Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion.

Background: Technological advances involving RNA-Seq and Bioinformatics allow quantifying the transcriptional levels of genes in cells, tissues, and cell lines, permitting the identification of Differentially Expressed Genes (DEGs). DESeq2 and edgeR are well-established computational tools used for this purpose and they are based upon generalized linear models (GLMs) that consider only fixed effects in modeling. However, the inclusion of random effects reduces the risk of missing potential DEGs that may be essential in the context of the biological phenomenon under investigation. The generalized linear mixed models (GLMM) can be used to include both effects. Methods: We present DEGRE (Differentially Expressed Genes with Random Effects), a user-friendly tool capable of inferring DEGs where fixed and random effects on individuals are considered in the experimental design of RNA-Seq research. DEGRE preprocesses the raw matrices before fitting GLMMs on the genes and the derived regression coefficients are analyzed using the Wald statistical test. DEGRE offers the Benjamini-Hochberg or Bonferroni techniques for P-value adjustment. Results: The datasets used for DEGRE assessment were simulated with known identification of DEGs. These have fixed effects, and the random effects were estimated and inserted to measure the impact of experimental designs with high biological variability. For DEGs' inference, preprocessing effectively prepares the data and retains overdispersed genes. The biological coefficient of variation is inferred from the counting matrices to assess variability before and after the preprocessing. The DEGRE is computationally validated through its performance by the simulation of counting matrices, which have biological variability related to fixed and random effects. DEGRE also provides improved assessment measures for detecting DEGs in cases with higher biological variability. We show that the preprocessing established here effectively removes technical variation from those matrices. This tool also detects new potential candidate DEGs in the transcriptome data of patients with bipolar disorder, presenting a promising tool to detect more relevant genes. Conclusions: DEGRE provides data preprocessing and applies GLMMs for DEGs' inference. The preprocessing allows efficient remotion of genes that could impact the inference. Also, the computational and biological validation of DEGRE has shown to be promising in identifying possible DEGs in experiments derived from complex experimental designs. This tool may help handle random effects on individuals in the inference of DEGs and presents a potential for discovering new interesting DEGs for further biological investigation.

Pervasive Inter-Individual Variation in Allele-Specific Expression in Monozygotic Twins.

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.

Maternal 5mCpG Imprints at the PARD6G-AS1 and GCSAML Differentially Methylated Regions Are Decoupled From Parent-of-Origin Expression Effects in Multiple Human Tissues.

A hallmark of imprinted genes in mammals is the occurrence of parent-of-origin-dependent asymmetry of DNA cytosine methylation (5mC) of alleles at CpG islands (CGIs) in their promoter regions. This 5mCpG asymmetry between the parental alleles creates allele-specific imprinted differentially methylated regions (iDMRs). iDMRs are often coupled to the transcriptional repression of the methylated allele and the activation of the unmethylated allele in a tissue-specific, developmental-stage-specific and/or isoform-specific fashion. iDMRs function as regulatory platforms, built through the recruitment of chemical modifications to histones to achieve differential, parent-of-origin-dependent chromatin segmentation states. Here, we used a comparative computational data mining approach to identify 125 novel constitutive candidate iDMRs that integrate the maximal number of allele-specific methylation region records overlapping CGIs in human methylomes. Twenty-nine candidate iDMRs display gametic 5mCpG asymmetry, and another 96 are candidate secondary iDMRs. We established the maternal origin of the 5mCpG imprints of one gametic (PARD6G-AS1) and one secondary (GCSAML) iDMRs. We also found a constitutively hemimethylated, nonimprinted domain at the PWWP2AP1 promoter CGI with oocyte-derived methylation asymmetry. Given that the 5mCpG level at the iDMRs is not a sufficient criterion to predict active or silent locus states and that iDMRs can regulate genes from a distance of more than 1 Mb, we used RNA-Seq experiments from the Genotype-Tissue Expression project and public archives to assess the transcriptional expression profiles of SNPs across 4.6 Mb spans around the novel maternal iDMRs. We showed that PARD6G-AS1 and GCSAML are expressed biallelically in multiple tissues. We found evidence of tissue-specific monoallelic expression of ZNF124 and OR2L13, located 363 kb upstream and 419 kb downstream, respectively, of the GCSAML iDMR. We hypothesize that the GCSAML iDMR regulates the tissue-specific, monoallelic expression of ZNF124 but not of OR2L13. We annotated the non-coding epigenomic marks in the two maternal iDMRs using data from the Roadmap Epigenomics project and showed that the PARD6G-AS1 and GCSAML iDMRs achieve contrasting activation and repression chromatin segmentations. Lastly, we found that the maternal 5mCpG imprints are perturbed in several hematopoietic cancers. We conclude that the maternal 5mCpG imprints at PARD6G-AS1 and GCSAML iDMRs are decoupled from parent-of-origin transcriptional expression effects in multiple tissues.

Trisomy 21 Alters DNA Methylation in Parent-of-Origin-Dependent and -Independent Manners.

The supernumerary chromosome 21 in Down syndrome differentially affects the methylation statuses at CpG dinucleotide sites and creates genome-wide transcriptional dysregulation of parental alleles, ultimately causing diverse pathologies. At present, it is unknown whether those effects are dependent or independent of the parental origin of the nondisjoined chromosome 21. Linkage analysis is a standard method for the determination of the parental origin of this aneuploidy, although it is inadequate in cases with deficiency of samples from the progenitors. Here, we assessed the reliability of the epigenetic 5mCpG imprints resulting in the maternally (oocyte)-derived allele methylation at a differentially methylated region (DMR) of the candidate imprinted WRB gene for asserting the parental origin of chromosome 21. We developed a methylation-sensitive restriction enzyme-specific PCR assay, based on the WRB DMR, across single nucleotide polymorphisms (SNPs) to examine the methylation statuses in the parental alleles. In genomic DNA from blood cells of either disomic or trisomic subjects, the maternal alleles were consistently methylated, while the paternal alleles were unmethylated. However, the supernumerary chromosome 21 did alter the methylation patterns at the RUNX1 (chromosome 21) and TMEM131 (chromosome 2) CpG sites in a parent-of-origin-independent manner. To evaluate the 5mCpG imprints, we conducted a computational comparative epigenomic analysis of transcriptome RNA sequencing (RNA-Seq) and histone modification expression patterns. We found allele fractions consistent with the transcriptional biallelic expression of WRB and ten neighboring genes, despite the similarities in the confluence of both a 17-histone modification activation backbone module and a 5-histone modification repressive module between the WRB DMR and the DMRs of six imprinted genes. We concluded that the maternally inherited 5mCpG imprints at the WRB DMR are uncoupled from the parental allele expression of WRB and ten neighboring genes in several tissues and that trisomy 21 alters DNA methylation in parent-of-origin-dependent and -independent manners.