Large scale gene duplication is a major force driving the evolution of genetic functional innovation.Whole genome duplications are widely believed to have played an important role in the evolution of the maize, yeast and vertebrate genomes. The use of evolutionary trees to analyze the history of gene duplication and estimate duplication times provides a powerful tool for studying this process. Many studies in the molecular evolution literature have used this approach on small data sets, using analyses performed by hand. The rapid growth of genetic sequence data will soon allow similar studies on a genomic scale, but such studies will be limited unless the analysis can be automated. Even existing data sets admit alternative hypotheses that would be too tedious to consider without automation.In this paper, we describe a program called NOTUNG that facilitates large scale analysis, using both rooted and unrooted trees. When tested on trees analyzed in the literature, NOTUNG consistently yielded results that agree with the assessments in the original publications. Thus, NOTUNG provides a basic building block for inferring duplication dates from gene trees automatically and can also be used as an exploratory analysis tool for evaluating alternative hypotheses.2

A central challenge in developing quantum computers and long-range quantum networks lies in the distribution of entanglement across many individually controllable qubits 1 . Colour centres in diamond have emerged as leading solid-state 'artificial atom' qubits 2,3 , enabling on-demand remote entanglement 4 , coherent control of over 10 ancillae qubits with minute-long coherence times 5 , and memory-enhanced quantum communication 6 . A critical next step is to integrate large numbers of artificial atoms with photonic architectures to enable large-scale quantum information processing systems. To date, these efforts have been stymied by qubit inhomogeneities, low device yield, and complex device requirements. Here, we introduce a process for the high-yield heterogeneous integration of 'quantum micro-chiplets' (QMCs) -diamond waveguide arrays containing highly coherent colour centreswith an aluminium nitride (AlN) photonic integrated circuit (PIC). Our process enables the development of a 72-channel defect-free array of germanium-vacancy (GeV) and silicon-vacancy (SiV) colour centres in a PIC. Photoluminescence spectroscopy reveals long-term stable and narrow average optical linewidths of 54 MHz (146 MHz) for GeV (SiV) emitters, close to the lifetime-limited linewidth of 32 MHz (93 MHz). Additionally, inhomogeneities in the individual qubits can be compensated in situ with integrated tuning of the optical frequencies over 100 GHz. The ability to assemble large numbers of nearly indistinguishable artificial atoms into phase-stable PICs provides an architecture toward multiplexed quantum repeaters 7,8 and general-purpose quantum computers [9][10][11] . Main textArtificial atom qubits in diamond combine minute-scale quantum memory times 5 with efficient spin-photon interfaces 2 , making them attractive for processing and distributing quantum information 1,3 . However, the low device yield of functional qubit systems presents a critical barrier to large-scale quantum information processing (QIP). Furthermore, although individual diamond cavity systems coupled to artificial atoms can now achieve excellent performance, the lack of active chip-integrated photonic components and wafer-scale single crystal diamond currently prohibit scaling to large-scale QIP applications [8][9][10][11] . A promising method to alleviate these constraints is heterogeneous integration (HI), which is increasingly used in advanced microelectronics to assemble separately fabricated sub-components into a single, multifunctional chip. HI approaches have also recently been used to integrate PICs with quantum devices, including quantum dot single-photon sources 12,13 , superconducting nanowire single-photon detectors 14 , and nitrogen-vacancy (NV) centre diamond waveguides 15 . However, these demonstrations assembled components one-by-one, which presents a formidable scaling challenge. The diamond 'quantum micro-chiplet (QMC)' introduced here significantly improves HI assembly yield and accuracy to enable a 72-channel defect-free waveguide-coupled art...

An obligate intermediate during microRNA (miRNA) biogenesis is an~22-nucleotide RNA duplex, from which the mature miRNA is preferentially incorporated into a silencing complex. Its partner miRNA* species is generally regarded as a passenger RNA, whose regulatory capacity has not been systematically examined in vertebrates. Our bioinformatic analyses demonstrate that a substantial fraction of miRNA* species are stringently conserved over vertebrate evolution, collectively exhibit greatest conservation in their seed regions, and define complementary motifs whose conservation across vertebrate 39-UTR evolution is statistically significant. Functional tests of 22 miRNA expression constructs revealed that a majority could repress both miRNA and miRNA* perfect match reporters, and the ratio of miRNA:miRNA* sensor repression was correlated with the endogenous ratio of miRNA:miRNA* reads. Analysis of microarray data provided transcriptome-wide evidence for the regulation of seedmatched targets for both mature and star strand species of several miRNAs relevant to oncogenesis, including mir-17, mir-34a, and mir-19. Finally, 39-UTR sensor assays and mutagenesis tests confirmed direct repression of five miR-19* targets via star seed sites. Overall, our data demonstrate that miRNA* species have demonstrable impact on vertebrate regulatory networks and should be taken into account in studies of miRNA functions and their contribution to disease states.

The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems.

BackgroundMicroRNAs (miRNAs) are established regulators of development, cell identity and disease. Although nearly two thousand human miRNA genes are known and new ones are continuously discovered, no attempt has been made to gauge the total miRNA content of the human genome.ResultsEmploying an innovative computational method on massively pooled small RNA sequencing data, we report 2,469 novel human miRNA candidates of which 1,098 are validated by in-house and published experiments. Almost 300 candidates are robustly expressed in a neuronal cell system and are regulated during differentiation or when biogenesis factors Dicer, Drosha, DGCR8 or Ago2 are silenced. To improve expression profiling, we devised a quantitative miRNA capture system. In a kidney cell system, 400 candidates interact with DGCR8 at transcript positions that suggest miRNA hairpin recognition, and 1,000 of the new miRNA candidates interact with Ago1 or Ago2, indicating that they are directly bound by miRNA effector proteins. From kidney cell CLASH experiments, in which miRNA-target pairs are ligated and sequenced, we observe hundreds of interactions between novel miRNAs and mRNA targets. The novel miRNA candidates are specifically but lowly expressed, raising the possibility that not all may be functional. Interestingly, the majority are evolutionarily young and overrepresented in the human brain.ConclusionsIn summary, we present evidence that the complement of human miRNA genes is substantially larger than anticipated, and that more are likely to be discovered in the future as more tissues and experimental conditions are sequenced to greater depth.