Donald Sharon

Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

A single-molecule long-read survey of the human transcriptome

Global RNA studies have become central to understanding biological processes, but methods such as microarrays and short-read sequencing are unable to describe an entire RNA molecule from 5′ to 3′ end. Here we use single-molecule long-read sequencing technology from Pacific Biosciences to sequence the polyadenylated RNA complement of a pooled set of 20 human organs and tissues without the need for fragmentation or amplification. We show that full-length RNA molecules of up to 1.5 kb can readily be monitored with little sequence loss at the 5′ ends. For longer RNA molecules more 5′ nucleotides are missing, but complete intron structures are often preserved. In total, we identify ∼14,000 spliced GENCODE genes. High-confidence mappings are consistent with GENCODE annotations, but >10% of the alignments represent intron structures that were not previously annotated. As a group, transcripts mapping to unannotated regions have features of long, noncoding RNAs. Our results show the feasibility of deep sequencing full-length RNA from complex eukaryotic transcriptomes on a single-molecule level.

Defining a personal, allele-specific, and single-molecule long-read transcriptome

Significance RNA molecules of higher eukaryotes can be thousands of nucleotides long and are expressed from two distinct alleles, which can differ by single nucleotide variations (SNVs) in the mature RNA molecule. The de facto standard in RNA biology is short (≤101 bp) read sequencing, which, although very useful, does not cover the entire molecule in a read. We show that using amplification-free long-read sequencing one can often (i) cover the entire molecule, (ii) determine the allele it originated from, and (iii) record its entire exon-intron structure within a single read, thus producing a full-length, allele-specific view of an individual’s transcriptome. By enhancing existing gene annotations using long reads and quantifying this enhanced annotation using >100 million 101-bp paired-end reads, we overcome the smaller number of long reads. Personal transcriptomes in which all of an individual’s genetic variants (e.g., single nucleotide variants) and transcript isoforms (transcription start sites, splice sites, and polyA sites) are defined and quantified for full-length transcripts are expected to be important for understanding individual biology and disease, but have not been described previously. To obtain such transcriptomes, we sequenced the lymphoblastoid transcriptomes of three family members (GM12878 and the parents GM12891 and GM12892) by using a Pacific Biosciences long-read approach complemented with Illumina 101-bp sequencing and made the following observations. First, we found that reads representing all splice sites of a transcript are evident for most sufficiently expressed genes ≤3 kb and often for genes longer than that. Second, we added and quantified previously unidentified splicing isoforms to an existing annotation, thus creating the first personalized annotation to our knowledge. Third, we determined SNVs in a de novo manner and connected them to RNA haplotypes, including HLA haplotypes, thereby assigning single full-length RNA molecules to their transcribed allele, and demonstrated Mendelian inheritance of RNA molecules. Fourth, we show how RNA molecules can be linked to personal variants on a one-by-one basis, which allows us to assess differential allelic expression (DAE) and differential allelic isoforms (DAI) from the phased full-length isoform reads. The DAI method is largely independent of the distance between exon and SNV—in contrast to fragmentation-based methods. Overall, in addition to improving eukaryotic transcriptome annotation, these results describe, to our knowledge, the first large-scale and full-length personal transcriptome.

Diverse protein kinase interactions identified by protein microarrays reveal novel connections between cellular processes

Protein kinases are key regulators of cellular processes. In spite of considerable effort, a full understanding of the pathways they participate in remains elusive. We globally investigated the proteins that interact with the majority of yeast protein kinases using protein microarrays. Eighty-five kinases were purified and used to probe yeast proteome microarrays. One-thousand-twenty-three interactions were identified, and the vast majority were novel. Coimmunoprecipitation experiments indicate that many of these interactions occurred in vivo. Many novel links of kinases to previously distinct cellular pathways were discovered. For example, the well-studied Kss1 filamentous pathway was found to bind components of diverse cellular pathways, such as those of the stress response pathway and the Ccr4-Not transcriptional/translational regulatory complex; genetic tests revealed that these different components operate in the filamentation pathway in vivo. Overall, our results indicate that kinases operate in a highly interconnected network that coordinates many activities of the proteome. Our results further demonstrate that protein microarrays uncover a diverse set of interactions not observed previously.

Systems biology approaches to disease marker discovery.

Our understanding of human disease and potential therapeutics is improving rapidly. In order to take advantage of these developments it is important to be able to identify disease markers. Many new high-throughput genomics and proteomics technologies are being implemented to identify candidate disease markers. These technologies include protein microarrays, next-generation DNA sequencing and mass spectrometry platforms. Such methods are particularly important for elucidating the repertoire of molecular markers in the genome, transcriptome, proteome and metabolome of patients with diseases such as cancer, autoimmune diseases, and viral infections, resulting from the disruption of many biological pathways. These new technologies have identified many potential disease markers. These markers are expected to be valuable to achieve the promise of truly personalized medicine.

Full-length isoform sequencing reveals novel transcripts and substantial transcriptional overlaps in a herpesvirus

Whole transcriptome studies have become essential for understanding the complexity of genetic regulation. However, the conventionally applied short-read sequencing platforms cannot be used to reliably distinguish between many transcript isoforms. The Pacific Biosciences (PacBio) RS II platform is capable of reading long nucleic acid stretches in a single sequencing run. The pseudorabies virus (PRV) is an excellent system to study herpesvirus gene expression and potential interactions between the transcriptional units. In this work, non-amplified and amplified isoform sequencing protocols were used to characterize the poly(A+) fraction of the lytic transcriptome of PRV, with the aim of a complete transcriptional annotation of the viral genes. The analyses revealed a previously unrecognized complexity of the PRV transcriptome including the discovery of novel protein-coding and non-coding genes, novel mono- and polycistronic transcription units, as well as extensive transcriptional overlaps between neighboring and distal genes. This study identified non-coding transcripts overlapping all three replication origins of the PRV, which might play a role in the control of DNA synthesis. We additionally established the relative expression levels of gene products. Our investigations revealed that the whole PRV genome is utilized for transcription, including both DNA strands in all coding and intergenic regions. The genome-wide occurrence of transcript overlaps suggests a crosstalk between genes through a network formed by interacting transcriptional machineries with a potential function in the control of gene expression.

Transglutaminase 4 as a prostate autoantigen in male subfertility

TGM4 is a male-specific autoantigen for prostatitis associated with autoimmune polyendocrine syndrome type 1. AIREing out autoimmunity Patients with autoimmune polyendocrine syndrome type 1(APS1) experience dysfunction in multiple endocrine glands due to mutations in the AIRE gene, which helps promote immune tolerance. These patients frequently are infertile; female infertility can be explained by autoimmune ovarian failure, but the causes of male infertility have remained unclear. Now, Landegren et al. report that the prostatic secretory molecule tranglutaminase 4 (TGM4) is a male-specific autoantigen in APS1 patients that could contribute to subfertility. They found autoantibodies to TGM4 in APS1 patients beginning at puberty, and confirmed in AIRE-deficient mice that TGM4 autoantibodies lead to a destructive prostatitis. These data could help explain infertility in male APS1 patients. Autoimmune polyendocrine syndrome type 1 (APS1), a monogenic disorder caused by AIRE gene mutations, features multiple autoimmune disease components. Infertility is common in both males and females with APS1. Although female infertility can be explained by autoimmune ovarian failure, the mechanisms underlying male infertility have remained poorly understood. We performed a proteome-wide autoantibody screen in APS1 patient sera to assess the autoimmune response against the male reproductive organs. By screening human protein arrays with male and female patient sera and by selecting for gender-imbalanced autoantibody signals, we identified transglutaminase 4 (TGM4) as a male-specific autoantigen. Notably, TGM4 is a prostatic secretory molecule with critical role in male reproduction. TGM4 autoantibodies were detected in most of the adult male APS1 patients but were absent in all the young males. Consecutive serum samples further revealed that TGM4 autoantibodies first presented during pubertal age and subsequent to prostate maturation. We assessed the animal model for APS1, the Aire-deficient mouse, and found spontaneous development of TGM4 autoantibodies specifically in males. Aire-deficient mice failed to present TGM4 in the thymus, consistent with a defect in central tolerance for TGM4. In the mouse, we further link TGM4 immunity with a destructive prostatitis and compromised secretion of TGM4. Collectively, our findings in APS1 patients and Aire-deficient mice reveal prostate autoimmunity as a major manifestation of APS1 with potential role in male subfertility.

Proteome-wide survey of the autoimmune target repertoire in autoimmune polyendocrine syndrome type 1

Autoimmune polyendocrine syndrome type 1 (APS1) is a monogenic disorder that features multiple autoimmune disease manifestations. It is caused by mutations in the Autoimmune regulator (AIRE) gene, which promote thymic display of thousands of peripheral tissue antigens in a process critical for establishing central immune tolerance. We here used proteome arrays to perform a comprehensive study of autoimmune targets in APS1. Interrogation of established autoantigens revealed highly reliable detection of autoantibodies, and by exploring the full panel of more than 9000 proteins we further identified MAGEB2 and PDILT as novel major autoantigens in APS1. Our proteome-wide assessment revealed a marked enrichment for tissue-specific immune targets, mirroring AIRE’s selectiveness for this category of genes. Our findings also suggest that only a very limited portion of the proteome becomes targeted by the immune system in APS1, which contrasts the broad defect of thymic presentation associated with AIRE-deficiency and raises novel questions what other factors are needed for break of tolerance.

Strain Kaplan of Pseudorabies Virus Genome Sequenced by PacBio Single-Molecule Real-Time Sequencing Technology

ABSTRACT Pseudorabies virus (PRV) is a neurotropic herpesvirus that causes Aujeszkys disease in pigs. PRV strains are widely used as transsynaptic tracers for mapping neural circuits. We present here the complete and fully annotated genome sequence of strain Kaplan of PRV, determined by Pacific Biosciences RSII long-read sequencing technology.

Characterization of the Dynamic Transcriptome of a Herpesvirus with Long-read Single Molecule Real-Time Sequencing

Herpesvirus gene expression is co-ordinately regulated and sequentially ordered during productive infection. The viral genes can be classified into three distinct kinetic groups: immediate-early, early, and late classes. In this study, a massively parallel sequencing technique that is based on PacBio Single Molecule Real-time sequencing platform, was used for quantifying the poly(A) fraction of the lytic transcriptome of pseudorabies virus (PRV) throughout a 12-hour interval of productive infection on PK-15 cells. Other approaches, including microarray, real-time RT-PCR and Illumina sequencing are capable of detecting only the aggregate transcriptional activity of particular genomic regions, but not individual herpesvirus transcripts. However, SMRT sequencing allows for a distinction between transcript isoforms, including length- and splice variants, as well as between overlapping polycistronic RNA molecules. The non-amplified Isoform Sequencing (Iso-Seq) method was used to analyse the kinetic properties of the lytic PRV transcripts and to then classify them accordingly. Additionally, the present study demonstrates the general utility of long-read sequencing for the time-course analysis of global gene expression in practically any organism.