Multiplexed long-read plasmid validation and analysis using OnRamp.

Recombinant plasmid vectors are versatile tools that have facilitated discoveries in molecular biology, genetics, proteomics, and many other fields. As the enzymatic and bacterial processes used to create recombinant DNA can introduce errors, sequence validation is an essential step in plasmid assembly. Sanger sequencing is the current standard for plasmid validation; however, this method is limited by an inability to sequence through complex secondary structure and lacks scalability when applied to full-plasmid sequencing of multiple plasmids owing to read-length limits. Although high-throughput sequencing does provide full-plasmid sequencing at scale, it is impractical and costly when used outside of library-scale validation. Here, we present Oxford nanopore-based rapid analysis of multiplexed plasmids (OnRamp), an alternative method for routine plasmid validation that combines the advantages of high-throughput sequencing's full-plasmid coverage and scalability with Sanger's affordability and accessibility by leveraging nanopore's long-read sequencing technology. We include customized wet-laboratory protocols for plasmid preparation along with a pipeline designed for analysis of read data obtained using these protocols. This analysis pipeline is deployed on the OnRamp web app, which generates alignments between actual and predicted plasmid sequences, quality scores, and read-level views. OnRamp is designed to be broadly accessible regardless of programming experience to facilitate more widespread adoption of long-read sequencing for routine plasmid validation. Here we describe the OnRamp protocols and pipeline and show our ability to obtain full sequences from pooled plasmids while detecting sequence variation even in regions of high secondary structure at less than half the cost of equivalent Sanger sequencing.

MapGL: inferring evolutionary gain and loss of short genomic sequence features by phylogenetic maximum parsimony.

BACKGROUND: Comparative genomics studies are growing in number partly because of their unique ability to provide insight into shared and divergent biology between species. Of particular interest is the use of phylogenetic methods to infer the evolutionary history of cis-regulatory sequence features, which contribute strongly to phenotypic divergence and are frequently gained and lost in eutherian genomes. Understanding the mechanisms by which cis-regulatory element turnover generate emergent phenotypes is crucial to our understanding of adaptive evolution. Ancestral reconstruction methods can place species-specific cis-regulatory features in their evolutionary context, thus increasing our understanding of the process of regulatory sequence turnover. However, applying these methods to gain and loss of cis-regulatory features historically required complex workflows, preventing widespread adoption by the broad scientific community. RESULTS: MapGL simplifies phylogenetic inference of the evolutionary history of short genomic sequence features by combining the necessary steps into a single piece of software with a simple set of inputs and outputs. We show that MapGL can reliably disambiguate the mechanisms underlying differential regulatory sequence content across a broad range of phylogenetic topologies and evolutionary distances. Thus, MapGL provides the necessary context to evaluate how genomic sequence gain and loss contribute to species-specific divergence. CONCLUSIONS: MapGL makes phylogenetic inference of species-specific sequence gain and loss easy for both expert and non-expert users, making it a powerful tool for gaining novel insights into genome evolution.

Conserved and species-specific transcription factor co-binding patterns drive divergent gene regulation in human and mouse.

The mouse is widely used as system to study human genetic mechanisms. However, extensive rewiring of transcriptional regulatory networks often confounds translation of findings between human and mouse. Site-specific gain and loss of individual transcription factor binding sites (TFBS) has caused functional divergence of orthologous regulatory loci, and so we must look beyond this positional conservation to understand common themes of regulatory control. Fortunately, transcription factor co-binding patterns shared across species often perform conserved regulatory functions. These can be compared to 'regulatory sentences' that retain the same meanings regardless of sequence and species context. By analyzing TFBS co-occupancy patterns observed in four human and mouse cell types, we learned a regulatory grammar: the rules by which TFBS are combined into meaningful regulatory sentences. Different parts of this grammar associate with specific sets of functional annotations regardless of sequence conservation and predict functional signatures more accurately than positional conservation. We further show that both species-specific and conserved portions of this grammar are involved in gene expression divergence and human disease risk. These findings expand our understanding of transcriptional regulatory mechanisms, suggesting that phenotypic divergence and disease risk are driven by a complex interplay between deeply conserved and species-specific transcriptional regulatory pathways.

Deciphering ENCODE.

The ENCODE project represents a major leap from merely describing and comparing genomic sequences to surveying them for direct indicators of function. The astounding quantity of data produced by the ENCODE consortium can serve as a map to locate specific landmarks, guide hypothesis generation, and lead us to principles and mechanisms underlying genome biology. Despite its broad appeal, the size and complexity of the repository can be intimidating to prospective users. We present here some background about the ENCODE data, survey the resources available for accessing them, and describe a few simple principles to help prospective users choose the data type(s) that best suit their needs, where to get them, and how to use them to their best advantage.

HaplotagLR: An efficient and configurable utility for haplotagging long reads.

Understanding the functional effects of sequence variation is crucial in genomics. Individual human genomes contain millions of variants that contribute to phenotypic variability and disease risks at the population level. Because variants rarely act in isolation, we must consider potential interactions of neighboring variants to accurately predict functional effects. We can accomplish this using haplotagging, which matches sequencing reads to their parental haplotypes using alleles observed at known heterozygous variants. However, few published tools for haplotagging exist and these share several technical and usability-related shortcomings that limit applicability, in particular a lack of insight or control over error rates, and lack of key metrics on the underlying sources of haplotagging error. Here we present HaplotagLR: a user-friendly tool that haplotags long sequencing reads based on a multinomial model and existing phased variant lists. HaplotagLR is user-configurable and includes a basic error model to control the empirical FDR in its output. We show that HaplotagLR outperforms the leading haplotagging method in simulated datasets, especially at high levels of specificity, and displays 7% greater sensitivity in haplotagging real data. HaplotagLR advances both the immediate utility of haplotagging and paves the way for further improvements to this important method.

Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes.

Understanding the genetic basis for complex, heterogeneous disorders, such as autism spectrum disorder (ASD), is a persistent challenge in human medicine. Owing to their phenotypic complexity, the genetic mechanisms underlying these disorders may be highly variable across individual patients. Furthermore, much of their heritability is unexplained by known regulatory or coding variants. Indeed, there is evidence that much of the causal genetic variation stems from rare and de novo variants arising from ongoing mutation. These variants occur mostly in noncoding regions, likely affecting regulatory processes for genes linked to the phenotype of interest. However, because there is no uniform code for assessing regulatory function, it is difficult to separate these mutations into likely functional and nonfunctional subsets. This makes finding associations between complex diseases and potentially causal de novo single-nucleotide variants (dnSNVs) a difficult task. To date, most published studies have struggled to find any significant associations between dnSNVs from ASD patients and any class of known regulatory elements. We sought to identify the underlying reasons for this and present strategies for overcoming these challenges. We show that, contrary to previous claims, the main reason for failure to find robust statistical enrichments is not only the number of families sampled, but also the quality and relevance to ASD of the annotations used to prioritize dnSNVs, and the reliability of the set of dnSNVs itself. We present a list of recommendations for designing future studies of this sort that will help researchers avoid common pitfalls.

LRphase: an efficient method for assigning haplotype identity to long reads.

Understanding the functional effects of sequence variation is among the primary goals of contemporary genomics. Individual human genomes contain millions of variants which are thought to contribute to phenotypic variability and differential disease risks at the population level. However, because variants rarely act in isolation, we cannot accurately predict functional effects without first considering the potential effects of other interacting variants on the same chromosome. This information can be obtained by phasing the read data from sequencing experiments. However, no standalone tools are available to simply phase reads based on known haplotypes. Here we present LRphase: a user-friendly utility for simple phasing of long sequencing reads.

Sperm chromatin structure and reproductive fitness are altered by substitution of a single amino acid in mouse protamine 1.

Conventional dogma presumes that protamine-mediated DNA compaction in sperm is achieved by electrostatic interactions between DNA and the arginine-rich core of protamines. Phylogenetic analysis reveals several non-arginine residues conserved within, but not across species. The significance of these residues and their post-translational modifications are poorly understood. Here, we investigated the role of K49, a rodent-specific lysine residue in protamine 1 (P1) that is acetylated early in spermiogenesis and retained in sperm. In sperm, alanine substitution (P1(K49A)) decreases sperm motility and male fertility-defects that are not rescued by arginine substitution (P1(K49R)). In zygotes, P1(K49A) leads to premature male pronuclear decompaction, altered DNA replication, and embryonic arrest. In vitro, P1(K49A) decreases protamine-DNA binding and alters DNA compaction and decompaction kinetics. Hence, a single amino acid substitution outside the P1 arginine core is sufficient to profoundly alter protein function and developmental outcomes, suggesting that protamine non-arginine residues are essential for reproductive fitness.

Genomic analyses of transcription factor binding, histone acetylation, and gene expression reveal mechanistically distinct classes of estrogen-regulated promoters.

To explore the global mechanisms of estrogen-regulated transcription, we used chromatin immunoprecipitation coupled with DNA microarrays to determine the localization of RNA polymerase II (Pol II), estrogen receptor alpha (ERalpha), steroid receptor coactivator proteins (SRC), and acetylated histones H3/H4 (AcH) at estrogen-regulated promoters in MCF-7 cells with or without estradiol (E2) treatment. In addition, we correlated factor occupancy with gene expression and the presence of transcription factor binding elements. Using this integrative approach, we defined a set of 58 direct E2 target genes based on E2-regulated Pol II occupancy and classified their promoters based on factor binding, histone modification, and transcriptional output. Many of these direct E2 target genes exhibit interesting modes of regulation and biological activities, some of which may be relevant to the onset and proliferation of breast cancers. Our studies indicate that about one-third of these direct E2 target genes contain promoter-proximal ERalpha-binding sites, which is considerably more than previous estimates. Some of these genes represent possible novel targets for regulation through the ERalpha/AP-1 tethering pathway. Our studies have also revealed several previously uncharacterized global features of E2-regulated gene expression, including strong positive correlations between Pol II occupancy and AcH levels, as well as between the E2-dependent recruitment of ERalpha and SRC at the promoters of E2-stimulated genes. Furthermore, our studies have revealed new mechanistic insights into E2-regulated gene expression, including the absence of SRC binding at E2-repressed genes and the presence of constitutively bound, promoter-proximally paused Pol IIs at some E2-regulated promoters. These mechanistic insights are likely to be relevant for understanding gene regulation by a wide variety of nuclear receptors.

Transposable elements contribute to cell and species-specific chromatin looping and gene regulation in mammalian genomes.

Chromatin looping is important for gene regulation, and studies of 3D chromatin structure across species and cell types have improved our understanding of the principles governing chromatin looping. However, 3D genome evolution and its relationship with natural selection remains largely unexplored. In mammals, the CTCF protein defines the boundaries of most chromatin loops, and variations in CTCF occupancy are associated with looping divergence. While many CTCF binding sites fall within transposable elements (TEs), their contribution to 3D chromatin structural evolution is unknown. Here we report the relative contributions of TE-driven CTCF binding site expansions to conserved and divergent chromatin looping in human and mouse. We demonstrate that TE-derived CTCF binding divergence may explain a large fraction of variable loops. These variable loops contribute significantly to corresponding gene expression variability across cells and species, possibly by refining sub-TAD-scale loop contacts responsible for cell-type-specific enhancer-promoter interactions.

Extraocular muscle morphogenesis and gene expression are regulated by Pitx2 gene dose.

PURPOSE: PITX2 gene dose plays a central role in Axenfeld-Rieger syndrome. The purpose of this study was to test the hypothesis that the effects of Pitx2 gene dose on eye development can be molecularly dissected in available Pitx2 mutant mice. METHODS: A panel of mice with Pitx2 gene dose ranging from wild-type (+/+) to none (-/-) was generated. Eye morphogenesis was assessed in animals with each Pitx2 gene dose. We also compared global gene expression in eye primordia taken from e12.5 Pitx2+/+, Pitx2+/-, Pitx2-/- embryos using gene microarrays. The validity of microarray results was confirmed by qRT-PCR. RESULTS: Morphogenesis of all extraocular muscle bundles correlated highly with Pitx2 gene dose, but there were some differences in sensitivity among muscle groups. Superior and inferior oblique muscles were most sensitive and disappeared before the four rectus muscles. Expression of muscle-specific genes was globally sensitive to Pitx2 gene dose, including the muscle-specific transcription factor genes Myf5, Myog, Myod1, Smyd1, Msc, and Csrp3. CONCLUSIONS: Pitx2 gene dose regulates both morphogenesis and gene expression in developing extraocular muscles. The expression of key muscle-specific transcription factor genes is regulated by Pitx2 gene dose, suggesting that sufficient levels of PITX2 protein are essential for early initiation of the myogenic regulatory cascade in extraocular muscles. These results document the first ocular tissue affected by Pitx2 gene dose in a model organism, where the underlying mechanisms can be analyzed, and provide a paradigm for future experiments designed to elucidate additional effects of Pitx2 gene dose during eye development.

Multiple sequence-specific DNA-binding proteins mediate estrogen receptor signaling through a tethering pathway.

The indirect recruitment (tethering) of estrogen receptors (ERs) to DNA through other DNA-bound transcription factors (e.g. activator protein 1) is an important component of estrogen-signaling pathways, but our understanding of the mechanisms of ligand-dependent activation in this pathway is limited. Using proteomic, genomic, and gene-specific analyses, we demonstrate that a large repertoire of DNA-binding transcription factors contribute to estrogen signaling through the tethering pathway. In addition, we define a set of endogenous genes for which ERα tethering through activator protein 1 (e.g. c-Fos) and cAMP response element-binding protein family members mediates estrogen responsiveness. Finally, we show that functional interplay between c-Fos and cAMP response element-binding protein 1 contributes to estrogen-dependent regulation through the tethering pathway. Based on our results, we conclude that ERα recruitment in the tethering pathway is dependent on the ligand-induced formation of transcription factor complexes that involves interplay between the transcription factors from different protein families.