptional response of B73 seedlings to cold, heat, salt and UV treatments. RESULTS: A total of 2,386 genes were identified to show allele specific expression. Of these, 277 showed an expression difference between Palomero Toluqueño and B73 alleles under benign conditions that anticipated the response of B73 cold, heat, salt and/or UV treatments, and, as such, were considered to display a prior stress response. Prior stress response candidates included genes associated with plant hormone signaling and a number of transcription factors. Construction of a gene co-expression network revealed further signaling and stress-related genes to be among the potential targets of the transcription factors candidates. DISCUSSION: Prior activation of responses may represent the best strategy when stresses are severe but predictable. Expression differences observed here between Palomero Toluqueño and B73 alleles indicate the presence of cis-acting regulatory variation linked to stress-related genes in Palomero Toluqueño. Considered alongside gene annotation and population data, allele specific expression analysis of plants grown under benign conditions provides an attractive strategy to identify functional variation potentially linked to local adaptation.