Nicholas Carriero

Linda in context

How can a system that differs sharply from all currently fashionable approaches score any kind of success? Heres how.

De novo mutations revealed by whole-exome sequencing are strongly associated with autism

Multiple studies have confirmed the contribution of rare de novo copy number variations to the risk for autism spectrum disorders. But whereas de novo single nucleotide variants have been identified in affected individuals, their contribution to risk has yet to be clarified. Specifically, the frequency and distribution of these mutations have not been well characterized in matched unaffected controls, and such data are vital to the interpretation of de novo coding mutations observed in probands. Here we show, using whole-exome sequencing of 928 individuals, including 200 phenotypically discordant sibling pairs, that highly disruptive (nonsense and splice-site) de novo mutations in brain-expressed genes are associated with autism spectrum disorders and carry large effects. On the basis of mutation rates in unaffected individuals, we demonstrate that multiple independent de novo single nucleotide variants in the same gene among unrelated probands reliably identifies risk alleles, providing a clear path forward for gene discovery. Among a total of 279 identified de novo coding mutations, there is a single instance in probands, and none in siblings, in which two independent nonsense variants disrupt the same gene, SCN2A (sodium channel, voltage-gated, type II, α subunit), a result that is highly unlikely by chance.

De novo mutations in histone-modifying genes in congenital heart disease.

Congenital heart disease (CHD) is the most frequent birth defect, affecting 0.8% of live births. Many cases occur sporadically and impair reproductive fitness, suggesting a role for de novo mutations. Here we compare the incidence of de novo mutations in 362 severe CHD cases and 264 controls by analysing exome sequencing of parent–offspring trios. CHD cases show a significant excess of protein-altering de novo mutations in genes expressed in the developing heart, with an odds ratio of 7.5 for damaging (premature termination, frameshift, splice site) mutations. Similar odds ratios are seen across the main classes of severe CHD. We find a marked excess of de novo mutations in genes involved in the production, removal or reading of histone 3 lysine 4 (H3K4) methylation, or ubiquitination of H2BK120, which is required for H3K4 methylation. There are also two de novo mutations in SMAD2, which regulates H3K27 methylation in the embryonic left–right organizer. The combination of both activating (H3K4 methylation) and inactivating (H3K27 methylation) chromatin marks characterizes ‘poised’ promoters and enhancers, which regulate expression of key developmental genes. These findings implicate de novo point mutations in several hundreds of genes that collectively contribute to approximately 10% of severe CHD.

PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data

Personal-genomics endeavors, such as the 1000 Genomes project, are generating maps of genomic structural variants by analyzing ends of massively sequenced genome fragments. To process these we developed Paired-End Mapper (PEMer; http://sv.gersteinlab.org/pemer). This comprises an analysis pipeline, compatible with several next-generation sequencing platforms; simulation-based error models, yielding confidence-values for each structural variant; and a back-end database. The simulations demonstrated high structural variant reconstruction efficiency for PEMers coverage-adjusted multi-cutoff scoring-strategy and showed its relative insensitivity to base-calling errors.

Distributed data structures in Linda

A <i>distributed data structure</i> is a data structure that can be manipulated by many parallel processes simultaneously. Distributed data structures are the natural complement to parallel program structures, where a <i>parallel program</i> (for our purposes) is one that is made up of many simultaneously active, communicating processes. Distributed data structures are impossible in most parallel programming languages, but they are supported in the parallel language Linda and they are central to Linda programming style. We outline Linda, then discuss some distributed data structures that have arisen in Linda programming experiments to date. Our intent is neither to discuss the design of the Linda system nor the performance of Linda programs, though we do comment on both topics; we are concerned instead with a few of the simpler and more basic techniques made possible by a language model that, we argue, is subtly but fundamentally different in its implications from most others.This material is based upon work supported by the National Science Foundation under Grant No. MCS-8303905. Jerry Leichter is supported by a Digital Equipment Corporation Graduate Engineering Education Program fellowship.

The S/Net's Linda kernel

Linda is a parallel programming language that differs from other parallel languages in its simplicity and in its support for distributed data structures. The S/Net is a multicomputer, designed and built at AT&T Bell Laboratories, that is based on a fast, word-parallel bus interconnect. We describe the Linda-supporting communication kernel we have implemented on the S/Net. The implementation suggests that Lindas unusual shared-memory-like communication primitives can be made to run well in the absence of physically shared memory; the simplicity of the language and of our implementations logical structure suggest that similar Linda implementations might readily be constructed on related architectures. We outline the language, and programming methodologies based on distributed data structures; we then describe the implementation, and the performance both of the Linda primitives themselves and of a simple S/Net-Linda matrix-multiplication program designed to exercise them.

Transcribed processed pseudogenes in the human genome: an intermediate form of expressed retrosequence lacking protein-coding ability

Pseudogenes, in the case of protein-coding genes, are gene copies that have lost the ability to code for a protein; they are typically identified through annotation of disabled, decayed or incomplete protein-coding sequences. Processed pseudogenes (PΨgs) are made through mRNA retrotransposition. There is overwhelming genomic evidence for thousands of human PΨgs and also dozens of human processed genes that comprise complete retrotransposed copies of other genes. Here, we survey for an intermediate entity, the transcribed processed pseudogene (TPΨg), which is disabled but nonetheless transcribed. TPΨgs may affect expression of paralogous genes, as observed in the case of the mouse makorin1-p1 TPΨg. To elucidate their role, we identified human TPΨgs by mapping expressed sequences onto PΨgs and, reciprocally, extracting TPΨgs from known mRNAs. We consider only those PΨgs that are homologous to either non-mammalian eukaryotic proteins or protein domains of known structure, and require detection of identical coding-sequence disablements in both the expressed and genomic sequences. Oligonucleotide microarray data provide further expression verification. Overall, we find 166–233 TPΨgs (∼4–6% of PΨgs). Proteins/transcripts with the highest numbers of homologous TPΨgs generally have many homologous PΨgs and are abundantly expressed. TPΨgs are significantly over-represented near both the 5′ and 3′ ends of genes; this suggests that TPΨgs can be formed through gene–promoter co-option, or intrusion into untranslated regions. However, roughly half of the TPΨgs are located away from genes in the intergenic DNA and thus may be co-opting cryptic promoters of undesignated origin. Furthermore, TPΨgs are unlike other PΨgs and processed genes in the following ways: (i) they do not show a significant tendency to either deposit on or originate from the X chromosome; (ii) only 5% of human TPΨgs have potential orthologs in mouse. This latter finding indicates that the vast majority of TPΨgs is lineage specific. This is likely linked to well-documented extensive lineage-specific SINE/LINE activity. The list of TPΨgs is available at: (or) .

Pseudogene.org: a comprehensive database and comparison platform for pseudogene annotation

The Pseudogene.org knowledgebase serves as a comprehensive repository for pseudogene annotation. The definition of a pseudogene varies within the literature, resulting in significantly different approaches to the problem of identification. Consequently, it is difficult to maintain a consistent collection of pseudogenes in detail necessary for their effective use. Our database is designed to address this issue. It integrates a variety of heterogeneous resources and supports a subset structure that highlights specific groups of pseudogenes that are of interest to the research community. Tools are provided for the comparison of sets and the creation of layered set unions, enabling researchers to derive a current ‘consensus’ set of pseudogenes. Additional features include versatile search, the capacity for robust interaction with other databases, the ability to reconstruct older versions of the database (accounting for changing genome builds) and an underlying object-oriented interface designed for researchers with a minimal knowledge of programming. At the present time, the database contains more than 100 000 pseudogenes spanning 64 prokaryote and 11 eukaryote genomes, including a collection of human annotations compiled from 16 sources.

Applications experience with Linda

We describe three experiments using C-Linda to write parallel codes. The first involves assessing the similarity of DNA sequences. The results demonstrate Lindas flexibility—Linda solutions are presented that work well at two quite different levels of granularity. The second uses a prime finder to illustrate a class of algorithms that do not (easily) submit to automatic parallelizers, but can be parallelized in straight-forward fashion using C-Linda. The final experiment describes the process lattice model, an “inherently” parallel application that is naturally conceived as multiple interacting processes. Taken together, the experience described here bolsters our claim that Linda can bridge the gap between the growing collection of parallel hardware and users eager to exploit parallelism. This work is supported by the NSF under grants DCR-8601920 and DCR-8657615 and by the ONR under grant N00014-86-K-0310. We are grateful to Argonne National Labs for providing access to a Sequent Symmetry.

The Linda alternative to message-passing systems

Abstract The use of distributed data structures in a logically-shared memory is a natural, readily-understood approach to parallel programming. The principal argument against such an approach for portable software has always been that efficient implementations could not scale to massively-parallel, distributed memory machines. Now, however, there is growing evidence that it is possible to develop efficient and portable implementations of virtual shared memory models on scalable architectures. In this paper we discuss one particular example: Linda. After presenting an introduction to the Linda model, we focus on the expressiveness of the model, on techniques required to build efficient implementations, and on observed performance both on workstation networks and distributed-memory parallel machines. Finally, we conclude by briefly discussing the range of applications developed with Linda and Lindas suitability for the sorts of heterogeneous, dynamically-changing computational environments that are of growing significance.