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Predicting nutrient content of ray-finned fishes using phylogenetic information.

ABSTRACT: Human food and nutrition security is dependent on marine ecosystems threatened by overfishing, climate change, and other processes. The consequences on human nutritional status are uncertain, in part because current methods of analyzing fish nutrient content are expensive. Here, we evaluate the possibility of predicting nutrient content of ray-finned fishes using existing phylogenetic and life history information. We focus on nutrients for which fish are important sources: protein, total fat, omega-3 and omega-6 fatty acids, iron, zinc, vitamin A, vitamin B12, and vitamin D. Our results show that life history traits are weak predictors of species nutrient content, but phylogenetic relatedness is associated with similar nutrient profiles. Further, we develop a method for predicting the nutrient content of 7500+ species based on phylogenetic relationships to species with known nutrient content. Our approach is a cost-effective means for estimating potential changes in human nutrient intake associated with altered access to ray-finned fishes.

SUBMITTER: Vaitla B

PROVIDER: S-EPMC6156416 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Predicting nutrient content of ray-finned fishes using phylogenetic information.

Vaitla Bapu B Collar David D Smith Matthew R MR Myers Samuel S SS Rice Benjamin L BL Golden Christopher D CD

Nature communications 20180925 1

Human food and nutrition security is dependent on marine ecosystems threatened by overfishing, climate change, and other processes. The consequences on human nutritional status are uncertain, in part because current methods of analyzing fish nutrient content are expensive. Here, we evaluate the possibility of predicting nutrient content of ray-finned fishes using existing phylogenetic and life history information. We focus on nutrients for which fish are important sources: protein, total fat, om ...[more]

PMID: 30254265

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Project description:Ray-finned fishes (Actinopterygii) are the largest and most diverse group of vertebrates, comprising over half of all living vertebrate species. Phylogenetic relationships between ray-finned fishes have historically pivoted on the study of morphology, which has notoriously failed to resolve higher order relationships, such as within the percomorphs. More recently, comprehensive genomic analyses have provided further resolution of actinopterygian phylogeny, including higher order relationships. Such analyses are rightfully regarded as the 'gold standard' for phylogenetics. However, DNA retrieval requires modern or well-preserved tissue and is less likely to be preserved in archaeological or fossil specimens. By contrast, some proteins, such as collagen, are phylogenetically informative and can survive into deep time. Here, we test the utility of collagen type I amino acid sequences for phylogenetic estimation of ray-finned fishes. We estimate topology using Bayesian approaches and compare the congruence of our estimated trees with published genomic phylogenies. Furthermore, we apply a Bayesian molecular clock approach and compare estimated divergence dates with previously published genomic clock analyses. Our collagen-derived trees exhibit 77% of node positions as congruent with recent genomic-derived trees, with the majority of discrepancies occurring in higher order node positions, almost exclusively within the Percomorpha. Our molecular clock trees present divergence times that are fairly comparable with genomic-based phylogenetic analyses. We estimate the mean node age of Actinopteri at ∼293 million years (Ma), the base of Teleostei at ∼211 Ma and the radiation of percomorphs beginning at ∼141 Ma (∼350 Ma, ∼250-283 Ma and ∼120-133 Ma in genomic trees, respectively). Finally, we show that the average rate of collagen (I) sequence evolution is 0.9 amino acid substitutions for every million years of divergence, with the α3 (I) sequence evolving the fastest, followed by the α2 (I) chain. This is the quickest rate known for any vertebrate group. We demonstrate that phylogenetic analyses using collagen type I amino acid sequences generate tangible signals for actinopterygians that are highly congruent with recent genomic-level studies. However, there is limited congruence within percomorphs, perhaps due to clade-specific functional constraints acting upon collagen sequences. Our results provide important insights for future phylogenetic analyses incorporating extinct actinopterygian species via collagen (I) sequencing.

Dataset Information

Predicting nutrient content of ray-finned fishes using phylogenetic information.

Publications

Predicting nutrient content of ray-finned fishes using phylogenetic information.

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