Fousteri G.,La Jolla Institute for Allergy and Immunology |
Jasinski J.,University of Colorado at Denver |
Jasinski J.,Partek, Inc. |
Dave A.,La Jolla Institute for Allergy and Immunology |
And 10 more authors.
In diabetic patients and susceptible mice, insulin is a targeted autoantigen. Insulin B chain 9-23 (B:9-23) autoreactive CD4 T cells are key for initiating autoimmune diabetes in NOD mice; however, little is known regarding their origin and function. To this end, B:9-23-specific, BDC12-4.1 T-cell receptor (TCR) transgenic (Tg) mice were studied, of which, despite expressing a single TCR on the recombination activating gene-deficient background, only a fraction develops diabetes in an asynchronous manner. BDC12-4.1 CD4 T cells convert into effector (Teff) and Foxp3 +-expressing adaptive regulatory T cells (aTregs) soon after leaving the thymus as a result of antigen recognition and homeostatic proliferation. The generation of aTreg causes the heterogeneous diabetes onset, since crossing onto the scurfy (Foxp3) mutation, BDC12-4.1 TCR Tg mice develop accelerated and fully penetrant diabetes. Similarly, adoptive transfer and bone marrow transplantation experiments showed differential diabetes kinetics based on Foxp3 + aTreg's presence in the BDC12-4.1 donors. A single-specificity, insulin-reactive TCR escapes thymic deletion and simultaneously converts into aTreg and Teff, establishing an equilibrium that determines diabetes penetrance. These results are of particular importance for understanding disease pathogenesis. They suggest that once central tolerance is bypassed, autoreactive cells arriving in the periphery do not by default follow solely a pathogenic fate upon activation. © 2012 by the American Diabetes Association. Source
Sawhney V.,St. Bartholomews Hospital |
Sawhney V.,Queen Mary, University of London |
Brouilette S.,Partek, Inc. |
Abrams D.,Childrens Hospital |
And 6 more authors.
Cardiovascular disease (CVD) is a heterogeneous, complex trait that has a major impact on human morbidity and mortality. Common genetic variation may predispose to common forms of CVD in the community, and rare genetic conditions provide unique pathogenetic insights into these diseases. With the advent of the Human Genome Project and the genomic era, new tools and methodologies have revolutionised the field of genetic research in cardiovascular medicine. In this review, we describe the rationale for the current emphasis on large-scale genomic studies, elaborate on genome wide association studies and summarise the impact of genomics on clinical cardiovascular medicine and how this may eventually lead to new therapeutics and personalised medicine. © 2012 Bentham Science Publishers. Source
Brouilette S.,Queen Mary, University of London |
Brouilette S.,Partek, Inc. |
Kuersten S.,Illumina |
Mein C.,Queen Mary, University of London |
And 14 more authors.
Background: Deep sequencing of single cell-derived cDNAs offers novel insights into oncogenesis and embryogenesis. However, traditional library preparation for RNA-seq analysis requires multiple steps with consequent sample loss and stochastic variation at each step significantly affecting output. Thus, a simpler and better protocol is desirable. The recently developed hyperactive Tn5-mediated library preparation, which brings high quality libraries, is likely one of the solutions. Results and Conclusions: Here, we tested the applicability of hyperactive Tn5-mediated library preparation to deep sequencing of single cell cDNA, optimized the protocol, and compared it with the conventional method based on sonication. This new technique does not require any expensive or special equipment, which secures wider availability. A library was constructed from only 100 ng of cDNA, which enables the saving of precious specimens. Only a few steps of robust enzymatic reaction resulted in saved time, enabling more specimens to be prepared at once, and with a more reproducible size distribution among the different specimens. The obtained RNA-seq results were comparable to the conventional method. Thus, this Tn5-mediated preparation is applicable for anyone who aims to carry out deep sequencing for single cell cDNAs. Developmental Dynamics 241:1584-1590, 2012. © 2012 Wiley Periodicals, Inc. Source
Liu W.,University of Missouri |
Liu W.,Sony Electronics Inc. |
Dong L.,Partek, Inc. |
Zeng W.,University of Missouri
IEEE Transactions on Circuits and Systems for Video Technology
During the past ten years, Wyner-Ziv video coding (WZVC) has gained a lot of research interests because of its unique characteristics of simple encoding, complex decoding. However, the performance gap between WZVC and conventional video coding has never been closed to the point promised by the information theory. In this paper, we illustrate the chicken-and-egg dilemma encountered in WZVC: high-efficiency WZVC requires good estimation of side information (SI); however, good SI estimation is not possible for the decoder without access to the decoded current frame. To resolve such a dilemma, we present and advocate a framework that explores an important concept of decoder-side progressive-learning. More specifically, a decoder-side multi-resolution motion refinement (MRMR) scheme is proposed, where the decoder is able to learn from the already-decoded lower-resolution data to refine the motion estimation (ME), which in turn greatly improves the SI quality as well as the coding efficiency for the higher resolution data. Theoretical analysis shows that at high rates, decoder-side MRMR outperforms motion extrapolation by as much as 5 dB, while falling behind conventional encoder-side inter-frame ME by only about 1.5 dB. In addition, since decoder-side ME does not suffer from the bit-rate overhead in transmitting the motion information, further performance gain can be achieved for decoder-side MRMR by incorporating fractional-pel motion search, block matching with smaller block sizes, and multiple hypothesis prediction. We also present a practical WZVC implementation with MRMR, which shows comparable coding performance as H.264 at very high bit-rates. © 2006 IEEE. Source
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 243.01K | Year: 2009
DESCRIPTION (provided by applicant): The broad, long-term objective of the proposed research is to develop a software product that can be used to facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie diseases such as autism spectrum disorder, bipolar disorder, and schizophrenia. Recent technological advances allow samples of DNA from patients to be analyzed on single nucleotide polymorphism (SNP) arrays, generating up to millions of data points from each sample. These data must be analyzed to identify chromosomal abnormalities (e.g. DNA mutations, hemizygous or homozygous deletions, or translocations) that confer risk for these diseases. Two main approaches to data analysis include copy number estimates (based on the intensity of hybridization of samples to SNP arrays) and genotype analysis (revealing heterozygosity and homozygosity). Software such as Partek Genomics Suite (GS) exists to perform data analysis and visualization. A goal of this proposal is to add another dimension to the analysis of high density SNP data by incorporating information about the genetic relatedness of individuals into the data analysis repertoire of Partek GS. The specific aims are as follows. (1) Incorporate SNPtrio into a new Partek GS module. This program analyzes genotype and copy number data from trios consisting of father, mother, and child and produces graphical and tabular descriptions of uniparental inheritance (e.g. uniparental isodisomy in which two copies of a chromosome or chromosomal segment are inherited from one parent; such a mechanism is known to cause a variety of mental retardation and other syndromes). (2) Incorporate SNPduo into PartekGS; this program performs pairwise analyses of SNP data sets, allowing the description of relatedness between individuals (by identity-by-state measurements). This is useful for a variety of purposes including identifying outliers, replicate samples, non-paternity, and confirming the genetic relatedness of members of a pedigree. (3) Incorporate a set of analytic tools that measure meiotic recombination in pedigrees consisting of one, two, or three generations. Such tools may be useful to exclude loci in association studies or to characterize mechanisms by which deletions or duplications occur. The software tools described in aims (1) to (3) will be assembled into a new prototype version of Partek GS. In aim (4), this prototype will be used to analyze a set of 500,000 SNPs measured in 2,883 individuals from 700 families having two or more individuals affected with autism. This analysis will demonstrate the functionality of the Partek GS prototype, demonstrating the usefulness of incorporating new tools for genetic analysis to discover chromosomal abnormalities that may have roles in autism. PUBLIC HEALTH RELEVANCE: Newly available technologies allow the measurement of millions of variations in DNA sequence between samples from individuals with diseases (such as autism and schizophrenia) relative to unaffected individuals (controls). The proposed research is designed to create software analysis tools that will facilitate the discovery of chromosomal abnormalities in diseases. This may lead to treatments for these disorders, serving a large public health need.