Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing

Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (~1.5–5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing

A High-Throughput Chromatin Immunoprecipitation Approach Reveals Principles of Dynamic Gene Regulation in Mammals

Understanding the principles governing mammalian gene regulation has been hampered by the difficulty in measuring in vivo binding dynamics of large numbers of transcription factors (TF) to DNA. Here, we develop a high-throughput Chromatin ImmunoPrecipitation (HT-ChIP) method to systematically map protein-DNA interactions. HT-ChIP was applied to define the dynamics of DNA binding by 25 TFs and 4 chromatin marks at 4 time-points following pathogen stimulus of dendritic cells. Analyzing over 180,000 TF-DNA interactions we find that TFs vary substantially in their temporal binding landscapes. This data suggests a model for transcription regulation whereby TF networks are hierarchically organized into cell differentiation factors, factors that bind targets prior to stimulus to prime them for induction, and factors that regulate specific gene programs. Overlaying HT-ChIP data on gene-expression dynamics shows that many TF-DNA interactions are established prior to the stimuli, predominantly at immediate-early genes, and identified specific TF ensembles that coordinately regulate gene-induction

Cell scientist to watch – Mitchell Guttman

Mitchell received a bachelor's degree in molecular and computational biology and a master's degree in computational biology and bioinformatics from the University of Pennsylvania. He then joined the laboratory of Eric Lander at the Broad Institute of MIT and Harvard and was awarded his PhD in 2012. The same year he was named in the Forbes ‘30 under 30: science and healthcare’ list of rising stars and received an NIH early independence award. Mitchell subsequently moved to the California Institute of Technology as an Assistant Professor to establish his own laboratory. He has received numerous awards, including being named a Robertson Investigator of the New York Stem Cell Foundation, an Investigator at the Heritage Medical Research Institute and a Pew-Stewart scholar for cancer research in 2015. Having identified and characterised a new class of functional large non-coding RNA (lncRNA) genes, his laboratory aims to understand the mechanisms by which lncRNAs act to control cellular functions through regulation of proteins, binding to genomic DNA targets and contributing to nuclear organisation

A high-resolution map of human evolutionary constraint using 29 mammals

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ~4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ~60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease

Methods for comprehensive experimental identification of RNA-protein interactions

The importance of RNA-protein interactions in controlling mRNA regulation and non-coding RNA function is increasingly appreciated. A variety of methods exist to comprehensively define RNA-protein interactions. We describe these methods and the considerations required for designing and interpreting these experiments

Computational methods for transcriptome annotation and quantification using RNA-seq

High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications

Quantifying the impact of climate change on drought regimes using the Standardised Precipitation Index

The study presents a methodology to characterise short- or long-term drought events, designed to aid understanding of how climate change may affect future risk. An indicator of drought magnitude, combining parameters of duration, spatial extent and intensity, is presented based on the Standardised Precipitation Index (SPI). The SPI is applied to observed (1955–2003) and projected (2003–2050) precipitation data from the Community Integrated Assessment System (CIAS). Potential consequences of climate change on drought regimes in Australia, Brazil, China, Ethiopia, India, Spain, Portugal and the USA are quantified. Uncertainty is assessed by emulating a range of global circulation models to project climate change. Further uncertainty is addressed through the use of a high-emission scenario and a low stabilisation scenario representing a stringent mitigation policy. Climate change was shown to have a larger effect on the duration and magnitude of long-term droughts, and Australia, Brazil, Spain, Portugal and the USA were highlighted as being particularly vulnerable to multi-year drought events, with the potential for drought magnitude to exceed historical experience. The study highlights the characteristics of drought which may be more sensitive under climate change. For example, on average, short-term droughts in the USA do not become more intense but are projected to increase in duration. Importantly, the stringent mitigation scenario had limited effect on drought regimes in the first half of the twenty-first century, showing that adaptation to drought risk will be vital in these regions

Xist recruits the X chromosome to the nuclear lamina to enable chromosome-wide silencing

The Xist long noncoding RNA orchestrates X chromosome inactivation, a process that entails chromosome-wide silencing and remodeling of the three-dimensional (3D) structure of the X chromosome. Yet, it remains unclear whether these changes in nuclear structure are mediated by Xist and whether they are required for silencing. Here, we show that Xist directly interacts with the Lamin B receptor, an integral component of the nuclear lamina, and that this interaction is required for Xist-mediated silencing by recruiting the inactive X to the nuclear lamina and by doing so enables Xist to spread to actively transcribed genes across the X. Our results demonstrate that lamina recruitment changes the 3D structure of DNA, enabling Xist and its silencing proteins to spread across the X to silence transcription

Approaches for Understanding the Mechanisms of Long Noncoding RNA Regulation of Gene Expression

Mammalian genomes encode tens of thousands of long noncoding RNAs (lncRNAs) that have been implicated in a diverse array of biological processes and human diseases. In recent years, the development of new tools for studying lncRNAs has enabled important progress in defining the mechanisms by which Xist and other lncRNAs function. This collective work provides a framework for how to define the mechanisms by which lncRNAs act. This includes defining lncRNA function, identifying and characterizing lncRNA–protein interactions, and lncRNA localization in the cell. In this review, we discuss various experimental approaches for deciphering lncRNA mechanisms and discuss issues and limitations in interpreting these results. We explore what these data can reveal about lncRNA function and mechanism as well as emerging insights into lncRNA biology that have been derived from these studies

Integrative Genomics Viewer

Author Manuscript 2012 May 07.To the Editor: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.National Institute of General Medical Sciences (U.S.) (R01GM074024)National Cancer Institute (U.S.) (R21CA135827)National Human Genome Research Institute (U.S.) (U54HG003067