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A comprehensive hybridization model allows whole HERV transcriptome profiling using high density microarray

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The recent sequencing of model organisms unveiled the large proportion of repetitive elements (REs) in many species. In human, it is estimated that half of the genome is populated by REs and that retrovirus-like sequences amount for 8% of its coverage [1]. HERVs and MaLRs elements are organized into multi-copy families, for each of which, tens to thousands of distinct loci are scattered throughout the human genome, representing a pool of approximately 200,000 individual HERV loci. While bioinformatics approaches identified 103 HERV families and 1 MaLR family [1], only 40 HERV families were characterized in wet-lab studies [24]. Part of this genomic heritage is thought to originate from ancestral and independent retroviral infections within the germ line, before reinfection, retro-transposition and error-prone amplification steps during the evolution, leading to the formation of multi-copy families [5]. To date, no infectious endogenous virus has been detected in human, however 30% of the whole retrovirome is estimated to have a transcriptional activity [6]. Multiple functions have been assigned to these elements: HERVs have been demonstrated to act as canonical and alternative transcription start sites [7] (up to 30% of human and mouse TSSs are located in REs [8]), transcription termination sites [9] as well as splice donor and splice acceptor sites [10]. REs have further been suggested to be instrumental in the long intergenic non-coding RNA (lincRNA) regulatory system, where a majority of lincRNAs have been found to contain REs [11]. HERVs are increasingly associated with distinct physiological and pathological processes. One notable example is provided by the two syncytins genes that have been co-opted in human (and other mammals) to mediate placentation [12]. More recently, HERV-H loci have been shown to be instrumental in the maintenance of pluripotency [13]. Other investigations have further described associations between HERVs reactivation and multiple sclerosis [1416], solid [17, 18] and hematological [19] tumors. Taken together, these studies show that REs provide binding sites for mammalian TFs and that they have rewired a number of developmental regulatory networks.

The central issue in the study of the HERV transcriptome arises from the phylogenetic proximity among the elements of a given HERV family, making the measure of each transcript technically challenging. Initially, RT-PCR techniques combined with degenerate primers [20] and low-density microarrays [18, 21] were developed to measure trends within families without, however, providing locus-specific information. Expressed sequence tags (ESTs) approaches gave a more comprehensive view of the HERV transcriptome but failed in many instances to identify the exact genomic source of expression [22]. Recent initiatives took advantage of probes targeting repetitive elements in commercial microarrays to monitor HERV behavior where, in addition to restricting their analysis to a small number of probes, the specificity of the probes was not evaluated [23]. More recently, HERVs transcription was also measured in various contexts using next generation sequencing (NGS) [24], which, while promising, remains difficult due to the ambiguity in assigning short reads mapping to more than one genomic location. For instance, in a study of HML-2 elements in teratocarcinoma cell line, Bhardwaj et al. showed that 47% of their reads had multiple alignments [25]. Two elegant initiatives sought to address this limitation by either using host surrounding sequences to anchor HERV copies [26] or by assigning multi-mapping reads probabilistically to specific locus based on the local genomic tag context [27]. However, in addition to assume that HERVs flanking regions are expressed, these approaches can probably not resolve multi-mapped reads for more than few hundred bases at the edges of HERV copies, leaving the ambiguity unchanged in the central regions.

Because HERV expression is globally low [28], very deep sequencing is required to capture the diversity of HERV transcripts among the many other and more abundant human transcripts, making unbiased NGS experiments costly and ineffective in this context. Targeted sequencing could alternatively be considered to reduce the experimental burden by specifically amplifying the transcripts of interest, as is typically applied in 16S metagenomic sequencing. This type of approach could either be performed at the family or locus level. The design of family-specific degenerate primers or locus-specific primers would however require an elaborate step of primer selection ensuring both family/locus specificity (as illustrated in Pichon et al. for PCR amplification of the Pol region [18]) and compatible annealing temperature for unbiased quantification. To our knowledge, no such systematic targeted sequencing approach has been proposed so far. The work presented in this study applies such methodology on microarray using a probe selection pipeline that aims to both maximize probe efficiency and mitigate non-specific reactions, minimizing thus the analysis step for the end-user. Microarrays platforms and in particular Affymetrix instruments are now deployed in many research laboratories and the cost per experiment makes microarrays affordable compared to NGS, with a reduced time-to-result.

Two custom microarrays were previously designed in the laboratory based on a unicity criterion and a specificity score. The first meant that only candidate probes with a single perfect match were selected [29], whereas the second estimated a cross-hybridization risk using the nature and position of mispairing (mismatches, MMs and gaps) in probe-target hybrids [13]. Training sets consisting of PM and MM probes were introduced on both arrays to evaluate and refine these strategies of cross-hybridization control. Both platforms allowed the identification of cancer-specific loci (testis [29], prostate [13, 30], colon [13] subsequently validated by qRT-PCR on a large cohort [31]) and the assignment of LTR functions [13, 29], but did not prevent cross-reactions to occur, raising the need for an improved approach.

Building on these two experiences and leveraging the high-density Affymetrix format (5 micron feature size), we introduce here a new platform HERV-V3 which, like the previous versions, aims at measuring HERVs at the locus level. The two main improvements lie in the almost complete coverage of HERVs and their ancestors as well as the introduction of a specificity criterion based on a new hybridization model, named hereafter, the Pentamer rEgion-dependent Hybridization Model (PEHM). The aim of this model is to predict the affinity of any probe-target hybrid, and therefore, to evaluate the potential of cross-hybridization by determining whether a probe of interest hybridizes only with its target. Along HERVs elements, five additional repertoires were introduced on HERV-V3 that fall in three categories, repetitive elements (MaLRs and active LINE-1 elements), non-repetitive elements (lncRNA and a selection of 1559 human genes) and common infectious viruses. While the array design is primarily aimed at identifying HERVs and MaLRs implicated in physiological and pathological processes, broader applications can be envisioned with these repertoires, such as the detection of virus replication along with the monitoring of HERVs/MaLRs and genes modulation. In the following, we successively (i) describe the main steps of the array design, (ii) compare our probesets with those of Affymetrix on 1559 common genes according to the MAQC criteria and (iii) demonstrate that for a selection of loci characterized as tissue/pathology specific, the pattern of expression observed on HERV-V3 is consistent, illustrating the relevance of such platform as research tool.

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