The Piwi pathway is deeply conserved amongst animals because one of its essential functions is to repress transposons. However, many Piwi-interacting RNAs (piRNAs) do not base-pair to transposons and remain mysterious in their targeting function. The sheer number of piRNA cluster (piC) loci in animal genomes and infrequent piRNA sequence conservation also present challenges in determining which piC loci are most important for development. To address this question, we determined the piRNA expression patterns of piC loci across a wide phylogenetic spectrum of animals, and reveal that most genic and intergenic piC loci evolve rapidly in their capacity to generate piRNAs, regardless of known transposon silencing function. Surprisingly, we also uncovered a distinct set of piC loci with piRNA expression conserved deeply in Eutherian mammals. We name these loci Eutherian-Conserved piRNA cluster (ECpiC) loci. Supporting the hypothesis that conservation of piRNA expression across ~100 million years of Eutherian evolution implies function, we determined that one ECpiC locus generates abundant piRNAs antisense to the STOX1 transcript, a gene clinically associated with preeclampsia. Furthermore, we confirmed reduced piRNAs in existing mouse mutations at ECpiC-Asb1 and -Cbl, which also display spermatogenic defects. The Asb1 mutant testes with strongly reduced Asb1 piRNAs also exhibit up-regulated gene expression profiles. These data indicate ECpiC loci may be specially adapted to support Eutherian reproduction.

Early environmental experiences profoundly influence adult phenotypes through complex mechanisms that are poorly understood. We previously showed that adult Caenorhabditis elegans that transiently passed through the stress-induced dauer larval stage (post-dauer adults) exhibit significant changes in gene expression profiles, chromatin states, and life history traits when compared with adults that bypassed the dauer stage (control adults). These wild-type, isogenic animals of equivalent developmental stages exhibit different signatures of molecular marks that reflect their distinct developmental trajectories. To gain insight into the mechanisms that contribute to these developmental history-dependent phenotypes, we profiled small RNAs from post-dauer and control adults by deep sequencing. RNA interference (RNAi) pathways are known to regulate genome-wide gene expression both at the chromatin and post-transcriptional level. By quantifying changes in endogenous small interfering RNA (endo-siRNA) levels in post-dauer as compared with control animals, our analyses identified a subset of genes that are likely targets of developmental history-dependent reprogramming through a complex RNAi-mediated mechanism. Mutations in specific endo-siRNA pathways affect expected gene expression and chromatin state changes for a subset of genes in post-dauer animals, as well as disrupt their increased brood size phenotype. We also find that both chromatin state and endo-siRNA distribution in dauers are unique, and suggest that remodeling in dauers provides a template for the subsequent establishment of adult post-dauer profiles. Our results indicate a role for endo-siRNA pathways as a contributing mechanism to early experience-dependent phenotypic plasticity in adults, and describe how developmental history can program adult physiology and behavior via epigenetic mechanisms.

We describe a method for discovering active motifs in a set of related protein sequences. The method is an automatic two step process: (1) find candidate motifs in a small sample of the sequences; (2) test whether these motifs are approximately present in all the sequences. To reduce the running time, we develop two optimization heuristics based on statistical estimation and pattern matching techniques. Experimental results obtained by running these algorithms on generated data and functionally related proteins demonstrate the good performance of the presented method compared with visual method of O'Farrell and Leopold. By combining the discovered motifs with an existing fingerprint technique, we develop a protein classifier. When we apply the classifier to the 698 groups of related proteins in the PROSITE catalog, it gives information that is complementary to the BLOCKS protein classifier of Henikoff and Henikoff. Thus, using our classifier in conjunction with theirs, one can obtain high confidence classifications (if BLOCKS and our classifier agree) or suggest a new hypothesis (if the two disagree).

We have studied five methods of protein classification and have applied them to the 768 groups of related proteins in the PROSITE catalog. Four of these methods are based on searching a database of blocks, and the other uses the frequently occurring motifs found in the protein families combined with a fingerprint technique. Our experimental results show that the block-based methods perform well when taking into account the probability of amino acids occurring in a block. Furthermore, the five methods give information that is complementary to each other. Thus, using the five methods together, one can obtain high confidence classifications (if the results agree) or suggest alternative hypotheses (if the results disagree). We also list those proteins whose current families documented in the PROSITE catalog differ from those suggested by our results. There are remarkably few of them, which is a testimony to the quality of PROSITE.

Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of the approximately 30000 known and predicted human coding genes are characterized and have been assigned at least one function, there remains a fair number of genes (about 12000) for which no annotation has been made. The recent sequencing of other genomes has provided us with a huge amount of auxiliary sequence data which could help in the characterization of the human genes. Clustering these sequences into families is one of the first steps to perform comparative studies across several genomes.