SUMMARY Transcription factor (TF) DNA sequence preferences direct their regulatory activity, but are currently known for only ~1% of all eukaryotic TFs. Broadly sampling DNA-binding domain (DBD) types from multiple eukaryotic clades, we determined DNA sequence preferences for >1,000 TFs encompassing 54 different DBD classes from 131 diverse eukaryotes. We find that closely related DBDs almost always have very similar DNA sequence preferences, enabling inference of motifs for ~34% of the ~170,000 known or predicted eukaryotic TFs. Sequences matching both measured and inferred motifs are enriched in ChIP-seq peaks and upstream of transcription start sites in diverse eukaryotic lineages. SNPs defining expression quantitative trait loci in Arabidopsis promoters are also enriched for predicted TF binding sites. Importantly, our motif “library” (http://cisbp.ccbr.utoronto.ca) can be used to identify specific TFs whose binding may be altered by human disease risk alleles. These data present a powerful resource for mapping transcriptional networks across eukaryotes.

To evaluate the effect of CG methylation on DNA binding of sequence-specific B-ZIP transcription factors (TFs) in a highthroughput manner, we enzymatically methylated the cytosine in the CG dinucleotide on protein binding microarrays. Two Agilent DNA array designs were used. One contained 40,000 features using de Bruijn sequences where each 8-mer occurs 32 times in various positions in the DNA sequence. The second contained 180,000 features with each CG containing 8-mer occurring three times. The first design was better for identification of binding motifs, while the second was better for quantification. Using this novel technology, we show that CG methylation enhanced binding for CEBPA and CEBPB and inhibited binding for CREB, ATF4, JUN, JUND, CEBPD, and CEBPG. The CEBPB|ATF4 heterodimer bound a novel motif CGAT|GCAA 10-fold better when methylated. The electrophoretic mobility shift assay (EMSA) confirmed these results. CEBPB ChIP-seq data using primary female mouse dermal fibroblasts with 503 methylome coverage for each strand indicate that the methylated sequences well-bound on the arrays are also bound in vivo. CEBPB bound 39% of the methylated canonical 10-mers ATTGC|GCAAT in the mouse genome. After ATF4 protein induction by thapsigargin which results in ER stress, CEBPB binds methylated CGAT|GCAA in vivo, recapitulating what was observed on the arrays. This methodology can be used to identify new methylated DNA sequences preferentially bound by TFs, which may be functional in vivo.

Here we develop a high-throughput single-cell ATAC-seq (assay for transposition of accessible chromatin) method to measure physical access to DNA in whole cells. Our approach integrates fluorescence imaging and addressable reagent deposition across a massively parallel (5184) nano-well array, yielding a nearly 20-fold improvement in throughput (up to ~1800 cells/chip, 4–5 h on-chip processing time) and library preparation cost (~81¢ per cell) compared to prior microfluidic implementations. We apply this method to measure regulatory variation in peripheral blood mononuclear cells (PBMCs) and show robust, de novo clustering of single cells by hematopoietic cell type.

BackgroundTechnological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable.ResultsHere we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells.ConclusionsOverall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3893-1) contains supplementary material, which is available to authorized users.

White spruce ( Picea glauca (Moench) Voss) is a characteristic primary species of the Canadian boreal forest region, where it occurs in conifer-dominated and mixedwood forest types. Genetic diversity and population structure of white spruce may differ between the conifer-dominated and mixedwood forest types owing to the inherent differences in stand structure and dynamics. The objective of our study was to determine genetic diversity and population structure of pristine white spruce stands as they occur in conifer-dominated and mixedwood forest types at the EMEND (Ecosystem Management Emulating Natural Disturbance) study sites in northern Alberta. Nuclear microsatellite DNA markers were used to examine genetic diversity and population structure of 16 pristine natural old-growth (≥100 years) white spruce stands (subpopulations) of fire origin; 8 from conifer-dominated and 8 from neighboring mixedwood forest types. High levels of genetic diversity were observed, as expected. The genetic diversity and genetic constitution of white spruce were similar between the conifer-dominated and mixedwood forest types. Most of the genetic variation resided within subpopulations, with only about 2% genetic differentiation detected among 16 subpopulations as well as among 8 subpopulations within the same forest type. The mean genetic distances among subpopulations within and between the forest types were similar. Our study suggests that white spruce genetic resources are similar in the conifer-dominated and mixedwood forest types located in the EMEND study area in northern Alberta, and it provides the benchmarks for determining and monitoring the genetic diversity impacts of forest harvesting and forest fires.