Although many long noncoding RNAs (lncRNAs) have been identified in human and other mammalian genomes, there has been limited systematic functional characterization of these elements. In particular, the contribution of lncRNAs to organ development remains largely unexplored. Here we analyse the expression patterns of lncRNAs across developmental time points in seven major organs, from early organogenesis to adulthood, in seven species (human, rhesus macaque, mouse, rat, rabbit, opossum and chicken). Our analyses identified approximately 15,000 to 35,000 candidate lncRNAs in each species, most of which show species specificity. We characterized the expression patterns of lncRNAs across developmental stages, and found many with dynamic expression patterns across time that show signatures of enrichment for functionality. During development, there is a transition from broadly expressed and conserved lncRNAs towards an increasing number of lineage- and organ-specific lncRNAs. Our study provides a resource of candidate lncRNAs and their patterns of expression and evolutionary conservation across mammalian organ development.

The evolution of gene expression in mammalian organ development remains largely uncharacterized. Here we report the transcriptomes of seven organs (cerebrum, cerebellum, heart, kidney, liver, ovary and testis) across developmental time points from early organogenesis to adulthood for human, rhesus macaque, mouse, rat, rabbit, opossum and chicken. Comparisons of gene expression patterns identified correspondences of developmental stages across species, and differences in the timing of key events during the development of the gonads. We found that the breadth of gene expression and the extent of purifying selection gradually decrease during development, whereas the amount of positive selection and expression of new genes increase. We identified differences in the temporal trajectories of expression of individual genes across species, with brain tissues showing the smallest percentage of trajectory changes, and the liver and testis showing the largest. Our work provides a resource of developmental transcriptomes of seven organs across seven species, and comparative analyses that characterize the development and evolution of mammalian organs.

Gene families evolve by the processes of speciation (creating orthologs), gene duplication (paralogs) and horizontal gene transfer (xenologs), in addition to sequence divergence and gene loss. Orthologs in particular play an essential role in comparative genomics and phylogenomic analyses. With the continued sequencing of organisms across the tree of life, the data are available to reconstruct the unique evolutionary histories of tens of thousands of gene families. Accurate reconstruction of these histories, however, is a challenging computational problem, and the focus of the Quest for Orthologs Consortium. We review the recent advances and outstanding challenges in this field, as revealed at a symposium and meeting held at the University of Southern California in 2017. Key advances have been made both at the level of orthology algorithm development and with respect to coordination across the community of algorithm developers and orthology end-users. Applications spanned a broad range, including gene function prediction, phylostratigraphy, genome evolution, and phylogenomics. The meetings highlighted the increasing use of meta-analyses integrating results from multiple different algorithms, and discussed ongoing challenges in orthology inference as well as the next steps toward improvement and integration of orthology resources.

© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs-corresponding genes across multiple species-but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0.

© 2019 Altenhoff et al.; Published by Cold Spring Harbor Laboratory Press.

The human gut is colonized by commensal microorganisms, predominately bacteria that have coevolved in symbiosis with their host. The gut microbiota has been extensively studied in recent years, and many important findings on how it can regulate host metabolism have been unraveled. In healthy individuals, feeding timing and type of food can influence not only the composition but also the circadian oscillation of the gut microbiota. Host feeding habits thus influence the type of microbial-derived metabolites produced and their concentrations throughout the day. These microbial-derived metabolites influence many aspects of host physiology, including energy metabolism and circadian rhythm. Peroxisome proliferator-activated receptors (PPARs) are a group of ligand-activated transcription factors that regulate various metabolic processes such as fatty acid metabolism. Similar to the gut microbiota, PPAR expression in various organs oscillates diurnally, and studies have shown that the gut microbiota can influence PPAR activities in various metabolic organs. For example, short-chain fatty acids, the most abundant type of metabolites produced by anaerobic fermentation of dietary fibers by the gut microbiota, are PPAR agonists. In this review, we highlight how the gut microbiota can regulate PPARs in key metabolic organs, namely, in the intestines, liver, and muscle. Knowing that the gut microbiota impacts metabolism and is altered in individuals with metabolic diseases might allow treatment of these patients using noninvasive procedures such as gut microbiota manipulation.-Oh, H. Y. P., Visvalingam, V., Wahli, W. The PPAR-microbiota-metabolic organ trilogy to fine-tune physiology.