Aboriginal Australians represent one of the longest continuous cultural complexes known. Archaeological evidence indicates that Australia and New Guinea were initially settled approximately 50 thousand years ago (ka); however, little is known about the processes underlying the enormous linguistic and phenotypic diversity within Australia. Here we report 111 mitochondrial genomes (mitogenomes) from historical Aboriginal Australian hair samples, whose origins enable us to reconstruct Australian phylogeographic history before European settlement. Marked geographic patterns and deep splits across the major mitochondrial haplogroups imply that the settlement of Australia comprised a single, rapid migration along the east and west coasts that reached southern Australia by 49-45 ka. After continent-wide colonization, strong regional patterns developed and these have survived despite substantial climatic and cultural change during the late Pleistocene and Holocene epochs. Remarkably, we find evidence for the continuous presence of populations in discrete geographic areas dating back to around 50 ka, in agreement with the notable Aboriginal Australian cultural attachment to their country.

Molecular sequence data that have evolved under the influence of heterotachous evolutionary processes are known to mislead phylogenetic inference. We introduce the General Heterogeneous evolution On a Single Topology (GHOST) model of sequence evolution, implemented under a maximum-likelihood framework in the phylogenetic program IQ-TREE (http://www.iqtree.org). Simulations show that using the GHOST model, IQ-TREE can accurately recover the tree topology, branch lengths, and substitution model parameters from heterotachously evolved sequences. We investigate the performance of the GHOST model on empirical data by sampling phylogenomic alignments of varying lengths from a plastome alignment. We then carry out inference under the GHOST model on a phylogenomic data set composed of 248 genes from 16 taxa, where we find the GHOST model concurs with the currently accepted view, placing turtles as a sister lineage of archosaurs, in contrast to results obtained using traditional variable rates-across-sites models. Finally, we apply the model to a data set composed of a sodium channel gene of 11 fish taxa, finding that the GHOST model is able to elucidate a subtle component of the historical signal, linked to the previously established convergent evolution of the electric organ in two geographically distinct lineages of electric fish. We compare inference under the GHOST model to partitioning by codon position and show that, owing to the minimization of model constraints, the GHOST model offers unique biological insights when applied to empirical data.

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Background: Though the functional states of other endocrine systems are not defined on the basis of levels of controlling hormones, the assessment of thyroid function is based on levels of the controlling hormone thyrotropin (TSH). We, therefore, addressed the question as to whether levels of thyroid hormones [free thyroxine (fT4), total triiodothyronine (TT3)/free triiodothyronine (fT3)], or TSH levels, within and beyond the reference ranges, provide the better guide to the range of clinical parameters associated with thyroid status. Methods: A PubMed/MEDLINE search of studies up to October 2019, examining associations of levels of thyroid hormones and TSH, taken simultaneously in the same individuals, with clinical parameters was performed. We analyzed atrial fibrillation, other cardiac parameters, osteoporosis and fracture, cancer, dementia, frailty, mortality, features of the metabolic syndrome, and pregnancy outcomes. Studies were assessed for quality by using a modified Newcastle-Ottawa score. Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed. A meta-analysis of the associations was performed to determine the relative likelihood of fT4, TT3/fT3, and TSH levels that are associated with the clinical parameters. Results: We identified 58 suitable articles and a total of 1880 associations. In general, clinical parameters were associated with thyroid hormone levels significantly more often than with TSH levels-the converse was not true for any of the clinical parameters. In the 1880 considered associations, fT4 levels were significantly associated with clinical parameters in 50% of analyses. The respective frequencies for TT3/fT3 and TSH levels were 53% and 23% (p < 0.0001 for both fT4 and TT3/fT3 vs. TSH). The fT4 and TT3/fT3 levels were comparably associated with clinical parameters (p = 0.71). More sophisticated statistical analyses, however, indicated that the associations with TT3/fT3 were not as robust as the associations with fT4. Conclusions: Thyroid hormones levels, and in particular fT4 levels, seem to have stronger associations with clinical parameters than do TSH levels. Associations of clinical parameters with TSH levels can be explained by the strong negative population correlation between thyroid hormones and TSH. Clinical and research components of thyroidology currently based on the measurement of the thyroid state by reference to TSH levels warrant reconsideration.