17 research outputs found
Bone-Associated Gene Evolution and the Origin of Flight in Birds
Background
Bones have been subjected to considerable selective pressure throughout vertebrate evolution, such as occurred during the adaptations associated with the development of powered flight. Powered flight evolved independently in two extant clades of vertebrates, birds and bats. While this trait provided advantages such as in aerial foraging habits, escape from predators or long-distance travels, it also imposed great challenges, namely in the bone structure.
Results
We performed comparative genomic analyses of 89 bone-associated genes from 47 avian genomes (including 45 new), 39 mammalian, and 20 reptilian genomes, and demonstrate that birds, after correcting for multiple testing, have an almost two-fold increase in the number of bone-associated genes with evidence of positive selection (~52.8 %) compared with mammals (~30.3 %). Most of the positive-selected genes in birds are linked with bone regulation and remodeling and thirteen have been linked with functional pathways relevant to powered flight, including bone metabolism, bone fusion, muscle development and hyperglycemia levels. Genes encoding proteins involved in bone resorption, such as TPP1, had a high number of sites under Darwinian selection in birds.
Conclusions
Patterns of positive selection observed in bird ossification genes suggest that there was a period of intense selective pressure to improve flight efficiency that was closely linked with constraints on body size
The Genetic Origins of Dragons
Dragons are popular creatures in fantasy that are large winged lizards that can be the size of a house. This report looks at the basic genetic requirements to produce Dragons. It finds that HOXD and HOXc-6 genes are necessary requirements for the formation of the dragon’s wings. It also investigates the size limits for birds and finds that due to the current bird size being limited by feather size dragons will likely lack them, and be closer to the ancient creatures that flew, such as the Quetzalcoatlus
Intraskeletal histovariability, allometric growth patterns, and their functional implications in bird-like dinosaurs
With their elongated forelimbs and variable aerial skills, paravian dinosaurs, a clade also comprising modern birds, are in the hotspot of vertebrate evolutionary research. Inferences on the early evolution of flight largely rely on bone and feather morphology, while osteohistological traits are usually studied to explore life-history characteristics. By sampling and comparing multiple homologous fore-and hind limb elements, we integrate for the first time qualitative and quantitative osteohistological approaches to get insight into the intraskeletal growth dynamics and their functional implications in five paravian dinosaur taxa, Anchiornis, Aurornis, Eosinopteryx, Serikornis, and Jeholornis. Our qualitative assessment implies a considerable diversity in allometric/isometric growth patterns among these paravians. Quantitative analyses show that neither taxa nor homologous elements have characteristic histology, and that ontogenetic stage, element size and the newly introduced relative element precocity only partially explain the diaphyseal histovariability. Still, Jeholornis, the only avialan studied here, is histologically distinct from all other specimens in the multivariate visualizations raising the hypothesis that its bone tissue characteristics may be related to its superior aerial capabilities compared to the non-avialan paravians. Our results warrant further research on the osteohistological correlates of flight and developmental strategies in birds and bird-like dinosaurs
Genomic adaptations to a high sugar diet in birds
While excessive consumption of glucose- and fructose-sweetened soft drinks is a major risk factor for type 2 diabetes and metabolic syndrome in humans, several nectarivorous bird lin- eages have adapted their metabolism to rely mostly on simple sugars obtained from flower nectar. These lineages are spread around the world and include hummingbirds (Americas), honeyeaters and lorikeets (Australasia), and sunbirds (Africa and Asia). All these nectarivores have evolved distinct phenotypic traits allowing them to rely mostly on nectar as a source of nutrients. However, the genomic underpinnings of these natural adaptations to nectarivory are largely unknown. In order to identify genomic changes underlying metabolic adaptations of nectarivorous birds, we produced new genomic and transcriptomic data, and combining them with publically avail- able data, we ran a number of comprehensive comparative screens. To confirm our theoretical findings, we complemented them with experimental validation. The genome-wide screen for hummingbird-specific gene losses identified the loss of FBP2, a gene encoding a key gluconeogenic enzyme that is normally active in muscles of all tetrapods. Loss of FBP2 occurred around a time where energy-demanding hovering flight is thought to have evolved in hummingbirds. We hypothesized that FBP2 loss could have contributed to the evolution of their metabolic adaptations in muscles. To test this, we downregulated the gene in a bird muscle cell line. Even a partial knockout of FBP2 significantly upregulated glycolysis and mitochondrial respiration in cells. In our experiments, we also show that the latter is likely happening due to the increased number of mitochondria. Together, these results suggest that FBP2 loss contributed to metabolic adaptations that likely enhanced hummingbirds’ ability to immediately process newly ingested sugars thus providing energy for the hovering flight. To study the convergence of adaptations to nectarivory, we ran a number of screens search- ing for convergent and lineage-specific genomic changes. A screen for rapid adaptive evolution identified that a rate-limiting glycolytic enzyme (hexokinase 3) evolved under strong positive se- lection in the stem honeyeaters, potentially underlying similar metabolic changes to what FBP2 loss has introduced in hummingbirds. These results provide a deep insight into the genomic basis of adaptations to high-sugar ‘soft drink-like’ diets in birds. These findings have the potential not only to answer important evolu- tionary questions but also to teach us lessons concerning type 2 diabetes, metabolic syndrome, and obesity in humans.:Zusammenfassung 4
Abstract 6
Chapter I. Introduction 8
Diet diversity in birds 8
Nectarivory and its challenges 8
Adaptations to nectarivory 11
Hummingbirds 13
Other nectar-feeding birds 14
Genomic changes underlying phenotypic variation 15
Gene copy-number variation 16
Gene duplication mechanisms and its evolutionary fates 17
Gene duplications contribute to adaptive evolution 17
Detection of gene duplications 19
Gene loss 19
The use-it-or-lose-it hypothesis 20
The less-is-more hypothesis 20
Detection of gene losses 20
Selection pressure 21
Positive selection can drive adaptive evolution 21
Detection of selection 22
Amino acid substitutions 23
Previous research on adaptations to nectarivory 23
Outline of the thesis 24
Chapter II. Genomic basis of metabolic adaptations in hummingbirds 26
Section I: Screen for hummingbird-specific gene losses 26
Overview 26
Results 26
Assembly of the long-tailed hermit genome 26
Identification of hummingbird-specific gene losses 27
Hummingbird muscle expresses no FBPases 29
Discussion 30
Section II: Experimental exploration of the metabolic role of the FBP2 loss 31
Overview 31
Results 31
Expression of FBPase encoding genes in cell lines 31
Inhibition of FBPases in QM7 32
Testing the FBPase inhibitor with glycogen assays 33
Testing the FBPase inhibitor with Seahorse Glycolytic Rate Assay 37
Generation of FBP2 knockout in QM7 38
Infection - transfection strategy 38
Electroporation strategy 40
Detection of FBP2-encoded protein with immunostaining 42
Knockout of FBP2 upregulates glycolysis in avian myoblast cells 44
FBP2 downregulation upregulates OXPHOS 44
FBP2 knockout increases the number of mitochondria 44
Genes important for mitochondrial biosynthesis and function are upregulated in hummingbirds 46
FBP2 knockout is associated with increased lipid deposition 49
Discussion 49
Section III: Hummingbird tissues analysis 50
Overview 50
Results 51
Glycogen content in hummingbirds tissues 51
Histological comparison 51
Biochemical quantification of total glycogen 52
Lipid content in hummingbird tissues 53
Discussion 54
Section IV: Evolution of glucose metabolism genes in hummingbirds 55
Overview 55
Results 55
Positive selection in glycolytic genes in hummingbirds 55
Copy number of glucose transporters in hummingbirds 57
Expression of glucose transporters in hummingbirds 58
Discussion 59
Chapter III. Convergence in the evolution of nectarivory 60
Overview 60
Results 61
Sequencing and assembly of new genomes of nectarivorous birds 61
Annotation of protein-coding genes 62
Gene families expansion-contraction 64
Signatures of positive selection related to nectarivory 65
The rate-controlling glycolytic enzyme evolved faster in honeyeaters 70
Discussion 72
Chapter IV. General discussion and outlook 72
Future work 75
Chapter V. Methods 77
Methods I: Screen for hummingbird-specific gene losses 77
Genome assembly 77
Modeling and masking repeats 77
Generating pairwise genome alignments 77
Detecting gene losses 77
Gene loss dating 77
Methods II: Experimental exploration of the metabolic role of the FBP2 loss 78
Cell culture 78
Guide RNA design 78
Infection and transfection of QM7 myoblasts 78
Electroporation of QM7 myoblasts 79
Genotyping of QM7 cell pools 79
RNA isolation 80
Real-time qPCR 80
Seahorse glycolytic rate assay 80
Cell number quantification 80
Mitochondrial number estimation 80
Biochemical glycogen qualification in cells 81
Fluorescent glycogen qualification in cells 81
Lipid quantification in cells 81
Western blot 82
Homology modeling 82
RNA sequencing 82
Analysis of transcriptomic data 83
Methods III: Hummingbird tissues analysis 83
Tissue preparation 83
Paraffin embedding and sectioning 83
Glycogen staining tissues 84
Freezing tissues and cryosectioning 84
Lipid staining tissues 84
Imaging histological sections 84
Biochemical glycogen qualification in tissues 84
Methods IV: Changes in glucose metabolism genes in hummingbirds 85
Positive selection analysis 85
Methods: Convergence in the evolution of nectarivory 85
Protein-coding gene annotation 85
Positive selection analysis 86
Estimating time-calibrated phylogeny 87
Gene families expansion-contraction analysis 87
Homology modeling 87
Appendix 8
Data for "Bone-associated gene evolution and the origin of flight in birds"
<div><div>The data contained in them pretains to the manuscript: </div><div><br></div><div>Machado, JP, Johnson, WE, Gilbert, MTP, Zhang, G, Jarvis, ED, O’Brien, SJ, & Antunes, A (2016). </div><div>Bone-associated gene evolution and the origin of flight in birds. BMC genomics, 17(1), 1.</div><div><br></div><div>4 zip files:</div><div><br></div><div><b>1) Codeml site models:</b></div><div> gene alignments,</div><div> tree,</div><div> parameters template.</div><div><br></div><div><b>2) Codeml branch models:</b></div><div> gene alignments,</div><div> tree,</div><div> parameters template,</div><div> results from Codeml.</div><div><br></div><div><b>3) Codeml branch-site models:</b></div><div> gene alignments,</div><div> tree,</div><div> parameters template,</div><div> results from Codeml. </div><div><br></div><div><b>4) CoEvol:</b></div><div> input files and results.</div></div><div><br></div
Additional file 19: Table S13. of Bone-associated gene evolution and the origin of flight in birds
Estimation of dN and dS for each branch under Model 0. For each branch, average of dN and dS and the corresponding standard deviation. (DOC 165 kb
Additional file 17: Figure S6. of Bone-associated gene evolution and the origin of flight in birds
Phylogenetic trees of reptiles used in CODEML analysis. (DOC 90 kb
Additional file 6: Table S4. of Bone-associated gene evolution and the origin of flight in birds
Positively selected sites of bone-associated genes in Reptilian dataset after multiple testing correction. The alignment length is on Amino acids (aa). Bold represents statistical significance (pâ<â0.05). Q-value estimations for multiple testing are represented as positive selected (1) and negative selected (0). (DOC 158 kb
Additional file 16: Table S12. of Bone-associated gene evolution and the origin of flight in birds
Covariance between dS, ω (dN/dS), gc content, and the three body mass measures (minimum, maximum and average) in 39 mammalian genomes using gene-based tree. The upper triangle shows the values obtained for all mammals and the lower triangle excluding bats. Each cell represent the covariance values and posterior probability are the bracketed values, posterior probability (** - < = 0.025 or > =0.975; * - < =0.05 or > =0.95) are highlighted in bold for the statistically significant correlations. (DOC 35 kb