Core RNA-processing reactions in eukaryotic cells occur cotranscriptionally in a chromatin context, but the relationship between chromatin structure and pre-mRNA processing is poorly understood. We ...observed strong nucleosome depletion around human polyadenylation sites (PAS) and nucleosome enrichment just downstream of PAS. In genes with multiple alternative PAS, higher downstream nucleosome affinity was associated with higher PAS usage, independently of known PAS motifs that function at the RNA level. Conversely, exons were associated with distinct peaks in nucleosome density. Exons flanked by long introns or weak splice sites exhibited stronger nucleosome enrichment, and incorporation of nucleosome density data improved splicing simulation accuracy. Certain histone modifications, including H3K36me3 and H3K27me2, were specifically enriched on exons, suggesting active marking of exon locations at the chromatin level. Together, these findings provide evidence for extensive functional connections between chromatin structure and RNA processing.
In read cloud approaches, microfluidic partitioning of long genomic DNA fragments and barcoding of shorter fragments derived from these fragments retains long-range information in short sequencing ...reads. This combination of short reads with long-range information represents a powerful alternative to single-molecule long-read sequencing. We develop Genome-wide Reconstruction of Complex Structural Variants (GROC-SVs) for SV detection and assembly from read cloud data and apply this method to Illumina-sequenced 10x Genomics sarcoma and breast cancer data sets. Compared with short-fragment sequencing, GROC-SVs substantially improves the specificity of breakpoint detection at comparable sensitivity. This approach also performs sequence assembly across multiple breakpoints simultaneously, enabling the reconstruction of events exhibiting remarkable complexity. We show that chromothriptic rearrangements occurred before copy number amplifications, and that rates of single-nucleotide variants and SVs are not correlated. Our results support the use of read cloud approaches to advance the characterization of large and complex structural variation.
Visualizing read alignments is the most effective way to validate candidate structural variants (SVs) with existing data. We present svviz, a sequencing read visualizer for SVs that sorts and ...displays only reads relevant to a candidate SV. svviz works by searching input bam(s) for potentially relevant reads, realigning them against the inferred sequence of the putative variant allele as well as the reference allele and identifying reads that match one allele better than the other. Separate views of the two alleles are then displayed in a scrollable web browser view, enabling a more intuitive visualization of each allele, compared with the single reference genome-based view common to most current read browsers. The browser view facilitates examining the evidence for or against a putative variant, estimating zygosity, visualizing affected genomic annotations and manual refinement of breakpoints. svviz supports data from most modern sequencing platforms.
svviz is implemented in python and freely available from http://svviz.github.io/.
The human genome contains variants ranging in size from small single nucleotide polymorphisms (SNPs) to large structural variants (SVs). High-quality benchmark small variant calls for the pilot ...National Institute of Standards and Technology (NIST) Reference Material (NA12878) have been developed by the Genome in a Bottle Consortium, but no similar high-quality benchmark SV calls exist for this genome. Since SV callers output highly discordant results, we developed methods to combine multiple forms of evidence from multiple sequencing technologies to classify candidate SVs into likely true or false positives. Our method (svclassify) calculates annotations from one or more aligned bam files from many high-throughput sequencing technologies, and then builds a one-class model using these annotations to classify candidate SVs as likely true or false positives.
We first used pedigree analysis to develop a set of high-confidence breakpoint-resolved large deletions. We then used svclassify to cluster and classify these deletions as well as a set of high-confidence deletions from the 1000 Genomes Project and a set of breakpoint-resolved complex insertions from Spiral Genetics. We find that likely SVs cluster separately from likely non-SVs based on our annotations, and that the SVs cluster into different types of deletions. We then developed a supervised one-class classification method that uses a training set of random non-SV regions to determine whether candidate SVs have abnormal annotations different from most of the genome. To test this classification method, we use our pedigree-based breakpoint-resolved SVs, SVs validated by the 1000 Genomes Project, and assembly-based breakpoint-resolved insertions, along with semi-automated visualization using svviz.
We find that candidate SVs with high scores from multiple technologies have high concordance with PCR validation and an orthogonal consensus method MetaSV (99.7 % concordant), and candidate SVs with low scores are questionable. We distribute a set of 2676 high-confidence deletions and 68 high-confidence insertions with high svclassify scores from these call sets for benchmarking SV callers. We expect these methods to be particularly useful for establishing high-confidence SV calls for benchmark samples that have been characterized by multiple technologies.
A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for ...large indels and structural variants (SVs) is more challenging. In this study, we manually curated 1235 SVs, which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app-SVCurator-to help GIAB curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy. SVCurator displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son NIST RM 8391/HG002. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. 'Expert' curators were 93% concordant with each other, and 37 of the 61 curators had at least 78% concordance with a set of 'expert' curators. The curators were least concordant for complex SVs and SVs that had inaccurate breakpoints or size predictions. After filtering events with low concordance among curators, we produced high confidence labels for 935 events. The SVCurator crowdsourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.
Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary ...genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors.
Variation in protein output across the genome is controlled at several levels, but the relative contributions of different regulatory mechanisms remain poorly understood. Here, we obtained global ...measurements of decay and translation rates for mRNAs with alternative 3' untranslated regions (3' UTRs) in murine 3T3 cells. Distal tandem isoforms had slightly but significantly lower mRNA stability and greater translational efficiency than proximal isoforms on average. The diversity of alternative 3' UTRs also enabled inference and evaluation of both positively and negatively acting cis-regulatory elements. The 3' UTR elements with the greatest implied influence were microRNA complementary sites, which were associated with repression of 32% and 4% at the stability and translational levels, respectively. Nonetheless, both the decay and translation rates were highly correlated for proximal and distal 3' UTR isoforms from the same genes, implying that in 3T3 cells, alternative 3' UTR sequences play a surprisingly small regulatory role compared to other mRNA regions.
The effects of genetic variation on gene regulation in the developing mammalian embryo remain largely unexplored. To globally quantify these effects, we crossed two divergent mouse strains and asked ...how genotype of the mother or of the embryo drives gene expression phenotype genomewide. Embryonic expression of 331 genes depends on the genotype of the mother. Embryonic genotype controls allele-specific expression of 1594 genes and a highly overlapping set of cis-expression quantitative trait loci (eQTL). A marked paucity of trans-eQTL suggests that the widespread expression differences do not propagate through the embryonic gene regulatory network. The cis-eQTL genes exhibit lower-than-average evolutionary conservation and are depleted for developmental regulators, consistent with purifying selection acting on expression phenotype of pattern formation genes. The widespread effect of maternal and embryonic genotype in conjunction with the purifying selection we uncovered suggests that embryogenesis is an important and understudied reservoir of phenotypic variation.
In the fission yeast Schizosaccharomyces pombe, the RNA interference (RNAi) machinery is required to generate small interfering RNAs (siRNAs) that mediate heterochromatic gene silencing. Efficient ...silencing also requires the TRAMP complex, which contains the noncanonical Cid14 poly(A) polymerase and targets aberrant RNAs for degradation. Here we use high-throughput sequencing to analyze Argonaute-associated small RNAs (sRNAs) in both the presence and absence of Cid14. Most sRNAs in fission yeast start with a 5' uracil, and we argue these are loaded most efficiently into Argonaute. In wild-type cells most sRNAs match to repeated regions of the genome, whereas in cid14Delta cells the sRNA profile changes to include major new classes of sRNAs originating from ribosomal RNAs and a tRNA. Thus, Cid14 prevents certain abundant RNAs from becoming substrates for the RNAi machinery, thereby freeing the RNAi machinery to act on its proper targets.
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