BACKGROUND: Many metazoan genomes conserve chromosome-scale gene linkage relationships ("macro-synteny") from the common ancestor of multicellular animal life 1234, but the biological explanation for this conservation is still unknown. Double cut and join (DCJ) is a simple, well-studied model of neutral genome evolution amenable to both simulation and mathematical analysis 5, but as we show here, it is not sufficent to explain long-term macro-synteny conservation. RESULTS: We examine a family of simple (one-parameter) extensions of DCJ to identify models and choices of parameters consistent with the levels of macro- and micro-synteny conservation observed among animal genomes. Our software implements a flexible strategy for incorporating genomic context into the DCJ model to incorporate various types of genomic context ("DCJ-[C]"), and is available as open source software from http://github.com/putnamlab/dcj-c. CONCLUSIONS: A simple model of genome evolution, in which DCJ moves are allowed only if they maintain chromosomal linkage among a set of constrained genes, can simultaneously account for the level of macro-synteny conservation and for correlated conservation among multiple pairs of species. Simulations under this model indicate that a constraint on approximately 7% of metazoan genes is sufficient to constrain genome rearrangement to an average rate of 25 inversions and 1.7 translocations per million years.

SUMMARY: PIQA is a quality analysis pipeline designed to examine genomic reads produced by Next Generation Sequencing technology (Illumina G1 Genome Analyzer). A short statistical summary, as well as tile-by-tile and cycle-by-cycle graphical representation of clusters density, quality scores and nucleotide frequencies allow easy identification of various technical problems including defective tiles, mistakes in sample/library preparations and abnormalities in the frequencies of appearance of sequenced genomic reads. PIQA is written in the R statistical programming language and is compatible with bustard, fastq and scarf Illumina G1 Genome Analyzer data formats. AVAILABILITY: The PIQA pipeline, installation instructions and examples are available at the supplementary web site (http://bioinfo.uh.edu/PIQA).

Recognizing and transforming loops are essential steps in any attempt to improve the running time of a program. Aggressive restructuring techniques have been developed for single-entry (reducible) loops, but restructurers and the dataflow and dependence analysis they rely on often give up in the presence of multientry (irreducible) loops. Thus one irreducible loop can prevent the improvement of all loops in a procedure. This article give an algorithm to build a loop nesting tree for a procedure with arbitrary control flow. The algorithm uses definitions of reducible and irreducible loops which allow either kind of loop to be nested in the other. The tree construction algorithm, an extension of Tarjan's algorithm for testing reducibility, runs in almost linear time. In the presence of irreducible loops, the loop nesting tree can depend on the depth-first spanning tree used to build it. In particular, the header node representing a reducible loop in one version of the loop nesting tree can be the representative of an irreducible loop in another. We give a normalization method that maximizes the set of reducible loops discovered, independent of the depth-first spanning tree used. The normalization require the insertion of at most one node and one edge per reducible loop.

This paper presents techniques for compiling loops with complex, indirect array accesses into loops whose array references have at most one level of indirection. The transformation allows prefetching of array indices for more efficient structuring of communication on distributed-memory machines. It can also improve performance on other architectures by enabling prefetching of data between levels of the memory hierarchy or exploitation of hardware support for vectorized gather/scatter. Our techniques are implemented in a compiler for Fortran D and execution speed improvements are given for multiprocessor and vector machines.

Regular section analysis, which summarizes interprocedural side effects on subarrays in a form useful to dependence analysis, while avoiding the complexity of prior solutions, is shown to be a practical addition to a production compiler. Optimizing compilers should produce efficient code even in the presence of high-level language constructs. However, current programming support systems are significantly lacking in their ability to analyze procedure calls. This deficiency complicates parallel programming, because loops with calls can be a significant source of parallelism. The performance of regular section analysis is compared to two benchmarks: the LINPACK library of linear algebra subroutines and the Rice Compiler Evaluation Program Suite (RiCEPS), a set of complete application codes from a variety of scientific disciplines. The experimental results demonstrate that regular section analysis is an effective means of discovering parallelism, given programs written in an appropriately modular programming style.>

The authors describe an implementation of regular section analysis in the Rice Parallel Fortran Converter (PFC), an automatic parallelization system. The overriding concern in the implementation is that it be efficient enough to be incorporated in a practical compilation system. This implementation of regular section analysis describes interprocedural side effects on subarrays in a form useful to dependence analysis while avoiding the complexity of prior solutions. The authors also examine the performance of regular section analysis on two benchmarks: the LINPACK library of linear algebra subroutines and the Rice Compiler Evaluation Program Suite, a set of complete application codes from a variety of scientific disciplines. It is demonstrated that regular section analysis is an effective means of discovering parallelism, given programs written in an appropriately modular programming style.>