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Abstract Background The de novo assembly of genomes and transcriptomes from short sequences is a challenging problem. Because of the high coverage needed to assemble short sequences as well as the overhead of modeling the assembly problem as a graph problem, the methods for short sequence assembly are often validated using data from BACs or small sized prokaryotic genomes. Results We present a parallel method for transcriptome assembly from large short sequence data sets. Our solution uses a rigorous graph theoretic framework and tames the computational and space complexity using parallel computers. First, we construct a distributed bidirected graph that captures overlap information. Next, we compact all chains in this graph to determine long unique contigs using undirected parallel list ranking, a problem for which we present an algorithm. Finally, we process this compacted distributed graph to resolve unique regions that are separated by repeats, exploiting the naturally occurring coverage variations arising from differential expression. Conclusion We demonstrate the validity of our method using a synthetic high coverage data set generated from the predicted coding regions of Zea mays. We assemble 925 million sequences consisting of 40 billion nucleotides in a few minutes on a 1024 processor Blue Gene/L. Our method is the first fully distributed method for assembling a non-hierarchical short sequence data set and can scale to large problem sizes.

Despite recent progress in characterizing the within-species variability ( WSV) of plant functional traits, the importance of this WSV in driving ecological processes such as leaf litter decomposability within species or at the whole community level is poorly understood., We ask whether leaf and litter functional traits vary within species to form a spectrum of variability analogous to the leaf economics spectrum that occurs among species. We also ask whether this spectrum of trait variation within species is an important driver of leaf litter decomposability. To address these questions, we quantified both WSV and between-species variation of leaf and litter traits and litter decomposability of 16 co-occurring temperate rain forest plant species along soil toposequences characterized by strong shifts in soil nutrient status in New Zealand., We found considerable WSV of both leaf and litter traits for all species, and a within-species spectrum of coordinated trait variation for 11 species. The WSV of leaf and to a lesser extent foliar litter C to N and C to P values were often strongly related to soil C to N and C to P ratios across plots. Further, in many cases, WSV and its covariation with species turnover contributed significantly to the community-level aggregate trait response to variation in soil fertility., Contrary to our expectations, the WSV in leaf and litter traits did not generally predict within-species variation in leaf litter mass loss, nor N and P release, during decomposition. Further, inclusion of WSV did not improve predictions of leaf litter decomposability using community-level trait measures., Synthesis. Our findings support the view that WSV of plant functional traits is an important component of plant community responses to environmental factors such as soil fertility. However, the apparent decoupling of WSV of leaf economic traits from WSV of ecological processes such as litter decomposability suggests that consideration of WSV may not be necessary to understand the contributions of trait variation to determining the breakdown of plant litter and therefore, potentially, ecosystem processes. [ABSTRACT FROM AUTHOR]

Background: The de novo assembly of genomes and transcriptomes from short sequences is a challenging problem. Because of the high coverage needed to assemble short sequences as well as the overhead of modeling the assembly problem as a graph problem, the methods for short sequence assembly are often validated using data from BACs or small sized prokaryotic genomes. Results: We present a parallel method for transcriptome assembly from large short sequence data sets. Our solution uses a rigorous graph theoretic framework and tames the computational and space complexity using parallel computers. First, we construct a distributed bidirected graph that captures overlap information. Next, we compact all chains in this graph to determine long unique contigs using undirected parallel list ranking, a problem for which we present an algorithm. Finally, we process this compacted distributed graph to resolve unique regions that are separated by repeats, exploiting the naturally occurring coverage variations arising from differential expression. Conclusion: We demonstrate the validity of our method using a synthetic high coverage data set generated from the predicted coding regions of Zea mays. We assemble 925 million sequences consisting of 40 billion nucleotides in a few minutes on a 1024 processor Blue Gene/L. Our method is the first fully distributed method for assembling a non-hierarchical short sequence data set and can scale to large problem sizes. [ABSTRACT FROM AUTHOR]

The article discusses several legal cases in various topics in the U.S. One of the case involved is Integra Lifesciences Corp. v. Merck & Co. Inc. which they failed to negotiate about the applications of RGD peptide for wound healing and prosthetics. The District Court for the South District of California dismissed the case against David Cheresh, a researcher of The Scripps Research Institute, however, a patent infringement of Merck remained in the court.