Refine
Language
- English (4)
Has Fulltext
- yes (4)
Is part of the Bibliography
- no (4)
Keywords
- ectosomes (1)
- exosomes (1)
- extracellular vesicles (1)
- guidelines (1)
- microparticles (1)
- microvesicles (1)
- minimal information requirements (1)
- reproducibility (1)
- rigor (1)
- standardization (1)
Institute
- Biochemie und Chemie (1)
- Georg-Speyer-Haus (1)
- Medizin (1)
A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
Nestling growth and development studies have been a topic of interest for a greater part of the last century (Sutton 1935, Walkinshaw 1948) and continue to be of interest today. This is not surprising since studies on nestling growth can provide a wealth of biological information that has larger implications for avian management and conservation. Despite this history of studying nestling development, basic information is still limited or absent for many species. Many questions remain unanswered, and contradictory conclusions are often found in the literature (Starck and Ricklefs 1998a). Therefore, much information on aging and development can still be gained from studying the development patterns of similar species and from comparative studies, across avian orders (Minea et al. 1982, Saunders and Hansen 1989, Carsson and Hörnfeldt 1993). Additionally, nestling growth studies can yield insight into the effects of different nesting strategies on productivity (O’Connor 1978), as well as the impacts of parental effort and environmental variables on fitness (Ross 1980, Ricklefs and Peters 1981, Magrath 1991). Since low reproductive success may play a significant role in the declines of many North American passerines (Sherry and Holmes 1992, Ballard et al. 2003), a better understanding of the factors that influence reproductive success is a vital component of avian conservation (Martin 1992). Data on nestling aging can be used to improve nest survival estimates (Dinsmore 2002, Nur et al. 2004), providing information that can be used to more precisely age nests (Pinkowski 1975, Podlesack and Blem 2002), (Jones and Geupel 2007). Indeed, the relatively short time period young spend developing in the nest is a critical part of a bird’s life cycle and a nestling’s developmental path can affect its survival to independence, its survival as an adult, and its future reproductive success.