A systematic evaluation of the design, orientation, and sequence context dependencies of massively parallel reporter assays, bioRxiv, 2019-03-14

ABSTRACTMassively parallel reporter assays (MPRAs) functionally screen thousands of sequences for regulatory activity in parallel. Although MPRAs have been applied to address diverse questions in gene regulation, there has been no systematic comparison of how differences in experimental design influence findings. Here, we screen a library of 2,440 sequences, representing candidate liver enhancers and controls, in HepG2 cells for regulatory activity using nine different approaches (including conventional episomal, STARR-seq, and lentiviral MPRA designs). We identify subtle but significant differences in the resulting measurements that correlate with epigenetic and sequence-level features. We also test this library in both orientations with respect to the promoter, validating en masse that enhancer activity is robustly independent of orientation. Finally, we develop and apply a novel method to assemble and functionally test libraries of the same putative enhancers as 192-mers, 354-mers, and 678-mers, and observe surprisingly large differences in functional activity. This work provides a framework for the experimental design of high-throughput reporter assays, suggesting that the extended sequence context of tested elements, and to a lesser degree the precise assay, influence MPRA results.

biorxiv genomics 0-100-users 2019

Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression, bioRxiv, 2019-03-14

AbstractSingle-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to technical factors, including the number of molecules detected in each cell, which can confound biological heterogeneity with technical effects. To address this, we present a modeling framework for the normalization and variance stabilization of molecular count data from scRNA-seq experiments. We propose that the Pearson residuals from ’regularized negative binomial regression’, where cellular sequencing depth is utilized as a covariate in a generalized linear model, successfully remove the influence of technical characteristics from downstream analyses while preserving biological heterogeneity. Importantly, we show that an unconstrained negative binomial model may overfit scRNA-seq data, and overcome this by pooling information across genes with similar abundances to obtain stable parameter estimates. Our procedure omits the need for heuristic steps including pseudocount addition or log-transformation, and improves common downstream analytical tasks such as variable gene selection, dimensional reduction, and differential expression. Our approach can be applied to any UMI-based scRNA-seq dataset and is freely available as part of the R package sctransform, with a direct interface to our single-cell toolkit Seurat.

biorxiv genomics 200-500-users 2019

Population histories of the United States revealed through fine-scale migration and haplotype analysis, bioRxiv, 2019-03-14

AbstractThe population of the United States is shaped by centuries of migration, isolation, growth, and admixture between ancestors of global origins. Here, we assemble a comprehensive view of recent population history by studying the ancestry and population structure of over 32,000 individuals in the US using genetic, ancestral birth origin, and geographic data from the National Geographic Genographic Project. We identify migration routes and barriers that reflect historical demographic events. We also uncover the spatial patterns of relatedness in subpopulations through the combination of haplotype clustering, ancestral birth origin analysis, and local ancestry inference. These patterns include substantial substructure and heterogeneity in HispanicsLatinos, isolation-by-distance in African Americans, elevated levels of relatedness and homozygosity in Asian immigrants, and fine-scale structure in European descents. Taken together, our results provide detailed insights into the genetic structure and demographic history of the diverse US population.

biorxiv genetics 100-200-users 2019

ARMOR an Automated Reproducible MOdular workflow for preprocessing and differential analysis of RNA-seq data, bioRxiv, 2019-03-13

AbstractThe extensive generation of RNA sequencing (RNA-seq) data in the last decade has resulted in a myriad of specialized software for its analysis. Each software module typically targets a specific step within the analysis pipeline, making it necessary to join several of them to get a single cohesive workflow. Multiple software programs automating this procedure have been proposed, but often lack modularity, transparency or flexibility. We present ARMOR, which performs an end-to-end RNA-seq data analysis, from raw read files, via quality checks, alignment and quantification, to differential expression testing, geneset analysis and browser-based exploration of the data. ARMOR is implemented using the Snakemake workflow management system and leverages conda environments; Bioconductor objects are generated to facilitate downstream analysis, ensuring seamless integration with many R packages. The workflow is easily implemented by cloning the GitHub repository, replacing the supplied input and reference files and editing a configuration file. Although we have selected the tools currently included in ARMOR, the setup is modular and alternative tools can be easily integrated.

biorxiv bioinformatics 100-200-users 2019

Frequent birth of de novo genes in the compact yeast genome, bioRxiv, 2019-03-13

AbstractEvidence has accumulated that some genes originate directly from previously non-genic sequences, or de novo, rather than by the duplication or fusion of existing genes. However, how de novo genes emerge and eventually become functional is largely unknown. Here we perform the first study on de novo genes that uses transcriptomics data from eleven different yeast species, all grown identically in both rich media and in oxidative stress conditions. The genomes of these species are densely-packed with functional elements, leaving little room for the co-option of genomic sequences into new transcribed loci. Despite this, we find that at least 213 transcripts (~5%) have arisen de novo in the past 20 million years of evolution of baker’s yeast-or approximately 10 new transcripts every million years. Nearly half of the total newly expressed sequences are generated from regions in which both DNA strands are used as templates for transcription, explaining the apparent contradiction between the limited ‘empty’ genomic space and high rate of de novo gene birth. In addition, we find that 40% of these de novo transcripts are actively translated and that at least a fraction of the encoded proteins are likely to be under purifying selection. This study shows that even in very highly compact genomes, de novo transcripts are continuously generated and can give rise to new functional protein-coding genes.

biorxiv evolutionary-biology 0-100-users 2019

Frequent birth ofde novogenes in the compact yeast genome, bioRxiv, 2019-03-13

AbstractEvidence has accumulated that some genes originate directly from previously non-genic sequences, orde novo, rather than by the duplication or fusion of existing genes. However, howde novogenes emerge and eventually become functional is largely unknown. Here we perform the first study onde novogenes that uses transcriptomics data from eleven different yeast species, all grown identically in both rich media and in oxidative stress conditions. The genomes of these species are densely-packed with functional elements, leaving little room for the co-option of genomic sequences into new transcribed loci. Despite this, we find that at least 213 transcripts (~5%) have arisende novoin the past 20 million years of evolution of baker’s yeast-or approximately 10 new transcripts every million years. Nearly half of the total newly expressed sequences are generated from regions in which both DNA strands are used as templates for transcription, explaining the apparent contradiction between the limited ‘empty’ genomic space and high rate ofde novogene birth. In addition, we find that 40% of thesede novotranscripts are actively translated and that at least a fraction of the encoded proteins are likely to be under purifying selection. This study shows that even in very highly compact genomes,de novotranscripts are continuously generated and can give rise to new functional protein-coding genes.

biorxiv evolutionary-biology 0-100-users 2019