Damek V. Spacek

Extensive variation in chromatin states across humans.

DNA Differences The extent to which genetic variation affects an individuals phenotype has been difficult to predict because the majority of variation lies outside the coding regions of genes. Now, three studies examine the extent to which genetic variation affects the chromatin of individuals with diverse ancestry and genetic variation (see the Perspective by Furey and Sethupathy). Kasowski et al. (p. 750, published online 17 October) examined how genetic variation affects differences in chromatin states and their correlation to histone modifications, as well as more general DNA binding factors. Kilpinen et al. (p. 744, published online 17 October) document how genetic variation is linked to allelic specificity in transcription factor binding, histone modifications, and transcription. McVicker et al. (p. 747, published online 17 October) identified how quantitative trait loci affect histone modifications in Yoruban individuals and established which specific transcription factors affect such modifications. Variability among humans with different ancestry affects chromatin states and gene expression. [Also see Perspective by Furey and Sethupathy] The majority of disease-associated variants lie outside protein-coding regions, suggesting a link between variation in regulatory regions and disease predisposition. We studied differences in chromatin states using five histone modifications, cohesin, and CTCF in lymphoblastoid lines from 19 individuals of diverse ancestry. We found extensive signal variation in regulatory regions, which often switch between active and repressed states across individuals. Enhancer activity is particularly diverse among individuals, whereas gene expression remains relatively stable. Chromatin variability shows genetic inheritance in trios, correlates with genetic variation and population divergence, and is associated with disruptions of transcription factor binding motifs. Overall, our results provide insights into chromatin variation among humans.

High-Throughput Sequencing Technologies

The human genome sequence has profoundly altered our understanding of biology, human diversity, and disease. The path from the first draft sequence to our nascent era of personal genomes and genomic medicine has been made possible only because of the extraordinary advancements in DNA sequencing technologies over the past 10 years. Here, we discuss commonly used high-throughput sequencing platforms, the growing array of sequencing assays developed around them, as well as the challenges facing current sequencing platforms and their clinical application.

Recurrent somatic mutations in regulatory regions of human cancer genomes

Aberrant regulation of gene expression in cancer can promote survival and proliferation of cancer cells. Here we integrate whole-genome sequencing data from The Cancer Genome Atlas (TCGA) for 436 patients from 8 cancer subtypes with ENCODE and other regulatory annotations to identify point mutations in regulatory regions. We find evidence for positive selection of mutations in transcription factor binding sites, consistent with these sites regulating important cancer cell functions. Using a new method that adjusts for sample- and genomic locus–specific mutation rates, we identify recurrently mutated sites across individuals with cancer. Mutated regulatory sites include known sites in the TERT promoter and many new sites, including a subset in proximity to cancer-related genes. In reporter assays, two new sites display decreased enhancer activity upon mutation. These data demonstrate that many regulatory regions contain mutations under selective pressure and suggest a greater role for regulatory mutations in cancer than previously appreciated.

Inhibition of Pluripotency Networks by the Rb Tumor Suppressor Restricts Reprogramming and Tumorigenesis

Mutations in the retinoblastoma tumor suppressor gene Rb are involved in many forms of human cancer. In this study, we investigated the early consequences of inactivating Rb in the context of cellular reprogramming. We found that Rb inactivation promotes the reprogramming of differentiated cells to a pluripotent state. Unexpectedly, this effect is cell cycle independent, and instead reflects direct binding of Rb to pluripotency genes, including Sox2 and Oct4, which leads to a repressed chromatin state. More broadly, this regulation of pluripotency networks and Sox2 in particular is critical for the initiation of tumors upon loss of Rb in mice. These studies therefore identify Rb as a global transcriptional repressor of pluripotency networks, providing a molecular basis for previous reports about its involvement in cell fate pliability, and implicate misregulation of pluripotency factors such as Sox2 in tumorigenesis related to loss of Rb function.

Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans

Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding, and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy--many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation.

Simul-seq: combined DNA and RNA sequencing for whole-genome and transcriptome profiling

Paired DNA and RNA profiling is increasingly employed in genomics research to uncover molecular mechanisms of disease and to explore personal genotype and phenotype correlations. Here, we introduce Simul-seq, a technique for the production of high-quality whole-genome and transcriptome sequencing libraries from small quantities of cells or tissues. We apply the method to laser-capture-microdissected esophageal adenocarcinoma tissue, revealing a highly aneuploid tumor genome with extensive blocks of increased homozygosity and corresponding increases in allele-specific expression. Among this widespread allele-specific expression, we identify germline polymorphisms that are associated with response to cancer therapies. We further leverage this integrative data to uncover expressed mutations in several known cancer genes as well as a recurrent mutation in the motor domain of KIF3B that significantly affects kinesin–microtubule interactions. Simul-seq provides a new streamlined approach for generating comprehensive genome and transcriptome profiles from limited quantities of clinically relevant samples.

Emerging Technologies to Study Long Non-coding RNAs

It has been less than half a century since Robert W. Holley et al. used 140 kg of commercial baker’s yeast to characterize the first noncoding RNA (ncRNA), alanine tRNA. Now, 48 years later, advancements in genomic technologies have enabled scientists to study genomes, transcriptomes, and proteomes, on an unprecedented and high-throughput scale, and even at the single cell resolution. These discoveries have completely changed the classical view of the central dogma of molecular biology, as we now understand that protein coding genes account for less than 2 % of human genome, however, the vast majority of the genome is transcribed (Clark et al. 2011) {Lander, 2001 #41}. This means that the bulk of the genome encodes for ncRNA molecules, which can be further categorized into housekeeping and regulatory ncRNAs. The latter can be broadly classified based on their size as small ncRNAs ( 200 bp) (Nagano and Fraser 2011; Ponting et al. 2009). Many of the small ncRNAs have been identified and their mechanism of action has been heavily studied. However, the journey to study the lncRNAs has just begun (Gupta et al. 2010; Wilusz et al. 2009; Derrien et al. 2012).