Publications

2016

Roccaro, Aldo M, Antonio Sacco, Jiantao Shi, Marco Chiarini, Adriana Perilla-Glen, Salomon Manier, Siobhan Glavey, Yosra Aljawai, Yuji Mishima, Yawara Kawano, Michele Moschetta, Mick Correll, Ma Reina Improgo, Jennifer R Brown, Luisa Imberti, Giuseppe Rossi, Jorge J Castillo, Steven P Treon, Matthew L Freedman, Eliezer M Van Allen, Winston Hide, Elaine Hiller, Irene Rainville, and Irene M Ghobrial. [2016] 2016. “Exome Sequencing Reveals Recurrent Germ Line Variants in Patients With Familial Waldenström Macroglobulinemia..” Blood 127(21):2598-606. doi: 10.1182/blood-2015-11-680199.

Familial aggregation of Waldenström macroglobulinemia (WM) cases, and the clustering of B-cell lymphoproliferative disorders among first-degree relatives of WM patients, has been reported. Nevertheless, the possible contribution of inherited susceptibility to familial WM remains unrevealed. We performed whole exome sequencing on germ line DNA obtained from 4 family members in which coinheritance for WM was documented in 3 of them, and screened additional independent 246 cases by using gene-specific mutation sequencing. Among the shared germ line variants, LAPTM5(c403t) and HCLS1(g496a) were the most recurrent, being present in 3/3 affected members of the index family, detected in 8% of the unrelated familial cases, and present in 0.5% of the nonfamilial cases and in <0.05 of a control population. LAPTM5 and HCLS1 appeared as relevant WM candidate genes that characterized familial WM individuals and were also functionally relevant to the tumor clone. These findings highlight potentially novel contributors for the genetic predisposition to familial WM and indicate that LAPTM5(c403t) and HCLS1(g496a) may represent predisposition alleles in patients with familial WM.

Grasso, Carole, Matthew Anaka, Oliver Hofmann, Ramakrishna Sompallae, Kate Broadley, Winston Hide, Michael Berridge V, Jonathan Cebon, Andreas Behren, and Melanie J McConnell. [2016] 2016. “Iterative Sorting Reveals CD133+ and CD133- Melanoma Cells As Phenotypically Distinct Populations..” BMC Cancer 16(1):726. doi: 10.1186/s12885-016-2759-2.

BACKGROUND: The heterogeneity and tumourigenicity of metastatic melanoma is attributed to a cancer stem cell model, with CD133 considered to be a cancer stem cell marker in melanoma as well as other tumours, but its role has remained controversial.

METHODS: We iteratively sorted CD133+ and CD133- cells from 3 metastatic melanoma cell lines, and observed tumourigenicity and phenotypic characteristics over 7 generations of serial xeno-transplantation in NOD/SCID mice.

RESULTS: We demonstrate that iterative sorting is required to make highly pure populations of CD133+ and CD133- cells from metastatic melanoma, and that these two populations have distinct characteristics not related to the cancer stem cell phenotype. In vitro, gene set enrichment analysis indicated CD133+ cells were related to a proliferative phenotype, whereas CD133- cells were of an invasive phenotype. However, in vivo, serial transplantation of CD133+ and CD133- tumours over 7 generations showed that both populations were equally able to initiate and propagate tumours. Despite this, both populations remained phenotypically distinct, with CD133- cells only able to express CD133 in vivo and not in vitro. Loss of CD133 from the surface of a CD133+ cell was observed in vitro and in vivo, however CD133- cells derived from CD133+ retained the CD133+ phenotype, even in the presence of signals from the tumour microenvironment.

CONCLUSION: We show for the first time the necessity of iterative sorting to isolate pure marker-positive and marker-negative populations for comparative studies, and present evidence that despite CD133+ and CD133- cells being equally tumourigenic, they display distinct phenotypic differences, suggesting CD133 may define a distinct lineage in melanoma.

Salomonis, Nathan, Phillip J Dexheimer, Larsson Omberg, Robin Schroll, Stacy Bush, Jeffrey Huo, Lynn Schriml, Shannan Ho Sui, Mehdi Keddache, Christopher Mayhew, Shiva Kumar Shanmukhappa, James Wells, Kenneth Daily, Shane Hubler, Yuliang Wang, Elias Zambidis, Adam Margolin, Winston Hide, Antonis K Hatzopoulos, Punam Malik, Jose A Cancelas, Bruce J Aronow, and Carolyn Lutzko. [2016] 2016. “Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium..” Stem Cell Reports 7(1):110-25. doi: 10.1016/j.stemcr.2016.05.006.

The rigorous characterization of distinct induced pluripotent stem cells (iPSC) derived from multiple reprogramming technologies, somatic sources, and donors is required to understand potential sources of variability and downstream potential. To achieve this goal, the Progenitor Cell Biology Consortium performed comprehensive experimental and genomic analyses of 58 iPSC from ten laboratories generated using a variety of reprogramming genes, vectors, and cells. Associated global molecular characterization studies identified functionally informative correlations in gene expression, DNA methylation, and/or copy-number variation among key developmental and oncogenic regulators as a result of donor, sex, line stability, reprogramming technology, and cell of origin. Furthermore, X-chromosome inactivation in PSC produced highly correlated differences in teratoma-lineage staining and regulator expression upon differentiation. All experimental results, and raw, processed, and metadata from these analyses, including powerful tools, are interactively accessible from a new online portal at https://www.synapse.org to serve as a reusable resource for the stem cell community.

2015

Karp, Peter D, Bonnie Berger, Diane Kovats, Thomas Lengauer, Michal Linial, Pardis Sabeti, Winston Hide, and Burkhard Rost. [2015] 2015. “ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus..” F1000Research 4:12. doi: 10.12688/f1000research.6038.1.

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida).

Lizio, Marina, Jayson Harshbarger, Hisashi Shimoji, Jessica Severin, Takeya Kasukawa, Serkan Sahin, Imad Abugessaisa, Shiro Fukuda, Fumi Hori, Sachi Ishikawa-Kato, Christopher J Mungall, Erik Arner, Kenneth Baillie, Nicolas Bertin, Hidemasa Bono, Michiel de Hoon, Alexander D Diehl, Emmanuel Dimont, Tom C Freeman, Kaori Fujieda, Winston Hide, Rajaram Kaliyaperumal, Toshiaki Katayama, Timo Lassmann, Terrence F Meehan, Koro Nishikata, Hiromasa Ono, Michael Rehli, Albin Sandelin, Erik A Schultes, Peter A C ’t Hoen, Zuotian Tatum, Mark Thompson, Tetsuro Toyoda, Derek W Wright, Carsten O Daub, Masayoshi Itoh, Piero Carninci, Yoshihide Hayashizaki, Alistair R R Forrest, Hideya Kawaji, and FANTOM Consortium. [2015] 2015. “Gateways to the FANTOM5 Promoter Level Mammalian Expression Atlas..” Genome Biology 16(1):22. doi: 10.1186/s13059-014-0560-6.

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.

Karp, Peter D, Bonnie Berger, Diane Kovats, Thomas Lengauer, Michal Linial, Pardis Sabeti, Winston Hide, and Burkhard Rost. [2015] 2015. “Message from the ISCB: ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus..” Bioinformatics (Oxford, England) 31(4):616-7. doi: 10.1093/bioinformatics/btv019.

UNLABELLED: Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains and three-dimensional protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL).

CONTACT: dkovats@iscb.org or rost@in.tum.de.

Dimont, Emmanuel, Jiantao Shi, Rory Kirchner, and Winston Hide. [2015] 2015. “EdgeRun: an R Package for Sensitive, Functionally Relevant Differential Expression Discovery Using an Unconditional Exact Test..” Bioinformatics (Oxford, England) 31(15):2589-90. doi: 10.1093/bioinformatics/btv209.

Next-generation sequencing platforms for measuring digital expression such as RNA-Seq are displacing traditional microarray-based methods in biological experiments. The detection of differentially expressed genes between groups of biological conditions has led to the development of numerous bioinformatics tools, but so far, few exploit the expanded dynamic range afforded by the new technologies. We present edgeRun, an R package that implements an unconditional exact test that is a more powerful version of the exact test in edgeR. This increase in power is especially pronounced for experiments with as few as two replicates per condition, for genes with low total expression and with large biological coefficient of variation. In comparison with a panel of other tools, edgeRun consistently captures functionally similar differentially expressed genes.

Nishi, Yuichi, Xiaoxiao Zhang, Jieun Jeong, Kevin A Peterson, Anastasia Vedenko, Martha L Bulyk, Winston A Hide, and Andrew P McMahon. [2015] 2015. “A Direct Fate Exclusion Mechanism by Sonic Hedgehog-Regulated Transcriptional Repressors..” Development (Cambridge, England) 142(19):3286-93. doi: 10.1242/dev.124636.

Sonic hedgehog (Shh) signaling patterns the vertebrate spinal cord by activating a group of transcriptional repressors in distinct neural progenitors of somatic motor neuron and interneuron subtypes. To identify the action of this network, we performed a genome-wide analysis of the regulatory actions of three key ventral determinants in mammalian neural tube patterning: Nkx2.2, Nkx6.1 and Olig2. Previous studies have demonstrated that each factor acts predominantly as a transcriptional repressor, at least in part, to inhibit alternative progenitor fate choices. Here, we reveal broad and direct repression of multiple alternative fates as a general mechanism of repressor action. Additionally, the repressor network targets multiple Shh signaling components providing negative feedback to ongoing Shh signaling. Analysis of chromatin organization around Nkx2.2-, Nkx6.1- and Olig2-bound regions, together with co-analysis of engagement of the transcriptional activator Sox2, indicate that repressors bind to, and probably modulate the action of, neural enhancers. Together, the data suggest a model for neural progenitor specification downstream of Shh signaling, in which Nkx2.2 and Olig2 direct repression of alternative neural progenitor fate determinants, an action augmented by the overlapping activity of Nkx6.1 in each cell type. Integration of repressor and activator inputs, notably activator inputs mediated by Sox2, is probably a key mechanism in achieving cell type-specific transcriptional outcomes in mammalian neural progenitor fate specification.

Singh, Nakul, Arun D Singh, and Winston Hide. [2015] 2015. “Inferring an Evolutionary Tree of Uveal Melanoma From Genomic Copy Number Aberrations..” Investigative Ophthalmology & Visual Science 56(11):6801-9. doi: 10.1167/iovs.15-16822.

PURPOSE: The purpose of this study is to study the genomic evolution of primary uveal melanoma.

METHODS: Primary uveal melanoma genomic DNA was assayed on the Illumina Human660W-Quad v1.0 DNA Analysis BeadChip. Raw signal intensity data were quantile normalized to estimate copy number aberration with the Genome Alteration Print algorithm. Distance between samples was calculated as the Manhattan distance between the copy number profiles of the tumors. From the distance matrix, a phylogenetic network (evolutionary relationship inference) was estimated using SplitsTree4.

RESULTS: Of the 57 tumors, one (1.8%) was discarded because of a failed assay, and seven (12.3%) were revealed to be mixtures of several cell populations that could not be resolved. Three clades of tumor were identified (A [59.2%], B [32.7%], and C [6.1%]), each following a distinct evolutionary path and each associated with metastatic status (P = 0.01). One tumor (2.0%) did not fit into any clade. From a normal diploid melanocyte, a few tumors (clade C) lose a large portion of chromosome 6q, but do not develop any mutations on 8q. In an alternate path, the vast majority of tumors (clade A and clade B [91.9%]) gain a copy of the telomeric half of 8q. A majority of these tumors (clade A) subsequently lose a copy of chromosome 3, as well as gain the centromeric half of 8q. The other tumors (clade B) gain copies of 6p, as well as regions on 11p and 22q.

CONCLUSIONS: Our data suggest that there is little overlap in the subtypes of uveal melanoma after divergence (identified as clades A and B) and that these distinct subtypes are not likely to crossover or transform from one major clade to another.

2014

Zook, Justin M, Brad Chapman, Jason Wang, David Mittelman, Oliver Hofmann, Winston Hide, and Marc Salit. [2014] 2014. “Integrating Human Sequence Data Sets Provides a Resource of Benchmark SNP and Indel Genotype Calls..” Nature Biotechnology 32(3):246-51. doi: 10.1038/nbt.2835.

Clinical adoption of human genome sequencing requires methods that output genotypes with known accuracy at millions or billions of positions across a genome. Because of substantial discordance among calls made by existing sequencing methods and algorithms, there is a need for a highly accurate set of genotypes across a genome that can be used as a benchmark. Here we present methods to make high-confidence, single-nucleotide polymorphism (SNP), indel and homozygous reference genotype calls for NA12878, the pilot genome for the Genome in a Bottle Consortium. We minimize bias toward any method by integrating and arbitrating between 14 data sets from five sequencing technologies, seven read mappers and three variant callers. We identify regions for which no confident genotype call could be made, and classify them into different categories based on reasons for uncertainty. Our genotype calls are publicly available on the Genome Comparison and Analytic Testing website to enable real-time benchmarking of any method.