High-resolution, single-cell DNA domain analysis in vivo, identify domain structures that change with cell identity

Visualizing DNA folding and RNA in embryos at single-cell resolution

Leslie J. Mateo, Sedona E. Murphy, Antonina Hafner, Isaac S. Cinquini, Carly A. Walker & Alistair N. Boettiger Nature (Research Article)

Abstract

The establishment of cell types during development requires precise interactions between genes and distal regulatory sequences. We have a limited understanding of how these interactions look in three dimensions, vary across cell types in complex tissue, and relate to transcription. Here we describe optical reconstruction of chromatin architecture (ORCA), a method that can trace the DNA path in single cells with nanoscale accuracy and genomic resolution reaching two kilobases. We used ORCA to study a Hox gene cluster in cryosectioned Drosophila embryos and labelled around 30 RNA species in parallel. We identified cell-type-specific physical borders between active and Polycomb-repressed DNA, and unexpected Polycomb-independent borders. Deletion of Polycomb-independent borders led to ectopic enhancer–promoter contacts, aberrant gene expression, and developmental defects. Together, these results illustrate an approach for high-resolution, single-cell DNA domain analysis in vivo, identify domain structures that change with cell identity, and show that border elements contribute to the formation of physical domains in Drosophila.

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‘Jumping genes’ drive many cancers

‘Jumping genes’ drive many cancers

Mistakes in DNA are known to drive cancer growth. But a new study, from Washington University School of Medicine in St. Louis, heavily implicates a genetic phenomenon commonly known as “jumping genes” in the growth of tumors.

The study is published March 29 in the journal Nature Genetics.

Since jumping genes aren’t mutations — mistakes in the letters of the DNA sequence — they can’t be identified by traditional cancer genome sequencing. As such, this study opens up new lines of research for future cancer therapies that might target such genes.

Jumping genes, which scientists call transposable elements, are short sections of the DNA sequence that have been incorporated randomly into the genome over the long course of human evolution. The evolutionary histories of jumping genes are the subject of much current research, but viral infection is thought to play an important role in their origins.

Researchers led by Ting Wang, PhD, the Sanford C. and Karen P. Loewentheil Distinguished Professor of Medicine, have plumbed genomic databases, looking specifically for tumors whose jumping genes are driving cancer growth.

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Specificity helps with cancer outcome prediction, therapies

Acute Erythroleukemia Genomic Subtypes Help Predict Outcomes, Suggest Therapies

NEW YORK (GenomeWeb) – A new genomic analysis of acute erythroid leukemia (AEL) has uncovered recurrent tumor gene mutation and expression profiles, including genomic features that appear to coincide with outcomes for patients affected by the rare, difficult-to-treat form of acute myeloid leukemia (AML).

"These results mark a new era in understanding and treatment of AEL, an aggressive leukemia that has been plagued by diagnostic controversy and poor outcomes," senior author Charles Mullighan, a pathology researcher and co-leader of the St. Jude Children's Research Hospital's hematological malignancies program, said in a statement. 

As they reported online today in Nature Genetics, Mullighan and colleagues performed whole-genome, exome, targeted, and transcriptome sequencing on samples from 159 pediatric or adult AEL patients treated at sites around the world, comparing the somatic mutations and gene expression patterns they found to those in samples from more than 1,900 individuals with non-AEL conditions — from other forms of AML to myelodysplastic syndrome.

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Origins and Evolution of Mental Health Genetic Variants

Illumina and the Lundbeck Foundation GeoGenetics Centre Collaborate to Generate One of the Largest Ancient Genome Datasets to Decode the Genetic Origins and Evolution of Mental Health Issues

SAN DIEGO--(BUSINESS WIRE)--Illumina (NASDAQ:ILMN) and the Lundbeck Foundation GeoGenetics Centre at the University of Copenhagen, Denmark partner to explore the relationship between the evolutionary history of select mental and neurological disorders and infectious pathogens. One of the first projects of its kind worldwide, the endeavor aims to acquire new knowledge in terms of the medical and biological understanding of special factors underlying the development of human neuropsychiatric diseases through the ages. Ultimately, the project may provide a new approach to the development of medicines and other therapeutic treatments for mental and neurological conditions.

Where do brain disorders come from? In an effort to shed light on the role of microbes in the pathogenesis of neuropsychiatric illnesses, such as Alzheimer’s disease and schizophrenia, Professor Eske Willerslev and his team will build one of the largest genomic datasets of its kind, by complete DNA mapping of thousands of ancient Eurasian human remains. The data will be obtained from bones and teeth, the oldest remains dating back 10,000 years.

The international, multi-disciplinary team of scientists, which includes specialists in ancient genomics, neuro-genetics, population genetics, archaeology, linguistics, and experts in brain health, among others, will focus on creating two unique subsets of genomic data. The first panel is a 5,000 ancient human genomes panel. The second panel will consist of ancient pathogen DNA that is associated with human diseases. Both panels, which will be made publicly available, will together advance our understanding of the evolution of disease variance and its interaction with the human genome and pathogen pressure. The project will generate and analyze one of the largest sets of ancient human and pathogen genome panels ever created.

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Mapping the pharmacogenomic drug response landscape

Encircling the regions of the pharmacogenomic landscape that determine drug response

Adrià Fernández-Torras, Miquel Duran-Frigola & Patrick Aloy

Genome Medicine (Research Article)

Background

The integration of large-scale drug sensitivity screens and genome-wide experiments is changing the field of pharmacogenomics, revealing molecular determinants of drug response without the need for previous knowledge about drug action. In particular, transcriptional signatures of drug sensitivity may guide drug repositioning, prioritize drug combinations, and point to new therapeutic biomarkers. However, the inherent complexity of transcriptional signatures, with thousands of differentially expressed genes, makes them hard to interpret, thus giving poor mechanistic insights and hampering translation to clinics.

Methods

To simplify drug signatures, we have developed a network-based methodology to identify functionally coherent gene modules. Our strategy starts with the calculation of drug-gene correlations and is followed by a pathway-oriented filtering and a network-diffusion analysis across the interactome.

Results

We apply our approach to 189 drugs tested in 671 cancer cell lines and observe a connection between gene expression levels of the modules and mechanisms of action of the drugs. Further, we characterize multiple aspects of the modules, including their functional categories, tissue-specificity, and prevalence in clinics. Finally, we prove the predictive capability of the modules and demonstrate how they can be used as gene sets in conventional enrichment analyses.

Conclusions

Network biology strategies like module detection are able to digest the outcome of large-scale pharmacogenomic initiatives, thereby contributing to their interpretability and improving the characterization of the drugs screened.

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Hope in the fight against Glioblastoma

New Strategies Take On the Worst Cancer—Glioblastoma

““The most common form of malignant brain cancer—called a glioblastoma—is notoriously wily and considered the deadliest human cancer. Glioblastomas charge their way into normal brain tissue diffusely and erratically, making them surgical nightmares. And they mutate at such a rapid rate that most currently available cancer treatments can't keep up with them. Even neighboring tumor cells can be genetically distinct, and therefore hard to target with a single therapy. 

Survival rates from glioblastomas enjoyed a modest bump in the 1980s when radiation became a standard part of the treatment protocol. Patients could expect to live for nearly another year after diagnosis, up from just four to six months. The introduction of the chemotherapy drug temozolomide in the 2000s increased survival another few months. But since then patient survival rates have stalled… many experts insist the key to beating glioblastoma will entail personalizing care to a patient’s individual tumor and the particular molecular signature of a cancer.

One method of testing cancer therapies, including glioblastomas, has been so-called “ex vivo” cancer models, in which malignant cells are probed in the lab. Also known as tumor “avatars,” they allow researchers to test a drug on patients’ cancer cells before introducing it into their bodies. A number of ex vivo models have been tried over the years: culturing tumor cells in Petri dishes; grafting them into animal models; even growing “organoids” (three-dimensional tumors grown on a supporting matrix). These techniques have seen varying success depending on the tumor type at hand, but none have proven especially helpful for glioblastoma.

A report on new research technology published recently in the journal Nature Biomedical Engineering may address the limitations of previous ex vivo approaches. In short, researchers have concocted a glioblastoma-on-a-chip. Chip-based models of various organs and diseases—including many cancers—have debuted in the last few years. They are constructed by lining a plastic microchip with live human cells that mimic a particular organ or disease in order to simplify, cheapen and increase the efficiency of drug testing. The Wyss Institute at Harvard University and other groups have made impressive headway in developing a number of chip-based biologic models. Chip models of the lung, the intestine, skin, bone marrow ALS—even the blood-brain barrier—have been tested.”

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The Banana Genome Browser is Online

This may not be particularly useful for most readers, but you should check it out simply because it is the Banana Genome Hub.

Check it out …

Where mutations are not tolerated: a good summary of an outstanding study

Big datasets pinpoint new regions to explore the genome for disease

A dataset of more than 100,000 individuals allows researchers to identify genetic regions that are intolerant to change and may underlie developmental disorders.

Imagine rain falling on a square of sidewalk. While the raindrops appear to land randomly, over time a patch of sidewalk somehow remains dry. The emerging pattern suggests something special about this region. This analogy is akin to a new method devised by researchers at University of Utah Health. They explored more than 100,000 healthy humans to identify regions of our genes that are intolerant to change. They believe that DNA mutations in these "constrained" regions may cause severe pediatric diseases.

"Instead of focusing on where DNA changes are, we looked for parts of genes where DNA changes are not," said Aaron Quinlan, Ph.D., associate professor of Human Genetics and Biomedical Informatics at U of U Health and associate director of the USTAR Center for Genetic Discovery. "Our model searches for exceptions to the rule of dense genetic variation in this massive dataset to reveal constrained regions of genes that are devoid of variation. We believe these regions may be lethal or cause extreme phenotypes of disease when mutated."

While this approach is conceptually simple, only recently has there been enough human genomes available to make it happen. These new, invariable stretches may reveal new disease-causing genes and can be used to help pinpoint the cause of disease in patients with developmental disorders. The results of this study are available online in the December 10 issue of the journal Nature Genetics.

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Targeting Brain Tumors with Single-Cell RNA-seq

Brain Tumors Through the Single-Cell RNA Sequencing Lens: Researcher Interview with Mario Suvà

Read Peggy Wang’s interview with Mario Suvà for the National Cancer Institute. Dr. Suvà is an assistant professor of pathology at Massachusetts General Hospital and Harvard Medical School, an Institute Member at the Broad Institute, and uses single-cell RNA sequencing as a discovery tool for understanding brain cancer. Lean more about his work and this powerful new approach to understanding this important disease…

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New advance increasing the effectiveness of immunotherapies for cancer treatment

Harnessing T-cell “stemness” could enhance cancer immunotherapy

A new study led by scientists in the Center for Cancer Research (CCR) at the National Cancer Institute (NCI) sheds light on one way tumors may continue to grow despite the presence of cancer-killing immune cells. The findings, published March 29, 2019, in Science, suggest a way to enhance the effectiveness of immunotherapies for cancer treatment. NCI is part of the National Institutes of Health.

Dying cancer cells release the chemical potassium, which can reach high levels in some tumors. The research team reported that elevated potassium causes T cells to maintain a stem-cell-like quality, or “stemness,” that is closely tied to their ability to eliminate cancer during immunotherapy. The findings suggest that increasing T cells’ exposure to potassium—or mimicking the effects of high potassium—could make cancer immunotherapies more effective.

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BRCA Challenge creates database for fighting cancer

BRCA Exchange aggregates data on thousands of BRCA variants to inform understanding of cancer risk

A global resource that includes data on thousands of inherited variants in the BRCA1 and BRCA2 genes is available to the public. The BRCA Exchange was created through the BRCA Challenge, a long-term demonstration project initiated by the Global Alliance for Genomics and Health (GA4GH) to enhance sharing of BRCA1 andBRCA2 data. The resource, available through a website and a new smartphone appExit Disclaimer, allows clinicians to review expert classifications of variants in these major cancer predisposition genes as part of their individual assessment of complex questions related to cancer prevention, screening, and intervention for high-risk patients. 

The five-year BRCA Challenge project was funded in part by the National Cancer Institute (NCI), part of the National Institutes of Health, and through the Cancer Moonshot℠. A paper detailing the development of the BRCA Exchange was published January 8, 2019, in PLOS Genetics. READ MORE …

Common variants in ovarian tumors

Identifying Genetic Similarities in Tumors May Shed Light on Spread of Ovarian Cancer

Researchers define the genetic characteristics of ovarian tumors-- information that could lead to new opportunities for personalized therapy and may explain why screening programs for the disease haven’t been successful.

BY KATIE KOSKO

Yale Cancer Center researchers have defined the genetic characteristics of ovarian tumors, information that could lead to new opportunities for personalized therapy, according to study findings published in Proceedings of the National Academy of Science.

The team examined 64 primary, 41 metastatic and 17 recurrent tumors from 77 patients and then matched them with normal DNA by whole-exome sequencing, which is a technique for sequencing all the protein-coding region of genes in a genome.

The researchers identified several genes, including c-MYC and PIK3CA, that are frequently mutated in primary-metastatic and chemotherapy-resistant ovarian tumors.

In addition, about half of the patients harbored a germinal (inherited) or somatic (an alteration in DNA that occurs after conception) damaging mutation in a repair gene involved in predisposition to ovarian cancer.

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CRISPR cuts 13,000 times in one cell

Genome engineers made more than 13,000 CRISPR edits in a single cell

Rewriting Life

A team at George Church’s Harvard lab wants to redesign species with large-scale DNA changes.

by Antonio Regalado (MIT Technology Review)

Since its invention, CRISPR has let scientists introduce DNA changes at specific locations in a genome. Often these precise changes are made one at a time.

Perhaps not for much longer. A team at Harvard University says it has used the technique to make 13,200 genetic alterations to a single cell, a record for the gene-editing technology.

The group, led by gene technologist George Church, wants to rewrite genomes at a far larger scale than has currently been possible, something it says could ultimately lead to the “radical redesign” of species—even humans. Large-scale gene editing of this sort has been tried before. In 2017, an Australian team led by Paul Thomas peppered the Y chromosome of mice with edits and succeeded in blasting it out of existence. That strategy is being eyed as a potential treatment for Down syndrome, a genetic disorder caused by an extra chromosome.

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NGS-heavy investigation of Neuropsychiatric Disease

Illumina, University of Copenhagen to Study Genetic Evolution of Neuropsychiatric Disease

NEW YORK (GenomeWeb) – Illumina said today that it is working with the Lundbeck Foundation GeoGenetics Centre at the University of Copenhagen to study how infectious pathogens influenced the evolutionary history of certain mental and neurological disorders.

An international, multi-disciplinary team including specialists in ancient genomics, neurogenetics, population genetics, archaeology, linguistics, and brain health will create two subsets of genomics data: one consisting of 5,000 ancient human genomes, and another consisting of ancient pathogen DNA associated with human diseases. Both datasets will be made publicly available.

The research team will use Illumina's NovaSeq 6000 system with S4 flow cells to sequence up to 20 billion ancient DNA fragments every two days, Illumina said.

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Functional genomics of Diabetes SNPs

Risk variants disrupting enhancers of TH1 and TREG cells in type 1 diabetes

Peng Gao, Yasin Uzun, Bing He, Sarah E. Salamati, Julie K. M. Coffey, Eva Tsalikian, & Kai Tan

PNAS (Research Article)

Functional interpretation of noncoding genetic variants identified by genome-wide association studies is a major challenge in human genetics and gene regulation. We generated epigenomics data using primary cells from type 1 diabetes patients. Using these data, we identified and validated multiple novel risk variants for this disease. In addition, our ranked list of candidate risk SNPs represents the most comprehensive annotation based on T1D-specific T-cell data. Because many autoimmune diseases share some genetic underpinnings, our dataset may be used to understand causal noncoding mutations in related autoimmune diseases.

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Mushroom multicellularity illuminated by gene expression analysis

Transcriptomic atlas of mushroom development reveals conserved genes behind complex multicellularity in fungi

Krisztina Krizsán, Éva Almási, Zsolt Merényi, Neha Sahu, Máté Virágh, Tamás Kószó, Stephen Mondo, Brigitta Kiss, Balázs Bálint, Ursula Kües, Kerrie Barry, Judit Cseklye, Botond Hegedüs, Bernard Henrissat, Jenifer Johnson, Anna Lipzen, Robin A. Ohm, István Nagy, Jasmyn Pangilinan, Juying Yan, Yi Xiong, Igor V. Grigoriev, David S. Hibbett, and László G. Nagy

PNAS (Research Article)

Complex multicellularity is a major evolutionary innovation in the history of life. Mushroom-forming fungi (Agaricomycetes) represent one of the most diverse complex multicellular clades, yet the genetic bases and evolutionary origins of their multicellular development are hardly known. We used readouts of gene expression in six species to find genes with a dynamic expression during the development of fruiting bodies. Comparisons across species and to 200 fungal genomes identified the gene families with a conserved expression dynamics in multicellular fruiting bodies and their ancient evolutionary origins. These data outline the major multicellularity-related and developmental processes of mushrooms, including the role of transcriptional reprogramming, gene coexpression networks, and alternative splicing, and reveal significant convergence with other complex multicellular lineages.

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Paternal mitochondrial contributions may be just as rare as we always thought

Extraordinary claims require extraordinary evidence in the case of asserted mtDNA biparental inheritance

Antonio Salas, Sebastian Schoenherr, Hans Jurgen Bandelt, View ORCID ProfileAlberto Gomez-Carballa, & Hansi Weissensteiner

bioRxiv (Research Article)

Abstract—A breakthrough article published in PNAS by Luo et al. (2018) challenges a central dogma in biology which states that the mitochondrial DNA (mtDNA) is inherited exclusively from the mother. By sequencing the mitogenomes of several members of three independent families, the authors inferred an unprecedented pattern of biparental inheritance that requires the participation of an autosomal nuclear factor in the molecular process. However, a comprehensive analysis of their data reveals a number of issues that must be carefully addressed before challenging the current paradigm. Unfortunately, the methods section lacks any description of sample management, validation of their results in independent laboratories was deficient, and the reported findings have been observed at a frequency at complete variance with established evidence. Moreover, the remarkably high (and unusually homogeneous) levels of heteroplasmy reported can be readily detected using classical techniques for DNA sequencing. By reassessing the raw sequencing data with an alternative computational pipeline, we report strong correlation to the NextGENe results provided by the authors on a per sample base. However, the sequencing replicates from the same donors show aberrations in the variants detected that need further investigation to exclude contributions from other sources or methodological artifacts. Finally, applying the principle of reductio ad absurdum, we demonstrate that the nuclear factor invoked by the authors would need to be extraordinarily complex and precise in order to preclude linear accumulation of mtDNA lineages across generations. We discuss alternate scenarios that explain findings of the same nature as reported by Luo et al., in the context of in-vitro fertilization and therapeutic mtDNA replacement ooplasmic transplantation.

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Good review of major microbial genome web portals

A Comparison of Microbial Genome Web Portals

Peter D. Karp, Natalia Ivanova, Markus Krummenacker, Nikos Kyrpides, Mario Latendresse, Peter Midford, Wai Kit Ong, Suzanne Paley, & Rekha Seshadri

Frontiers in Microbiology (Research Article)

Microbial genome web portals have a broad range of capabilities that address a number of information-finding and analysis needs for scientists. This article compares the capabilities of the major microbial genome web portals to aid researchers in determining which portal(s) are best suited to their needs. We assessed both the bioinformatics tools and the data content of BioCyc, KEGG, Ensembl Bacteria, KBase, IMG, and PATRIC. For each portal, our assessment compared and tallied the available capabilities. The strengths of BioCyc include its genomic and metabolic tools, multi-search capabilities, table-based analysis tools, regulatory network tools and data, omics data analysis tools, breadth of data content, and large amount of curated data. The strengths of KEGG include its genomic and metabolic tools. The strengths of Ensembl Bacteria include its genomic tools and large number of genomes. The strengths of KBase include its genomic tools and metabolic models. The strengths of IMG include its genomic tools, multi-search capabilities, large number of genomes, table-based analysis tools, and breadth of data content. The strengths of PATRIC include its large number of genomes, table-based analysis tools, metabolic models, and breadth of data content.

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Gene interactions are a potential key to personalized medicine

Gene interactions identified as personalized medicine’s missing link

“The ability to affordably sequence genomes has prompted numerous predictions about the rise of personalised medicine, however so far this has failed to come to pass. But in research published today, scientists have identified gene interactions as the key barrier to this medical revolution taking off.

Personalised medicine, where individuals are prescribed pharmaceuticals based on their own genetic makeup, has been raised as a possibility since the Human Genome Project was completed in 2003. It was thought that as more people had their genomes sequenced scientists would unearth genes responsible for predispositions to specific diseases, which would enable medication to be tailored to individuals.

However, while tens of thousands of people around the world have now had their genomes sequenced, it has not produced the clear genetic interactions initially predicted. And the reason for this is gene interactions: how different genes impact each other in the results and responses they produce.”

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Single sperm sequencing to understand meiotic recombination

Factors influencing meiotic recombination revealed by whole-genome sequencing of single sperm

Anjali Gupta Hinch, Gang Zhang, Philipp W. Becker, Daniela Moralli, Robert Hinch, Benjamin Davies, Rory Bowden, & Peter Donnelly

Science (Research Article)

Sequencing and the single sperm

During meiosis, homologous chromosomes undergo doublestrand breaks in DNA that can cross over, shuffling genetic material. However, not every double-strand break resolves in a crossover event. Hinch et al. wanted to determine the rules governing DNA recombination. They developed a method to sequence individual mouse sperm and applied it to mice carrying two different alleles of a protein involved in mammalian crossovers. A high-resolution genetic map revealed the relationships between the distribution of crossovers, proteins involved in recombination, and specific factors determining whether a double-strand break becomes a crossover.

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