The bee family Halictidae (Hymenoptera, Apoidea) from Central Asia collected by the Kyushu and Shimane Universities Expeditions

Central Asia is one of the important centers of bee diversity in the Palearctic Region. However, there is insufficient information for many taxa in the central Asian bee fauna. The Kyushu and Shimane Universities (Japan) Expeditions to Kazakhstan, Kyrgyzstan, Uzbekistan, and Xinjiang Uyghur of China were conducted in the years 2000 to 2004 and 2012 to 2014. Eighty-eight species of the bee family Halictidae Thomson, 1869 are enumerated including new localities in central Asia. Halictus tibialis Walker, 1871, H. persephone Ebmer, 1976, Lasioglossum denislucum (Strand, 1909), L. griseolum (Morawitz, 1872), L. melanopus (Dalla Torre, 1896), L. nitidiusculum (Kirby, 1802), L. sexnotatulum (Nylander, 1852), L. subequestre (Blüthgen, 1931), L. sublaterale (Blüthgen, 1931), and L. zonulum (Smith, 1848) are recorded from central Asia for the first time. Thirty-two species are newly recorded from Kazakhstan, 19 spp. from Kyrgyzstan, 2 spp. from Uzbekistan, and 11 spp. from Xinjiang Uyghur of China. The genus Lasioglossum dominated the number of species and individuals in the collection. The halictid fauna mostly composed of western to central Asian elements in our surveyed area

Colletes jankowskyi (Hymenoptera: Colletidae) newly recorded from Japan, with some biological notes and DNA barcodes

Colletes jankowskyi Radoszkowski is recorded from Japan for the first time.  It is similar to C. babai Hirashima & Tadauchi and C. floralis Eversmann of the Japanese congeners, but is separated from these allied species by the combination of following characters: malar space short, less than one-half of basal width of mandible; mesoscutum with whitish hairs mixed with darker ones; first metasomal tergum with dense punctures; and hair zone on disc of seventh metasomal sternum narrow in central area.  DNA barcodes are also useful for discrimination among these three species.  The habitat of Japanese C. jankowskyi may be limited to semi-natural grassland.  Adults appeared from mid-August to mid-September.  The number of individuals is richest from late August to early September, although the species had been collected earlier in the season on the Asian mainland.  Most specimens were collected on flowers of Lespedeza cyrtobotrya Miq. (Fabaceae).  In Japan, C. jankowskyi is suggested as a relict species judging from the distribution and habitat information

Extensive Association of Functionally and Cytotopically Related mRNAs with Puf Family RNA-Binding Proteins in Yeast

Genes encoding RNA-binding proteins are diverse and abundant in eukaryotic genomes. Although some have been shown to have roles in post-transcriptional regulation of the expression of specific genes, few of these proteins have been studied systematically. We have used an affinity tag to isolate each of the five members of the Puf family of RNA-binding proteins in Saccharomyces cerevisiae and DNA microarrays to comprehensively identify the associated mRNAs. Distinct groups of 40–220 different mRNAs with striking common themes in the functions and subcellular localization of the proteins they encode are associated with each of the five Puf proteins: Puf3p binds nearly exclusively to cytoplasmic mRNAs that encode mitochondrial proteins; Puf1p and Puf2p interact preferentially with mRNAs encoding membrane-associated proteins; Puf4p preferentially binds mRNAs encoding nucleolar ribosomal RNA-processing factors; and Puf5p is associated with mRNAs encoding chromatin modifiers and components of the spindle pole body. We identified distinct sequence motifs in the 3′-untranslated regions of the mRNAs bound by Puf3p, Puf4p, and Puf5p. Three-hybrid assays confirmed the role of these motifs in specific RNA–protein interactions in vivo. The results suggest that combinatorial tagging of transcripts by specific RNA-binding proteins may be a general mechanism for coordinated control of the localization, translation, and decay of mRNAs and thus an integral part of the global gene expression program

Tinkering Evolution of Post-Transcriptional RNA Regulons: Puf3p in Fungi as an Example

Genome-wide studies of post-transcriptional mRNA regulation in model organisms indicate a “post-transcriptional RNA regulon” model, in which a set of functionally related genes is regulated by mRNA–binding RNAs or proteins. One well-studied post-transcriptional regulon by Puf3p functions in mitochondrial biogenesis in budding yeast. The evolution of the Puf3p regulon remains unclear because previous studies have shown functional divergence of Puf3p regulon targets among yeast, fruit fly, and humans. By analyzing evolutionary patterns of Puf3p and its targeted genes in forty-two sequenced fungi, we demonstrated that, although the Puf3p regulon is conserved among all of the studied fungi, the dedicated regulation of mitochondrial biogenesis by Puf3p emerged only in the Saccharomycotina clade. Moreover, the evolution of the Puf3p regulon was coupled with evolution of codon usage bias in down-regulating expression of genes that function in mitochondria in yeast species after genome duplication. Our results provide a scenario for how evolution like a tinker exploits pre-existing materials of a conserved post-transcriptional regulon to regulate gene expression for novel functional roles

Comparative Analysis of mRNA Targets for Human PUF-Family Proteins Suggests Extensive Interaction with the miRNA Regulatory System

Genome-wide identification of mRNAs regulated by RNA-binding proteins is crucial to uncover post-transcriptional gene regulatory systems. The conserved PUF family RNA-binding proteins repress gene expression post-transcriptionally by binding to sequence elements in 3′-UTRs of mRNAs. Despite their well-studied implications for development and neurogenesis in metazoa, the mammalian PUF family members are only poorly characterized and mRNA targets are largely unknown. We have systematically identified the mRNAs associated with the two human PUF proteins, PUM1 and PUM2, by the recovery of endogenously formed ribonucleoprotein complexes and the analysis of associated RNAs with DNA microarrays. A largely overlapping set comprised of hundreds of mRNAs were reproducibly associated with the paralogous PUM proteins, many of them encoding functionally related proteins. A characteristic PUF-binding motif was highly enriched among PUM bound messages and validated with RNA pull-down experiments. Moreover, PUF motifs as well as surrounding sequences exhibit higher conservation in PUM bound messages as opposed to transcripts that were not found to be associated, suggesting that PUM function may be modulated by other factors that bind conserved elements. Strikingly, we found that PUF motifs are enriched around predicted miRNA binding sites and that high-confidence miRNA binding sites are significantly enriched in the 3′-UTRs of experimentally determined PUM1 and PUM2 targets, strongly suggesting an interaction of human PUM proteins with the miRNA regulatory system. Our work suggests extensive connections between the RBP and miRNA post-transcriptional regulatory systems and provides a framework for deciphering the molecular mechanism by which PUF proteins regulate their target mRNAs

Learning a Prior on Regulatory Potential from eQTL Data

Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of “regulatory features”—including the function of the gene and the conservation, type, and position of genetic polymorphisms—that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3—a sequence-specific RNA binding protein—and P-bodies—cytoplasmic structures that regulate translation and RNA stability—as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway