Grand Opportunities: Strategies for Addressing Grand Challenges in Organismal Animal Biology

Stillman, Jonathon H.; Denny, Mark W.; Padilla, Dianna K.; Wake, Marvalee H.; Patek, S. N.; Tsukimura, Brian

doi:10.1093/icb/icr052

Cited by 11 publications

(6 citation statements)

References 11 publications

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“…Explaining emergent properties of complex organisms represents a grand challenge of biology (Schwenk et al, 2009). Emergent properties are often based on nonlinear interactions of their molecular constituents (Stillman et al, 2011). Despite the known nonlinearity of the genome to phenome continuum many biological studies rely heavily on correlations of complex organismal phenotypes (traits) with genomic variation (e.g., SNPs and other types of sequence variation) via QTL or GWAS analyses (Kratochwil & Meyer, 2015; Wray et al, 2013) and mRNA abundance changes via transcriptomics while proteome dynamics is less commonly investigated (Evans, 2015).…”

Section: Introductionmentioning

confidence: 99%

A data‐independent acquisition (DIA) assay library for quantitation of environmental effects on the kidney proteome of Oreochromis niloticus

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MacNiven

et al. 2021

Molecular Ecology Resources

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Explaining emergent properties of complex organisms represents a grand challenge of biology (Schwenk et al., 2009). Emergent properties are often based on nonlinear interactions of their molecular constituents (Stillman et al., 2011). Despite the known nonlinearity of the genome to phenome continuum many biological studies rely heavily on correlations of complex organismal phenotypes (traits) with genomic variation (e.g., SNPs and other types of sequence variation) via QTL or GWAS analyses (Kratochwil & Meyer,

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Section: Introductionmentioning

confidence: 99%

A data‐independent acquisition (DIA) assay library for quantitation of environmental effects on the kidney proteome of Oreochromis niloticus

Root

Campo

MacNiven

et al. 2021

Molecular Ecology Resources

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show abstract

“…Explaining emergent properties of complex organisms represents a grand challenge of biology (Schwenk, Padilla, Bakken, & Full, 2009). Emergent properties are often based on non-linear interactions of their molecular constituents (Stillman et al, 2011). Despite the known non-linearity of the genome to phenome continuum many biological studies rely heavily on correlations of complex organismal phenotypes (traits) with genomic variation (e.g.…”

mentioning

confidence: 99%

A data-independent acquisition (DIA) assay library for quantitation of environmental effects on the kidney proteome of Oreochromis niloticus

Root

Campo

MacNiven

et al. 2020

Preprint

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Interactions of organisms with their environment are complex and environmental regulation at different levels of biological organization is often non-linear. Therefore, the genotype to phenotype continuum requires study at multiple levels of organization. While studies of transcriptome regulation are now common for many species, quantitative studies of environmental effects on proteomes are needed. Here we report the generation of a data-independent acquisition (DIA) assay library that enables simultaneous targeted proteomics of thousands of Oreochromis niloticus kidney proteins using a label-and gel-free workflow that is well suited for ecologically relevant field samples. We demonstrate the usefulness of this DIA assay library by discerning environmental effects on the kidney proteome of O. niloticus. Moreover, we demonstrate that the DIA assay library approach generates data that are complimentary rather than redundant to transcriptomics data. Transcript and protein abundance differences in kidneys of tilapia acclimated to freshwater and brackish water (25 g/kg) were correlated for 2114 unique genes. A high degree of non-linearity in salinity-dependent regulation of transcriptomes and proteomes was revealed suggesting that the regulation of O. niloticus renal function by environmental salinity relies heavily on post-transcriptional mechanisms. The application of functional enrichment analyses using STRING and KEGG to DIA assay datasets is demonstrated by identifying myo-inositol metabolism, antioxidant and xenobiotic functions, and signaling mechanisms as key elements controlled by salinity in tilapia kidneys. The DIA assay library resource presented here can be adopted for other tissues and other organisms to study proteome dynamics during changing ecological contexts.

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“…SICB quickly and enthusiastically identified five grand challenges (Schwenk et al 2009). Subsequent publications and several workshops served to continue these discussions and to stimulate community organization (Stillman et al 2011). The challenge for this community (as for others) has been overcoming the tendency of researchers to focus on their own subdisciplines; it is a problem all too common in our scientific culture.…”

Section: K Nowledgeable Observers Shouldmentioning

confidence: 99%

A Cohesive Biology of Organisms Is on the Horizon

Zamer¹

2011

BioScience

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Grand Opportunities: Strategies for Addressing Grand Challenges in Organismal Animal Biology

Cited by 11 publications

References 11 publications

A data‐independent acquisition (DIA) assay library for quantitation of environmental effects on the kidney proteome of Oreochromis niloticus

A data‐independent acquisition (DIA) assay library for quantitation of environmental effects on the kidney proteome of Oreochromis niloticus

A data-independent acquisition (DIA) assay library for quantitation of environmental effects on the kidney proteome of Oreochromis niloticus

A Cohesive Biology of Organisms Is on the Horizon

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