Unraveling the clonal hierarchy of somatic genomic aberrations

Defining the chronology of molecular alterations may identify milestones in carcinogenesis. To unravel the temporal evolution of aberrations from clinical tumors, we developed CLONET, which upon estimation of tumor admixture and ploidy infers the clonal hierarchy of genomic aberrations. Comparative analysis across 100 sequenced genomes from prostate, melanoma, and lung cancers established diverse evolutionary hierarchies, demonstrating the early disruption of tumor-specific pathways. The analyses highlight the diversity of clonal evolution within and across tumor types that might be informative for risk stratification and patient selection for targeted therapies. CLONET addresses heterogeneous clinical samples seen in the setting of precision medicine. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0439-6) contains supplementary material, which is available to authorized users

Research priorities for next-generation breeding of tropical forages in Brazil.

ABSTRACT: Pasture is the main food source for more than 200 million cattle heads in Brazil. Although Brazilian forage breeding programs have successfully released well-adapted, high-yielding cultivars over the years, the use of genomic tools in these programs is currently limited. These tools are required to tackle the main challenges for tropical forage breeding in Brazil. In this context, this notes lists the main research priorities raised at the workshop ?Breeding Forages in the Genomic Era?, which are necessary to accelerate the use of genomic tools for next-generation breeding of tropical forages and allow breeders to increase genetic gains. Additionally, an online discussion forum (hosted at http://www.cnpgl.embrapa.br/genfor) has been launched to strengthen collaborations among research groups. The research priorities and more synergistic collaborations will assist researchers and decision-makers in delivering a sustainable increase in production of animal products, especially beef and milk, which are required to feed a rising world population

Research priorities for next-generation breeding of tropical forages in Brazil.

ABSTRACT: Pasture is the main food source for more than 200 million cattle heads in Brazil. Although Brazilian forage breeding programs have successfully released well-adapted, high-yielding cultivars over the years, the use of genomic tools in these programs is currently limited. These tools are required to tackle the main challenges for tropical forage breeding in Brazil. In this context, this notes lists the main research priorities raised at the workshop “Breeding Forages in the Genomic Era”, which are necessary to accelerate the use of genomic tools for next-generation breeding of tropical forages and allow breeders to increase genetic gains. Additionally, an online discussion forum (hosted at http://www.cnpgl.embrapa.br/genfor) has been launched to strengthen collaborations among research groups. The research priorities and more synergistic collaborations will assist researchers and decision-makers in delivering a sustainable increase in production of animal products, especially beef and milk, which are required to feed a rising world population

Transcriptomic Characterization of a Synergistic Genetic Interaction during Carpel Margin Meristem Development in Arabidopsis thaliana

In flowering plants the gynoecium is the female reproductive structure. In Arabidopsis thaliana ovules initiate within the developing gynoecium from meristematic tissue located along the margins of the floral carpels. When fertilized the ovules will develop into seeds. SEUSS (SEU) and AINTEGUMENTA (ANT) encode transcriptional regulators that are critical for the proper formation of ovules from the carpel margin meristem (CMM). The synergistic loss of ovule initiation observed in the seu ant double mutant suggests that SEU and ANT share overlapping functions during CMM development. However the molecular mechanism underlying this synergistic interaction is unknown. Using the ATH1 transcriptomics platform we identified transcripts that were differentially expressed in seu ant double mutant relative to wild type and single mutant gynoecia. In particular we sought to identify transcripts whose expression was dependent on the coordinated activities of the SEU and ANT gene products. Our analysis identifies a diverse set of transcripts that display altered expression in the seu ant double mutant tissues. The analysis of overrepresented Gene Ontology classifications suggests a preponderance of transcriptional regulators including multiple members of the REPRODUCTIVE MERISTEMS (REM) and GROWTH-REGULATING FACTOR (GRF) families are mis-regulated in the seu ant gynoecia. Our in situ hybridization analyses indicate that many of these genes are preferentially expressed within the developing CMM. This study is the first step toward a detailed description of the transcriptional regulatory hierarchies that control the development of the CMM and ovule initiation. Understanding the regulatory hierarchy controlled by SEU and ANT will clarify the molecular mechanism of the functional redundancy of these two genes and illuminate the developmental and molecular events required for CMM development and ovule initiation

Androgen receptor gene status in plasma DNA associates with worse outcome on enzalutamide or abiraterone for castration-resistant prostate cancer: a multi-institution correlative biomarker study.

Background There is an urgent need to identify biomarkers to guide personalized therapy in castration-resistant prostate cancer (CRPC). We aimed to clinically qualify androgen receptor (AR) gene status measurement in plasma DNA using multiplex droplet digital PCR (ddPCR) in pre- and post-chemotherapy CRPC.Methods We optimized ddPCR assays for AR copy number and mutations and retrospectively analyzed plasma DNA from patients recruited to one of the three biomarker protocols with prospectively collected clinical data. We evaluated associations between plasma AR and overall survival (OS) and progression-free survival (PFS) in 73 chemotherapy-naïve and 98 post-docetaxel CRPC patients treated with enzalutamide or abiraterone (Primary cohort) and 94 chemotherapy-naïve patients treated with enzalutamide (Secondary cohort; PREMIERE trial).Results In the primary cohort, AR gain was observed in 10 (14%) chemotherapy-naïve and 33 (34%) post-docetaxel patients and associated with worse OS [hazard ratio (HR), 3.98; 95% CI 1.74-9.10; P A (p.L702H) and 2632A>G (p.T878A)] were observed in eight (11%) post-docetaxel but no chemotherapy-naïve abiraterone-treated patients and were also associated with worse OS (HR 3.26; 95% CI 1.47-not reached; P = 0.004). There was no interaction between AR and docetaxel status (P = 0.83 for OS, P = 0.99 for PFS). In the PREMIERE trial, 11 patients (12%) with AR gain had worse PSA-PFS (sPFS) (HR 4.33; 95% CI 1.94-9.68; P < 0.001), radiographic-PFS (rPFS) (HR 8.06; 95% CI 3.26-19.93; P < 0.001) and OS (HR 11.08; 95% CI 2.16-56.95; P = 0.004). Plasma AR was an independent predictor of outcome on multivariable analyses in both cohorts.Conclusion Plasma AR status assessment using ddPCR identifies CRPC with worse outcome to enzalutamide or abiraterone. Prospective evaluation of treatment decisions based on plasma AR is now required.Clinical trial number NCT02288936 (PREMIERE trial)

Androgen receptor gene status in plasma DNA associates with worse outcome on enzalutamide or abiraterone for castration-resistant prostate cancer: a multi-institution correlative biomarker study

2632A>G (p.T878A)] were observed in eight (11%) post-docetaxel but no chemotherapy-naı¨ve abiraterone-treated patients and were also associated with worse OS (HR 3.26; 95% CI 1.47-not reached; P¼0.004). There was no interaction between AR and docetaxel status (P¼0.83 for OS, P¼0.99 for PFS). In the PREMIERE trial, 11 patients (12%) with AR gain had worse PSA-PFS (sPFS) (HR 4.33; 95% CI 1.94-9.68; PA (p.L702H) and 520 3

Advances in genetics: widening our understanding of prostate cancer

Prostate cancer is a leading cause of cancer-related death in Western men. Our understanding of the genetic alterations associated with disease predisposition, development, progression, and therapy response is rapidly improving, at least in part, owing to the development of next-generation sequencing technologies. Large advances have been made in our understanding of the genetics of prostate cancer through the application of whole-exome sequencing, and this review summarises recent advances in this field and discusses how exome sequencing could be used clinically to promote personalised medicine for prostate cancer patients.</ns4:p

Allele specific repair of splicing mutations in cystic fibrosis through AsCas12a genome editing.

Funder: Fondazione Fibrosi Cistica - FFC#1/2017Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in the CFTR gene. The 3272-26A>G and 3849+10kbC>T CFTR mutations alter the correct splicing of the CFTR gene, generating new acceptor and donor splice sites respectively. Here we develop a genome editing approach to permanently correct these genetic defects, using a single crRNA and the Acidaminococcus sp. BV3L6, AsCas12a. This genetic repair strategy is highly precise, showing very strong discrimination between the wild-type and mutant sequence and a complete absence of detectable off-targets. The efficacy of this gene correction strategy is verified in intestinal organoids and airway epithelial cells derived from CF patients carrying the 3272-26A>G or 3849+10kbC>T mutations, showing efficient repair and complete functional recovery of the CFTR channel. These results demonstrate that allele-specific genome editing with AsCas12a can correct aberrant CFTR splicing mutations, paving the way for a permanent splicing correction in genetic diseases

Snazer: the simulations and networks analyzer

<p>Abstract</p> <p>Background</p> <p>Networks are widely recognized as key determinants of structure and function in systems that span the biological, physical, and social sciences. They are static pictures of the interactions among the components of complex systems. Often, much effort is required to identify networks as part of particular patterns as well as to visualize and interpret them.</p> <p>From a pure dynamical perspective, simulation represents a relevant <it>way</it>-<it>out</it>. Many simulator tools capitalized on the "noisy" behavior of some systems and used formal models to represent cellular activities as temporal trajectories. Statistical methods have been applied to a fairly large number of replicated trajectories in order to infer knowledge.</p> <p>A tool which both graphically manipulates reactive models and deals with sets of simulation time-course data by aggregation, interpretation and statistical analysis is missing and could add value to simulators.</p> <p>Results</p> <p>We designed and implemented <it>Snazer</it>, the simulations and networks analyzer. Its goal is to aid the processes of visualizing and manipulating reactive models, as well as to share and interpret time-course data produced by stochastic simulators or by any other means.</p> <p>Conclusions</p> <p><it>Snazer </it>is a solid prototype that integrates biological network and simulation time-course data analysis techniques.</p