Honey bees (Apis mellifera) play a critical role in global food production as pollinators of numerous crops. Recently, honey bee populations in the United States, Canada, and Europe have suffered an unexplained increase in annual losses due to a phenomenon known as Colony Collapse Disorder (CCD). Epidemiological analysis of CCD is confounded by a relative dearth of bee pathogen field studies. To identify what constitutes an abnormal pathophysiological condition in a honey bee colony, it is critical to have characterized the spectrum of exogenous infectious agents in healthy hives over time. We conducted a prospective study of a large scale migratory bee keeping operation using high-frequency sampling paired with comprehensive molecular detection methods, including a custom microarray, qPCR, and ultra deep sequencing. We established seasonal incidence and abundance of known viruses, Nosema sp., Crithidia mellificae, and bacteria. Ultra deep sequence analysis further identified four novel RNA viruses, two of which were the most abundant observed components of the honey bee microbiome (∼10(11) viruses per honey bee). Our results demonstrate episodic viral incidence and distinct pathogen patterns between summer and winter time-points. Peak infection of common honey bee viruses and Nosema occurred in the summer, whereas levels of the trypanosomatid Crithidia mellificae and Lake Sinai virus 2, a novel virus, peaked in January.
Bee microbiome paired-end, part A
The paired-end deep-sequence data from this paper was generated as a single lane of Illumina data, but was split up into 6 parts (A-F) for Dryad submission. This is part A. The file will unzip into two files containing the paired-end reads for the first 5.5M sequenced clusters. Phred+64 quality score encoding. Library prep details can be found in the Methods of the linked manuscript.
s_4_partA.tar.gz
Bee microbiome paired-end, part B
The paired-end deep-sequence data from this paper was generated as a single lane of Illumina data, but was split up into 6 parts (A-F) for Dryad submission. This is part B. The file will unzip into two files containing the paired-end reads for the second 5.5M sequenced clusters. Phred+64 quality score encoding. Library prep details can be found in the Methods of the linked manuscript.
s_4_partB.tar.gz
Bee microbiome paired-end, part C
The paired-end deep-sequence data from this paper was generated as a single lane of Illumina data, but was split up into 6 parts (A-F) for Dryad submission. This is part C. The file will unzip into two files containing the paired-end reads for the third 5.5M sequenced clusters. Phred+64 quality score encoding. Library prep details can be found in the Methods of the linked manuscript.
s_4_partC.tar.gz
Bee microbiome paired-end, part D
The paired-end deep-sequence data from this paper was generated as a single lane of Illumina data, but was split up into 6 parts (A-F) for Dryad submission. This is part D. The file will unzip into two files containing the paired-end reads for the fourth 5.5M sequenced clusters. Phred+64 quality score encoding. Library prep details can be found in the Methods of the linked manuscript.
s_4_partD.tar.gz
Bee microbiome paired-end, part E
The paired-end deep-sequence data from this paper was generated as a single lane of Illumina data, but was split up into 6 parts (A-F) for Dryad submission. This is part E. The file will unzip into two files containing the paired-end reads for the fifth 5.5M sequenced clusters. Phred+64 quality score encoding. Library prep details can be found in the Methods of the linked manuscript.
s_4_partE.tar.gz
Bee microbiome paired-end, part F
The paired-end deep-sequence data from this paper was generated as a single lane of Illumina data, but was split up into 6 parts (A-F) for Dryad submission. This is part F. The file will unzip into two files containing the paired-end reads for the last less-than-5.5M sequenced clusters. Phred+64 quality score encoding. Library prep details can be found in the Methods of the linked manuscript.
s_4_partF.tar.gz