HPRep: Quantifying Reproducibility in HiChIP and PLAC-Seq Datasets

HiChIP and PLAC-Seq are emerging technologies for studying genome-wide long-range chromatin interactions mediated by the protein of interest, enabling more sensitive and cost-efficient interrogation of protein-centric chromatin conformation. However, due to the unbalanced read distribution introduced by protein immunoprecipitation, existing reproducibility measures developed for Hi-C data are not appropriate for the analysis of HiChIP and PLAC-Seq data. Here, we present HPRep, a stratified and weighted correlation metric derived from normalized contact counts, to quantify reproducibility in HiChIP and PLAC-Seq data. We applied HPRep to multiple real datasets and demonstrate that HPRep outperforms existing reproducibility measures developed for Hi-C data. Specifically, we applied HPRep to H3K4me3 PLAC-Seq data from mouse embryonic stem cells and mouse brain tissues as well as H3K27ac HiChIP data from human lymphoblastoid cell line GM12878 and leukemia cell line K562, showing that HPRep can more clearly separate among pseudo-replicates, real replicates, and non-replicates. Furthermore, in an H3K4me3 PLAC-Seq dataset consisting of 11 samples from four human brain cell types, HPRep demonstrated the expected clustering of data that could not be achieved by existing methods developed for Hi-C data, highlighting the need for a reproducibility metric tailored to HiChIP and PLAC-Seq data.

Extending the lymphoblastoid cell line model for drug combination pharmacogenomics

Combination drug therapies have become an integral part of precision oncology, and while evidence of clinical effectiveness continues to grow, the underlying mechanisms supporting synergy are poorly understood. Immortalized human lymphoblastoid cell lines (LCLs) have been proven as a particularly useful, scalable and low-cost model in pharmacogenetics research, and are suitable for elucidating the molecular mechanisms of synergistic combination therapies. In this review, we cover the advantages of LCLs in synergy pharmacogenomics and consider recent studies providing initial evidence of the utility of LCLs in synergy research. We also discuss several opportunities for LCL-based systems to address gaps in the research through the expansion of testing regimens, assessment of new drug classes and higher-order combinations, and utilization of integrated omics technologies.

Human Chromosome 18 and Acrocentrics: A Dangerous Liaison

The presence of thousands of repetitive sequences makes the centromere a fragile region subject to breakage. In this study we collected 31 cases of rearrangements of chromosome 18, of which 16 involved an acrocentric chromosome, during genetic screening done in three centers. We noticed a significant enrichment of reciprocal translocations between the centromere of chromosome 18 and the centromeric or pericentromeric regions of the acrocentrics. We describe five cases with translocation between chromosome 18 and an acrocentric chromosome, and one case involving the common telomere regions of chromosomes 18p and 22p. In addition, we bring evidence to support the hypothesis that chromosome 18 preferentially recombines with acrocentrics: (i) the presence on 18p11.21 of segmental duplications highly homologous to acrocentrics, that can justify a NAHR mechanism; (ii) the observation by 2D-FISH of the behavior of the centromeric regions of 18 respect to the centromeric regions of acrocentrics in the nuclei of normal subjects; (iii) the contact analysis among these regions on published Hi-C data from the human lymphoblastoid cell line (GM12878).

Diverse molecular mechanisms contribute to differential expression of human duplicated genes

Emerging evidence links genes within human-specific segmental duplications (HSDs) to traits and diseases unique to our species. Strikingly, despite being nearly identical by sequence (>98.5%), paralogous HSD genes are differentially expressed across human cell and tissue types, though the underlying mechanisms have not been examined. We compared cross-tissue mRNA levels of 75 HSD genes from 30 families between humans and chimpanzees and found expression patterns consistent with relaxed selection on or neofunctionalization of derived paralogs. In general, ancestral paralogs exhibited greatest expression conservation with chimpanzee orthologs, though exceptions suggest certain derived paralogs may retain or supplant ancestral functions. Concordantly, analysis of long-read isoform sequencing datasets from diverse human tissues and cell lines found that about half of derived paralogs exhibited globally lower expression. To understand mechanisms underlying these differences, we leveraged data from human lymphoblastoid cell lines (LCLs) and found no relationship between paralogous expression divergence and post-transcriptional regulation, sequence divergence, or copy number variation. Considering cis-regulation, we reanalyzed ENCODE data and recovered hundreds of previously unidentified candidate CREs in HSDs. We also generated large-insert ChIP-sequencing data for active chromatin features in an LCL to better distinguish paralogous regions. Some duplicated CREs were sufficient to drive differential reporter activity, suggesting they may contribute to divergent cis-regulation of paralogous genes. This work provides evidence that cis-regulatory divergence contributes to novel expression patterns of recent gene duplicates in humans.

Diverse molecular mechanisms contribute to differential expression of human duplicated genes

ABSTRACTEmerging evidence links genes within human-specific segmental duplications (HSDs) to traits and diseases unique to our species. Strikingly, despite being nearly identical by sequence (>98.5%), paralogous HSD genes are differentially expressed across human cell and tissue types, though the underlying mechanisms have not been examined. Comparing cross-tissue mRNA levels between humans and chimpanzees, we determined that broadly, HSD paralogs (75 genes from 30 families) display expression patterns consistent with pseudo- or neofunctionalization. In general, the ancestral paralog exhibited greatest expression conservation with the chimpanzee ortholog, though exceptions suggest duplicate paralogs that may retain or supplant ancestral functions. To understand mechanisms underlying this observed regulatory divergence, we reanalyzed data from human lymphoblastoid cell lines (LCLs) (n=445), showing that ~75% of derived HSD paralogs exhibit significant differential expression and a greater than two-fold difference from their ancestral counterpart. To identify active cis-regulatory elements (CREs) in HSDs, we reanalyzed ENCODE data to recover hundreds of candidate CREs in these regions. Further, we generated ChIP-seq data for active chromatin features in an LCL using longer Illumina reads to better distinguish peaks in paralogous regions. Some of these duplicated CREs are sufficient to drive differential reporter activity, suggesting they may contribute to divergent cis-regulation of paralogs. This work provides evidence that cis-regulatory divergence contributes to novel expression patterns of recent gene duplicates in humans.

Population-scale study of eRNA transcription reveals bipartite functional enhancer architecture

Enhancer RNAs (eRNA) are unstable non-coding RNAs, transcribed bidirectionally from active regulatory sequences, whose expression levels correlate with enhancer activity. We use capped-nascent-RNA sequencing to efficiently capture bidirectional transcription initiation across several human lymphoblastoid cell lines (Yoruba population) and detect ~75,000 eRNA transcription sites with high sensitivity and specificity. The use of nascent-RNA sequencing sidesteps the confounding effect of eRNA instability. We identify quantitative trait loci (QTLs) associated with the level and directionality of eRNA expression. High-resolution analyses of these two types of QTLs reveal distinct positions of enrichment at the central transcription factor (TF) binding regions and at the flanking eRNA initiation regions, both of which are associated with mRNA expression QTLs. These two regions—the central TF-binding footprint and the eRNA initiation cores—define a bipartite architecture of enhancers, inform enhancer function, and can be used as an indicator of the significance of non-coding regulatory variants.

HPRep: Quantifying reproducibility in HiChIP and PLAC-seq datasets

HiChIP and PLAC-seq are emerging technologies for studying genome-wide long-range chromatin interactions mediated by protein of interest, enabling more sensitive and cost-efficient interrogation of protein-centric chromatin conformation. However, due to the unbalanced read distribution introduced by protein immunoprecipitation, existing reproducibility measures developed for Hi-C data are not appropriate for the analysis of HiChIP and PLAC-seq data.Here, we present HPRep, a stratified and weighted correlation metric derived from normalized contact counts, to quantify reproducibility in HiChIP and PLAC-seq data. We applied HPRep to multiple real datasets and demonstrate that HPRep outperforms existing reproducibility measures developed for Hi-C data. Specifically, we applied HPRep to H3K4me3 PLAC-seq data from mouse embryonic stem cells and mouse brain tissues, as well as H3K27ac HiChIP data from human lymphoblastoid cell line GM12878 and leukemia cell line K562, showing that HPRep can more clearly separate among pseudo-replicates, real replicates, and non-replicates. Furthermore, in an H3K4me3 PLAC-seq dataset consisting of 11 samples from four human brain cell types, HPRep demonstrates expected clustering of data which could not be achieved by existing methods developed for Hi-C data, highlighting the need of a reproducibility metric tailored to HiChIP and PLAC-seq data.

Multiple-endpoint in vitro carcinogenicity test in human cell line TK6 distinguishes carcinogens from non-carcinogens and highlights mechanisms of action

Current in vitro genotoxicity tests can produce misleading positive results, indicating an inability to effectively predict a compound’s subsequent carcinogenic potential in vivo. Such oversensitivity can incur unnecessary in vivo tests to further investigate positive in vitro results, supporting the need to improve in vitro tests to better inform risk assessment. It is increasingly acknowledged that more informative in vitro tests using multiple endpoints may support the correct identification of carcinogenic potential. The present study, therefore, employed a holistic, multiple-endpoint approach using low doses of selected carcinogens and non-carcinogens (0.001–770 µM) to assess whether these chemicals caused perturbations in molecular and cellular endpoints relating to the Hallmarks of Cancer. Endpoints included micronucleus induction, alterations in gene expression, cell cycle dynamics, cell morphology and bioenergetics in the human lymphoblastoid cell line TK6. Carcinogens ochratoxin A and oestradiol produced greater Integrated Signature of Carcinogenicity scores for the combined endpoints than the “misleading” in vitro positive compounds, quercetin, 2,4-dichlorophenol and quinacrine dihydrochloride and toxic non-carcinogens, caffeine, cycloheximide and phenformin HCl. This study provides compelling evidence that carcinogens can successfully be distinguished from non-carcinogens using a holistic in vitro test system. Avoidance of misleading in vitro outcomes could lead to the reduction and replacement of animals in carcinogenicity testing.