Advances in the identification and analysis of allele-specific expression

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Near-gapless genome and transcriptome analyses provide insights into fruiting body development in Lentinula edodes

Fruiting body development in macrofungi is an intensive research subject. In this study, high-quality genomes were assembled for two sexually compatible monokaryons from a heterokaryotic Lentinula edodes strain WX1, and variations in L. edodes genomes were analyzed. Specifically, differential gene expression and allele-specific expression (ASE) were analyzed using the two monokaryotic genomes and transcriptome data from four different stages of fruiting body development in WX1. Results revealed that after aeration, mycelia sensed cell wall stress, pheromones, and a decrease in CO2 concentration, leading to up-regulated expression in genes related to cell adhesion, cell wall remodeling, proteolysis, and lipid metabolism, which may promote primordium differentiation. Aquaporin genes and those related to proteolysis, mitosis, lipid, and carbohydrate metabolism may play important roles in primordium development, while genes related to tissue differentiation and sexual reproduction were active in fruiting body. Several essential genes for fruiting body development were allele-specifically expressed and the two nuclear types could synergistically regulate fruiting body development by dominantly expressing genes with different functions. ASE was probably induced by long terminal repeat-retrotransposons. Findings here contribute to the further understanding of the mechanism of fruiting body development in macrofungi.

DNA methylation entropy as a measure of stem cell replication and aging

BACKGROUND

Epigenetic marks are encoded by DNA methylation and accumulate errors as organisms age. This drift correlates with lifespan, but the biology of how this occurs is still unexplained. We analyze DNA methylation with age in mouse intestinal stem cells and compare them to nonstem cells.

RESULTS

Age-related changes in DNA methylation are identical in stem and nonstem cells, affect most prominently CpG islands and correlate weakly with gene expression. Age-related DNA methylation entropy, measured by the Jensen-Shannon Distribution, affects up to 25% of the detectable CpG sites and is a better measure of aging than individual CpG methylation. We analyze this entropy as a function of age in seven other tissues (heart, kidney, skeletal muscle, lung, liver, spleen, and blood) and it correlates strikingly with tissue-specific stem cell division rates. Thus, DNA methylation drift and increased entropy with age are primarily caused by and are sensors for, stem cell replication in adult tissues.

CONCLUSIONS

These data have implications for the mechanisms of tissue-specific functional declines with aging and for the development of DNA-methylation-based biological clocks.

Miniature inverted repeat transposable elements cis-regulate circular RNA expression and promote ethylene biosynthesis, reducing heat tolerance in Populus tomentosa

Transposable elements (TEs) and their reverse complementary sequence pairs (RCPs) are enriched around loci that produce circular RNAs (circRNAs) in plants. However, the function of these TE-RCP pairs in modulating circRNA expression remains elusive. Here, we identified 4609 circRNAs in poplar (Populus tomentosa) and showed that miniature inverted repeat transposable elements (MITEs)-RCPs were enriched in circRNA flanking regions. Moreover, we used expression quantitative trait nucleotide (eQTN) mapping to decipher the cis-regulatory role of MITEs. eQTN results showed that 14 single-nucleotide polymorphisms (SNPs) were significantly associated with Circ_0000408 and Circ_0003418 levels and the lead associated SNPs were located in MITE-RCP regions, indicating that MITE-RCP sequence variations affect exon circularization. Overexpression and knockdown analysis showed that Circ_0003418 positively modulated its parental gene, which encodes the RING-type E3 ligase XBAT32, and specifically increased the expression of the PtoXBAT32.5 transcript variant, which lacks the E3 ubiquitin ligase domain. Under heat stress, PtoXBAT32.5 expression was induced with up-regulation of Circ_0003418, resulting in increased production of ethylene and peroxidation of membrane lipids. Our findings thus reveal the cis-regulatory mechanism by which a MITE-RCP pair affects circRNA abundance in poplar and indicate that Circ_0003418 is a negative regulator of poplar heat tolerance via the ubiquitin-mediated protein modification pathway.

aScan: A Novel Method for the Study of Allele Specific Expression in Single Individuals

In diploid organisms, two copies of each allele are normally inherited from parents. Paternal and maternal alleles can be regulated and expressed unequally, which is referred to as allele-specific expression (ASE). In this work, we present aScan, a novel method for the identification of ASE from the analysis of matched individual genomic and RNA sequencing data. By performing extensive analyses of both real and simulated data, we demonstrate that aScan can correctly identify ASE with high accuracy and sensitivity in different experimental settings. Additionally, by applying our method to a small cohort of individuals that are not included in publicly available databases of human genetic variation, we outline the value of possible applications of ASE analysis in single individuals for deriving a more accurate annotation of "private" low-frequency genetic variants associated with regulatory effects on transcription. All in all, we believe that aScan will represent a beneficial addition to the set of bioinformatics tools for the analysis of ASE. Finally, while our method was initially conceived for the analysis of RNA-seq data, it can in principle be applied to any quantitative NGS assay for which matched genotypic and expression data are available. AVAILABILITY: aScan is currently available in the form of an open source standalone software package at: https://github.com/Federico77z/aScan/. aScan version 1.0.3, available at https://github.com/Federico77z/aScan/releases/tag/1.0.3, has been used for all the analyses included in this manuscript. A Docker image of the tool has also been made available at https://github.com/pmandreoli/aScanDocker.

Allele-specific expression of Parkinson's disease susceptibility genes in human brain

Genome-wide association studies have identified genetic variation in genomic loci associated with susceptibility to Parkinson’s disease (PD), the most common neurodegenerative movement disorder worldwide. We used allelic expression profiling of genes located within PD-associated loci to identify cis-regulatory variation affecting gene expression. DNA and RNA were extracted from post-mortem superior frontal gyrus tissue and whole blood samples from PD patients and controls. The relative allelic expression of transcribed SNPs in 12 GWAS risk genes was analysed by real-time qPCR. Allele-specific expression was identified for 9 out of 12 genes tested (GBA, TMEM175, RAB7L1, NUCKS1, MCCC1, BCKDK, ZNF646, LZTS3, and WDHD1) in brain tissue samples. Three genes (GPNMB, STK39 and SIPA1L2) did not show significant allele-specific effects. Allele-specific effects were confirmed in whole blood for three genes (BCKDK, LZTS3 and MCCC1), whereas two genes (RAB7L1 and NUCKS1) showed brain-specific allelic expression. Our study supports the hypothesis that changes to the cis-regulation of gene expression is a major mechanism behind a large proportion of genetic associations in PD. Interestingly, allele-specific expression was also observed for coding variants believed to be causal variants (GBA and TMEM175), indicating that splicing and other regulatory mechanisms may be involved in disease development.

Allele-Specific Expression of CD4+ T Cells in Response to Marek's Disease Virus Infection

Marek's disease (MD) is a T cell lymphoma disease induced by Marek's disease virus (MDV), a highly oncogenic α herpesvirus primarily affecting chickens. MD is a chronic infectious disease that threatens the poultry industry. However, the mechanisms of genetic resistance for MD are complex and not completely understood. In this study, to identify high-confidence candidate genes of MD genetic resistance, high throughput sequencing (RNA-seq) was used to obtain transcriptomic data of CD4+ T cells isolated from MDV-infected and non-infected groups of two reciprocal crosses of individuals mating by two highly inbred chicken lines (63 MD-resistant and 72 MD-susceptible). After RNA-seq analysis with two biological replicates in each group, we identified 61 and 123 single nucleotide polymorphisms (SNPs) (false discovery rate (FDR) < 0.05) annotated in 39 and 132 genes in intercrosses 63 × 72 and 72 × 63, respectively, which exhibited allele-specific expression (ASE) in response to MDV infection. Similarly, we identified 62 and 79 SNPs annotated in 66 and 96 genes in infected and non-infected groups, respectively. We identified 534 and 1543 differentially expressed genes (DEGs) (FDR < 0.05) related to MDV infection in intercrosses 63 × 72 and 72 × 63, respectively. We also identified 328 and 20 DEGs in infected and non-infected groups, respectively. The qRT-PCR using seven DEGs further verified our results of RNA-seq analysis. The qRT-PCR of 11 important ASE genes was performed for gene functional validation in CD4+ T cells and tumors. Combining the analyses, six genes (MCL1, SLC43A2, PDE3B, ADAM33, BLB1, and DMB2), especially MCL1, were highlighted as the candidate genes with the potential to be involved in MDV infection. Gene-set enrichment analysis revealed that many ASE genes are linked to T cell activation, T cell receptor (TCR), B cell receptor (BCR), ERK/MAPK, and PI3K/AKT-mTOR signaling pathways, which play potentially important roles in MDV infection. Our approach underlines the importance of comprehensive functional studies for gaining valuable biological insight into the genetic factors behind MD and other complex traits, and our findings provide additional insights into the mechanisms of MD and disease resistance breeding in poultry.

Osmotic stress-responsive promoter upstream transcripts (PROMPTs) act as carriers of MYB transcription factors to induce the expression of target genes in Populus simonii

Complex RNA transcription and processing produces a diverse range catalog of long noncoding RNAs (lncRNAs), important biological regulators that have been implicated in osmotic stress responses in plants. Promoter upstream transcript (PROMPT) lncRNAs share some regulatory elements with the promoters of their neighbouring protein-coding genes. However, their function remains unknown. Here, using strand-specific RNA sequencing, we identified 209 differentially regulated osmotic-responsive PROMPTs in poplar (Populus simonii). PROMPTs are transcribed bidirectionally and are more stable than other lncRNAs. Co-expression analysis of PROMPTs and protein-coding genes divided the regulatory network into five independent subnetworks including 27 network modules. Significantly enriched PROMPTs in the network were selected to validate their regulatory roles. We used delaminated layered double hydroxide lactate nanosheets (LDH-lactate-NS) to transport synthetic nucleic acids into live tissues to mimic overexpression and interference of a specific PROMPT. The altered expression of PROMPT_1281 induced the expression of its cis and trans targets, and this interaction was governed by its secondary structure rather than just its primary sequence. Based on this example, we proposed a model that a concentration gradient of PROMPT_1281 is established, which increases the probability of its interaction with targets near its transcription site that shares common motifs. Our results firstly demonstrated that PROMPT_1281 act as carriers of MYB transcription factors to induce the expression of target genes under osmotic stress. In sum, our study identified and validated a set of poplar PROMPTs that likely have regulatory functions in osmotic responses.

Investigation of allele-specific expression of genes involved in adipogenesis and lipid metabolism suggests complex regulatory mechanisms of PPARGC1A expression in porcine fat tissues

Background

The expression of genes involved in regulating adipogenesis and lipid metabolism may affect economically important fatness traits in pigs. Allele-specific expression (ASE) reflects imbalance between allelic transcript levels and can be used to identify underlying cis-regulatory elements. ASE has not yet been intensively studied in pigs. The aim of this investigation was to analyze the differential allelic expression of four genes, PPARA, PPARG, SREBF1, and PPARGC1A, which are involved in the regulation of fat deposition in porcine subcutaneous and visceral fat and longissimus dorsi muscle.

Results

Quantification of allelic proportions by pyrosequencing revealed that both alleles of PPARG and SREBF1 are expressed at similar levels. PPARGC1A showed the greatest ASE imbalance in fat deposits in Polish Large White (PLW), Polish Landrace and Pietrain pigs; and PPARA in PLW pigs. Significant deviations of mean PPARGC1A allelic transcript ratio between cDNA and genomic DNA were detected in all tissues, with the most pronounced difference (p < 0.001) in visceral fat of PLW pigs. To search for potential cis-regulatory elements affecting ASE in the PPARGC1A gene we analyzed the effects of four SNPs (rs337351686, rs340650517, rs336405906 and rs345224049) in the promoter region, but none were associated with ASE in the breeds studied. DNA methylation analysis revealed significant CpG methylation differences between samples showing balanced (allelic transcript ratio ≈1) and imbalanced allelic expression for CpG site at the genomic position in chromosome 8 (SSC8): 18527678 in visceral fat (p = 0.017) and two CpG sites (SSC8:18525215, p = 0.030; SSC8:18525237, p = 0.031) in subcutaneous fat.

Conclusions

Our analysis of differential allelic expression suggests that PPARGC1A is subjected to cis-regulation in porcine fat tissues. Further studies are necessary to identify other regulatory elements localized outside the PPARGC1A proximal promoter region.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0696-6) contains supplementary material, which is available to authorized users.

Identification of SNPs potentially related to immune responses and growth performance in Litopenaeus vannamei by RNA-seq analyses

Litopenaeus vannamei is one of the most important shrimp species for worldwide aquaculture. Despite this, little genomic information is available for this penaeid and other closely related taxonomic crustaceans. Consequently, genes, proteins and their respective polymorphisms are poorly known for these species. In this work, we used the RNA sequencing technology (RNA-seq) in L. vannamei shrimp evaluated for growth performance, and exposed to the White Spot Syndrome Virus (WSSV), in order to investigate the presence of Single Nucleotide Polymorphisms (SNPs) within genes related to innate immunity and growth, both features of great interest for aquaculture activity. We analyzed individuals with higher and lower growth rates; and infected (unhealthy) and non-infected (healthy), after exposure to WSSV. Approximately 7,000 SNPs were detected in the samples evaluated for growth, being 3,186 and 3,978 exclusive for individuals with higher and lower growth rates, respectively. In the animals exposed to WSSV we found about 16,300 unique SNPs, in which 9,338 were specific to non-infected shrimp, and 7,008 were exclusive to individuals infected with WSSV and symptomatic. In total, we describe 4,312 unigenes containing SNPs. About 60% of these unigenes returned GO blastX hits for Biological Process, Molecular Function and Cellular Component ontologies. We identified 512 KEGG unique KOs distributed among 275 pathways, elucidating the majority of metabolism roles related to high protein metabolism, growth and immunity. These polymorphisms are all located in coding regions, and certainly can be applied in further studies involving phenotype expression of complex traits, such as growth and immunity. Overall, the set of variants raised herein enriches the genomic databases available for shrimp, given that SNPs originated from nextgen are still rare for this relevant crustacean group, despite their huge potential of use in genomic selection approaches.

SCALE: modeling allele-specific gene expression by single-cell RNA sequencing

Allele-specific expression is traditionally studied by bulk RNA sequencing, which measures average expression across cells. Single-cell RNA sequencing allows the comparison of expression distribution between the two alleles of a diploid organism and the characterization of allele-specific bursting. Here, we propose SCALE to analyze genome-wide allele-specific bursting, with adjustment of technical variability. SCALE detects genes exhibiting allelic differences in bursting parameters and genes whose alleles burst non-independently. We apply SCALE to mouse blastocyst and human fibroblast cells and find that cis control in gene expression overwhelmingly manifests as differences in burst frequency.

Analysis of Allelic Imbalance in Rice Hybrids Under Water Stress and Association of Asymmetrically Expressed Genes with Drought-Response QTLs

BACKGROUND

Information on the effect of stress on the allele-specific expression (ASE) profile of rice hybrids is limited. More so, the association of allelically imbalanced genes to important traits is yet to be understood. Here we assessed allelic imbalance (AI) in the heterozygote state of rice under non- and water-stress treatments and determined association of asymmetrically expressed genes with grain yield (GY) under drought stress by in-silico co-localization analysis and selective genotyping. The genotypes IR64, Apo and their F1 hybrid (IR64 × Apo) were grown under normal and water-limiting conditions. We sequenced the total RNA transcripts for all genotypes then reconstructed the two chromosomes in the heterozygote.

RESULTS

We are able to estimate the transcript abundance of and the differential expression (DE) between the two parent-specific alleles in the rice hybrids. The magnitude and direction of AI are classified into two categories: (1) symmetrical or biallelic and (2) asymmetrical. The latter can be further classified as either IR64- or Apo-favoring gene. Analysis showed that in the hybrids grown under non-stress conditions, 179 and 183 favor Apo- and IR64-specific alleles, respectively. Hence, the number of IR64- and Apo-favoring genes is relatively equal. Under water-stress conditions, 179 and 255 favor Apo- and IR64-specific alleles, respectively, indicating that the number of allelically imbalanced genes is skewed towards IR64. This is nearly 40-60 % preference for Apo and IR64 alleles, respectively, to the hybrid transcriptome. We also observed genes which exhibit allele preference switching when exposed to water-stress conditions. Results of in-silico co-localization procedure and selective genotyping of Apo/IR64 F3:5 progenies revealed significant association of several asymmetrically expressed genes with GY under drought stress conditions.

CONCLUSION

Our data suggest that water stress skews AI on a genome-wide scale towards the IR64 allele, the cross-specific maternal allele. Several asymmetrically expressed genes are strongly associated with GY under drought stress which may shed hints that genes associated with important traits are allelically imbalanced. Our approach of integrating hybrid expression analysis and QTL mapping analysis may be an efficient strategy for shortlisting candidate genes for gene discovery.

Discovering Single Nucleotide Polymorphisms Regulating Human Gene Expression Using Allele Specific Expression from RNA-seq Data

The study of the genetics of gene expression is of considerable importance to understanding the nature of common, complex diseases. The most widely applied approach to identifying relationships between genetic variation and gene expression is the expression quantitative trait loci (eQTL) approach. Here, we increased the computational power of eQTL with an alternative and complementary approach based on analyzing allele specific expression (ASE). We designed a novel analytical method to identify cis-acting regulatory variants based on genome sequencing and measurements of ASE from RNA-sequencing (RNA-seq) data. We evaluated the power and resolution of our method using simulated data. We then applied the method to map regulatory variants affecting gene expression in lymphoblastoid cell lines (LCLs) from 77 unrelated northern and western European individuals (CEU), which were part of the HapMap project. A total of 2309 SNPs were identified as being associated with ASE patterns. The SNPs associated with ASE were enriched within promoter regions and were significantly more likely to signal strong evidence for a regulatory role. Finally, among the candidate regulatory SNPs, we identified 108 SNPs that were previously associated with human immune diseases. With further improvements in quantifying ASE from RNA-seq, the application of our method to other datasets is expected to accelerate our understanding of the biological basis of common diseases.

Allele-specific expression of mutated in colorectal cancer (MCC) gene and alternative susceptibility to colorectal cancer in schizophrenia

Evidence has indicated that the incidence of colorectal cancer (CRC) among schizophrenia is lower than normal. To explore this potential protective effect, we employed an innovative strategy combining association study with allele-specific expression (ASE) analysis in MCC gene. We first genotyped four polymorphisms within MCC in 312 CRC patients, 270 schizophrenia patients and 270 controls. Using the MassArray technique, we performed ASE measurements in a second sample series consisting of 50 sporadic CRC patients, 50 schizophrenia patients and 52 controls. Rs2227947 showed significant differences between schizophrenia cases and controls, and haplotype analysis reported some significant discrepancies among these three subject groups. ASE values of rs2227948 and rs2227947 presented consistently differences between CRC (or schizophrenia) patients and controls. Of the three groups, highest frequencies of ASE in MCC were concordantly found in CRC group, whereas lowest frequencies of ASE were observed in schizophrenia group. Similar trends were confirmed in both haplotype frequencies and ASE frequencies (i.e. CRC > control > schizophrenia). We provide a first indication that MCC might confer alterative genetic susceptibility to CRC in individuals with schizophrenia promising to shed more light on the relationship between schizophrenia and cancer progression.

Comparing computational methods for identification of allele-specific expression based on next generation sequencing data

Allele-specific expression (ASE) studies have wide-ranging implications for genome biology and medicine. Whole transcriptome RNA sequencing (RNA-Seq) has emerged as a genome-wide tool for identifying ASE, but suffers from mapping bias favoring reference alleles. Two categories of methods are adopted nowadays, to reduce the effect of mapping bias on ASE identification-normalizing RNA allelic ratio with the parallel genomic allelic ratio (pDNAar) and modifying reference genome to make reads carrying both alleles with the same chance to be mapped (mREF). We compared the sensitivity and specificity of both methods with simulated data, and demonstrated that the pDNAar, though ideally practical, was lower in sensitivity, because of its lower mapping rate of reads carrying nonreference (alternative) alleles, although mREF achieved higher sensitivity and specificity for its efficiency in mapping reads carrying both alleles. Application of these two methods in real sequencing data showed that mREF were able to identify more ASE loci because of its higher mapping efficiency, and able to correcting some seemly incorrect ASE loci identified by pDNAar due to the inefficiency in mapping reads carrying alternative alleles of pDNAar. Our study provides useful information for RNA sequencing data processing in the identification of ASE.

RNA-seq as a powerful tool for penaeid shrimp genetic progress

The sequences of all different RNA transcripts present in a cell or tissue that are related to the gene expression and its functional control represent what it is called a transcriptome. The transcripts vary between cells, tissues, ontogenetic and environmental conditions, and the knowledge that can be gained through them is of a solid relevance for genetic applications in aquaculture. Some of the techniques used in transcriptome studies, such as microarrays, are being replaced for next-generation sequencing approaches. RNA-seq emerges as a new possibility for the transcriptome complexity analysis as well as for the candidate genes and polymorphisms identification of penaeid species. Thus, it may also help to understand the determination of complex traits mechanisms and genetic improvement of stocks. In this review, it is first introduced an overview of transcriptome analysis by RNA-seq, followed by a discussion of how this approach may be applied in genetic progress within penaeid stocks.

Comparative analysis of response to selection with three insecticides in the dengue mosquito Aedes aegypti using mRNA sequencing

Background

Mosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance. Such resistance can be the consequence of changes in proteins targeted by insecticides (target site mediated resistance), increased insecticide biodegradation (metabolic resistance), altered transport, sequestration or other mechanisms. As opposed to target site resistance, other mechanisms are far from being fully understood. Indeed, insecticide selection often affects a large number of genes and various biological processes can hypothetically confer resistance. In this context, the aim of the present study was to use RNA sequencing (RNA-seq) for comparing transcription level and polymorphism variations associated with adaptation to chemical insecticides in the mosquito Aedes aegypti. Biological materials consisted of a parental susceptible strain together with three child strains selected across multiple generations with three insecticides from different classes: the pyrethroid permethrin, the neonicotinoid imidacloprid and the carbamate propoxur.

Results

After ten generations, insecticide-selected strains showed elevated resistance levels to the insecticides used for selection. RNA-seq data allowed detecting over 13,000 transcripts, of which 413 were differentially transcribed in insecticide-selected strains as compared to the susceptible strain. Among them, a significant enrichment of transcripts encoding cuticle proteins, transporters and enzymes was observed. Polymorphism analysis revealed over 2500 SNPs showing > 50% allele frequency variations in insecticide-selected strains as compared to the susceptible strain, affecting over 1000 transcripts. Comparing gene transcription and polymorphism patterns revealed marked differences among strains. While imidacloprid selection was linked to the over transcription of many genes, permethrin selection was rather linked to polymorphism variations. Focusing on detoxification enzymes revealed that permethrin selection strongly affected the polymorphism of several transcripts encoding cytochrome P450 monooxygenases likely involved in insecticide biodegradation.

Conclusions

The present study confirmed the power of RNA-seq for identifying concomitantly quantitative and qualitative transcriptome changes associated with insecticide resistance in mosquitoes. Our results suggest that transcriptome modifications can be selected rapidly by insecticides and affect multiple biological functions. Previously neglected by molecular screenings, polymorphism variations of detoxification enzymes may play an important role in the adaptive response of mosquitoes to insecticides.

RNA-Seq technology and its application in fish transcriptomics

High-throughput sequencing technologies, also known as next-generation sequencing (NGS) technologies, have revolutionized the way that genomic research is advancing. In addition to the static genome, these state-of-art technologies have been recently exploited to analyze the dynamic transcriptome, and the resulting technology is termed RNA sequencing (RNA-seq). RNA-seq is free from many limitations of other transcriptomic approaches, such as microarray and tag-based sequencing method. Although RNA-seq has only been available for a short time, studies using this method have completely changed our perspective of the breadth and depth of eukaryotic transcriptomes. In terms of the transcriptomics of teleost fishes, both model and non-model species have benefited from the RNA-seq approach and have undergone tremendous advances in the past several years. RNA-seq has helped not only in mapping and annotating fish transcriptome but also in our understanding of many biological processes in fish, such as development, adaptive evolution, host immune response, and stress response. In this review, we first provide an overview of each step of RNA-seq from library construction to the bioinformatic analysis of the data. We then summarize and discuss the recent biological insights obtained from the RNA-seq studies in a variety of fish species.

Bulk segregant RNA-seq reveals expression and positional candidate genes and allele-specific expression for disease resistance against enteric septicemia of catfish

Background

The application of RNA-seq has accelerated gene expression profiling and identification of gene-associated SNPs in many species. However, the integrated studies of gene expression along with SNP mapping have been lacking. Coupling of RNA-seq with bulked segregant analysis (BSA) should allow correlation of expression patterns and associated SNPs with the phenotypes.

Results

In this study, we demonstrated the use of bulked segregant RNA-seq (BSR-Seq) for the analysis of differentially expressed genes and associated SNPs with disease resistance against enteric septicemia of catfish (ESC). A total of 1,255 differentially expressed genes were found between resistant and susceptible fish. In addition, 56,419 SNPs residing on 4,304 unique genes were identified as significant SNPs between susceptible and resistant fish. Detailed analysis of these significant SNPs allowed differentiation of significant SNPs caused by genetic segregation and those caused by allele-specific expression. Mapping of the significant SNPs, along with analysis of differentially expressed genes, allowed identification of candidate genes underlining disease resistance against ESC disease.

Conclusions

This study demonstrated the use of BSR-Seq for the identification of genes involved in disease resistance against ESC through expression profiling and mapping of significantly associated SNPs. BSR-Seq is applicable to analysis of genes underlining various performance and production traits without significant investment in the development of large genotyping platforms such as SNP arrays.

iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets

BACKGROUND

ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles.

RESULTS

We develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately.

CONCLUSIONS

iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB.

Increased risk of lung cancer associated with a functionally impaired polymorphic variant of the human DNA glycosylase NEIL2

Human NEIL2, one of five oxidized base-specific DNA glycosylases, is unique in preferentially repairing oxidative damage in transcribed genes. Here we show that depletion of NEIL2 causes a 6-7-fold increase in spontaneous mutation frequency in the HPRT gene of the V79 Chinese hamster lung cell line. This prompted us to screen for NEIL2 variants in lung cancer patients' genomic DNA. We identified several polymorphic variants, among which R103Q and R257L were frequently observed in lung cancer patients. We then characterized these variants biochemically, and observed a modest decrease in DNA glycosylase activity relative to the wild type (WT) only with the R257L mutant protein. However, in reconstituted repair assays containing WT NEIL2 or its R257L and R103Q variants together with other DNA base excision repair (BER) proteins (PNKP, Polβ, Lig IIIα and XRCC1) or using NEIL2-FLAG immunocomplexes, an ~5-fold decrease in repair was observed with the R257L variant compared to WT or R103Q NEIL2, apparently due to the R257L mutant's lower affinity for other repair proteins, particularly Polβ. Notably, increased endogenous DNA damage was observed in NEIL2 variant (R257L)-expressing cells relative to WT cells. Taken together, our results suggest that the decreased DNA repair capacity of the R257L variant can induce mutations that lead to lung cancer development.

A putative "hepitype" in the ATM gene associated with chronic lymphocytic leukemia risk

Chronic lymphocytic leukemia (CLL) cells are characterized by several chromosomal lesions. Some of these aberrations imply chromosome breaks as a result of unrepaired double strand breaks (DSBs) in the DNA. The ATM (ataxia telangiectasia-mutated) protein is the principal integrator of cellular responses to DSBs. ATM deletion is also an adverse prognostic factor in CLL. Taking this into account, we evaluated if genetic and/or epigenetic variation in the ATM gene may modulate the individual susceptibility to develop CLL. Our case-control association study was performed in a large Spanish population of 1,503 individuals, including 742 patients with CLL and 761 controls. We identified one haplotype within the ATM gene that confers an increased risk of CLL development (OR = 1.33; 95% CI: 1.10-1.60). Two polymorphisms of this ATM haplotype eliminated one CpG site each in Introns 15 and 61, causing changes in DNA methylation pattern. These data provide the first evidence for the existence of a putative "hepitype" in the ATM gene associated with CLL risk.

Pipeline for large-scale microdroplet bisulfite PCR-based sequencing allows the tracking of hepitype evolution in tumors

Cytosine methylation provides an epigenetic level of cellular plasticity that is important for development, differentiation and cancerogenesis. We adopted microdroplet PCR to bisulfite treated target DNA in combination with second generation sequencing to simultaneously assess DNA sequence and methylation. We show measurement of methylation status in a wide range of target sequences (total 34 kb) with an average coverage of 95% (median 100%) and good correlation to the opposite strand (rho = 0.96) and to pyrosequencing (rho = 0.87). Data from lymphoma and colorectal cancer samples for SNRPN (imprinted gene), FGF6 (demethylated in the cancer samples) and HS3ST2 (methylated in the cancer samples) serve as a proof of principle showing the integration of SNP data and phased DNA-methylation information into “hepitypes” and thus the analysis of DNA methylation phylogeny in the somatic evolution of cancer.

Integration of genomic and epigenomic DNA methylation data in common complex diseases by haplotype-specific methylation analysis

The analysis of complex diseases was revolutionized by the ability to genotype at a genome-wide level tagging common SNPs in sufficiently large, and therefore adequately powered, population sample sets. This technological breakthrough has led to thousands of genetic variants being robustly associated with a multitude of phenotypic traits. These findings have illuminated novel genes and previously unknown pathways in the pathogenesis of disease, although in the majority of loci the functional mechanism remains unknown. The integration of this genomic information with epigenomic and transcriptomic data from these regions is one of the next steps in unraveling their biological significance. Allele-specific methylation influences allele-specific expression; therefore, the methylation state of the haplotypes within genetically associated regions can determine epigenetic differences with potential functional effects. DNA methylation data and association-determined risk and nonrisk haplotypes can be compared by a haplotype-specific methylation analysis. These are the first forays into what will become an increasingly routine multidimensional analysis as whole-genome, epigenome and transcriptome sequencing data become easily obtainable, with existing second- and soon to be available third-generation sequencing analyzers. Concise understanding of the functional implications of these genome-wide association-derived risk factors, plus rare variants discovered from deep sequencing experiments currently underway, will enable personalized risk and prevention profiling, as well as treatment, to come to fruition.

The DNA methylome of human peripheral blood mononuclear cells

Analysis across the genome of patterns of DNA methylation reveals a rich landscape of allele-specific epigenetic modification and consequent effects on allele-specific gene expression.

DNA methylation plays an important role in biological processes in human health and disease. Recent technological advances allow unbiased whole-genome DNA methylation (methylome) analysis to be carried out on human cells. Using whole-genome bisulfite sequencing at 24.7-fold coverage (12.3-fold per strand), we report a comprehensive (92.62%) methylome and analysis of the unique sequences in human peripheral blood mononuclear cells (PBMC) from the same Asian individual whose genome was deciphered in the YH project. PBMC constitute an important source for clinical blood tests world-wide. We found that 68.4% of CpG sites and <0.2% of non-CpG sites were methylated, demonstrating that non-CpG cytosine methylation is minor in human PBMC. Analysis of the PBMC methylome revealed a rich epigenomic landscape for 20 distinct genomic features, including regulatory, protein-coding, non-coding, RNA-coding, and repeat sequences. Integration of our methylome data with the YH genome sequence enabled a first comprehensive assessment of allele-specific methylation (ASM) between the two haploid methylomes of any individual and allowed the identification of 599 haploid differentially methylated regions (hDMRs) covering 287 genes. Of these, 76 genes had hDMRs within 2 kb of their transcriptional start sites of which >80% displayed allele-specific expression (ASE). These data demonstrate that ASM is a recurrent phenomenon and is highly correlated with ASE in human PBMCs. Together with recently reported similar studies, our study provides a comprehensive resource for future epigenomic research and confirms new sequencing technology as a paradigm for large-scale epigenomics studies.

Epigenetic modifications such as addition of methyl groups to cytosine in DNA play a role in regulating gene expression. To better understand these processes, knowledge of the methylation status of all cytosine bases in the genome (the methylome) is required. DNA methylation can differ between the two gene copies (alleles) in each cell. Such allele-specific methylation (ASM) can be due to parental origin of the alleles (imprinting), X chromosome inactivation in females, and other as yet unknown mechanisms. This may significantly alter the expression profile arising from different allele combinations in different individuals. Using advanced sequencing technology, we have determined the methylome of human peripheral blood mononuclear cells (PBMC). Importantly, the PBMC were obtained from the same male Han Chinese individual whose complete genome had previously been determined. This allowed us, for the first time, to study genome-wide differences in ASM. Our analysis shows that ASM in PBMC is higher than can be accounted for by regions known to undergo parent-of-origin imprinting and frequently (>80%) correlates with allele-specific expression (ASE) of the corresponding gene. In addition, our data reveal a rich landscape of epigenomic variation for 20 genomic features, including regulatory, coding, and non-coding sequences, and provide a valuable resource for future studies. Our work further establishes whole-genome sequencing as an efficient method for methylome analysis.

The epigenomic interface between genome and environment in common complex diseases

The epigenome plays the pivotal role as interface between genome and environment. True genome-wide assessments of epigenetic marks, such as DNA methylation (methylomes) or chromatin modifications (chromatinomes), are now possible, either through high-throughput arrays or increasingly by second-generation DNA sequencing methods. The ability to collect these data at this level of resolution enables us to begin to be able to propose detailed questions, and interrogate this information, with regards to changes that occur due to development, lineage and tissue-specificity, and significantly those caused by environmental influence, such as ageing, stress, diet, hormones or toxins. Common complex traits are under variable levels of genetic influence and additionally epigenetic effect. The detection of pathological epigenetic alterations will reveal additional insights into their aetiology and how possible environmental modulation of this mechanism may occur. Due to the reversibility of these marks, the potential for sequence-specific targeted therapeutics exists. This review surveys recent epigenomic advances and their current and prospective application to the study of common diseases.