Diet and host phylogeny drive the taxonomic and functional contents of the gut microbiome in mammals, yet it is unknown whether these patterns hold across all vertebrate lineages. Here, we assessed gut microbiomes from ∼900 vertebrate species, including 315 mammals and 491 birds, assessing contributions of diet, phylogeny, and physiology to structuring gut microbiomes. In most nonflying mammals, strong correlations exist between microbial community similarity, host diet, and host phylogenetic distance up to the host order level. In birds, by contrast, gut microbiomes are only very weakly correlated to diet or host phylogeny. Furthermore, while most microbes resident in mammalian guts are present in only a restricted taxonomic range of hosts, most microbes recovered from birds show little evidence of host specificity. Notably, among the mammals, bats host especially bird-like gut microbiomes, with little evidence for correlation to host diet or phylogeny. This suggests that host-gut microbiome phylosymbiosis depends on factors convergently absent in birds and bats, potentially associated with physiological adaptations to flight. Our findings expose major variations in the behavior of these important symbioses in endothermic vertebrates and may signal fundamental evolutionary shifts in the cost/benefit framework of the gut microbiome. IMPORTANCE In this comprehensive survey of microbiomes of >900 species, including 315 mammals and 491 birds, we find a striking convergence of the microbiomes of birds and animals that fly. In nonflying mammals, diet and short-term evolutionary relatedness drive the microbiome, and many microbial species are specific to a particular kind of mammal, but flying mammals and birds break this pattern with many microbes shared across different species, with little correlation either with diet or with relatedness of the hosts. This finding suggests that adaptation to flight breaks long-held relationships between hosts and their microbes.
We present a new software package (HZAR) that provides functions for fitting molecular genetic and morphological data from hybrid zones to classic equilibrium cline models using the Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm. The software applies likelihood functions appropriate for different types of data, including diploid and haploid genetic markers and quantitative morphological traits. The modular design allows flexibility in fitting cline models of varying complexity. To facilitate hypothesis testing, an autofit function is included that allows automated model selection from a set of nested cline models. Cline parameter values, such as cline centre and cline width, are estimated and may be compared statistically across clines. The package is written in the R language and is available through the Comprehensive R Archive Network (CRAN; http://cran.r-project.org/). Here, we describe HZAR and demonstrate its use with a sample data set from a well-studied hybrid zone in western Panama between white-collared (Manacus candei) and golden-collared manakins (M. vitellinus). Comparisons of our results with previously published results for this hybrid zone validate the hzar software. We extend analysis of this hybrid zone by fitting additional models to molecular data where appropriate.
Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.
Next‐generation sequencing has greatly expanded the utility and value of museum collections by revealing specimens as genomic resources. As the field of museum genomics grows, so does the need for extraction methods that maximize DNA yields. For avian museum specimens, the established method of extracting DNA from toe pads works well for most specimens. However, for some specimens, especially those of birds that are very small or very large, toe pads can be a poor source of DNA. In this study, we apply two DNA extraction methods (phenol–chloroform and silica column) to three different sources of DNA (toe pad, skin punch and bone) from 10 historical avian museum specimens. We show that a modified phenol–chloroform protocol yielded significantly more DNA than a silica column protocol (e.g., Qiagen DNeasy Blood & Tissue Kit) across all tissue types. However, extractions using the silica column protocol contained longer fragments on average than those using the phenol–chloroform protocol, probably as a result of loss of small fragments through the silica column. While toe pads yielded more DNA than skin punches and bone fragments, skin punches proved to be a reliable alternative source of DNA and might be especially appealing when toe pad extractions are impractical. Overall, we found that historical bird museum specimens contain substantial amounts of DNA for genomic studies under most extraction scenarios, but that a phenol–chloroform protocol consistently provides the high quantities of DNA required for most current genomic protocols.
a b s t r a c tNext generation sequencing (NGS) technologies are revolutionizing many biological disciplines but have been slow to take root in phylogeography. This is partly due to the difficulty of using NGS to sequence orthologous DNA fragments for many individuals at low cost. We explore cases of recent divergence in four phylogenetically diverse avian systems using a method for quick and cost-effective generation of primary DNA sequence data using pyrosequencing. NGS data were processed using an analytical pipeline that reduces many reads into two called alleles per locus per individual. Using single nucleotide polymorphisms (SNPs) mined from the loci, we detected population differentiation in each of the four bird systems, including: a case of ecological speciation in rails (Rallus); a rapid postglacial radiation in the genus Junco; recent in situ speciation among hummingbirds (Trochilus) in Jamaica; and subspecies of white-crowned sparrows (Zonotrichia leucophrys) along the Pacific coast. The number of recovered loci aligning closely to chromosomal locations on the zebra finch (Taeniopygia guttata) genome was highly correlated to the size of the chromosome, suggesting that loci are randomly distributed throughout the genome. Using eight loci found in Zonotrichia and Junco lineages, we were also able to generate a species tree of these sparrow sister genera, demonstrating the potential of this method for generating data amenable to coalescent-based analysis. We discuss improvements that should enhance the method's utility for primary data generation.
Comparing inferences among datasets generated using short read sequencing may provide insight into the concerted impacts of divergence, gene flow and selection across organisms, but comparisons are complicated by biases introduced during dataset assembly. Sequence similarity thresholds allow the de novo assembly of short reads into clusters of alleles representing different loci, but the resulting datasets are sensitive to both the similarity threshold used and to the variation naturally present in the organism under study. Thresholds that require high sequence similarity among reads for assembly (stringent thresholds) as well as highly variable species may result in datasets in which divergent alleles are lost or divided into separate loci (‘over-splitting’), whereas liberal thresholds increase the risk of paralogous loci being combined into a single locus (‘under-splitting’). Comparisons among datasets or species are therefore potentially biased if different similarity thresholds are applied or if the species differ in levels of within-lineage genetic variation. We examine the impact of a range of similarity thresholds on assembly of empirical short read datasets from populations of four different non-model bird lineages (species or species pairs) with different levels of genetic divergence. We find that, in all species, stringent similarity thresholds result in fewer alleles per locus than more liberal thresholds, which appears to be the result of high levels of over-splitting. The frequency of putative under-splitting, conversely, is low at all thresholds. Inferred genetic distances between individuals, gene tree depths, and estimates of the ancestral mutation-scaled effective population size (θ) differ depending upon the similarity threshold applied. Relative differences in inferences across species differ even when the same threshold is applied, but may be dramatically different when datasets assembled under different thresholds are compared. These differences not only complicate comparisons across species, but also preclude the application of standard mutation rates for parameter calibration. We suggest some best practices for assembling short read data to maximize comparability, such as using more liberal thresholds and examining the impact of different thresholds on each dataset.
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BackgroundHaldane’s Rule, the tendency for the heterogametic sex to show reduced fertility in hybrid crosses, can obscure the signal of gene flow in mtDNA between species where females are heterogametic. Therefore, it is important when studying speciation and species limits in female-heterogametic species like birds to assess the signature of gene flow in the nuclear genome as well. We studied introgression of microsatellites and mtDNA across a secondary contact zone between coastal and interior lineages of Western Scrub-Jays (Aphelocoma californica) to test for a signature of Haldane’s Rule: a narrower cline of introgression in mtDNA compared to nuclear markers.ResultsOur initial phylogeographic analysis revealed that there is only one major area of contact between coastal and interior lineages and identified five genetic clusters with strong spatial structuring: Pacific Slope, Interior US, Edwards Plateau (Texas), Northern Mexico, and Southern Mexico. Consistent with predictions from Haldane’s Rule, mtDNA showed a narrower cline than nuclear markers across a transect through the hybrid zone. This result is not being driven by female-biased dispersal because neutral diffusion analysis, which included estimates of sex-specific dispersal rates, also showed less diffusion of mtDNA. Lineage-specific plumage traits were associated with nuclear genetic profiles for individuals in the hybrid zone, indicating that these differences are under genetic control.ConclusionsThis study adds to a growing list of studies that support predictions of Haldane’s Rule using cline analysis of multiple loci of differing inheritance modes, although alternate hypotheses like selection on different mtDNA types cannot be ruled out. That Haldane’s Rule appears to be operating in this system suggests a measure of reproductive isolation between the Pacific Slope and interior lineages. Based on a variety of evidence from the phenotype, ecology, and genetics, we recommend elevating three lineages to species level: A. californica (Pacific Slope); A. woodhouseii (Interior US plus Edwards Plateau plus Northern Mexico); A. sumichrasti (Southern Mexico). The distinctive Edwards Plateau population in Texas, which was monophyletic in mtDNA except for one individual, should be studied in greater detail given habitat threat.
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