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Ferrari RR, Ricardo PC, Dias FC, de Souza Araujo N, Soares DO, Zhou QS, Zhu CD, Coutinho LL, Arias MC, Batista TM. The nuclear and mitochondrial genome assemblies of Tetragonisca angustula (Apidae: Meliponini), a tiny yet remarkable pollinator in the Neotropics. BMC Genomics 2024; 25:587. [PMID: 38862915 PMCID: PMC11167848 DOI: 10.1186/s12864-024-10502-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 06/05/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND The field of bee genomics has considerably advanced in recent years, however, the most diverse group of honey producers on the planet, the stingless bees, are still largely neglected. In fact, only eleven of the ~ 600 described stingless bee species have been sequenced, and only three using a long-read (LR) sequencing technology. Here, we sequenced the nuclear and mitochondrial genomes of the most common, widespread and broadly reared stingless bee in Brazil and other neotropical countries-Tetragonisca angustula (popularly known in Brazil as jataí). RESULTS A total of 48.01 Gb of DNA data were generated, including 2.31 Gb of Pacific Bioscience HiFi reads and 45.70 Gb of Illumina short reads (SRs). Our preferred assembly comprised 683 contigs encompassing 284.49 Mb, 62.84 Mb of which (22.09%) corresponded to 445,793 repetitive elements. N50, L50 and complete BUSCOs reached 1.02 Mb, 91 contigs and 97.1%, respectively. We predicted that the genome of T. angustula comprises 17,459 protein-coding genes and 4,108 non-coding RNAs. The mitogenome consisted of 17,410 bp, and all 37 genes were found to be on the positive strand, an unusual feature among bees. A phylogenomic analysis of 26 hymenopteran species revealed that six odorant receptor orthogroups of T. angustula were found to be experiencing rapid evolution, four of them undergoing significant contractions. CONCLUSIONS Here, we provided the first nuclear and mitochondrial genome assemblies for the ecologically and economically important T. angustula, the fourth stingless bee species to be sequenced with LR technology thus far. We demonstrated that even relatively small amounts of LR data in combination with sufficient SR data can yield high-quality genome assemblies for bees.
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Affiliation(s)
- Rafael Rodrigues Ferrari
- Centro de Formação em Ciências Ambientais, Universidade Federal do Sul da Bahia, Porto Seguro, Brazil
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Paulo Cseri Ricardo
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Felipe Cordeiro Dias
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | | | - Dalliane Oliveira Soares
- Centro de Formação em Ciências Ambientais, Universidade Federal do Sul da Bahia, Porto Seguro, Brazil
| | - Qing-Song Zhou
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Chao-Dong Zhu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- Sate Key Laboratory of Integrated Pest Management, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Luiz Lehmann Coutinho
- Departamento de Ciências Animais, Universidade de São Paulo/ESALQ, Piracicaba, Brazil
| | - Maria Cristina Arias
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil.
| | - Thiago Mafra Batista
- Centro de Formação em Ciências Ambientais, Universidade Federal do Sul da Bahia, Porto Seguro, Brazil.
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Yusuf AA, Pirk CWW, Buttstedt A. Expression of honey bee (Apis mellifera) sterol homeostasis genes in food jelly producing glands of workers. JOURNAL OF EXPERIMENTAL ZOOLOGY. PART A, ECOLOGICAL AND INTEGRATIVE PHYSIOLOGY 2024; 341:627-641. [PMID: 38567629 DOI: 10.1002/jez.2813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 03/15/2024] [Accepted: 03/19/2024] [Indexed: 04/04/2024]
Abstract
Adult workers of Western honey bees (Apis mellifera L.) acquire sterols from their pollen diet. These food sterols are transported by the hemolymph to peripheral tissues such as the mandibular and the hypopharyngeal glands in the worker bees' heads that secrete food jelly which is fed to developing larvae. As sterols are obligatory components of biological membranes and essential precursors for molting hormone synthesis in insects, they are indispensable to normal larval development. Thus, the study of sterol delivery to larvae is important for a full understanding of honey bee larval nutrition and development. Whereas hypopharyngeal glands only require sterols for their membrane integrity, mandibular glands add sterols, primarily 24-methylenecholesterol, to its secretion. For this, sterols must be transported through the glandular epithelial cells. We have analyzed for the first time in A. mellifera the expression of genes which are involved in intracellular movement of sterols. Mandibular and hypopharyngeal glands were dissected from newly emerged bees, 6-day-old nurse bees that feed larvae and 26-day-old forager bees. The expression of seven genes involved in intracellular sterol metabolism was measured with quantitative real-time PCR. Relative transcript abundance of sterol metabolism genes was significantly influenced by the age of workers and specific genes but not by gland type. Newly emerged bees had significantly more transcripts for six out of seven genes than older bees indicating that the bulk of the proteins needed for sterol metabolism are produced directly after emergence.
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Affiliation(s)
- Abdullahi A Yusuf
- Social Insects Research Group, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa
| | - Christian W W Pirk
- Social Insects Research Group, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa
| | - Anja Buttstedt
- Social Insects Research Group, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa
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3
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Wakamiya T, Kamioka T, Ishii Y, Takahashi J, Maeda T, Kawata M. Genetic differentiation and local adaptation of the Japanese honeybee, Apis cerana japonica. Ecol Evol 2023; 13:e10573. [PMID: 37780082 PMCID: PMC10541296 DOI: 10.1002/ece3.10573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 09/13/2023] [Accepted: 09/18/2023] [Indexed: 10/03/2023] Open
Abstract
We examine the population genetic structure and divergence among the regional populations of the Japanese honeybee, Apis cerana japonica, by re-sequencing the genomes of 105 individuals from the three main Japanese islands with diverse climates. The genetic structure results indicated that these individuals are distinct from the mainland Chinese A. cerana samples. Furthermore, population structure analyses have identified three genetically distinct geographic regions in Japan: Northern (Tohoku-Kanto-Chubu districts), Central (Chugoku district), and Southern (Kyushu district). In some districts, "possible non-native" individuals, likely introduced from other regions in recent years, were discovered. Then, genome-wide scans were conducted to detect candidate genes for adaptation by two different approaches. We performed a population branch statistics (PBS) analysis to identify candidate genes for population-specific divergence. A latent factor mixed model (LFMM) was used to identify genes associated with climatic variables along a geographic gradient. The PBSmax analysis identified 25 candidate genes for population-specific divergence whereas the LFMM analysis identified 73 candidate genes for adaptation to climatic variables along a geographic gradient. However, no common genes were identified by both methods.
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Affiliation(s)
- Takeshi Wakamiya
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
- Department of Biological SciencesTokyo Metropolitan UniversityHachiojiJapan
| | | | - Yuu Ishii
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | | | - Taro Maeda
- Institute for Agro‐Environmental Sciences (NIAES)NAROTsukubaJapan
| | - Masakado Kawata
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
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Vertacnik KL, Herrig DK, Godfrey RK, Hill T, Geib SM, Unckless RL, Nelson DR, Linnen CR. Evolution of five environmentally responsive gene families in a pine-feeding sawfly, Neodiprion lecontei (Hymenoptera: Diprionidae). Ecol Evol 2023; 13:e10506. [PMID: 37791292 PMCID: PMC10542623 DOI: 10.1002/ece3.10506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 10/05/2023] Open
Abstract
A central goal in evolutionary biology is to determine the predictability of adaptive genetic changes. Despite many documented cases of convergent evolution at individual loci, little is known about the repeatability of gene family expansions and contractions. To address this void, we examined gene family evolution in the redheaded pine sawfly Neodiprion lecontei, a noneusocial hymenopteran and exemplar of a pine-specialized lineage evolved from angiosperm-feeding ancestors. After assembling and annotating a draft genome, we manually annotated multiple gene families with chemosensory, detoxification, or immunity functions before characterizing their genomic distributions and molecular evolution. We find evidence of recent expansions of bitter gustatory receptor, clan 3 cytochrome P450, olfactory receptor, and antimicrobial peptide subfamilies, with strong evidence of positive selection among paralogs in a clade of gustatory receptors possibly involved in the detection of bitter compounds. In contrast, these gene families had little evidence of recent contraction via pseudogenization. Overall, our results are consistent with the hypothesis that in response to novel selection pressures, gene families that mediate ecological interactions may expand and contract predictably. Testing this hypothesis will require the comparative analysis of high-quality annotation data from phylogenetically and ecologically diverse insect species and functionally diverse gene families. To this end, increasing sampling in under-sampled hymenopteran lineages and environmentally responsive gene families and standardizing manual annotation methods should be prioritized.
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Affiliation(s)
- Kim L. Vertacnik
- Department of EntomologyUniversity of KentuckyLexingtonKentuckyUSA
| | | | - R. Keating Godfrey
- McGuire Center for Lepidoptera and Biodiversity, University of FloridaGainesvilleFloridaUSA
| | - Tom Hill
- National Institute of Allergy and Infectious DiseasesBethesdaMarylandUSA
| | - Scott M. Geib
- Tropical Crop and Commodity Protection Research UnitUnited States Department of Agriculture: Agriculture Research Service Pacific Basin Agricultural Research CenterHiloHawaiiUSA
| | - Robert L. Unckless
- Department of Molecular BiosciencesUniversity of KansasLawrenceKansasUSA
| | - David R. Nelson
- Department of Microbiology, Immunology and BiochemistryUniversity of Tennessee Health Science CenterMemphisTennesseeUSA
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Cao L, Dai Z, Tan H, Zheng H, Wang Y, Chen J, Kuang H, Chong RA, Han M, Hu F, Sun W, Sun C, Zhang Z. Population Structure, Demographic History, and Adaptation of Giant Honeybees in China Revealed by Population Genomic Data. Genome Biol Evol 2023; 15:7044694. [PMID: 36799935 PMCID: PMC9991589 DOI: 10.1093/gbe/evad025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 02/05/2023] [Accepted: 02/11/2023] [Indexed: 02/18/2023] Open
Abstract
There have been many population-based genomic studies on human-managed honeybees (Apis mellifera and Apis cerana), but there has been a notable lack of analysis with regard to wild honeybees, particularly in relation to their evolutionary history. Nevertheless, giant honeybees have been found to occupy distinct habitats and display remarkable characteristics, which are attracting an increased amount of attention. In this study, we de novo sequenced and then assembled the draft genome sequence of the Himalayan giant honeybee, Apis laboriosa. Phylogenetic analysis based on genomic information indicated that A. laboriosa and its tropical sister species Apis dorsata diverged ∼2.61 Ma, which supports the speciation hypothesis that links A. laboriosa to geological changes throughout history. Furthermore, we re-sequenced A. laboriosa and A. dorsata samples from five and six regions, respectively, across their population ranges in China. These analyses highlighted major genetic differences for Tibetan A. laboriosa as well as the Hainan Island A. dorsata. The demographic history of most giant honeybee populations has mirrored glacial cycles. More importantly, contrary to what has occurred among human-managed honeybees, the demographic history of these two wild honeybee species indicates a rapid decline in effective population size in the recent past, reflecting their differences in evolutionary histories. Several genes were found to be subject to selection, which may help giant honeybees to adapt to specific local conditions. In summary, our study sheds light on the evolutionary and adaptational characteristics of two wild giant honeybee species, which was useful for giant honeybee conservation.
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Affiliation(s)
- Lianfei Cao
- Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Zhijun Dai
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Hongwei Tan
- School of Life Sciences, Chongqing University, Chongqing, China.,Chongqing General Station of Animal Husbandry Technology Extension, Chongqing, China
| | - Huoqing Zheng
- College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Yun Wang
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Jie Chen
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Haiou Kuang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, China
| | - Rebecca A Chong
- School of Life Sciences, University of Hawai'i at Mānoa, Honolulu, Hawai'i, USA
| | - Minjin Han
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing, China
| | - Fuliang Hu
- College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Wei Sun
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Cheng Sun
- College of Life Sciences, Capital Normal University, Beijing, China
| | - Ze Zhang
- School of Life Sciences, Chongqing University, Chongqing, China
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6
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Zhao X, Liu Y. Current Knowledge on Bee Innate Immunity Based on Genomics and Transcriptomics. Int J Mol Sci 2022; 23:ijms232214278. [PMID: 36430757 PMCID: PMC9692672 DOI: 10.3390/ijms232214278] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/28/2022] [Accepted: 11/14/2022] [Indexed: 11/19/2022] Open
Abstract
As important pollinators, bees play a critical role in maintaining the balance of the ecosystem and improving the yield and quality of crops. However, in recent years, the bee population has significantly declined due to various pathogens and environmental stressors including viruses, bacteria, parasites, and increased pesticide application. The above threats trigger or suppress the innate immunity of bees, their only immune defense system, which is essential to maintaining individual health and that of the colony. In addition, bees can be divided into solitary and eusocial bees based on their life traits, and eusocial bees possess special social immunities, such as grooming behavior, which cooperate with innate immunity to maintain the health of the colony. The omics approach gives us an opportunity to recognize the distinctive innate immunity of bees. In this regard, we summarize innate bee immunity from a genomic and transcriptomic perspective. The genetic characteristics of innate immunity were revealed by the multiple genomes of bees with different kinds of sociality, including honeybees, bumblebees, wasps, leaf-cutter bees, and so on. Further substantial transcriptomic data of different tissues from diverse bees directly present the activation or suppression of immune genes under the infestation of pathogens or toxicity of pesticides.
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Affiliation(s)
- Xiaomeng Zhao
- College of Engineering, Hebei Normal University, Shijiazhuang 050024, China
| | - Yanjie Liu
- Key Laboratory for Insect-Pollinator Biology of the Ministry of Agriculture and Rural Affairs, Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China
- Correspondence:
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7
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Cui M, Cheng C, Zhang L. High-throughput proteomics: a methodological mini-review. J Transl Med 2022; 102:1170-1181. [PMID: 36775443 PMCID: PMC9362039 DOI: 10.1038/s41374-022-00830-7] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 07/06/2022] [Accepted: 07/10/2022] [Indexed: 11/15/2022] Open
Abstract
Proteomics plays a vital role in biomedical research in the post-genomic era. With the technological revolution and emerging computational and statistic models, proteomic methodology has evolved rapidly in the past decade and shed light on solving complicated biomedical problems. Here, we summarize scientific research and clinical practice of existing and emerging high-throughput proteomics approaches, including mass spectrometry, protein pathway array, next-generation tissue microarrays, single-cell proteomics, single-molecule proteomics, Luminex, Simoa and Olink Proteomics. We also discuss important computational methods and statistical algorithms that can maximize the mining of proteomic data with clinical and/or other 'omics data. Various principles and precautions are provided for better utilization of these tools. In summary, the advances in high-throughput proteomics will not only help better understand the molecular mechanisms of pathogenesis, but also to identify the signature signaling networks of specific diseases. Thus, modern proteomics have a range of potential applications in basic research, prognostic oncology, precision medicine, and drug discovery.
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Affiliation(s)
- Miao Cui
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Pathology, Mount Sinai West, New York, NY, USA
| | - Chao Cheng
- Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine, Houston, TX, USA. .,Department of Medicine, Baylor College of Medicine, Houston, TX, USA. .,Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
| | - Lanjing Zhang
- Department of Biological Sciences, Rutgers University, Newark, NJ, USA. .,Department of Pathology, Princeton Medical Center, Plainsboro, NJ, USA. .,Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA. .,Department of Chemical Biology, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ, USA.
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8
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Yokoi K, Kimura K, Bono H. Revealing Landscapes of Transposable Elements in Apis Species by Meta-Analysis. INSECTS 2022; 13:insects13080698. [PMID: 36005323 PMCID: PMC9408917 DOI: 10.3390/insects13080698] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/29/2022] [Accepted: 08/01/2022] [Indexed: 12/04/2022]
Abstract
Transposable elements (TEs) are grouped into several families with diverse sequences. Owing to their diversity, studies involving the detection, classification, and annotation of TEs are difficult tasks. Moreover, simple comparisons of TEs among different species with different methods can lead to misinterpretations. The genome data of several honey bee (Apis) species are available in public databases. Therefore, we conducted a meta-analysis of TEs, using 11 sets of genome data for Apis species, in order to establish data of “landscape of TEs”. Consensus TE sequences were constructed and their distributions in the Apis genomes were determined. Our results showed that TEs belonged to four to seven TE families among 13 and 15 families of TEs detected in classes I and II respectively mainly consisted of Apis TEs and that more DNA/TcMar-Mariner consensus sequences and copies were present in all Apis genomes tested. In addition, more consensus sequences and copy numbers of DNA/TcMar-Mariner were detected in Apis mellifera than in other Apis species. These results suggest that TcMar-Mariner might exert A. mellifera-specific effects on the host A. mellifera species. In conclusion, our unified approach enabled comparison of Apis genome sequences to determine the TE landscape, which provide novel evolutionary insights into Apis species.
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Affiliation(s)
- Kakeru Yokoi
- Insect Design Technology Group, Division of Insect Advanced Technology, Institute of Agrobiological Sciences, National Agriculture and Food Research Organization (NARO), 1-2 Owashi, Tsukuba, Ibaraki 305-8634, Japan
- Correspondence: ; Tel.: +81-29-838-6129
| | - Kiyoshi Kimura
- Smart Livestock Facilities Group, Division of Advanced Feeding Technology Research, National Institute of Livestock and Grassland Science (NILGS), National Agriculture and Food Research Organization (NARO), Tsukuba, 2 Ikenodai, Tsukuba, Ibaraki 305-0901, Japan;
| | - Hidemasa Bono
- Laboratory of BioDX, Genome Editing Innovation Center, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima City, Hiroshima 739-0046, Japan;
- Laboratory of Genome Informatics, Graduate School of Integrated Sciences for Life, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima City, Hiroshima 739-0046, Japan
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9
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Nakajima Y, Ogura A. Genomics and effective trait candidates of edible insects. FOOD BIOSCI 2022. [DOI: 10.1016/j.fbio.2022.101793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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10
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Lin D, Lan L, Zheng T, Shi P, Xu J, Li J. Comparative Genomics Reveals Recent Adaptive Evolution in Himalayan Giant Honeybee Apis laboriosa. Genome Biol Evol 2021; 13:6380142. [PMID: 34599331 PMCID: PMC8536543 DOI: 10.1093/gbe/evab227] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2021] [Indexed: 01/07/2023] Open
Abstract
The Himalayan giant honeybee, Apis laboriosa, is the largest individual honeybee with major ecological and economic importance in high-latitude environments. However, our understanding of its environmental adaptations is circumscribed by the paucity of genomic data for this species. Here, we provide a draft genome of wild A. laboriosa, along with a comparison to its closely related species, Apis dorsata. The draft genome of A. laboriosa based on the de novo assembly is 226.1 Mbp in length with a scaffold N50 size of 3.34 Mbp, a GC content of 32.2%, a repeat content of 6.86%, and a gene family number of 8,404. Comparative genomics analysis revealed that the genes in A. laboriosa genome have undergone stronger positive selection (2.5 times more genes) and more recent duplication/loss events (6.1 times more events) than those in the A. dorsata genome. Our study implies the potential molecular mechanisms underlying the high-altitude adaptation of A. laboriosa and will catalyze future comparative studies to understand the environmental adaptation of modern honeybees.
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Affiliation(s)
- Dan Lin
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Lan Lan
- College of Life Sciences, Chongqing Normal University, Chongqing, China
| | - Tingting Zheng
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Peng Shi
- College of Life Sciences, Chongqing Normal University, Chongqing, China
| | - Jinshan Xu
- College of Life Sciences, Chongqing Normal University, Chongqing, China
| | - Jun Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.,School of Data Science, City University of Hong Kong, Hong Kong, China
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11
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Liu Y, Zong W, Diaby M, Lin Z, Wang S, Gao B, Ji T, Song C. Diversity and Evolution of pogo and Tc1/mariner Transposons in the Apoidea Genomes. BIOLOGY 2021; 10:940. [PMID: 34571816 PMCID: PMC8472432 DOI: 10.3390/biology10090940] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/14/2021] [Accepted: 09/16/2021] [Indexed: 11/16/2022]
Abstract
Bees (Apoidea), the largest and most crucial radiation of pollinators, play a vital role in the ecosystem balance. Transposons are widely distributed in nature and are important drivers of species diversity. However, transposons are rarely reported in important pollinators such as bees. Here, we surveyed 37 bee genomesin Apoidea, annotated the pogo and Tc1/mariner transposons in the genome of each species, and performed a phylogenetic analysis and determined their overall distribution. The pogo and Tc1/mariner families showed high diversity and low abundance in the 37 species, and their proportion was significantly higher in solitary bees than in social bees. DD34D/mariner was found to be distributed in almost all species and was found in Apis mellifera, Apis mellifera carnica, Apis mellifera caucasia, and Apis mellifera mellifera, and Euglossa dilemma may still be active. Using horizontal transfer analysis, we found that DD29-30D/Tigger may have experienced horizontal transfer (HT) events. The current study displayed the evolution profiles (including diversity, activity, and abundance) of the pogo and Tc1/mariner transposons across 37 species of Apoidea. Our data revealed their contributions to the genomic variations across these species and facilitated in understanding of the genome evolution of this lineage.
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Affiliation(s)
| | | | | | | | | | | | | | - Chengyi Song
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (Y.L.); (W.Z.); (M.D.); (Z.L.); (S.W.); (B.G.); (T.J.)
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Sirur FM, Wilson W, Gopinathan V, Chethana AS, Lekha N. Hymenoptera heartaches -cardiac manifestation with hymenoptera stings, a retrospective study from a tertiary care hospital in South India. Am J Emerg Med 2021; 50:294-300. [PMID: 34425322 DOI: 10.1016/j.ajem.2021.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 07/29/2021] [Accepted: 08/02/2021] [Indexed: 10/20/2022] Open
Abstract
INTRODUCTION Hymenoptera stings usually have a multitude of presentations from very subtle to life-threatening conditions. Various cardiac manifestations including Kounis syndrome often get missed due to lack of suspicion. The aim of the study was to describe the clinical profile of the cardiac etiologies associated with hymenoptera stings and review literature with focus on diagnosis and treatment strategies. METHODOLOGY A retrospective chart analysis was performed including all adult patients who had a hymenoptera sting during a two-year window (October 2018 - October 2020). Of these, patients with cardiac features were enrolled. A structured case record form was used to capture information like basic demography, clinical profile, and outcomes. RESULTS Thirteen cases presented with hymenoptera stings of which six cases had cardiac presentation and were considered. The most common presentations were breathlessness and generalised itching with only one patient complaining of chest pain. All patients(with available data) had ECG changes suggestive of ischemia and associated raised troponin levels with 2D echo changes. The diagnoses considered included Kounis syndrome, hypersensitivity myocarditis, and Takotsubo cardiomyopathy. Patients were managed conservatively with one patient undergoing a coronary angiography. All patients were stable at discharge. CONCLUSION Cardiac manifestations with hymenoptera stings although rare may complicate diagnosis and treatment.It should be borne in mind during assessment and standardised guidelines should be developed for ED treatment such as the one recommended in this study.
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Affiliation(s)
- Freston Marc Sirur
- Department of Emergency Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - William Wilson
- Department of Emergency Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India.
| | - Vivek Gopinathan
- Department of Emergency Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - A S Chethana
- Department of Emergency Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Nymisha Lekha
- Department of Emergency Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India
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A Rapid and Cost-Effective Identification of Invertebrate Pests at the Borders Using MinION Sequencing of DNA Barcodes. Genes (Basel) 2021; 12:genes12081138. [PMID: 34440312 PMCID: PMC8392835 DOI: 10.3390/genes12081138] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 07/23/2021] [Accepted: 07/24/2021] [Indexed: 12/12/2022] Open
Abstract
The rapid and accurate identification of invertebrate pests detected at the border is a challenging task. Current diagnostic methods used at the borders are mainly based on time consuming visual and microscopic examinations. Here, we demonstrate a rapid in-house workflow for DNA extraction, PCR amplification of the barcode region of the mitochondrial cytochrome oxidase subunit I (COI) gene and Oxford Nanopore Technologies (ONT) MinION sequencing of amplified products multiplexed after barcoding on ONT Flongle flow cells. A side-by-side comparison was conducted of DNA barcode sequencing-based identification and morphological identification of both large (>0.5 mm in length) and small (<0.5 mm in length) invertebrate specimens intercepted at the Australian border. DNA barcode sequencing results supported the morphological identification in most cases and enabled immature stages of invertebrates and their eggs to be identified more confidently. Results also showed that sequencing the COI barcode region using the ONT rapid sequencing principle is a cost-effective and field-adaptable approach for the rapid and accurate identification of invertebrate pests. Overall, the results suggest that MinION sequencing of DNA barcodes offers a complementary tool to the existing morphological diagnostic approaches and provides rapid, accurate, reliable and defendable evidence for identifying invertebrate pests at the border.
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14
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Fouks B, Brand P, Nguyen HN, Herman J, Camara F, Ence D, Hagen DE, Hoff KJ, Nachweide S, Romoth L, Walden KKO, Guigo R, Stanke M, Narzisi G, Yandell M, Robertson HM, Koeniger N, Chantawannakul P, Schatz MC, Worley KC, Robinson GE, Elsik CG, Rueppell O. The genomic basis of evolutionary differentiation among honey bees. Genome Res 2021; 31:1203-1215. [PMID: 33947700 PMCID: PMC8256857 DOI: 10.1101/gr.272310.120] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 04/22/2021] [Indexed: 02/06/2023]
Abstract
In contrast to the western honey bee, Apis mellifera, other honey bee species have been largely neglected despite their importance and diversity. The genetic basis of the evolutionary diversification of honey bees remains largely unknown. Here, we provide a genome-wide comparison of three honey bee species, each representing one of the three subgenera of honey bees, namely the dwarf (Apis florea), giant (A. dorsata), and cavity-nesting (A. mellifera) honey bees with bumblebees as an outgroup. Our analyses resolve the phylogeny of honey bees with the dwarf honey bees diverging first. We find that evolution of increased eusocial complexity in Apis proceeds via increases in the complexity of gene regulation, which is in agreement with previous studies. However, this process seems to be related to pathways other than transcriptional control. Positive selection patterns across Apis reveal a trade-off between maintaining genome stability and generating genetic diversity, with a rapidly evolving piRNA pathway leading to genomes depleted of transposable elements, and a rapidly evolving DNA repair pathway associated with high recombination rates in all Apis species. Diversification within Apis is accompanied by positive selection in several genes whose putative functions present candidate mechanisms for lineage-specific adaptations, such as migration, immunity, and nesting behavior.
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Affiliation(s)
- Bertrand Fouks
- Department of Biology, University of North Carolina at Greensboro, Greensboro, North Carolina 27403, USA
- Institute for Evolution and Biodiversity, Molecular Evolution and Bioinformatics, Westfälische Wilhelms-Universität, 48149 Münster, Germany
| | - Philipp Brand
- Department of Evolution and Ecology, Center for Population Biology, University of California, Davis, Davis, California 95161, USA
- Laboratory of Neurophysiology and Behavior, The Rockefeller University, New York, New York 10065, USA
| | - Hung N Nguyen
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
| | - Jacob Herman
- Department of Biology, University of North Carolina at Greensboro, Greensboro, North Carolina 27403, USA
| | - Francisco Camara
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08036 Barcelona, Spain
| | - Daniel Ence
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
- Department of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA
| | - Darren E Hagen
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, Oklahoma 74078, USA
| | - Katharina J Hoff
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
- University of Greifswald, Center for Functional Genomics of Microbes, 17489 Greifswald, Germany
| | - Stefanie Nachweide
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
| | - Lars Romoth
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
| | - Kimberly K O Walden
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Roderic Guigo
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08036 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
| | - Mario Stanke
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
- University of Greifswald, Center for Functional Genomics of Microbes, 17489 Greifswald, Germany
| | | | - Mark Yandell
- Department of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA
- Utah Center for Genetic Discovery, University of Utah, Salt Lake City, Utah 84112, USA
| | - Hugh M Robertson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Nikolaus Koeniger
- Department of Behavioral Physiology and Sociobiology (Zoology II), University of Würzburg, 97074 Würzburg, Germany
| | - Panuwan Chantawannakul
- Environmental Science Research Center (ESRC) and Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Michael C Schatz
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Kim C Worley
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Gene E Robinson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Christine G Elsik
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
- Division of Animal Sciences, University of Missouri, Columbia, Missouri 65211, USA
- Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211, USA
| | - Olav Rueppell
- Department of Biology, University of North Carolina at Greensboro, Greensboro, North Carolina 27403, USA
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada
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15
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Sun C, Huang J, Wang Y, Zhao X, Su L, Thomas GWC, Zhao M, Zhang X, Jungreis I, Kellis M, Vicario S, Sharakhov IV, Bondarenko SM, Hasselmann M, Kim CN, Paten B, Penso-Dolfin L, Wang L, Chang Y, Gao Q, Ma L, Ma L, Zhang Z, Zhang H, Zhang H, Ruzzante L, Robertson HM, Zhu Y, Liu Y, Yang H, Ding L, Wang Q, Ma D, Xu W, Liang C, Itgen MW, Mee L, Cao G, Zhang Z, Sadd BM, Hahn MW, Schaack S, Barribeau SM, Williams PH, Waterhouse RM, Mueller RL. Genus-Wide Characterization of Bumblebee Genomes Provides Insights into Their Evolution and Variation in Ecological and Behavioral Traits. Mol Biol Evol 2021; 38:486-501. [PMID: 32946576 PMCID: PMC7826183 DOI: 10.1093/molbev/msaa240] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Bumblebees are a diverse group of globally important pollinators in natural ecosystems and for agricultural food production. With both eusocial and solitary life-cycle phases, and some social parasite species, they are especially interesting models to understand social evolution, behavior, and ecology. Reports of many species in decline point to pathogen transmission, habitat loss, pesticide usage, and global climate change, as interconnected causes. These threats to bumblebee diversity make our reliance on a handful of well-studied species for agricultural pollination particularly precarious. To broadly sample bumblebee genomic and phenotypic diversity, we de novo sequenced and assembled the genomes of 17 species, representing all 15 subgenera, producing the first genus-wide quantification of genetic and genomic variation potentially underlying key ecological and behavioral traits. The species phylogeny resolves subgenera relationships, whereas incomplete lineage sorting likely drives high levels of gene tree discordance. Five chromosome-level assemblies show a stable 18-chromosome karyotype, with major rearrangements creating 25 chromosomes in social parasites. Differential transposable element activity drives changes in genome sizes, with putative domestications of repetitive sequences influencing gene coding and regulatory potential. Dynamically evolving gene families and signatures of positive selection point to genus-wide variation in processes linked to foraging, diet and metabolism, immunity and detoxification, as well as adaptations for life at high altitudes. Our study reveals how bumblebee genes and genomes have evolved across the Bombus phylogeny and identifies variations potentially linked to key ecological and behavioral traits of these important pollinators.
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Affiliation(s)
- Cheng Sun
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jiaxing Huang
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yun Wang
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Xiaomeng Zhao
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Long Su
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Gregg W C Thomas
- Division of Biological Sciences, University of Montana, Missoula, MT
| | - Mengya Zhao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
| | - Xingtan Zhang
- Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Irwin Jungreis
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA.,Broad Institute of MIT and Harvard, Cambridge, MA
| | - Manolis Kellis
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA.,Broad Institute of MIT and Harvard, Cambridge, MA
| | - Saverio Vicario
- Institute of Atmospheric Pollution Research-Italian National Research Council C/O Department of Physics, University of Bari, Bari, Italy
| | - Igor V Sharakhov
- Department of Entomology, Virginia Polytechnic and State University, Blacksburg, VA.,Department of Cytology and Genetics, Tomsk State University, Tomsk, Russian Federation
| | - Semen M Bondarenko
- Department of Entomology, Virginia Polytechnic and State University, Blacksburg, VA
| | - Martin Hasselmann
- Department of Livestock Population Genomics, Institute of Animal Science, University of Hohenheim, Stuttgart, Germany
| | - Chang N Kim
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA
| | | | - Li Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yuxiao Chang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Qiang Gao
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Ling Ma
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Lina Ma
- China National Center for Bioinformation & Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhang Zhang
- China National Center for Bioinformation & Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Hongbo Zhang
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Huahao Zhang
- College of Pharmacy and Life Science, Jiujiang University, Jiujiang, China
| | - Livio Ruzzante
- Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Hugh M Robertson
- Department of Entomology, University of Illinois at Urbana-Champaign, Champaign, IL
| | - Yihui Zhu
- Department of Medical Microbiology and Immunology, Genome Center, and MIND Institute, University of California Davis, Davis, CA
| | - Yanjie Liu
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huipeng Yang
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lele Ding
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Quangui Wang
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dongna Ma
- Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Weilin Xu
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Cheng Liang
- Institute of Sericultural and Apiculture, Yunnan Academy of Agricultural Sciences, Mengzi, China
| | - Michael W Itgen
- Department of Biology, Colorado State University, Fort Collins, CO
| | - Lauren Mee
- Department of Ecology, Evolution and Behaviour, Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Gang Cao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
| | - Ze Zhang
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Ben M Sadd
- School of Biological Sciences, Illinois State University, Normal, IL
| | - Matthew W Hahn
- Department of Biology, Indiana University, Bloomington, IN.,Department of Computer Science, Indiana University, Bloomington, IN
| | | | - Seth M Barribeau
- Department of Ecology, Evolution and Behaviour, Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Paul H Williams
- Department of Life Sciences, Natural History Museum, London, United Kingdom
| | - Robert M Waterhouse
- Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics, Lausanne, Switzerland
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16
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17
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Karpe SD, Tiwari V, Ramanathan S. InsectOR-Webserver for sensitive identification of insect olfactory receptor genes from non-model genomes. PLoS One 2021; 16:e0245324. [PMID: 33465132 PMCID: PMC7815150 DOI: 10.1371/journal.pone.0245324] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Accepted: 12/29/2020] [Indexed: 11/18/2022] Open
Abstract
Insect Olfactory Receptors (ORs) are diverse family of membrane protein receptors responsible for most of the insect olfactory perception and communication, and hence they are of utmost importance for developing repellents or pesticides. Accurate gene prediction of insect ORs from newly sequenced genomes is an important but challenging task. We have developed a dedicated webserver, 'insectOR', to predict and validate insect OR genes using multiple gene prediction algorithms, accompanied by relevant validations. It is possible to employ this server nearly automatically and perform rapid prediction of the OR gene loci from thousands of OR-protein-to-genome alignments, resolve gene boundaries for tandem OR genes and refine them further to provide more complete OR gene models. InsectOR outperformed the popular genome annotation pipelines (MAKER and NCBI eukaryotic genome annotation) in terms of overall sensitivity at base, exon and locus level, when tested on two distantly related insect genomes. It displayed more than 95% nucleotide level precision in both tests. Finally, given the same input data and parameters, InsectOR missed less than 2% gene loci, in contrast to 55% loci missed by MAKER for Drosophila melanogaster. The webserver is freely available on the web at http://caps.ncbs.res.in/insectOR/ and the basic package can be downloaded from https://github.com/sdk15/insectOR for local use. This tool will allow biologists to perform quick preliminary identification of insect olfactory receptor genes from newly sequenced genomes and also assist in their further detailed annotation. Its usage can also be extended to other divergent gene families.
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Affiliation(s)
- Snehal Dilip Karpe
- National Centre for Biological Sciences (NCBS), TIFR, Bengaluru, Karnataka, India
| | - Vikas Tiwari
- National Centre for Biological Sciences (NCBS), TIFR, Bengaluru, Karnataka, India
| | - Sowdhamini Ramanathan
- National Centre for Biological Sciences (NCBS), TIFR, Bengaluru, Karnataka, India
- * E-mail:
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18
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de Paula Freitas FC, Lourenço AP, Nunes FMF, Paschoal AR, Abreu FCP, Barbin FO, Bataglia L, Cardoso-Júnior CAM, Cervoni MS, Silva SR, Dalarmi F, Del Lama MA, Depintor TS, Ferreira KM, Gória PS, Jaskot MC, Lago DC, Luna-Lucena D, Moda LM, Nascimento L, Pedrino M, Oliveira FR, Sanches FC, Santos DE, Santos CG, Vieira J, Barchuk AR, Hartfelder K, Simões ZLP, Bitondi MMG, Pinheiro DG. The nuclear and mitochondrial genomes of Frieseomelitta varia - a highly eusocial stingless bee (Meliponini) with a permanently sterile worker caste. BMC Genomics 2020; 21:386. [PMID: 32493270 PMCID: PMC7268684 DOI: 10.1186/s12864-020-06784-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 05/14/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Most of our understanding on the social behavior and genomics of bees and other social insects is centered on the Western honey bee, Apis mellifera. The genus Apis, however, is a highly derived branch comprising less than a dozen species, four of which genomically characterized. In contrast, for the equally highly eusocial, yet taxonomically and biologically more diverse Meliponini, a full genome sequence was so far available for a single Melipona species only. We present here the genome sequence of Frieseomelitta varia, a stingless bee that has, as a peculiarity, a completely sterile worker caste. RESULTS The assembly of 243,974,526 high quality Illumina reads resulted in a predicted assembled genome size of 275 Mb composed of 2173 scaffolds. A BUSCO analysis for the 10,526 predicted genes showed that these represent 96.6% of the expected hymenopteran orthologs. We also predicted 169,371 repetitive genomic components, 2083 putative transposable elements, and 1946 genes for non-coding RNAs, largely long non-coding RNAs. The mitochondrial genome comprises 15,144 bp, encoding 13 proteins, 22 tRNAs and 2 rRNAs. We observed considerable rearrangement in the mitochondrial gene order compared to other bees. For an in-depth analysis of genes related to social biology, we manually checked the annotations for 533 automatically predicted gene models, including 127 genes related to reproductive processes, 104 to development, and 174 immunity-related genes. We also performed specific searches for genes containing transcription factor domains and genes related to neurogenesis and chemosensory communication. CONCLUSIONS The total genome size for F. varia is similar to the sequenced genomes of other bees. Using specific prediction methods, we identified a large number of repetitive genome components and long non-coding RNAs, which could provide the molecular basis for gene regulatory plasticity, including worker reproduction. The remarkable reshuffling in gene order in the mitochondrial genome suggests that stingless bees may be a hotspot for mtDNA evolution. Hence, while being just the second stingless bee genome sequenced, we expect that subsequent targeting of a selected set of species from this diverse clade of highly eusocial bees will reveal relevant evolutionary signals and trends related to eusociality in these important pollinators.
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Affiliation(s)
- Flávia C. de Paula Freitas
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
- Departamento de Biologia Celular e do Desenvolvimento, Instituto de Ciências Biomédicas, Universidade Federal de Alfenas, Alfenas, MG Brazil
| | - Anete P. Lourenço
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
- Departamento de Ciências Biológicas, Faculdade de Ciências Biológicas e da Saúde, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG Brazil
| | - Francis M. F. Nunes
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | | | - Fabiano C. P. Abreu
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Fábio O. Barbin
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Luana Bataglia
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Carlos A. M. Cardoso-Júnior
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, SP 14049-900 Brazil
| | - Mário S. Cervoni
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, SP 14049-900 Brazil
| | - Saura R. Silva
- Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista “Júlio de Mesquita Filho”, Jaboticabal, SP Brazil
| | - Fernanda Dalarmi
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Marco A. Del Lama
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | - Thiago S. Depintor
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Kátia M. Ferreira
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | - Paula S. Gória
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | - Michael C. Jaskot
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | - Denyse C. Lago
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Danielle Luna-Lucena
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Livia M. Moda
- Departamento de Biologia Celular e do Desenvolvimento, Instituto de Ciências Biomédicas, Universidade Federal de Alfenas, Alfenas, MG Brazil
| | - Leonardo Nascimento
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Matheus Pedrino
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | - Franciene Rabiço Oliveira
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Fernanda C. Sanches
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP Brazil
| | - Douglas E. Santos
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, SP 14049-900 Brazil
| | - Carolina G. Santos
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, SP 14049-900 Brazil
| | - Joseana Vieira
- Departamento de Biologia Celular e do Desenvolvimento, Instituto de Ciências Biomédicas, Universidade Federal de Alfenas, Alfenas, MG Brazil
| | - Angel R. Barchuk
- Departamento de Biologia Celular e do Desenvolvimento, Instituto de Ciências Biomédicas, Universidade Federal de Alfenas, Alfenas, MG Brazil
| | - Klaus Hartfelder
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Av. Bandeirantes 3900, Ribeirão Preto, SP 14049-900 Brazil
| | - Zilá L. P. Simões
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Márcia M. G. Bitondi
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP Brazil
| | - Daniel G. Pinheiro
- Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista “Júlio de Mesquita Filho”, Jaboticabal, SP Brazil
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