RESUMO
In recent years, there has been a significant increase in the number of completely sequenced plant genomes. The comparison of fully sequenced genomes allows for identification of new gene family members, as well as comprehensive analysis of gene family evolution. The aldehyde dehydrogenase (ALDH) gene superfamily comprises a group of enzymes involved in the NAD(+)- or NADP(+)-dependent conversion of various aldehydes to their corresponding carboxylic acids. ALDH enzymes are involved in processing many aldehydes that serve as biogenic intermediates in a wide range of metabolic pathways. In addition, many of these enzymes function as 'aldehyde scavengers' by removing reactive aldehydes generated during the oxidative degradation of lipid membranes, also known as lipid peroxidation. Plants and animals share many ALDH families, and many genes are highly conserved between these two evolutionarily distinct groups. Conversely, both plants and animals also contain unique ALDH genes and families. Herein we carried out genome-wide identification of ALDH genes in a number of plant species-including Arabidopsis thaliana (thale crest), Chlamydomonas reinhardtii (unicellular algae), Oryza sativa (rice), Physcomitrella patens (moss), Vitis vinifera (grapevine) and Zea mays (maize). These data were then combined with previous analysis of Populus trichocarpa (poplar tree), Selaginella moellindorffii (gemmiferous spikemoss), Sorghum bicolor (sorghum) and Volvox carteri (colonial algae) for a comprehensive evolutionary comparison of the plant ALDH superfamily. As a result, newly identified genes can be more easily analyzed and gene names can be assigned according to current nomenclature guidelines; our goal is to clarify previously confusing and conflicting names and classifications that might confound results and prevent accurate comparisons between studies.
Assuntos
Aldeído Desidrogenase/genética , Família Multigênica , Proteínas de Plantas/genética , Plantas/genética , Aldeído Desidrogenase/metabolismo , Aldeídos/metabolismo , Animais , Arabidopsis/enzimologia , Arabidopsis/genética , Bryopsida/enzimologia , Bryopsida/genética , Chlamydomonas reinhardtii/enzimologia , Chlamydomonas reinhardtii/genética , Mapeamento Cromossômico , Cromossomos de Plantas/genética , Evolução Molecular , Genoma de Planta/genética , Genômica/métodos , Oryza/enzimologia , Oryza/genética , Proteínas de Plantas/metabolismo , Plantas/classificação , Plantas/enzimologia , Populus/enzimologia , Populus/genética , Selaginellaceae/enzimologia , Selaginellaceae/genética , Sorghum/enzimologia , Sorghum/genética , Terminologia como Assunto , Vitis/enzimologia , Vitis/genética , Volvox/enzimologia , Volvox/genética , Zea mays/enzimologia , Zea mays/genéticaRESUMO
Understanding the role that the environment plays in influencing public health often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient information and confront significant unknowns in the field of environmental public health, yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable (FAIR) data. Even when data are readily available, the ability to create, analyze, and draw conclusions from these data using emerging computational tools, such as augmented and artificial inteligence (AI) and machine learning, requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. We argue that collaborative efforts in data curation and storage, scientific computing, and training are of paramount importance to empower researchers within environmental sciences and the broader public health community to apply AI approaches and fully realize their potential. Leaders in the field were asked to prioritize challenges in incorporating big data in environmental public health research: inconsistent implementation of FAIR principles in data collection and sharing, a lack of skilled data scientists and appropriate cyber-infrastructures, and limited understanding of possibilities and communication of benefits were among those identified. These issues are discussed, and actionable recommendations are provided.