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Snake venoms are integrated systems, but abundant venom proteins evolve more rapidly.

Aird SD, Aggarwal S, Villar-Briones A, Tin MM, Terada K, Mikheyev AS - BMC Genomics (2015)

Bottom Line: Hybrids produced most proteins found in both parental venoms.Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness.Adaptive evolution of venoms may occur most rapidly through changes in expression levels that alter fitness contributions, and thus the strength of selection acting on specific secretome components.

View Article: PubMed Central - PubMed

Affiliation: Okinawa Institute of Science and Technology Graduate University, Tancha 1919-1, Onna-son, Kunigami-gun, Okinawa-ken, 904-0412, Japan. steven.aird@oist.jp.

ABSTRACT

Background: While many studies have shown that extracellular proteins evolve rapidly, how selection acts on them remains poorly understood. We used snake venoms to understand the interaction between ecology, expression level, and evolutionary rate in secreted protein systems. Venomous snakes employ well-integrated systems of proteins and organic constituents to immobilize prey. Venoms are generally optimized to subdue preferred prey more effectively than non-prey, and many venom protein families manifest positive selection and rapid gene family diversification. Although previous studies have illuminated how individual venom protein families evolve, how selection acts on venoms as integrated systems, is unknown.

Results: Using next-generation transcriptome sequencing and mass spectrometry, we examined microevolution in two pitvipers, allopatrically separated for at least 1.6 million years, and their hybrids. Transcriptomes of parental species had generally similar compositions in regard to protein families, but for a given protein family, the homologs present and concentrations thereof sometimes differed dramatically. For instance, a phospholipase A2 transcript comprising 73.4 % of the Protobothrops elegans transcriptome, was barely present in the P. flavoviridis transcriptome (<0.05 %). Hybrids produced most proteins found in both parental venoms. Protein evolutionary rates were positively correlated with transcriptomic and proteomic abundances, and the most abundant proteins showed positive selection. This pattern holds with the addition of four other published crotaline transcriptomes, from two more genera, and also for the recently published king cobra genome, suggesting that rapid evolution of abundant proteins may be generally true for snake venoms. Looking more broadly at Protobothrops, we show that rapid evolution of the most abundant components is due to positive selection, suggesting an interplay between abundance and adaptation.

Conclusions: Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness. Natural selection then acts on the additive genetic variance of these components, in proportion to their contributions to overall fitness. Adaptive evolution of venoms may occur most rapidly through changes in expression levels that alter fitness contributions, and thus the strength of selection acting on specific secretome components.

No MeSH data available.


Transcriptomic and proteomic data present generally concordant pictures. When mapped against their own references, the proteomic and transcriptomic measures of abundance were correlated (Spearman rank p = 1.5 × 10−9, 5.3 × 10−9, for P. elegans and P. flavoviridis, respectively). Individual proteomic samples are represented by different shapes, with the sample used for the reference transcriptome shown as an open circle. Since only one transcriptome was sequenced for each species, biological replicates share the same X-coordinate. The methodology employed herein was that reported in [42]
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Fig4: Transcriptomic and proteomic data present generally concordant pictures. When mapped against their own references, the proteomic and transcriptomic measures of abundance were correlated (Spearman rank p = 1.5 × 10−9, 5.3 × 10−9, for P. elegans and P. flavoviridis, respectively). Individual proteomic samples are represented by different shapes, with the sample used for the reference transcriptome shown as an open circle. Since only one transcriptome was sequenced for each species, biological replicates share the same X-coordinate. The methodology employed herein was that reported in [42]

Mentions: Proteomic data can be quantified by standardizing absolute peptide abundance by the predicted protein length [42]. This approach produced significant correlations between protein and transcriptomic abundance estimates, with close agreement between protein sample replicates from different individuals (Fig. 4). However, reference transcripts were only available for the parent species, and not for the putative hybrids. In order to make comparisons of protein abundance, a common reference was needed. We identified peptides using each transcriptome as a reference, in order to determine which performed better. The P. flavoviridis reference produced the most significant correlation between transcriptomic and proteomic data for both species (Spearman correlation with P. elegans: r = 0.29, p = 0.011, P. flavoviridis r = 0.50, p = 5.3 × 10−9), so it was used to call peptides for the hybrids (Fig. 4).Fig. 4


Snake venoms are integrated systems, but abundant venom proteins evolve more rapidly.

Aird SD, Aggarwal S, Villar-Briones A, Tin MM, Terada K, Mikheyev AS - BMC Genomics (2015)

Transcriptomic and proteomic data present generally concordant pictures. When mapped against their own references, the proteomic and transcriptomic measures of abundance were correlated (Spearman rank p = 1.5 × 10−9, 5.3 × 10−9, for P. elegans and P. flavoviridis, respectively). Individual proteomic samples are represented by different shapes, with the sample used for the reference transcriptome shown as an open circle. Since only one transcriptome was sequenced for each species, biological replicates share the same X-coordinate. The methodology employed herein was that reported in [42]
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4552096&req=5

Fig4: Transcriptomic and proteomic data present generally concordant pictures. When mapped against their own references, the proteomic and transcriptomic measures of abundance were correlated (Spearman rank p = 1.5 × 10−9, 5.3 × 10−9, for P. elegans and P. flavoviridis, respectively). Individual proteomic samples are represented by different shapes, with the sample used for the reference transcriptome shown as an open circle. Since only one transcriptome was sequenced for each species, biological replicates share the same X-coordinate. The methodology employed herein was that reported in [42]
Mentions: Proteomic data can be quantified by standardizing absolute peptide abundance by the predicted protein length [42]. This approach produced significant correlations between protein and transcriptomic abundance estimates, with close agreement between protein sample replicates from different individuals (Fig. 4). However, reference transcripts were only available for the parent species, and not for the putative hybrids. In order to make comparisons of protein abundance, a common reference was needed. We identified peptides using each transcriptome as a reference, in order to determine which performed better. The P. flavoviridis reference produced the most significant correlation between transcriptomic and proteomic data for both species (Spearman correlation with P. elegans: r = 0.29, p = 0.011, P. flavoviridis r = 0.50, p = 5.3 × 10−9), so it was used to call peptides for the hybrids (Fig. 4).Fig. 4

Bottom Line: Hybrids produced most proteins found in both parental venoms.Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness.Adaptive evolution of venoms may occur most rapidly through changes in expression levels that alter fitness contributions, and thus the strength of selection acting on specific secretome components.

View Article: PubMed Central - PubMed

Affiliation: Okinawa Institute of Science and Technology Graduate University, Tancha 1919-1, Onna-son, Kunigami-gun, Okinawa-ken, 904-0412, Japan. steven.aird@oist.jp.

ABSTRACT

Background: While many studies have shown that extracellular proteins evolve rapidly, how selection acts on them remains poorly understood. We used snake venoms to understand the interaction between ecology, expression level, and evolutionary rate in secreted protein systems. Venomous snakes employ well-integrated systems of proteins and organic constituents to immobilize prey. Venoms are generally optimized to subdue preferred prey more effectively than non-prey, and many venom protein families manifest positive selection and rapid gene family diversification. Although previous studies have illuminated how individual venom protein families evolve, how selection acts on venoms as integrated systems, is unknown.

Results: Using next-generation transcriptome sequencing and mass spectrometry, we examined microevolution in two pitvipers, allopatrically separated for at least 1.6 million years, and their hybrids. Transcriptomes of parental species had generally similar compositions in regard to protein families, but for a given protein family, the homologs present and concentrations thereof sometimes differed dramatically. For instance, a phospholipase A2 transcript comprising 73.4 % of the Protobothrops elegans transcriptome, was barely present in the P. flavoviridis transcriptome (<0.05 %). Hybrids produced most proteins found in both parental venoms. Protein evolutionary rates were positively correlated with transcriptomic and proteomic abundances, and the most abundant proteins showed positive selection. This pattern holds with the addition of four other published crotaline transcriptomes, from two more genera, and also for the recently published king cobra genome, suggesting that rapid evolution of abundant proteins may be generally true for snake venoms. Looking more broadly at Protobothrops, we show that rapid evolution of the most abundant components is due to positive selection, suggesting an interplay between abundance and adaptation.

Conclusions: Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness. Natural selection then acts on the additive genetic variance of these components, in proportion to their contributions to overall fitness. Adaptive evolution of venoms may occur most rapidly through changes in expression levels that alter fitness contributions, and thus the strength of selection acting on specific secretome components.

No MeSH data available.