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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Reporter: Stephen J. Williams, PhD

 Minisymposium: Evaluating Cancer Genomics from Normal Tissues through Evolution to Metastatic Disease

Oncologic therapy shapes the fitness landscape of clonal hematopoiesis

April 28, 2020, 4:10 PM – 4:20 PM

Presenter/Authors
Kelly L. Bolton, Ryan N. Ptashkin, Teng Gao, Lior Braunstein, Sean M. Devlin, Minal Patel, Antonin Berthon, Aijazuddin Syed, Mariko Yabe, Catherine Coombs, Nicole M. Caltabellotta, Mike Walsh, Ken Offit, Zsofia Stadler, Choonsik Lee, Paul Pharoah, Konrad H. Stopsack, Barbara Spitzer, Simon Mantha, James Fagin, Laura Boucai, Christopher J. Gibson, Benjamin Ebert, Andrew L. Young, Todd Druley, Koichi Takahashi, Nancy Gillis, Markus Ball, Eric Padron, David Hyman, Jose Baselga, Larry Norton, Stuart Gardos, Virginia Klimek, Howard Scher, Dean Bajorin, Eder Paraiso, Ryma Benayed, Maria Arcilla, Marc Ladanyi, David Solit, Michael Berger, Martin Tallman, Montserrat Garcia-Closas, Nilanjan Chatterjee, Luis Diaz, Ross Levine, Lindsay Morton, Ahmet Zehir, Elli Papaemmanuil. Memorial Sloan Kettering Cancer Center, New York, NY, University of North Carolina at Chapel Hill, Chapel Hill, NC, University of Cambridge, Cambridge, United Kingdom, Dana-Farber Cancer Institute, Boston, MA, Washington University, St Louis, MO, The University of Texas MD Anderson Cancer Center, Houston, TX, Moffitt Cancer Center, Tampa, FL, National Cancer Institute, Bethesda, MD

Abstract
Recent studies among healthy individuals show evidence of somatic mutations in leukemia-associated genes, referred to as clonal hematopoiesis (CH). To determine the relationship between CH and oncologic therapy we collected sequential blood samples from 525 cancer patients (median sampling interval time = 23 months, range: 6-53 months) of whom 61% received cytotoxic therapy or external beam radiation therapy and 39% received either targeted/immunotherapy or were untreated. Samples were sequenced using deep targeted capture-based platforms. To determine whether CH mutational features were associated with tMN risk, we performed Cox proportional hazards regression on 9,549 cancer patients exposed to oncologic therapy of whom 75 cases developed tMN (median time to transformation=26 months). To further compare the genetic and clonal relationships between tMN and the proceeding CH, we analyzed 35 cases for which paired samples were available. We compared the growth rate of the variant allele fraction (VAF) of CH clones across treatment modalities and in untreated patients. A significant increase in the growth rate of CH mutations was seen in DDR genes among those receiving cytotoxic (p=0.03) or radiation therapy (p=0.02) during the follow-up period compared to patients who did not receive therapy. Similar growth rates among treated and untreated patients were seen for non-DDR CH genes such as DNMT3A. Increasing cumulative exposure to cytotoxic therapy (p=0.01) and external beam radiation therapy (2×10-8) resulted in higher growth rates for DDR CH mutations. Among 34 subjects with at least two CH mutations in which one mutation was in a DDR gene and one in a non-DDR gene, we studied competing clonal dynamics for multiple gene mutations within the same patient. The risk of tMN was positively associated with CH in a known myeloid neoplasm driver mutation (HR=6.9, p<10-6), and increased with the total number of mutations and clone size. The strongest associations were observed for mutations in TP53 and for CH with mutations in spliceosome genes (SRSF2, U2AF1 and SF3B1). Lower hemoglobin, lower platelet counts, lower neutrophil counts, higher red cell distribution width and higher mean corpuscular volume were all positively associated with increased tMN risk. Among 35 cases for which paired samples were available, in 19 patients (59%), we found evidence of at least one of these mutations at the time of pre-tMN sequencing and in 13 (41%), we identified two or more in the pre-tMN sample. In all cases the dominant clone at tMN transformation was defined by a mutation seen at CH Our serial sampling data provide clear evidence that oncologic therapy strongly selects for clones with mutations in the DDR genes and that these clones have limited competitive fitness, in the absence of cytotoxic or radiation therapy. We further validate the relevance of CH as a predictor and precursor of tMN in cancer patients. We show that CH mutations detected prior to tMN diagnosis were consistently part of the dominant clone at tMN diagnosis and demonstrate that oncologic therapy directly promotes clones with mutations in genes associated with chemo-resistant disease such as TP53.

  • therapy resulted also in clonal evolution and saw changes in splice variants and spliceosome
  • therapy promotes current DDR mutations
  • clonal hematopoeisis due to selective pressures
  • mutations, variants number all predictive of myeloid disease
  • deferring adjuvant therapy for breast cancer patients with patients in highest MDS risk group based on biomarkers, greatly reduced their risk for MDS

5704 – Pan-cancer genomic characterization of patient-matched primary, extracranial, and brain metastases

Presenter/AuthorsOlivia W. Lee, Akash Mitra, Won-Chul Lee, Kazutaka Fukumura, Hannah Beird, Miles Andrews, Grant Fischer, John N. Weinstein, Michael A. Davies, Jason Huse, P. Andrew Futreal. The University of Texas MD Anderson Cancer Center, TX, The University of Texas MD Anderson Cancer Center, TX, Olivia Newton-John Cancer Research Institute and School of Cancer Medicine, La Trobe University, AustraliaDisclosures O.W. Lee: None. A. Mitra: None. W. Lee: None. K. Fukumura: None. H. Beird: None. M. Andrews: ; Merck Sharp and Dohme. G. Fischer: None. J.N. Weinstein: None. M.A. Davies: ; Bristol-Myers Squibb. ; Novartis. ; Array BioPharma. ; Roche and Genentech. ; GlaxoSmithKline. ; Sanofi-Aventis. ; AstraZeneca. ; Myriad Genetics. ; Oncothyreon. J. Huse: None. P. Futreal: None.

Abstract: Brain metastases (BM) occur in 10-30% of patients with cancer. Approximately 200,000 new cases of brain metastases are diagnosed in the United States annually, with median survival after diagnosis ranging from 3 to 27 months. Recently, studies have identified significant genetic differences between BM and their corresponding primary tumors. It has been shown that BM harbor clinically actionable mutations that are distinct from those in the primary tumor samples. Additional genomic profiling of BM will provide deeper understanding of the pathogenesis of BM and suggest new therapeutic approaches.
We performed whole-exome sequencing of BM and matched tumors from 41 patients collected from renal cell carcinoma (RCC), breast cancer, lung cancer, and melanoma, which are known to be more likely to develop BM. We profiled total 126 fresh-frozen tumor samples and performed subsequent analyses of BM in comparison to paired primary tumor and extracranial metastases (ECM). We found that lung cancer shared the largest number of mutations between BM and matched tumors (83%), followed by melanoma (74%), RCC (51%), and Breast (26%), indicating that cancer type with high tumor mutational burden share more mutations with BM. Mutational signatures displayed limited differences, suggesting a lack of mutagenic processes specific to BM. However, point-mutation heterogeneity revealed that BM evolve separately into different subclones from their paired tumors regardless of cancer type, and some cancer driver genes were found in BM-specific subclones. These models and findings suggest that these driver genes may drive prometastatic subclones that lead to BM. 32 curated cancer gene mutations were detected and 71% of them were shared between BM and primary tumors or ECM. 29% of mutations were specific to BM, implying that BM often accumulate additional cancer gene mutations that are not present in primary tumors or ECM. Co-mutation analysis revealed a high frequency of TP53 nonsense mutation in BM, mostly in the DNA binding domain, suggesting TP53 nonsense mutation as a possible prerequisite for the development of BM. Copy number alteration analysis showed statistically significant differences between BM and their paired tumor samples in each cancer type (Wilcoxon test, p < 0.0385 for all). Both copy number gains and losses were consistently higher in BM for breast cancer (Wilcoxon test, p =1.307e-5) and lung cancer (Wilcoxon test, p =1.942e-5), implying greater genomic instability during the evolution of BM.
Our findings highlight that there are more unique mutations in BM, with significantly higher copy number alterations and tumor mutational burden. These genomic analyses could provide an opportunity for more reliable diagnostic decision-making, and these findings will be further tested with additional transcriptomic and epigenetic profiling for better characterization of BM-specific tumor microenvironments.

  • are there genomic signatures different in brain mets versus non metastatic or normal?
  • 32 genes from curated databases were different between brain mets and primary tumor
  • frequent nonsense mutations in TP53
  • divergent clonal evolution of drivers in BMets from primary
  • they were able to match BM with other mutational signatures like smokers and lung cancer signatures

5707 – A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations

Presenter/AuthorsPeter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. National Center for Tumor Diseases, Heidelberg, Germany, Washington University School of Medicine, St. Louis, MO, Mayo Clinic, Rochester, MN, Georgetown University Medical Center, Washington, DC, Dana-Farber Cancer Institute, Boston, MA, Frederick National Laboratory for Cancer Research, Rockville, MD, University of Southern California, Los Angeles, CA, Sunquest, Boston, MA, Baylor College of Medicine, Houston, TX, Memorial Sloan Kettering Cancer Center, New York, NY, National Cancer Institute, Rockville, MDDisclosures P. Horak: None. M. Griffith: None. A. Danos: None. B.A. Pitel: None. S. Madhavan: ; Perthera Inc. X. Liu: None. J. Lee: None. G. Raca: None. S. Li: ; Sunquest Information Systems, Inc. A.H. Wagner: None. S. Kulkarni: ; Baylor Genetics. O.L. Griffith: None. D. Chakravarty: None. D. Sonkin: None.AbstractSomatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/.

  • best to use this SOP for somatic mutations and not rearangements
  • variants based on oncogenicity as strong to weak
  • useful variant knowledge on pathogenicity curated from known databases
  • the recommendations would provide some guideline on curating unknown somatic variants versus known variants of hereditary diseases
  • they have not curated RB1 mutations or variants (or for other RBs like RB2? p130?)

 

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Evolution of the Human Cell Genome Biology Field of Gene Expression, Gene Regulation, Gene Regulatory Networks and Application of Machine Learning Algorithms in Large-Scale Biological Data Analysis

Curator & Reporter: Aviva Lev-Ari, PhD, RN

 

Subjects:

The Scientific Frontier is presented in Deciphering eukaryotic gene-regulatory logic with 100 million random promoters

Boer, C.G., Vaishnav, E.D., Sadeh, R. et al. Deciphering eukaryotic gene-regulatory logic with 100 million random promotersNat Biotechnol (2019) doi:10.1038/s41587-019-0315-8

Abstract

How transcription factors (TFs) interpret cis-regulatory DNA sequence to control gene expression remains unclear, largely because past studies using native and engineered sequences had insufficient scale. Here, we measure the expression output of >100 million synthetic yeast promoter sequences that are fully random. These sequences yield diverse, reproducible expression levels that can be explained by their chance inclusion of functional TF binding sites. We use machine learning to build interpretable models of transcriptional regulation that predict ~94% of the expression driven from independent test promoters and ~89% of the expression driven from native yeast promoter fragments. These models allow us to characterize each TF’s specificity, activity and interactions with chromatin. TF activity depends on binding-site strand, position, DNA helical face and chromatin context. Notably, expression level is influenced by weak regulatory interactions, which confound designed-sequence studies. Our analyses show that massive-throughput assays of fully random DNA can provide the big data necessary to develop complex, predictive models of gene regulation.

The Evolution of the Human Cell Genome Biology Field of Gene Expression, Gene Regulation, Gene Regulatory Networks and Application of Machine Learning Algorithms in Large-Scale Biological Data Analysis is presented in the following Table

 

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4 van Arensbergen, J. et al. Genome-wide mapping of autonomous promoter activity in human cells. Nat. Biotechnol. 35, 145–153 (2017).
14 Cuperus, J. T. et al. Deep learning of the regulatory grammar of yeast 5’ untranslated regions from 500,000 random sequences. Genome Res. 27, 2015–2024 (2017).
31 Levo, M. et al. Systematic investigation of transcription factor activity in the context of chromatin using massively parallel binding and expression assays. Mol. Cell 65, 604–617 e606 (2017).
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9 Hughes, T. R. & de Boer, C. G. Mapping yeast transcriptional networks. Genetics 195, 9–36 (2013).
10 Jolma, A. et al. DNA-binding specificities of human transcription factors. Cell 152, 327–339 (2013).
19 Kosuri, S. et al. Composability of regulatory sequences controlling transcription and translation in Escherichia coli. Proc. Natl Acad. Sci. USA 110, 14024–14029 (2013).
7 Sharon, E. et al. Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters. Nat. Biotechnol. 30, 521–530 (2012).
18 de Boer, C. G. & Hughes, T. R. YeTFaSCo: a database of evaluated yeast transcription factor sequence specificities. Nucleic Acids Res. 40, D169–D179 (2012).
56 Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
61 Cherry, J. M. et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 40, D700–D705 (2012).
11 Nutiu, R. et al. Direct measurement of DNA affinity landscapes on a high-throughput sequencing instrument. Nat. Biotechnol. 29, 659–664 (2011).
26 Zhang, Z. et al. A packing mechanism for nucleosome organization reconstituted across a eukaryotic genome. Science 332, 977–980 (2011).
30 Ganapathi, M. et al. Extensive role of the general regulatory factors, Abf1 and Rap1, in determining genome-wide chromatin structure in budding yeast. Nucleic Acids Res. 39, 2032–2044 (2011).
52 Erb, I. & van Nimwegen, E. Transcription factor binding site positioning in yeast: proximal promoter motifs characterize TATA-less promoters. PloS One 6, e24279 (2011).
3 Kinney, J. B., Murugan, A., Callan, C. G. Jr. & Cox, E. C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc. Natl Acad. Sci. USA107, 9158–9163 (2010).
8 Gertz, J., Siggia, E. D. & Cohen, B. A. Analysis of combinatorial cis-regulation in synthetic and genomic promoters. Nature 457, 215–218 (2009).
16 Wunderlich, Z. & Mirny, L. A. Different gene regulation strategies revealed by analysis of binding motifs. Trends Genet. 25, 434–440 (2009).
27 Hesselberth, J. R. et al. Global mapping of protein–DNA interactions in vivo by digital genomic footprinting. Nat. Methods 6, 283–289 (2009).
29 Hartley, P. D. & Madhani, H. D. Mechanisms that specify promoter nucleosome location and identity. Cell 137, 445–458 (2009).
51 Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).
58 Segal, E. & Widom, J. From DNA sequence to transcriptional behaviour: a quantitative approach. Nat. Rev. Genet. 10, 443–456 (2009).
2 Yuan, Y., Guo, L., Shen, L. & Liu, J. S. Predicting gene expression from sequence: a reexamination. PLoS Comput. Biol. 3, e243 (2007).
46 Hibbs, M. A. et al. Exploring the functional landscape of gene expression: directed search of large microarray compendia. Bioinformatics 23, 2692–2699 (2007).
25 Liu, X., Lee, C. K., Granek, J. A., Clarke, N. D. & Lieb, J. D. Whole-genome comparison of Leu3 binding in vitro and in vivo reveals the importance of nucleosome occupancy in target site selection. Genome Res. 16, 1517–1528 (2006).
34 Roberts, G. G. & Hudson, A. P. Transcriptome profiling of Saccharomyces cerevisiae during a transition from fermentative to glycerol-based respiratory growth reveals extensive metabolic and structural remodeling. Mol. Genet. Genomics 276, 170–186 (2006).
48 Tanay, A. Extensive low-affinity transcriptional interactions in the yeast genome. Gen. Res. 16, 962–972 (2006).
53 Tong, A. H. & Boone, C. Synthetic genetic array analysis in Saccharomyces cerevisiae. Methods Mol. Biol. 313, 171–192 (2006).
57 Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).
62 Chua, G. et al. Identifying transcription factor functions and targets by phenotypic activation. Proc. Natl Acad. Sci. USA 103, 12045–12050 (2006).
17 Arnosti, D. N. & Kulkarni, M. M. Transcriptional enhancers: intelligent enhanceosomes or flexible billboards? J. Cell. Biochem. 94, 890–898 (2005).
21 Granek, J. A. & Clarke, N. D. Explicit equilibrium modeling of transcription-factor binding and gene regulation. Genome Biol. 6, R87 (2005).
1 Beer, M. A. & Tavazoie, S. Predicting gene expression from sequence. Cell 117, 185–198 (2004).
28 Bernstein, B. E., Liu, C. L., Humphrey, E. L., Perlstein, E. O. & Schreiber, S. L. Global nucleosome occupancy in yeast. Genome Biol. 5, R62 (2004).
44 Kim, T. S., Kim, H. Y., Yoon, J. H. & Kang, H. S. Recruitment of the Swi/Snf complex by Ste12-Tec1 promotes Flo8-Mss11-mediated activation of STA1 expression. Mol. Cell. Biol. 24, 9542–9556 (2004).
45 Harbison, C. T. et al. Transcriptional regulatory code of a eukaryotic genome. Nature 431, 99–104 (2004).
60 Kent, N. A., Eibert, S. M. & Mellor, J. Cbf1p is required for chromatin remodeling at promoter-proximal CACGTG motifs in yeast. J. Biol. Chem. 279, 27116–27123 (2004).
22 Kulkarni, M. M. & Arnosti, D. N. Information display by transcriptional enhancers. Development 130, 6569–6575 (2003).
24 Conlon, E. M., Liu, X. S., Lieb, J. D. & Liu, J. S. Integrating regulatory motif discovery and genome-wide expression analysis. Proc. Natl Acad. Sci. USA 100, 3339–3344 (2003).
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23 Bussemaker, H. J., Li, H. & Siggia, E. D. Regulatory element detection using correlation with expression. Nat. Genet. 27, 167–171 (2001).
37 Haurie, V. et al. The transcriptional activator Cat8p provides a major contribution to the reprogramming of carbon metabolism during the diauxic shift in Saccharomyces cerevisiae. J. Biol. Chem. 276, 76–85 (2001).
39 Grauslund, M. & Ronnow, B. Carbon source-dependent transcriptional regulation of the mitochondrial glycerol-3-phosphate dehydrogenase gene, GUT2, from Saccharomyces cerevisiae. Can. J. Microbiol. 46, 1096–1100 (2000).
42 Cullen, P. J. & Sprague, G. F. Jr. Glucose depletion causes haploid invasive growth in yeast. Proc. Natl Acad. Sci. USA 97, 13619–13624 (2000).
38 Sato, T. et al. TheE-box DNA binding protein Sgc1p suppresses the gcr2 mutation, which is involved in transcriptional activation of glycolytic genes in Saccharomyces cerevisiae. FEBS Lett. 463, 307–311 (1999).
40 Madhani, H. D. & Fink, G. R. Combinatorial control required for the specificity of yeast MAPK signaling. Science 275, 1314–1317 (1997).
41 Gavrias, V., Andrianopoulos, A., Gimeno, C. J. & Timberlake, W. E. Saccharomyces cerevisiae TEC1 is required for pseudohyphal growth. Mol. Microbiol. 19, 1255–1263 (1996).
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47 Bednar, J. et al. Determination of DNA persistence length by cryo-electron microscopy. Separation of the static and dynamic contributions to the apparent persistence length of DNA. J. Mol. Biol. 254, 579–594 (1995).
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To access each reference as a live link, go to the number in the first column in the Table and look it up in the List of References in the Link, below

https://www.nature.com/articles/s41587-019-0315-8

Author information

C.G.D. and A.R. drafted the manuscript, with all authors contributing. C.G.D. analyzed the data. C.G.D., E.D.V., E.L.A. and R.S. performed the experiments. A.R. and N.F. supervised the research.

Correspondence to Carl G. de Boer or Aviv Regev.

Ethics declarations

Competing interests

A.R. is an SAB member of Thermo Fisher Scientific, Neogene Therapeutics, Asimov, and Syros Pharmaceuticals, an equity holder of Immunitas, and a founder of and equity holder in Celsius Therapeutics. All other authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Cite this article

Boer, C.G., Vaishnav, E.D., Sadeh, R. et al. Deciphering eukaryotic gene-regulatory logic with 100 million random promoters. Nat Biotechnol (2019) doi:10.1038/s41587-019-0315-8

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Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality after cardiac catheterization

Reporter: Aviva Lev-Ari, PhD, RN

 

A genome-wide Polygenic risk scores (PRS) improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

 

Background:

Coronary artery disease (CAD) is influenced by genetic variation and traditional risk factors. Polygenic risk scores (PRS), which can be ascertained before the development of traditional risk factors, have been shown to identify individuals at elevated risk of CAD. Here, we demonstrate that a genome-wide PRS for CAD predicts all-cause mortality after accounting for not only traditional cardiovascular risk factors but also angiographic CAD itself.

Methods:

Individuals who underwent coronary angiography and were enrolled in an institutional biobank were included; those with prior myocardial infarction or heart transplant were excluded. Using a pruning-and-thresholding approach, a genome-wide PRS comprised of 139 239 variants was calculated for 1503 participants who underwent coronary angiography and genotyping. Individuals were categorized into high PRS (hiPRS) and low-PRS control groups using the maximally selected rank statistic. Stratified analysis based on angiographic findings was also performed. The primary outcome was all-cause mortality following the index coronary angiogram.

Results:

Individuals with hiPRS were younger than controls (66 years versus 69 years; P=2.1×10-5) but did not differ by sex, body mass index, or traditional risk-factor profiles. Individuals with hiPRS were at significantly increased risk of all-cause mortality after cardiac catheterization, adjusting for traditional risk factors and angiographic extent of CAD (hazard ratio, 1.6; 95% CI, 1.2–2.2; P=0.004). The strongest increase in risk of all-cause mortality conferred by hiPRS was seen among individuals without angiographic CAD (hazard ratio, 2.4; 95% CI, 1.1–5.5; P=0.04). In the overall cohort, adding hiPRS to traditional risk assessment improved prediction of 5-year all-cause mortality (area under the receiver-operating curve 0.70; 95% CI, 0.66–0.75 versus 0.66; 95% CI, 0.61–0.70; P=0.001).

Conclusions:

A genome-wide PRS improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

Footnotes

https://www.ahajournals.org/journal/circgen

*A list of all Regeneron Genetics Center members is given in the Data Supplement.

Guest Editor for this article was Christopher Semsarian, MBBS, PhD, MPH.

The Data Supplement is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCGEN.118.002352.

Scott M. Damrauer, MD, Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce St, Silverstein 4, Philadelphia, PA 19104. Email 
SOURCE

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Biology of aging research goal: Defeating Death – California Life Company (Calicolabs.com), A Billion-dollar Longevity Lab, since 2013, GOOGLE cofounder and CEO Larry Page, formation of a new Alphabet entity is using consumer genetics and genealogy firm Ancestry’s forest of family trees

Reporter: Aviva Lev-Ari, PhD, RN

 

Conclusion – “Don’t smoke, and don’t go to war.”

Humans have more control over how long they live than their genes do. It’s all the other things that families share—homes and neighborhoods, culture and cuisine, access to education and health care—that make a much bigger difference in the set of numbers that might one day grace your tombstone.

Analyzing the pedigrees of more than 400 million people who lived and died in Europe and America going back to 1800 was that although longevity tends to run in families, your DNA has far less influence on how long you live than previously thought. The results, published Tuesday in the journal Genetics, is the first research to be made public from the collaboration, which ended quietly in July and whose terms remain confidential.

“The true heritability of human longevity for that cohort is likely no more than seven percent,” says Ruby. Previous estimates for how much genes explain variations in lifespan have ranged from around 15 to 30 percent. So what did Ruby uncover that previous studies had missed? Just how often amorous humans go against the old adage that “opposites attract.”

For example, you might choose a partner who also has curly hair, and if the curly-haired trait winds up being somehow associated with long lifespans, this would inflate estimates of lifespan heritability passed on to your kids. Same thing for non-genetic traits like wealth, education, and access to good health care. People tend to choose partners in their same income bracket with the same terminal degree, both of which are associated with living longer, healthier lives.

Calicolabs.com – NEWS

Genetics Society of America press release on Calico paper titled, “Estimates of the heritability of human longevity are substantially inflated due to assortative mating.”Nov 6, 2018

AbbVie and Calico Announce Extension of Groundbreaking Collaboration June 26, 2018

Calico Scientists Publish Paper in eLife Demonstrating that the Naked Mole Rat’s Risk of Death Does Not Increase With AgeJanuary 25, 2018

C4 Therapeutics and Calico Enter Strategic Partnership to Discover Novel Therapeutics Based on Targeted Protein DegradationMarch 23, 2017

Daphne Koller Named to FiercePharma’s “Fierce Women in Biopharma 2016” ListOctober 13, 2016

Calico Appoints Daphne Koller as Chief Computing OfficerAugust 17, 2016

The Jackson Laboratory and Calico to Investigate Basic Biology of AgingApril 26, 2016

David Botstein receives the Double Helix Medal from Cold Spring Harbor LaboratoryNovember 9, 2015 | Cold Spring Harbor Laboratory

AncestryDNA and Calico to Research the Genetics of Human LifespanJuly 21, 2015

Cynthia Kenyon named one of the “15 Most Amazing Women in Science Today”July 20, 2015 | Business Insider

Calico enters into agreement with the Buck Institute to conduct research into the biology of aging and to identify potential therapeutics for age-related diseasesApril 28, 2015

Calico licenses technology from acclaimed UCSF laboratoryMarch 31, 2015

Calico and QB3 announce partnership to conduct research into the biology of aging and to identify potential therapeutics for age-related diseasesMarch 24, 2015

Broad Institute and Calico announce an extensive collaboration focused on the biology of aging and therapeutic approaches to diseases of agingMarch 17, 2015

Art Levinson to receive National Medal of Technology and InnovationOctober 3, 2014

UT Southwestern researchers discover novel class of NAMPT activators for neurodegenerative disease; Calico enters into exclusive collaboration with 2M to develop UTSW technologySeptember 11, 2014

AbbVie and Calico Announce a Novel Collaboration to Accelerate the Discovery, Development, and Commercialization of New TherapiesSeptember 3, 2014

Google announces Calico, a new company focused on health and well-being (Google News)September 18, 2013

SOURCE

https://www.calicolabs.com/

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Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute

 

Curator: Aviva Lev-Ari, PhD, RN

 

Dana Pe’er, PhD, now chair of computational and systems biology at the Sloan Kettering Institute at the Memorial Sloan Kettering Cancer Center and a member of the Human Cell Atlas Organizing Committee,

what really sets Regev apart is the elegance of her work. Regev, says Pe’er, “has a rare, innate ability of seeing complex biology and simplifying it and formalizing it into beautiful, abstract, describable principles.”

Dr. Aviv Regev, an MIT biology professor who is also chair of the faculty of the Broad and director of its Klarman Cell Observatory and Cell Circuits Program, was reviewing a newly published white paper detailing how the Human Cell Atlas is expected to change the way we diagnose, monitor, and treat disease at a gathering of international scientists at Israel’s Weizmann Institute of Science, 10/2017.

For Regev, the importance of the Human Cell Atlas goes beyond its promise to revolutionize biology and medicine. As she once put it, without an atlas of our cells, “we don’t really know what we’re made of.”

Regev, turned to a technique known as RNA interference (she now uses CRISPR), which allowed her to systematically shut genes down. Then she looked at which genes were expressed to determine how the cells’ response changed in each case. Her team singled out 100 different genes that were involved in regulating the response to the pathogens—some of which weren’t previously known to be involved in immune function. The study, published in Science, generated headlines.

The project, the Human Cell Atlas, aims to create a reference map that categorizes all the approximately 37 trillion cells that make up a human. The Human Cell Atlas is often compared to the Human Genome Project, the monumental scientific collaboration that gave us a complete readout of human DNA, or what might be considered the unabridged cookbook for human life. In a sense, the atlas is a continuation of that project’s work. But while the same DNA cookbook is found in every cell, each cell type reads only some of the recipes—that is, it expresses only certain genes, following their DNA instructions to produce the proteins that carry out a cell’s activities. The promise of the Human Cell Atlas is to reveal which specific genes are expressed in every cell type, and where the cells expressing those genes can be found.

Regev says,

The final product, will amount to nothing less than a “periodic table of our cells,” a tool that is designed not to answer one specific question but to make countless new discoveries possible.

Sequencing the RNA of the cells she’s studying can tell her only so much. To understand how the circuits change under different circumstances, Regev subjects cells to different stimuli, such as hormones or pathogens, to see how the resulting protein signals change.

“the modeling step”—creating algorithms that try to decipher the most likely sequence of molecular events following a stimulus. And just as someone might study a computer by cutting out circuits and seeing how that changes the machine’s operation, Regev tests her model by seeing if it can predict what will happen when she silences specific genes and then exposes the cells to the same stimulus.

By sequencing the RNA of individual cancer cells in recent years—“Every cell is an experiment now,” she says—she has found remarkable differences between the cells of a single tumor, even when they have the same mutations. (Last year that work led to Memorial Sloan Kettering’s Paul Marks Prize for Cancer Research.) She found that while some cancers are thought to develop resistance to therapy, a subset of melanoma cells were resistant from the start. And she discovered that two types of brain cancer, oligodendroglioma and astrocytoma, harbor the same cancer stem cells, which could have important implications for how they’re treated.

As a 2017 overview of the Human Cell Atlas by the project’s organizing committee noted, an atlas “is a map that aims to show the relationships among its elements.” Just as corresponding coastlines seen in an atlas of Earth offer visual evidence of continental drift, compiling all the data about our cells in one place could reveal relationships among cells, tissues, and organs, including some that are entirely unexpected. And just as the periodic table made it possible to predict the existence of elements yet to be observed, the Human Cell Atlas, Regev says, could help us predict the existence of cells that haven’t been found.

This year alone it will fund 85 Human Cell Atlas grants. Early results are already pouring in.

  • In March, Swedish researchers working on cells related to human development announced they had sequenced 250,000 individual cells.
  • In May, a team at the Broad made a data set of more than 500,000 immune cells available on a preview site.

The goal, Regev says, is for researchers everywhere to be able to use the open-source platform of the Human Cell Atlas to perform joint analyses.

Eric Lander, PhDthe founding director and president of the Broad Institute and a member of the Human Cell Atlas Organizing Committee, likens it to genomics.

“People thought at the beginning they might use genomics for this application or that application,” he says. “Nothing has failed to be transformed by genomics, and nothing will fail to be transformed by having a cell atlas.”

“How did we ever imagine we were going to solve a problem without single-cell resolution?”

SOURCE

https://www.technologyreview.com/s/611786/the-cartographer-of-cells/?utm_source=MIT+Technology+Review&utm_campaign=Alumni-Newsletter_Sep-Oct-2018&utm_medium=email

Other related articles published in this Open Access Online Scientific Journal include the following:

 

University of California Santa Cruz’s Genomics Institute will create a Map of Human Genetic Variations

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/01/13/university-of-california-santa-cruzs-genomics-institute-will-create-a-map-of-human-genetic-variations/

 

Recognitions for Contributions in Genomics by Dan David Prize Awards

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/31/recognitions-for-contributions-in-genomics-by-dan-david-prize-awards/

 

ENCODE (Encyclopedia of DNA Elements) program: ‘Tragic’ Sequestration Impact on NHGRI Programs

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/09/18/encode-encyclopedia-of-dna-elements-program-tragic-sequestration-impact-on-nhgri-programs/

 

Single-cell Sequencing

Genomic Diagnostics: Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single Molecule DNA Sequencing

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/04/genomic-diagnostics-three-techniques-to-perform-single-cell-gene-expression-and-genome-sequencing-single-molecule-dna-sequencing/

 

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT – See, Aviv Regev

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/03/13/16th-annual-cancer-research-symposium-koch-institute-friday-june-16-9am-5pm-kresge-auditorium-mit/

 

LIVE 11/3/2015 1:30PM @The 15th Annual EmTech MIT – MIT Media Lab: Top 10 Breakthrough Technologies & 2015 Innovators Under 35 – See, Gilead Evrony

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2015/11/03/live-1132015-130pm-the-15th-annual-emtech-mit-mit-media-lab-top-10-breakthrough-technologies-2015-innovators-under-35/

 

Cellular Guillotine Created for Studying Single-Cell Wound Repair

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2017/06/29/cellular-guillotine-created-for-studying-single-cell-wound-repair/

 

New subgroups of ILC immune cells discovered through single-cell RNA sequencing

Reporter: Stephen J Williams, PhD

https://pharmaceuticalintelligence.com/2016/02/17/new-subgroups-of-ilc-immune-cells-discovered-through-single-cell-rna-sequencing-from-karolinska-institute/

 

#JPM16: Illumina’s CEO on new genotyping array called Infinium XT and Bio-Rad Partnership for single-cell sequencing workflow

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/jpm16-illuminas-ceo-on-new-genotyping-array-called-infinium-xt-and-bio-rad-partnership-for-single-cell-sequencing-workflow/

 

Juno Acquires AbVitro for $125M: high-throughput and single-cell sequencing capabilities for Immune-Oncology Drug Discovery

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/juno-acquires-abvitro-for-125m-high-throughput-and-single-cell-sequencing-capabilities-for-immune-oncology-drug-discovery/

 

NIH to Award Up to $12M to Fund DNA, RNA Sequencing Research: single-cell genomics,  sample preparation,  transcriptomics and epigenomics, and  genome-wide functional analysis.

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/10/27/nih-to-award-up-to-12m-to-fund-dna-rna-sequencing-research-single-cell-genomics-sample-preparation-transcriptomics-and-epigenomics-and-genome-wide-functional-analysis/

 

Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2012/08/07/genome-wide-single-cell-analysis-of-recombination-activity-and-de-novo-mutation-rates-in-human-sperm/

REFERENCES to Original studies

In Science, 2018

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors

 See all authors and affiliations

Science  21 Apr 2017:
Vol. 356, Issue 6335, eaah4573
DOI: 10.1126/science.aah4573
Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

See all authors and affiliations

Science  26 Apr 2018:
eaar3131
DOI: 10.1126/science.aar3131

In Nature, 2018 and 2017

How to build a human cell atlas

Aviv Regev is a maven of hard-core biological analyses. Now she is part of an effort to map every cell in the human body.

  1. Research | 

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  6. Amendments and Corrections | 

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  10. Comments and Opinion | 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Researchers have embraced CRISPR gene-editing as a method for altering genomes, but some have reported that unwanted DNA changes may slip by undetected. The tool can cause large DNA deletions and rearrangements near its target site on the genome. Such alterations can confuse the interpretation of experimental results and could complicate efforts to design therapies based on CRISPR. The finding is in line with previous results from not only CRISPR but also other gene-editing systems.

 

CRISPR -Cas9 gene editing relies on the Cas9 enzyme to cut DNA at a particular target site. The cell then attempts to reseal this break using its DNA repair mechanisms. These mechanisms do not always work perfectly, and sometimes segments of DNA will be deleted or rearranged, or unrelated bits of DNA will become incorporated into the chromosome.

 

Researchers often use CRISPR to generate small deletions in the hope of knocking out a gene’s function. But when examining CRISPR edits, researchers found large deletions (often several thousand nucleotides) and complicated rearrangements of DNA sequences in which previously distant DNA sequences were stitched together. Many researchers use a method for amplifying short snippets of DNA to test whether their edits have been made properly. But this approach might miss larger deletions and rearrangements.

 

These deletions and rearrangements occur only with gene-editing techniques that rely on DNA cutting and not with some other types of CRISPR modifications that avoid cutting DNA. Such as a modified CRISPR system to switch one nucleotide for another without cutting DNA and other systems use inactivated Cas9 fused to other enzymes to turn genes on or off, or to target RNA. Overall, these unwanted edits are a problem that deserves more attention, but this should not stop anyone from using CRISPR. Only when people use it, they need to do a more thorough analysis about the outcome.

 

References:

 

https://www.nature.com/articles/d41586-018-05736-3?utm_source=briefing-dy

 

https://www.ncbi.nlm.nih.gov/pubmed/28561021

 

https://www.ncbi.nlm.nih.gov/pubmed/30010673

 

https://www.ncbi.nlm.nih.gov/pubmed/24651067

 

https://www.ncbi.nlm.nih.gov/pubmed/25398350

 

https://www.ncbi.nlm.nih.gov/pubmed/24838573

 

https://www.ncbi.nlm.nih.gov/pubmed/25200087

 

https://www.ncbi.nlm.nih.gov/pubmed/25757625

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Long interspersed nuclear elements 1 (LINE1) is repeated half a million times in the human genome, making up nearly a fifth of the DNA in every cell. But nobody cared to study it and may be the reason to call it junk DNA. LINE1, like other transposons (or “jumping genes”), has the unusual ability to copy and insert itself in random places in the genome. Many other research groups uncovered possible roles in early mouse embryos and in brain cells. But nobody quite established a proper report about the functions of LINE1.

 

Geneticists gave attention to LINE1 when it was found to cause cancer or genetic disorders like hemophilia. But researchers at University of California at San Francisco suspected there was more characteristics of LINE1. They suspected that if it can be most harmless then it can be worst harmful also.

 

Many reports showed that LINE1 is especially active inside developing embryos, which suggests that the segment actually plays a key role in coordinating the development of cells in an embryo. Researchers at University of California at San Francisco figured out how to turn LINE1 off in mouse embryos by blocking LINE1 RNA. As a result the embryos got stuck in the two-cell stage, right after a fertilized egg has first split. Without LINE1, embryos essentially stopped developing.

 

The researchers thought that LINE1 RNA particles act as molecular “glue,” bringing together a suite of molecules that switch off the two-cell stage and kick it into the next phase of development. In particular, it turns off a gene called Dux, which is active in the two-cell stage.

 

LINE1’s ability to copy itself, however, seems to have nothing to do with its role in embryonic development. When LINE1 was blocked from inserting itself into the genome, the embryonic stem cells remained unaffected. It’s possible that cells in embryos have a way of making LINE1 RNA while also preventing its potentially harmful “jumping” around in the genome. But it’s unlikely that every one of the thousands of copies of LINE1 is actually being used to regulate embryonic development.

 

LINE1 is abundant in the genomes of almost all mammals. Other transposons, also once considered junk DNA, have turned out to have critical roles in development in human cells too. There are differences between mice and humans, so, the next obvious step is to study LINE1 in human cells, where it makes up 17 percent of the genome.

 

References:

 

https://www-theatlantic-com.cdn.ampproject.org/c/s/www.theatlantic.com/amp/article/563354/

 

https://www.ncbi.nlm.nih.gov/pubmed/29937225

 

https://www.nature.com/scitable/topicpage/transposons-the-jumping-genes-518

 

https://www.sciencedaily.com/releases/2018/06/180621141038.htm

 

https://www.ncbi.nlm.nih.gov/pubmed/16015595

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Biologists may have been building a more nuanced view of sex, but society has yet to catch up. True, more than half a century of activism from members of the lesbian, gay, bisexual and transgender community has softened social attitudes to sexual orientation and gender. Many societies are now comfortable with men and women crossing conventional societal boundaries in their choice of appearance, career and sexual partner. But when it comes to sex, there is still intense social pressure to conform to the binary model.

 

This pressure has meant that people born with clear DSDs (difference/disorder of sex development) often undergo surgery to ‘normalize’ their genitals. Such surgery is controversial because it is usually performed on babies, who are too young to consent, and risks assigning a sex at odds with the child’s ultimate gender identity — their sense of their own gender. Intersex advocacy groups have therefore argued that doctors and parents should at least wait until a child is old enough to communicate their gender identity, which typically manifests around the age of three, or old enough to decide whether they want surgery at all.

 

As many as 1 person in 100 has some form of “DSD” with or without external manifestation. Diagnoses of DSDs previously relied on hormone tests, anatomical inspections and imaging, followed by painstaking tests of one gene at a time. Now, advances in genetic techniques mean that teams can analyze multiple genes at once, aiming straight for a genetic diagnosis and making the process less stressful for families. Children with DSDs are treated by multidisciplinary teams that aim to tailor management and support to each individual and their family, but this usually involves raising a child as male or female even if no surgery is done.

 

The simple scenario that all learn is that two X chromosomes make someone female, and an X and a Y chromosome make someone male. These are simplistic ways of thinking about what is scientifically very complex. Anatomy, hormones, cells, and chromosomes (and also personal identity convictions) are actually not usually aligned with this binary classification.

 

More than 25 genes that affect sex development have now been identified, and they have a wide range of variations that affect people in subtle ways. Many differences aren’t even noticed until incidental medical encounters, such as a forty-six-year-old woman pregnant with her third child, found after amniocentesis that half her cells carry male chromosomes. Or a seventy-year-old father of three who learns during a hernia repair that he has a uterus.

 

Furthermore, scientists now understood that everyone’s body is made up of a patchwork of genetically distinct cells, some of which may have a different sex than the rest. This “mosaicism” can have effects ranging from undetectable to extraordinary, such as “identical” twins of different sexes. An extremely common instance of mosaicism comes from cells passing over the placental barrier during pregnancy. Men often carry female cells from their mothers, and women carry male cells from their sons. Research has shown that these cells remain present for decades, but what effects they have on disease and behavior is an essentially unstudied question.

 

References:

 

https://www.theguardian.com/science/2017/mar/02/cambridge-scientists-create-first-self-developing-embryo-from-stem-cells

 

https://www.ncbi.nlm.nih.gov/pubmed/25693544

 

http://onlinelibrary.wiley.com/doi/10.1002/ajmg.a.34123/abstract;jsessionid=A330AD995EE25C7A0AD5EA478694ADD8.f04t01

 

https://www.ncbi.nlm.nih.gov/pubmed/25091731

 

https://www.ncbi.nlm.nih.gov/pubmed/1695712

 

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Genomic Diagnostics: Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single Molecule DNA Sequencing

Curator: Aviva Lev-Ari, PhD, RN

 

This article presents Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single molecule DNA sequencing

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Ido Sagi – PhD Student @HUJI, 2017 Kaye Innovation Award winner for leading research that yielded the first successful isolation and maintenance of haploid embryonic stem cells in humans.

Reporter: Aviva Lev-Ari, PhD, RN

 

Ido Sagi – PhD Student, Silberman Institute of Life Sciences, HUJI, Israel

  • Ido Sagi’s research focuses on studying genetic and epigenetic phenomena in human pluripotent stem cells, and his work has been published in leading scientific journals, including NatureNature Genetics and Cell Stem Cell.
  • Ido Sagi received BSc summa cum laude in Life Sciences from the Hebrew University, and currently pursues a PhD at the laboratory of Prof. Nissim Benvenisty at the university’s Department of Genetics in the Alexander Silberman Institute of Life Sciences.

The Kaye Innovation Awards at the Hebrew University of Jerusalem have been awarded annually since 1994. Isaac Kaye of England, a prominent industrialist in the pharmaceutical industry, established the awards to encourage faculty, staff and students of the Hebrew University to develop innovative methods and inventions with good commercial potential, which will benefit the university and society.

Publications – Ido Sagi

Comparable frequencies of coding mutations and loss of imprinting in human pluripotent cells derived by nuclear transfer and defined factors.
Cell Stem Cell 2014 Nov 6;15(5):634-42. Epub 2014 Nov 6.
The New York Stem Cell Foundation Research Institute, New York, NY 10032, USA; Naomi Berrie Diabetes Center & Department of Pediatrics, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA. Electronic address:

November 2014

 



Stem cells: Aspiring to naivety.
Nature 2016 12 30;540(7632):211-212. Epub 2016 Nov 30.
The Azrieli Center for Stem Cells and Genetic Research, Department of Genetics, Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.
November 2016

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SOURCE

Other related articles on Genetic and Epigenetic phenomena in human pluripotent stem cells published by LPBI Group can be found in the following e-Books on Amazon.com

e-Books in Medicine

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    Etiologies of Cardiovascular Diseases: Epigenetics, Genetics and Genomics

    Nov 28, 2015 | Kindle eBook

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