Genomics, transcriptomics and proteomics: enabling insights into social evolution and disease challenges for managed and wild bees

Trapp, Judith; McAfee, Alison; Foster, Leonard J.

doi:10.1111/mec.13986

Cited by 29 publications

(21 citation statements)

References 166 publications

(244 reference statements)

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“…These complexities trickled downstream to challenge those working on gene annotation. Trapp, McAfee, and Foster () reveal that these species represent a case where descriptive ‘omics studies, rather than theory‐driven work, continue to provide unexpected insights, which are expected to fuel hypothesis‐driven studies that address of bees’ ability to adapt to and withstand climate change, pesticide and increasing disease challenges. Kafer, Marais, and Pannell () shine a spotlight on a little considered hypothesis concerning the rarity of dioecy in plants. While much attention has been paid to the astonishing number of times dioecy has evolved independently in different plant lineages, little examination has been made concerning the fact that it nonetheless remains rare.…”

Section: Highlights Of 2017mentioning

confidence: 99%

Editorial 2018

Rieseberg¹,

Geraldes²,

Chambers³

et al. 2018

Molecular Ecology

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Molecular Ecology continues to perform well. It was the second largest evolutionary biology journal (392 articles) in 2016 according to ISI Web of Knowledge, and had the sixth highest citation impact factor (6.1). In terms of overall impact, Molecular Ecology ranks second among ecology or evolution journals according to Google Scholar's h5-index, which rates journals by cumulative hindex over the past five years. Our push to streamline the review process over the past year has begun to pay off, and the time to decision on original manuscript submissions averaged 30 days in 2017.We continue in our efforts to enhance the experience of our authors. Wiley has introduced a new page design for Molecular Ecology, which has been optimized for the online environment. Our website has been updated and reformatted to increase usability, and our Author Guidelines have been updated in a format intended to be less "text dense" for our authors. In addition, the scope statement for the journal now appears in both English and Chinese, as we strive to be more welcoming to our Chinese authors.In October 2017, we were most pleased to welcome a dedicated Editorial Assistant, David Crespo, to the Molecular Ecology staff. Many of you may have heard from him already as he manages the molecol email box and patrols our Scholar One Manuscript Central site. Thus, we expect that the editorial office will be able to respond more quickly to author questions and concerns in 2018. | AN NOUNCEMEN TS | Molecular ecology prizeThe 2017 Molecular Ecology Prize has been awarded to Professor Nancy Moran for her pioneering studies of symbiosis and bacterial genome evolution. The Prize is awarded annually to "an outstanding scientist who has made significant contributions to molecular ecology," as selected by an independent award committee. A biography of Nancy and her contributions to the field of molecular ecology can be found on pages XX-XX of this issue. | The Harry Smith prizeAt the Molecular Ecology editorial meeting this summer, we decided to offer a new prize to that would recognize the best paper published in Molecular Ecology by graduate students or early career scholars with no more than five years of postdoctoral or fellowship experience. As with the Molecular Ecology Prize, the winner of this annual prize will be selected by an independent award committee. A call for nominations will be made in spring, 2018.The prize is named after Professor Harry Smith FRS, who founded the journal and served as both its Chief and Managing Editor during the journal's critical early years. He continued as the journal's Managing Editor until 2008, and he went out of his way to encourage early career scholars. In addition to his editorial work, Harry was one of the world's foremost researchers in photomorphogenesis, where he determined how plants respond to shading, leading to concepts such as "neighbour detection" and "shade avoidance," which are fundamental to understanding plant responses to crowding and competition. More broadly, his research provided an ear...

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Section: Highlights Of 2017mentioning

confidence: 99%

Editorial 2018

Rieseberg¹,

Geraldes²,

Chambers³

et al. 2018

Molecular Ecology

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“…Although the year 2006 was not the most significant split in the cluster analysis, the network graphs ( Figure 3 and Figure 4 ) indicated connections between CCD and the genome release. For example, our post-2006 keyword network showed the co-occurrence of words related to genomic tools (RT-PCR and genome) and health (virus and immunity), which suggested that genomic tools were increasingly used to study honey bee health-related topics [ 14 , 53 , 54 ]. For example, genomic tools such as gene expression analysis facilitated understanding disease susceptibility, social immunity mechanisms, and response to environmental stressors [ 55 , 56 ].…”

Section: Discussionmentioning

confidence: 99%

Using Manual and Computer-Based Text-Mining to Uncover Research Trends for Apis mellifera

Amiri

Waiker

Rueppell

et al. 2020

Veterinary Sciences

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Honey bee research is believed to be influenced dramatically by colony collapse disorder (CCD) and the sequenced genome release in 2006, but this assertion has never been tested. By employing text-mining approaches, research trends were tested by analyzing over 14,000 publications during the period of 1957 to 2017. Quantitatively, the data revealed an exponential growth until 2010 when the number of articles published per year ceased following the trend. Analysis of author-assigned keywords revealed that changes in keywords occurred roughly every decade with the most fundamental change in 1991–1992, instead of 2006. This change might be due to several factors including the research intensification on the Varroa mite. The genome release and CCD had quantitively only minor effects, mainly on honey bee health-related topics post-2006. Further analysis revealed that computational topic modeling can provide potentially hidden information and connections between some topics that might be ignored in author-assigned keywords.

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“…Untargeted discovery proteomics is termed Data Independent Acquisition (DIA) and allows the most comprehensive combination with other omics sets (Hu et al, 2016). This process facilitates the tracking of genes to proteins in a manner that produces functional data (Tocchetti et al, 2015;Trapp et al, 2016;Kedaigle and Fraenkel, 2018).…”

Section: Assessing the Utility Of Proteomics Within Multi-omics Datamentioning

confidence: 99%

The Progress of Multi-Omics Technologies: Determining Function in Lactic Acid Bacteria Using a Systems Level Approach

2020

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Lactic Acid Bacteria (LAB) have long been recognized as having a significant impact ranging from commercial to health domains. A vast amount of research has been carried out on these microbes, deciphering many of the pathways and components responsible for these desirable effects. However, a large proportion of this functional information has been derived from a reductionist approach working with pure culture strains. This provides limited insight into understanding the impact of LAB within intricate systems such as the gut microbiome or multi strain starter cultures. Whole genome sequencing of strains and shotgun metagenomics of entire systems are powerful techniques that are currently widely used to decipher function in microbes, but they also have their limitations. An available genome or metagenome can provide an image of what a strain or microbiome, respectively, is potentially capable of and the functions that they may carry out. A top-down, multi-omics approach has the power to resolve the functional potential of an ecosystem into an image of what is being expressed, translated and produced. With this image, it is possible to see the real functions that members of a system are performing and allow more accurate and impactful predictions of the effects of these microorganisms. This review will discuss how technological advances have the potential to increase the yield of information from genomics, transcriptomics, proteomics and metabolomics. The potential for integrated omics to resolve the role of LAB in complex systems will also be assessed. Finally, the current software approaches for managing these omics data sets will be discussed.

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Genomics, transcriptomics and proteomics: enabling insights into social evolution and disease challenges for managed and wild bees

Cited by 29 publications

References 166 publications

Editorial 2018

Editorial 2018

Using Manual and Computer-Based Text-Mining to Uncover Research Trends for Apis mellifera

The Progress of Multi-Omics Technologies: Determining Function in Lactic Acid Bacteria Using a Systems Level Approach

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