Genetic heterogeneity of induced pluripotent stem cells: results from 24 clones derived from a single C57BL/6 mouse.

This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.0120585Induced pluripotent stem cells (iPSCs) have tremendous potential as a tool for disease modeling, drug testing, and other applications. Since the generation of iPSCs "captures" the genetic history of the individual cell that was reprogrammed, iPSC clones (even those derived from the same individual) would be expected to demonstrate genetic heterogeneity. To assess the degree of genetic heterogeneity, and to determine whether some cells are more genetically "fit" for reprogramming, we performed exome sequencing on 24 mouse iPSC clones derived from skin fibroblasts obtained from two different sites of the same 8-week-old C57BL/6J male mouse. While no differences in the coding regions were detected in the two parental fibroblast pools, each clone had a unique genetic signature with a wide range of heterogeneity observed among the individual clones: a total of 383 iPSC variants were validated for the 24 clones (mean 16.0/clone, range 0-45). Since these variants were all present in the vast majority of the cells in each clone (variant allele frequencies of 40-60% for heterozygous variants), they most likely preexisted in the individual cells that were reprogrammed, rather than being acquired during reprogramming or cell passaging. We then tested whether this genetic heterogeneity had functional consequences for hematopoietic development by generating hematopoietic progenitors in vitro and enumerating colony forming units (CFUs). While there was a range of hematopoietic potentials among the 24 clones, only one clone failed to differentiate into hematopoietic cells; however, it was able to form a teratoma, proving its pluripotent nature. Further, no specific association was found between the mutational spectrum and the hematopoietic potential of each iPSC clone. These data clearly highlight the genetic heterogeneity present within individual fibroblasts that is captured by iPSC generation, and suggest that most of the changes are random, and functionally benign.This work was supported by grants from the NIH (CA101937 and CA162086, to TJL, and HL116605, to JMK), the Barnes Jewish Hospital Foundation (00335-0505-02, to TJL), and the Burroughs Wellcome Fund (to JMK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

The western painted turtle genome, a model for the evolution of extreme physiological adaptations in a slowly evolving lineage

Background: We describe the genome of the western painted turtle, Chrysemys picta bellii, one of the most widespread, abundant, and well-studied turtles. We place the genome into a comparative evolutionary context, and focus on genomic features associated with tooth loss, immune function, longevity, sex differentiation and determination, and the species' physiological capacities to withstand extreme anoxia and tissue freezing.Results: Our phylogenetic analyses confirm that turtles are the sister group to living archosaurs, and demonstrate an extraordinarily slow rate of sequence evolution in the painted turtle. The ability of the painted turtle to withstand complete anoxia and partial freezing appears to be associated with common vertebrate gene networks, and we identify candidate genes for future functional analyses. Tooth loss shares a common pattern of pseudogenization and degradation of tooth-specific genes with birds, although the rate of accumulation of mutations is much slower in the painted turtle. Genes associated with sex differentiation generally reflect phylogeny rather than convergence in sex determination functionality. Among gene families that demonstrate exceptional expansions or show signatures of strong natural selection, immune function and musculoskeletal patterning genes are consistently over-represented.Conclusions: Our comparative genomic analyses indicate that common vertebrate regulatory networks, some of which have analogs in human diseases, are often involved in the western painted turtle's extraordinary physiological capacities. As these regulatory pathways are analyzed at the functional level, the painted turtle may offer important insights into the management of a number of human health disorders

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Comparison of hematopoietic potential of iPSCs to mouse ESCs.

<p>Fractions of Lin⁻ cells (A), KLS cells (B), Kit+Lin-Sca-1- Progenitors (C), GMPs (D), CMPs (E), and MEPs (F) from iPSCs relative to mouse ESCs after 7 days of OP9 coculture (unsorted).</p

Validation array coverage.

<p>Validation array coverage.</p

Hematopoietic differentiation potential of the 24 iPSC clones.

<p>100,000 cells from OP9 cocultured mESCs (B6/BLU) or iPSCs were plated in methylcellulose media containing hematopoietic cytokines (SCF, IL-3, IL-6, and Epo). <b>A.</b> CFUs were counted after 7 additional days of culture. The relative number of CFUs per 100,000 cells plated from Day7 iPSC-derived progenitors vs. Day7 ESC (B6/BLU)-derived progenitors are shown. iPSC clones are ranked from the highest to the lowest average of two independent experiments. Error bars represent the means +/− one standard deviation. <b>B.</b> Morphology of day 7 OP9 cocultured ESC-derived cells after 7–8 days of additional culture in MethoCult media containing hematopoietic cytokines (SCF, IL-3, IL-6, and Epo). A scale bar of 20 μm is shown. <b>(C-E)</b>. Fractions of CD11b⁺ (<b>C</b>), CD34⁺Kit⁺ (<b>D</b>), and Ter119⁺ (<b>E</b>) cells obtained after 7 days of methylcellulose culture containing hematopoietic cytokines (SCF, IL-3, IL-6, and Epo), comparing iPSC-derived progenitors relative to ESC-derived progenitors, in the same order as panel A. <b>F.</b> Lack of correlation between the number of mutations and the hematopoietic differentiation potential of the iPSC clones (r² = 0.0006065).</p

Hematopoietic differentiation from murine ESCs.

<p><b>A.</b> Morphology of wild type ESC-derived cells after 7 days of OP9 coculture (unsorted) by Wright-Giemsa staining. A scale bar of 20 μm is shown. (B-D). Immunophenotyping of hematopoietic progenitor cells from wild-type mouse bone marrow cells (panel B), murine ESCs after 7 days of OP9 coculture (panel C), and iPSC clone Ax1-14 after 7 days of OP9 coculture (panel D). Lineage⁻ (Lin⁻), KLS (Lin⁻Kit⁺Sca-1⁺), progenitors (Lin⁻Kit⁺Sca-1⁻), CMPs (Lin⁻Kit⁺Sca-1⁻CD34⁺FCγ⁻), GMPs (Lin⁻Kit⁺Sca-1⁻CD34⁺FCγ⁺), and MEPs (Lin⁻Kit⁺Sca-1⁻CD34⁻FCγ-).</p