In sexual reproduction, ejaculate components that males transfer into the females vary because of various factors. For male honey bees, the entirety of their sperm is stored in the seminal vesicles until the first copulation with a female and subsequent ejaculation, after which the male will die. Therefore, we can evaluate age-related ejaculate alterations by investigating internal sexual organ changes with age. This study found that seminal vesicle wet weight decreased following sperm transfer from testes to seminal vesicles, while mucus gland weight was unchanged, thus resulting in increased sperm density in the seminal vesicles. This suggests that the decrease of seminal fluid in the seminal vesicles may be the underlying cause for age-related ejaculate component alterations.

Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment.

This chapter describes biochemical pathways operating in aerobic methylotrophic bacteria. We first define aerobic methylotrophy as a specific metabolic capability and describe the phylogenetic diversity of these bacteria. We then describe enzymes involved in primary oxidation of different single carbon substrates, resulting in formaldehyde or methyl or methylene radical, and describe the variety of pathways used for their assimilation and dissimilation. We also give a brief account of genetic manipulation tools in methylotrophic bacteria and examples of systems approaches for studying their metabolism, including availability of whole genome sequence information.

 Traditional honey bee hunting and beekeeping are vital to the economic and spiritual lives of Asians. Bee products are known as not only food/food supplement but also traditional medicine for aiming to promote good health, especially in eastern regions. Honey bees also play crucial roles in pollination. Asia is regarded as the homeland of honey bees as it hosts at least nine honey bee species. The European honey bee was introduced from Europe, North America, and Oceania to Russia, Japan, India and other countries in Asia. The growth of global human population size, globalized trade economic wealth, and technological developments in transportation efficacy has promoted the transmission of bee diseases, parasites and pests. A great concern over honeybee population decline has accelerated research in bee diseases, parasites, and pests. This chapter provides an up-to-date information on bee diseases, parasites, and pests in Asia.

A colony-level phenotype was used to map the major sex determination locus (designatedX) in the honey bee (Apis mellifera). Individual queen bees (reproductive females) were mated to single drones (fertile males) by instrumental insemination. Haploid drone progeny of an F1 queen were each backcrossed to daughter queens from one of the parental lines. Ninety-eight of the resulting colonies containing backcross progeny were evaluated for the trait ‘low brood-viability’ resulting from the production of diploid drones that were homozygous atX. DNA samples from the haploid drone fathers of these colonies were used individually in polymerase chain reactions (PCR) with 10-base primers. These reactions generated random amplified polymorphic DNA (RAPD) markers that were analyzed for cosegregation with the colony-level phenotype. One RAPD marker allele was shared by 22 of 25 drones that fathered low brood-viability colonies. The RAPD marker fragment was cloned and partially sequenced. Two primers were designed that define a sequence-tagged site (STS) for this locus. The primers amplified DNA marker fragments that cosegregated with the original RAPD marker. In order to more precisely estimate the linkage betweenX and the STS locus, another group of bees consisting of progeny from one of the low-brood viability colonies was used in segregation analysis. Four diploid drones and 181 of their diploid sisters (workers, nonfertile females) were tested for segregation of the RAPD and STS markers. The cosegregating RAPD and STS markers were codominant due to the occurrence of fragment-length alleles. The four diploid drones were homozygous for these markers but only three of the 181 workers were homozygotes (recombinants). Therefore the distance betweenX and the STS locus was estimated at 1.6 cM. An additional linked marker was found that was 6.6 cM from the STS locus.

We tested whether flow cytometry can be used for assessment of viability of honey bee (Apis mellifera) sperm. The method was used to detect possible competition between the sperm of different drones. The flow cytometry analysis of semen stained with SYBR-14/propidium iodide revealed significant differences between fresh and freeze-thawed samples. The identification of populations corresponding to viable and nonviable sperm allowed us to assess the sperm viability. The comparison of single-drone semen with mixed semen of two unrelated drones showed that sperm viability was not affected by mixing, but there were differences between mixed and unmixed semen in side scatter, which correlates with shape and optical homogeneity of particles. The proportion of particles in different populations also was affected by mixing of the semen. The results suggest that there are interactions between ejaculates of different drones, possibly related to sperm competition.

Summary

A deterministic model is presented which shows that multiple mating reduces the conflict between workers and queen in the optimal investment ratio in each sex. The natural risk of the nuptual flights of honeybee queens fits well into the theoretically determined risk when queens tend to optimize the numbers of drones with which they mate.

Background

A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data.

Results

We present acdc, a tool specifically developed to aid the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows.

Conclusions

Acdc can reliably detect contamination in single-cell genome data. In addition to database-driven detection, it complements existing tools by its unsupervised techniques, which allow for the detection of de novo contaminants. Our contribution has the potential to drastically reduce the amount of resources put into these processes, particularly in the context of limited availability of reference species. As single-cell genome data continues to grow rapidly, acdc adds to the toolkit of crucial quality assurance tools.

Honeybees are the most important pollinators of agricultural and horticultural crops. Most fruit, small seed and many vegetable crops require pollination for the production of economic yields. The value of the honeybee as a pollinator is far greater than its value as a honey producer. Not all crops need pollination. Some can produce fruit without fertilization of the flower. Some flowers are self pollinated, which means that pollen is transferred from the anther to the stigma of the same flower or flowers on the same plant variety. Although this transfer can be achieved by wind or rain, insect pollinators are the most effective. Of all the insects, hive bees are the most practical for crop pollination can be reared in sufficient numbers and placed in orchards wherever and whenever required for effective pollination. It has been found that the use of hive bees results in a manifold increase in yields and an improvement in the quality of produce.