Alignment and Prediction of cis-Regulatory Modules Based on a Probabilistic Model of Evolution

Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs) and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs) and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i) the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii) binding sites in distal bound sequences (relative to transcription start sites) tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis), ready to be applied in a broad biological context

Impact of family capital & social capital on youth entrepreneurship – a study of Uttarakhand state, India

The research paper intends to interpret how the three forms of family capital viz. family's financial capital, family's man power capital and family's human capital influences the career choice intention of students of HEI's of Uttarakhand, India. Additionally the study also evaluates the impact of student's individual social capital on his career intent. This is a quantitative study conducted at Uttarakhand state of India on a large sample of students studying in various professional courses of Uttarakhand. The research validates a positive relationship between the family's financial capital and higher education intention of students. The study found no influence of family's financial capital (measured as father's annual income), manpower capital (measured as family size) and human capital (measured as father's occupation) on career intentions of students. The study confirmed that there is a significant impact of students' social capital network span on his career intentions, especially in taking up entrepreneurship as a career choice

Management of pancreaticobiliary disease using a new intra-ductal endoscope: The Texas experience

AIM: To evaluate a new single-operator mini-endoscope, Spyglass®, for its performance, feasibility and safety in the management of pancreaticobiliary disease

National attachments, economic competition, and social exclusion of non-ethnic migrants in Israel: a mixed-methods approach

National identity, Chauvinism, Perceived threat, Labor migrants, Israel, Mixed-methods,