Three grants totaling $2,634,668 were awarded to Individual Investigator Research Awards for Computational Biology. Our group is fortunate to be funded by CPRIT for our work on “Development and Validation of a Network-guided, Multi-objective Optimization Model for Cancer Data Analysis (Zhandong Liu) – $889,679”.
Hari developed a new tool to discover non-canonical splicing events in RNA-seq: http://www.liuzlab.org/CrypSplice/
Copy number variations have been frequently associated with developmental delay, intellectual disability and autism spectrum disorders. MECP2 duplication syndrome is one of the most common genomic rearrangements in males and is characterized by autism, intellectual disability, motor dysfunction, anxiety, epilepsy, recurrent respiratory tract infections and early death. The broad range of deficits caused by methyl-CpG-binding protein 2 (MeCP2) overexpression poses a daunting challenge to traditional biochemical-pathway-based therapeutic approaches. Accordingly, we sought strategies that directly target MeCP2 and are amenable to translation into clinical therapy. The first question that we addressed was whether the neurological dysfunction is reversible after symptoms set in. Reversal of phenotypes in adult symptomatic mice has been demonstrated in some models of monogenic loss-of-function neurological disorders, including loss of MeCP2 in Rett syndrome, indicating that, at least in some cases, the neuroanatomy may remain sufficiently intact so that correction of the molecular dysfunction underlying these disorders can restore healthy physiology. Given the absence of neurodegeneration in MECP2 duplication syndrome, we propose that restoration of normal MeCP2 levels in MECP2 duplication adult mice would rescue their phenotype. By generating and characterizing a conditional Mecp2-overexpressing mouse model, here we show that correction of MeCP2 levels largely reverses the behavioural, molecular and electrophysiological deficits. We also reduced MeCP2 using an antisense oligonucleotide strategy, which has greater translational potential. Antisense oligonucleotides are small, modified nucleic acids that can selectively hybridize with messenger RNA transcribed from a target gene and silence it, and have been successfully used to correct deficits in different mouse models. We find that antisense oligonucleotide treatment induces a broad phenotypic rescue in adult symptomatic transgenic MECP2 duplication mice (MECP2-TG), and corrected MECP2 levels in lymphoblastoid cells from MECP2 duplication patients in a dose-dependent manner.
Post-transcriptional regulation of SHANK3 expression by microRNAs related to multiple neuropsychiatric disorders. Our study provides new insight into the miRNA-mediated regulation of SHANK3 expression, and its potential implication in multiple neuropsychiatric disorders associated with altered SHANK3 and miRNA expression profiles.
Congratulations to Kanchana to be selected as the semis-finalist of The Siemens Competition in Math, Science & Technology. Great job.
Congratulations to Kanchana Raja for winning a first place award from the American Statistical Society and third place award in the Computer Science division in Houston Science Fair. Kanchana a junior at St. John’s school did her summer intern with us 2014.
Congrats to Andrew Laitman for getting the NLM training fellowship!!!
Our project on Viral MicroRNAs in Ovarian Cancer Growth and Metastasis is funded through CPRIT.
Congratulations to Ying-Wooi Wan. Her collaborative work with Dr. Bellen’s lab was accepted by Cell.
A grant from hearing health foundation has been awarded to us in collaboration with the Groves lab to study the hair cell regeneration.
NATURE METHODS | RESEARCH HIGHLIGHTS | METHODS IN BRIEF
miRNA profiling depends on platform
Nature Methods 11, 369 (2014) doi:10.1038/nmeth.2905
Published online 28 March 2014
et al. PLoS One 9, e87782 (2014).
MicroRNAs (miRNAs) regulate diverse processes in the cell by tuning the levels of target RNAs. By comparing miRNA expression between tumor and matched nontumor tissue, scientists can identify miRNAs that play a role in cancer. Two common profiling methods are miRNA microarrays and high-throughput miRNA sequencing. A report by Wan et al. indicates that results from these platforms should be interpreted with caution. The researchers find very low concordance between array and sequencing data on identical ovarian cancer s…
When researchers at Baylor College of Medicine (www.bcm.edu) sought to mine The Cancer Genome Atlas for information on the effects of small bits of genetic material called microRNAs on survival for patients with ovarian cancer, they made a startling discovery.
Using a technique called microarray or gene chips, they identified 61 microRNAs associated with survival in 469 ovarian cancers. However, when they used next generation sequencing to ask the same question, they found 12 in the same specimens. Only one microRNA was associated with survival in both data sets. A report on their work appears in the open access journal PLOS One.
Our study on the reproducibility between miRNA microarray and sequencing technology was published in PLOS ONE [PDF]. This study found that large percentage of miRNAs demonstrated poor correlation between the array and seq platforms. (Figure below).
Kaifang’s paper on combinatorial drug therapy through mixed integer linear programming was accepted for publication in Bioinformatics as an original research article.
Welcome to Denise who has now formally joined our group as a postdoctoral fellow!
Congratulations to Andrew for passing his qulification exam.
We just got two collaborative awards with Sardiello and Mirjana Maletic-Savatic lab. These two grants will enable us to generate a strong set of preliminary data for our future grants.
Congratulations to William who just won the 1st place in Graduate Student Research Symposium!
Our paper titled ‘IDENTIFYING CANCER BIOMARKERS THROUGH A NETWORK REGULARIZED COX MODEL’ has been accepted as a regular paper to be presented in the 2013 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS 2013). Congratulations to Ying-Wooi Wan and John Nagorski.
Congratulations to Sangeetha and Wooi. Their paper on ” NLRP7 affects trophoblast lineage differentiation, binds to overexpressed YY1 and alters CpG methylation” was accepted by Human Molecular Genetics.
National Science Foundation DMS-1263932 collaborative grant to study “Statistical Methods for Integrated Analysis of High-Throughput Biomedical Data”, September 2013-2017, with Genevera Allen and Pradeep Ravikumar.
In the joint DMS/NIGMS Initiative to Support Research at the Interface of the Biological and Mathematical Sciences, each proposal received a NIH priority score from each panelist, as well as a consensus panel ranking in three categories: (i) highly competitive, (ii) competitive, and (iii) not competitive. Less than 10% of the projects were placed in the highly competitive category, approximately 30% in the competitive, and the remainder in the not competitive. Our proposal was put in the “highly competitive” category by the NSF panel.
Congrats to Wen Zhang who has been chosen to receive an ICIBM 2013 Student & Trainee Travel Award.
Congrats to Wen Zhang and Wooi Wan for their manuscript “Molecular pathway identification using biological network-regularized logistic models” that was accepted by BMC Genomcis!