Analysis of the porcine APOA2 gene expression in liver,polymorphism identification and association with fatty acid composition traits

APOA2 is a protein implicated in triglyceride, fatty acid and glucose metabolism. In pigs, the APOA2 gene is located on pig chromosome 4 (SSC4) in a QTL region affecting fatty acid composition, fatness and growth traits. In this study, we evaluated APOA2 as a candidate gene for meat quality traits in an Iberian × Landrace backcross population. The APOA2:c.131T>A polymorphism, located in exon 3 of APOA2 and determining a missense mutation, was associated with the percentage of hexadecenoic acid [C16:1(n–9)], linoleic acid [C18:2(n–6)], α‐linolenic acid [C18:3(n–3)], dihomo‐gamma‐linolenic acid [C20:3(n–6)] and polyunsaturated fatty acids (PUFAs) in backfat. Furthermore, this SNP was associated with the global mRNA expression levels of APOA2 in liver and was used as a marker to determine allelic expression imbalance by pyrosequencing. We determined an overexpression of the T allele in heterozygous samples with a mean ratio of 2.8 (T/A), observing a high variability in the allelic expression among individuals. This result suggests that complex regulatory mechanisms, beyond a single polymorphism (e.g. epigenetic effects or multiple cis‐acting polymorphisms), may be regulating APOA2 gene expression.     

Large-scale profiling and identification of potential regulatory mechanisms for allelic gene expression in colorectal cancer cells

Allelic variation in gene expression is common in humans and this variation is associated with phenotypic variation. In this study, we employed high-density single nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs to identify genes with allelic gene expression in cells from colorectal cancer cell lines. We found 2 monoallelically expressed genes (ERAP2 and MYLK4), 32 genes with an allelic imbalance in their expression, and 13 genes showing allele substitution by RNA editing. Among a total of 34 allelically expressed genes in colorectal cancer cells, 15 genes (44.1%) were associated with cis-acting eQTL, indicating that large portions of allelically expressed genes are regulated by cis-acting mechanisms of gene expression. In addition, potential regulatory variants present in the proximal promoter regions of genes showing either monoallelic expression or allelic imbalance were not tightly linked with coding SNPs, which were detected with allelic gene expression. These results suggest that multiple rare variants could be involved in the cis-acting regulatory mechanism of allelic gene expression. In the comparison with allelic gene expression data from Centre d'Etude du Polymorphisme Humain (CEPH) family B cells, 12 genes showed B-cell specific allelic imbalance and 1 noncoding SNP showed colorectal cancer cell-specific allelic imbalance. In addition, different patterns of allele substitution were observed between B cells and colorectal cancer cells. Overall, our study not only indicates that allelic gene expression is common in colorectal cancer cells, but our study also provides a better understanding of allele-specific gene expression in colorectal cancer cells.     

Monozygotic twins reveal germline contribution to allelic expression differences

Variation in the level of gene expression is a major determinant of a cell's function and characteristics. Common allelic variants of genes can be expressed at different levels and thus contribute to phenotypic diversity. We have measured allelic expression differences at heterozygous loci in monozygotic twins and in unrelated individuals. We show that the extent of differential allelic expression is highly similar within monozygotic twin pairs for many loci, implying that allelic differences in gene expression are under genetic control. We also show that even subtle departures from equal allelic expression are often genetically determined.     

The impact of cis-acting polymorphisms on the human phenotype

Cis-acting polymorphisms that affect gene expression are now known to be frequent, although the extent and mechanisms by which such variation affects the human phenotype are, as yet, only poorly understood. Key signatures of cis-acting variation are differences in gene expression that are tightly associated with regulatory SNPs or expression Quantitative Trait Loci (eQTL) and an imbalance of allelic expression (AEI) in heterozygous samples. Such cis-acting sequence differences appear often to have been under selection within and between populations and are also thought to be important in speciation. Here we describe the example of lactase persistence. In medical research, variants that affect regulation in cis have been implicated in both monogenic and polygenic disorders, and in the metabolism of drugs. In this review we suggest that by further understanding common regulatory variations and how they interact with other genetic and environmental variables it will be possible to gain insight into important mechanisms behind complex disease, with the potential to lead to new methods of diagnosis and treatments.     

Allelic imbalance metre (Allim), a new tool for measuring allele‐specific gene expression with RNA‐seq data

Estimating differences in gene expression among alleles is of high interest for many areas in biology and medicine. Here, we present a user‐friendly software tool, Allim, to estimate allele‐specific gene expression. Because mapping bias is a major problem for reliable estimates of allele‐specific gene expression using RNA‐seq, Allim combines two different strategies to account for the mapping biases. In order to reduce the mapping bias, Allim first generates a polymorphism‐aware reference genome that accounts for the sequence variation between the alleles. Then, a sequence‐specific simulation tool estimates the residual mapping bias. Statistical tests for allelic imbalance are provided that can be used with the bias corrected RNA‐seq data.     

Erasure and reestablishment of random allelic expression imbalance after epigenetic reprogramming

Clonal level random allelic expression imbalance and random monoallelic expression provides cellular heterogeneity within tissues by modulating allelic dosage. Although such expression patterns have been observed in multiple cell types, little is known about when in development these stochastic allelic choices are made. We examine allelic expression patterns in human neural progenitor cells before and after epigenetic reprogramming to induced pluripotency, observing that loci previously characterized by random allelic expression imbalance (0.63% of expressed genes) are generally reset to a biallelic state in induced pluripotent stem cells (iPSCs). We subsequently neuralized the iPSCs and profiled isolated clonal neural stem cells, observing that significant random allelic expression imbalance is reestablished at 0.65% of expressed genes, including novel loci not found to show allelic expression imbalance in the original parental neural progenitor cells. Allelic expression imbalance was associated with altered DNA methylation across promoter regulatory regions, with clones characterized by skewed allelic expression being hypermethylated compared to their biallelic sister clones. Our results suggest that random allelic expression imbalance is established during lineage commitment and is associated with increased DNA methylation at the gene promoter.     

Differential allelic expression in the human genome: a robust approach to identify genetic and epigenetic cis-acting mechanisms regulating gene expression

The recent development of whole genome association studies has lead to the robust identification of several loci involved in different common human diseases. Interestingly, some of the strongest signals of association observed in these studies arise from non-coding regions located in very large introns or far away from any annotated genes, raising the possibility that these regions are involved in the etiology of the disease through some unidentified regulatory mechanisms. These findings highlight the importance of better understanding the mechanisms leading to inter-individual differences in gene expression in humans. Most of the existing approaches developed to identify common regulatory polymorphisms are based on linkage/association mapping of gene expression to genotypes. However, these methods have some limitations, notably their cost and the requirement of extensive genotyping information from all the individuals studied which limits their applications to a specific cohort or tissue. Here we describe a robust and high-throughput method to directly measure differences in allelic expression for a large number of genes using the Illumina Allele-Specific Expression BeadArray platform and quantitative sequencing of RT-PCR products. We show that this approach allows reliable identification of differences in the relative expression of the two alleles larger than 1.5-fold (i.e., deviations of the allelic ratio larger than 6040) and offers several advantages over the mapping of total gene expression, particularly for studying humans or outbred populations. Our analysis of more than 80 individuals for 2,968 SNPs located in 1,380 genes confirms that differential allelic expression is a widespread phenomenon affecting the expression of 20% of human genes and shows that our method successfully captures expression differences resulting from both genetic and epigenetic cis-acting mechanisms.     

Effects of 5' regulatory-region polymorphisms on paraoxonase-gene (PON1) expression

Human HDL-associated paraoxonase (PON1) hydrolyzes a number of toxic organophosphorous compounds and reduces oxidation of LDLs and HDLs. These properties of PON1 account for its ability to protect against pesticide poisonings and atherosclerosis. PON1 also hydrolyzes a number of lactone and cyclic-carbonate drugs. Among individuals in a population, PON1 levels vary widely. We previously identified three polymorphisms in the PON1 regulatory region that affect expression levels in cultured human hepatocytes. In this study, we determined the genotypes of three regulatory-region polymorphisms for 376 white individuals and examined their effect on plasma-PON1 levels, determined by rates of phenylacetate hydrolysis. The -108 polymorphism had a significant effect on PON1-activity level, whereas the -162 polymorphism had a lesser effect. The -909 polymorphism, which is in linkage disequilibrium with the other sites, appears to have little or no independent effect on PON1-activity level in vivo. Other studies have found that the L55M polymorphism in the PON1-coding region is associated with differences in both PON1-mRNA and PON1-activity levels. The results presented here indicate that the L55M effect of lowered activity is not due to the amino acid change but is, rather, largely due to linkage disequilibrium with the -108 regulatory-region polymorphism. The codon 55 polymorphism marginally appeared to account for 15.3% of the variance in PON1 activity, but this dropped to 5% after adjustments for the effects of the -108 and Q192R polymorphisms were made. The -108C/T polymorphism accounted for 22.8% of the observed variability in PON1-expression levels, which was much greater than that attributable to the other PON1 polymorphisms. We also identified four sequence differences in the 3' UTR of the PON1 mRNA.     

AllelicImbalance: an R/ bioconductor package for detecting,managing, and visualizing allele expression imbalance data from RNA sequencing

Background

One aspect in which RNA sequencing is more valuable than microarray-based methods is the ability to examine the allelic imbalance of the expression of a gene. This process is often a complex task that entails quality control, alignment, and the counting of reads over heterozygous single-nucleotide polymorphisms. Allelic imbalance analysis is subject to technical biases, due to differences in the sequences of the measured alleles. Flexible bioinformatics tools are needed to ease the workflow while retaining as much RNA sequencing information as possible throughout the analysis to detect and address the possible biases.

Results

We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons.

Conclusions

The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization, within the robust and versatile management class, ASEset.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0620-2) contains supplementary material, which is available to authorized users.     

Parent-of-origin effects on mRNA expression in Drosophila melanogaster not caused by genomic imprinting

Parent-of-origin effects create differences in gene expression among genetically identical individuals. Using measurements of allele-specific expression, we demonstrate that previously reported parent-of-origin effects on standing mRNA levels in Drosophila melanogaster are not attributable to genomic imprinting. Offspring from reciprocal crosses exhibit differences in total expression without differences in allelic expression, indicating that other types of maternal and/or paternal effects alter expression.     

Genotype of an individual single nucleotide polymorphism regulates DNA methylation at the TRPC3 alternative promoter

A fundamental challenge in the post-genomics era is to understand how genetic variants can influence phenotypic variability and disease. Recent observations from a number of studies have highlighted a mechanism by which common genetic polymorphisms can influence DNA methylation, a major epigenetic silencing mechanism. We report that the alternative promoter of the human TRPC3 gene is regulated by allelic DNA methylation, dictated by the genotype of a single base pair polymorphism, rs13121031 located within the promoter CpG island. The common G allele is associated with high levels of methylation, while the less prevalent C allele is unmethylated. This methylation profile is observed in many tissue types, despite the expression of?TRPC3?being restricted to brain and heart.?TRPC3?is prominently expressed in the hindbrain, and a heterozygous brain sample showed modest skewing according to the allelic methylation, with preferential expression from the C allele. The?TRPC3?gene encodes a transient receptor potential channel that has been implicated in cerebellar ataxia and heart hypertrophy. The genotype-frequencies of rs13121031 were determined in cohorts of ataxia patients and in individuals with cardiac hypertrophy. These analyses revealed a statistical trend for the rare unmethylated homozygous C genotype to be present at a higher frequency in idiopathic ataxia patients (Fisher's test p=0.06), but not in those patients with known mutations (Fisher's test p=0.55) or in individuals with heart disease (Fisher's test p=0.807), when compared to a control population. Our results suggest that the?TRPC3?alternative promoter is a methylation quantitative-trait locus that may be involved in modulating the ataxia phenotype.     

Allelic gene expression imbalance of bovine IGF2, LEP and CCL2 genes in liver, kidney and pituitary

Allelic expression imbalance (AEI) is an important genetic factor being the cause of differences in phenotypic traits that can be heritable. Studying AEI can be useful in searching for factors that modulate gene expression and help to understand molecular mechanisms underlying phenotypic changes. Although it was commonly recognized in many species and we know many genes show allelic expression imbalance, this phenomena was not studied on a larger scale in cattle. Using the pyrosequencing method we analyzed a set of 29 bovine genes in order to find those that have preferential allelic expression. The study was conducted in three tissues: liver, pituitary and kindey. Out of the studied group of genes 3 of them—LEP (leptin), IGF2 (insulin-like growth factor 2), CCL2 (chemokine C–C motif ligand 2) showed allelic expression imbalance.     

Polygenic evolution drives species divergence and climate adaptation in corals

Closely related species often show substantial differences in ecological traits that allow them to occupy different environmental niches. For few of these systems is it clear what the genomic basis of adaptation is and whether a few loci of major effect or many genome‐wide differences drive species divergence. Four cryptic species of the tabletop coral Acropora hyacinthus are broadly sympatric in American Samoa; here we show that two common species have differences in key environmental traits such as microhabitat distributions and thermal stress tolerance. We compared gene expression patterns and genetic polymorphism between these two species using RNA‐Seq. The vast majority of polymorphisms are shared between species, but the two species show widespread differences in allele frequencies and gene expression, and tend to host different symbiont types. We find that changes in gene expression are related to changes in the frequencies of many gene regulatory variants, but that many of these differences are consistent with the action of genetic drift. However, we observe greater genetic divergence between species in amino acid replacement polymorphisms compared to synonymous variants. These findings suggest that polygenic evolution plays a major role in driving species differences in ecology and resilience to climate change.