Joseph Dhahbi

Identification and correction of systematic error in high-throughput sequence data.

BackgroundA feature common to all DNA sequencing technologies is the presence of base-call errors in the sequenced reads. The implications of such errors are application specific, ranging from minor informatics nuisances to major problems affecting biological inferences. Recently developed next-gen sequencing technologies have greatly reduced the cost of sequencing, but have been shown to be more error prone than previous technologies. Both position specific (depending on the location in the read) and sequence specific (depending on the sequence in the read) errors have been identified in Illumina and Life Technology sequencing platforms. We describe a new type of systematic error that manifests as statistically unlikely accumulations of errors at specific genome (or transcriptome) locations.ResultsWe characterize and describe systematic errors using overlapping paired reads from high-coverage data. We show that such errors occur in approximately 1 in 1000 base pairs, and that they are highly replicable across experiments. We identify motifs that are frequent at systematic error sites, and describe a classifier that distinguishes heterozygous sites from systematic error. Our classifier is designed to accommodate data from experiments in which the allele frequencies at heterozygous sites are not necessarily 0.5 (such as in the case of RNA-Seq), and can be used with single-end datasets.ConclusionsSystematic errors can easily be mistaken for heterozygous sites in individuals, or for SNPs in population analyses. Systematic errors are particularly problematic in low coverage experiments, or in estimates of allele-specific expression from RNA-Seq data. Our characterization of systematic error has allowed us to develop a program, called SysCall, for identifying and correcting such errors. We conclude that correction of systematic errors is important to consider in the design and interpretation of high-throughput sequencing experiments.

Genome methylation in D. melanogaster is found at specific short motifs and is independent of DNMT2 activity

Cytosine methylation in the genome of Drosophila melanogaster has been elusive and controversial: Its location and function have not been established. We have used a novel and highly sensitive genomewide cytosine methylation assay to detect and map genome methylation in stage 5 Drosophila embryos. The methylation we observe with this method is highly localized and strand asymmetrical, limited to regions covering ∼1% of the genome, dynamic in early embryogenesis, and concentrated in specific 5-base sequence motifs that are CA- and CT-rich but depleted of guanine. Gene body methylation is associated with lower expression, and many genes containing methylated regions have developmental or transcriptional functions. The only known DNA methyltransferase in Drosophila is the DNMT2 homolog MT2, but lines deficient for MT2 retain genomic methylation, implying the presence of a novel methyltransferase. The association of methylation with a lower expression of specific developmental genes at stage 5 raises the possibility that it participates in controlling gene expression during the maternal-zygotic transition.

Deep Sequencing of Serum Small RNAs Identifies Patterns of 5' tRNA Half and YRNA Fragment Expression Associated with Breast Cancer

Small noncoding RNAs circulating in the blood may serve as signaling molecules because of their ability to carry out a variety of cellular functions. We have previously described tRNA- and YRNA-derived small RNAs circulating as components of larger complexes in the blood of humans and mice; the characteristics of these small RNAs imply specific processing, secretion, and physiological regulation. In this study, we have asked if changes in the serum abundance of these tRNA and YRNA fragments are associated with a diagnosis of cancer. We used deep sequencing and informatics analysis to catalog small RNAs in the sera of breast cancer cases and normal controls. 5′ tRNA halves and YRNA fragments are abundant in both groups, but we found that a breast cancer diagnosis is associated with changes in levels of specific subtypes. This prompted us to look at existing sequence datasets of serum small RNAs from 42 breast cancer cases, taken at the time of diagnosis. We find significant changes in the levels of specific 5′ tRNA halves and YRNA fragments associated with clinicopathologic characteristics of the cancer. Although these findings do not establish causality, they suggest that circulating 5′ tRNA halves and YRNA fragments with known cellular functions may participate in breast cancer syndromes and have potential as circulating biomarkers. Larger studies with multiple types of cancer are needed to adequately evaluate their potential use for the development of noninvasive cancer screening.

MetMap enables genome-scale Methyltyping for determining methylation states in populations.

The ability to assay genome-scale methylation patterns using high-throughput sequencing makes it possible to carry out association studies to determine the relationship between epigenetic variation and phenotype. While bisulfite sequencing can determine a methylome at high resolution, cost inhibits its use in comparative and population studies. MethylSeq, based on sequencing of fragment ends produced by a methylation-sensitive restriction enzyme, is a method for methyltyping (survey of methylation states) and is a site-specific and cost-effective alternative to whole-genome bisulfite sequencing. Despite its advantages, the use of MethylSeq has been restricted by biases in MethylSeq data that complicate the determination of methyltypes. Here we introduce a statistical method, MetMap, that produces corrected site-specific methylation states from MethylSeq experiments and annotates unmethylated islands across the genome. MetMap integrates genome sequence information with experimental data, in a statistically sound and cohesive Bayesian Network. It infers the extent of methylation at individual CGs and across regions, and serves as a framework for comparative methylation analysis within and among species. We validated MetMaps inferences with direct bisulfite sequencing, showing that the methylation status of sites and islands is accurately inferred. We used MetMap to analyze MethylSeq data from four human neutrophil samples, identifying novel, highly unmethylated islands that are invisible to sequence-based annotation strategies. The combination of MethylSeq and MetMap is a powerful and cost-effective tool for determining genome-scale methyltypes suitable for comparative and association studies.

piRNA-like small RNAs mark extended 3’UTRs present in germ and somatic cells

BackgroundPiwi-interacting RNAs (piRNAs) are a class of small RNAs; distinct types of piRNAs are expressed in the mammalian testis at different stages of development. The function of piRNAs expressed in the adult testis is not well established. We conducted a detailed characterization of piRNAs aligning at or near the 3’ UTRs of protein-coding genes in a deep dataset of small RNAs from adult mouse testis.ResultsWe identified 2710 piRNA clusters associated with 3’ UTRs, including 1600 that overlapped genes not previously associated with piRNAs. 35xa0% of the clusters extend beyond the annotated transcript; we find that these clusters correspond to, and are likely derived from, novel polyadenylated mRNA isoforms that contain previously unannotated extended 3’UTRs. Extended 3’ UTRs, and small RNAs derived from them, are also present in somatic tissues; a subset of these somatic 3’UTR small RNA clusters are absent in mice lacking MIWI2, indicating a role for MIWI2 in the metabolism of somatic small RNAs.ConclusionsThe finding that piRNAs are processed from extended 3’ UTRs suggests a role for piRNAs in the remodeling of 3’ UTRs. The presence of both clusters and extended 3’UTRs in somatic cells, with evidence for involvement of MIWI2, indicates that this pathway is more broadly distributed than currently appreciated.

Deficiency of MIWI2 (Piwil4) Induces Mouse Erythroleukemia Cell Differentiation, but Has No Effect on Hematopoiesis In Vivo

Piwi proteins and their small non-coding RNA partners are involved in the maintenance of stem cell character and genome integrity in the male germ cells of mammals. MIWI2, one of the mouse Piwi-like proteins, is expressed in the prepachytene phase of spermatogenesis during the period of de novo methylation. Absence of this protein leads to meiotic defects and a progressive loss of germ cells. There is an accumulation of evidence that Piwi proteins may be active in hematopoietic tissues. Thus, MIWI2 may have a role in hematopoietic stem and/or progenitor cell self-renewal and differentiation, and defects in MIWI2 may lead to abnormal hematopoiesis. MIWI2 mRNA can be detected in a mouse erythroblast cell line by RNA-seq, and shRNA-mediated knockdown of this mRNA causes the cells to take on characteristics of differentiated erythroid precursors. However, there are no detectable hematopoietic abnormalities in a MIWI2-deficient mouse model. While subtle, non-statistically significant changes were noted in the hematopoietic function of mice without a functional MIWI2 gene when compared to wild type mice, our results show that MIWI2 is not solely necessary for hematopoiesis within the normal life span of a mouse.

MicroRNAs Circulate in the Hemolymph of Drosophila and Accumulate Relative to Tissue microRNAs in an Age-Dependent Manner

In mammals, extracellular miRNAs circulate in biofluids as stable entities that are secreted by normal and diseased tissues, and can enter cells and regulate gene expression. Drosophila melanogaster is a proven system for the study of human diseases. They have an open circulatory system in which hemolymph (HL) circulates in direct contact with all internal organs, in a manner analogous to vertebrate blood plasma. Here, we show using deep sequencing that Drosophila HL contains RNase-resistant circulating miRNAs (HL-miRNAs). Limited subsets of body tissue miRNAs (BT-miRNAs) accumulated in HL, suggesting that they may be specifically released from cells or particularly stable in HL. Alternatively, they might arise from specific cells, such as hemocytes, that are in intimate contact with HL. Young and old flies accumulated unique populations of HL-miRNAs, suggesting that their accumulation is responsive to the physiological status of the fly. These HL-miRNAs in flies may function similar to the miRNAs circulating in mammalian biofluids. The discovery of these HL-miRNAs will provide a new venue for health and disease-related research in Drosophila.