Biochemical and molecular confirmation of alkaptonuria in a Sumatran orangutan (Pongo abelii)

A 6-yr-old female orangutan presented with a history of dark urine that turned brown upon standing since birth. Repeated routine urinalysis and urine culture were unremarkable. Urine organic acid analysis showed elevation in homogentisic acid consistent with alkaptonuria. Sequence analysis identified a homozygous missense variant, c.1081G>A (p.Gly361Arg), of the homogentisate 1,2-dioxygenase (HGD) gene. Familial studies, molecular modeling, and comparison to human variant databases support this variant as the underlying cause of alkaptonuria in this orangutan. This is the first report of molecular confirmation of alkaptonuria in a nonhuman primate.

A community-maintained standard library of population genetic models

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

Characterisation of the hepatitis B virus cross-species transmission pattern via Na+/taurocholate co-transporting polypeptides from 11 New World and Old World primate species

The hepatic Na+/taurocholate co-transporting polypeptide (NTCP in man, Ntcp in animals) is the high-affinity receptor for the hepatitis B (HBV) and hepatitis D (HDV) viruses. Species barriers for human HBV/HDV within the order Primates were previously attributed to Ntcp sequence variations that disable virus-receptor interaction. However, only a limited number of primate Ntcps have been analysed so far. In the present study, a total of 11 Ntcps from apes, Old and New World monkeys were cloned and expressed in vitro to characterise their interaction with HBV and HDV. All Ntcps showed intact bile salt transport. Human NTCP as well as the Ntcps from the great apes chimpanzee and orangutan showed transport-competing binding of HBV derived myr-preS1-peptides. In contrast, all six Ntcps from the group of Old World monkeys were insensitive to HBV myr-preS1-peptide binding and HBV/HDV infection. This is basically predetermined by the amino acid arginine at position 158 of all studied Old World monkey Ntcps. An exchange from arginine to glycine (as present in humans and great apes) at this position (R158G) alone was sufficient to achieve full transport-competing HBV myr-preS1-peptide binding and susceptibility for HBV/HDV infection. New World monkey Ntcps showed higher sequence heterogeneity, but in two cases with 158G showed transport-competing HBV myr-preS1-peptide binding, and in one case (Saimiri sciureus) even susceptibility for HBV/HDV infection. In conclusion, amino acid position 158 of NTCP/Ntcp is sufficient to discriminate between the HBV/HDV susceptible group of humans and great apes (158G) and the non-susceptible group of Old World monkeys (158R). In the case of the phylogenetically more distant New World monkey Ntcps amino acid 158 plays a significant, but not exclusive role.

Estimating divergence time and ancestral effective population size of Bornean and Sumatran orangutan subspecies using a coalescent hidden Markov model

Due to genetic variation in the ancestor of two populations or two species, the divergence time for DNA sequences from two populations is variable along the genome. Within genomic segments all bases will share the same divergence—because they share a most recent common ancestor—when no recombination event has occurred to split them apart. The size of these segments of constant divergence depends on the recombination rate, but also on the speciation time, the effective population size of the ancestral population, as well as demographic effects and selection. Thus, inference of these parameters may be possible if we can decode the divergence times along a genomic alignment. Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. The model is efficient enough to allow inference on whole-genome data sets. We first investigate the power and consistency of the model with coalescent simulations and then apply it to the whole-genome sequences of the two orangutan sub-species, Bornean (P. p. pygmaeus) and Sumatran (P. p. abelii) orangutans from the Orangutan Genome Project. We estimate the speciation time between the two sub-species to be thousand years ago and the effective population size of the ancestral orangutan species to be , consistent with recent results based on smaller data sets. We also report a negative correlation between chromosome size and ancestral effective population size, which we interpret as a signature of recombination increasing the efficacy of selection.

We present a hidden Markov model that uses variation in coalescence times between two distantly related populations, or closely related species, to infer population genetics parameters in ancestral population or species. The model infers the divergence times in segments along the alignment. Using coalescent simulations, we show that the model accurately estimates the divergence time between the two populations and the effective population size of the ancestral population. We apply the model to the recently sequenced orangutan sub-species and estimate their divergence time and the effective population size of their ancestor population.