The MORPH Algorithm: Ranking Candidate Genes for Membership in Arabidopsis and Tomato Pathways

Closing gaps in our current knowledge about biological pathways is a fundamental challenge. The development of novel computational methods along with high-throughput experimental data carries the promise to help in the challenge. We present an algorithm called MORPH (for module-guided ranking of candidate pathway genes) for revealing unknown genes in biological pathways. The method receives as input a set of known genes from the target pathway, a collection of expression profiles, and interaction and metabolic networks. Using machine learning techniques, MORPH selects the best combination of data and analysis method and outputs a ranking of candidate genes predicted to belong to the target pathway. We tested MORPH on 230 known pathways in Arabidopsis thaliana and 93 known pathways in tomato (Solanum lycopersicum) and obtained high-quality cross-validation results. In the photosynthesis light reactions, homogalacturonan biosynthesis, and chlorophyll biosynthetic pathways of Arabidopsis, genes ranked highly by MORPH were recently verified to be associated with these pathways. MORPH candidates ranked for the carotenoid pathway from Arabidopsis and tomato are derived from pathways that compete for common precursors or from pathways that are coregulated with or regulate the carotenoid biosynthetic pathway.     

A novel knowledge-based approach to design inorganic-binding peptides

MOTIVATION: The discovery of solid-binding peptide sequences is accelerating along with their practical applications in biotechnology and materials sciences. A better understanding of the relationships between the peptide sequences and their binding affinities or specificities will enable further design of novel peptides with selected properties of interest both in engineering and medicine. RESULTS: A bioinformatics approach was developed to classify peptides selected by in vivo techniques according to their inorganic solid-binding properties. Our approach performs all-against-all comparisons of experimentally selected peptides with short amino acid sequences that were categorized for their binding affinity and scores the alignments using sequence similarity scoring matrices. We generated novel scoring matrices that optimize the similarities within the strong-binding peptide sequences and the differences between the strong- and weak-binding peptide sequences. Using the scoring matrices thus generated, a given peptide is classified based on the sequence similarity to a set of experimentally selected peptides. We demonstrate the new approach by classifying experimentally characterized quartz-binding peptides and computationally designing new sequences with specific affinities. Experimental verifications of binding of these computationally designed peptides confirm our predictions with high accuracy. We further show that our approach is a general one and can be used to design new sequences that bind to a given inorganic solid with predictable and enhanced affinity.     

Personal adaptive clusters as containers for scientific jobs

We describe a system for creating personal clusters in user-space to support the submission and management of thousands of compute-intensive serial jobs to the network-connected compute resources on the NSF TeraGrid. The system implements a robust infrastructure that submits and manages job proxies across a distributed computing environment. These job proxies contribute resources to personal clusters created dynamically for a user on-demand. The personal clusters then adapt to the prevailing job load conditions at the distributed sites by migrating job proxies to sites expected to provide resources more quickly. Furthermore, the system allows multiple instances of these personal clusters to be created as containers for individual scientific experiments, allowing the submission environment to be customized for each instance. The version of the system described in this paper allows users to build large personal Condor and Sun Grid Engine clusters on the TeraGrid. Users then manage their scientific jobs, within each personal cluster, with a single uniform interface using the feature-rich functionality found in these job management environments.

PRIMAL: Fast and Accurate Pedigree-based Imputation from Sequence Data in a Founder Population

Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.     

All-trans retinoic acid modifies the expression of clock and disease marker genes

Restricted feeding (RF), a regimen that restricts the duration of food availability with no calorie restriction, entrains the circadian clock in peripheral tissues. Restricted feeding leads to high-amplitude circadian rhythms, which have been shown to promote wellness and reduce disease and inflammatory markers. Retinoids, such as all-trans retinoic acid (ATRA), act as anti-inflammatory agents. Thus far, the effect of ATRA combined with RF on the ability to delay the occurrence of age-associated changes, such as cancer and inflammation, is not known. We measured circadian expression of clock genes, disease marker genes and inflammatory markers in the serum, liver and jejunum in mice fed ad libitum (AL) or RF supplemented with 15 or 250 μg/kg body/day ATRA for 16 weeks. Our results show that ATRA supplementation led to phase shifts and reduced amplitudes in clock genes. Under AL, ATRA reduced the average daily messenger RNA (mRNA) levels of some disease markers, such as liver Afp and jejunum Afp, Alt and Gadd45β and aspartate transaminase (AST) protein in the serum, but increased the expression level of liver Crp mRNA. Under RF, ATRA reduced the average daily levels of jejunum Alt and Gadd45β and AST protein in the serum, but increased liver Afp, Alt, Gadd45β and Arginase mRNA. Altogether, our findings suggest that ATRA strongly affects circadian oscillation and disease marker levels. Moreover, its impact is different depending on the feeding regimen (AL or RF).     

nMAT1, a nuclear-encoded maturase involved in the trans-splicing of nad1 intron 1, is essential for mitochondrial complex I assembly and function

Mitochondrial genomes (mtDNAs) in angiosperms contain numerous group II-type introns that reside mainly within protein-coding genes that are required for organellar genome expression and respiration. While splicing of group II introns in non-plant systems is facilitated by proteins encoded within the introns themselves (maturases), the mitochondrial introns in plants have diverged and have lost the vast majority of their intron-encoded ORFs. Only a single maturase gene (matR) is retained in plant mtDNAs, but its role(s) in the splicing of mitochondrial introns is currently unknown. In addition to matR, plants also harbor four nuclear maturase genes (nMat 1 to 4) encoding mitochondrial proteins that are expected to act in the splicing of group II introns. Recently, we established the role of one of these proteins, nMAT2, in the splicing of several mitochondrial introns in Arabidopsis. Here, we show that nMAT1 is required for trans-splicing of nad1 intron 1 and also functions in cis-splicing of nad2 intron 1 and nad4 intron 2. Homozygous nMat1 plants show retarded growth and developmental phenotypes, modified respiration activities and altered stress responses that are tightly correlated with mitochondrial complex I defects.     

Dynamics and persistence of Dead Sea microbial populations as shown by high-throughput sequencing of rRNA

16S rRNA amplicon libraries from a haloarchaeal bloom in the hypersaline Dead Sea in 1992 were analyzed together with the 2007 residual population and simulated blooms in experimental mesocosms. Significant population shifts were observed during the bloom, and surprisingly a signature from the bloom was retained 15 years later.