Research Overview

Archaic Introgression and High Altitude Adaptation

Archaic hominin Denisovans and the adaptive consequences of  their interactions with our species

 Methods Development in Population Genetics 

Machine Learning and statistical methods development for inferring genomic parameters and signals

Complex Traits and Diseases in Admixed Human Populations

Modeling polygenic risk of complex diseases in recently admixed human populations

Zoonotic Malaria in Humans and ​Non-Human Primates

Admixture history in primate populations and its influence on their susceptibility to malaria
Denisovan Introgression and High Altitude Adaptation on the Tibetan Plateau

​The discovery of Denisovans is one of the most exciting findings in human evolution in the past decade. However, as of today, more questions have been asked than the ones being answered regarding this mysterious archaic hominin. The striking similarity between sequences of the EPAS1 gene in Denisovans and modern Tibetans suggested adaptive introgression that facilitated high altitude adaptation, while the time and geographic ranges where the contact between species was made remain unknown.

In a recent work, I leveraged information of the EPAS1 gene in modern Tibetans, and determined the history of interactions between Denisovans and the ancestors of our species, via extensive applications of statistical methods and simulations. I show that among the multiple pulses of Denisovan introgression in East Asia, the beneficial EPAS1 haplotype was introduced by a group highly alike the Denisovan individual from the Altai mountains, while the positive selection on this gene did not start until after a long period being a neutral variant. 

My work on the adaptive introgression history on EPAS1 also spurred another opportunity to reexamine Tibetan population history, which remains perplexing after decades of work. In a new paper, colleagues and I leveraged genetic and archaeological evidence under a joint framework, resulting in two new models of the peopling of Tibetan Plateau by both Denisovans and modern humans. These new models will enable systematic hypothesis testing in the future.
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Reference:
1. Zhang et al., The history and evolution of the Denisovan-EPAS1 haplotype in Tibetans. Proceedings of the National Academy of Sciences Jun 2021, 118 (22) e2020803118; DOI: 10.1073/pnas.2020803118
2. Zhang*, Zhang* et al., Denisovans and Homo sapiens on the Tibetan Plateau: dispersals and adaptations. Trends in Ecology and Evolution, Jan 2022. https://doi.org/10.1016/j.tree.2021.11.004 *These authors contributed equally
​3. Findley A, Zhang X, Boye C, Lin Y, Kalita C, Barreiro L, Lohmueller K, Pique-Regi R, Luca F. A signature of Neanderthal introgression on molecular mechanisms of environmental responses. PLOS Genetics 17(9): e1009493. https://doi.org/10.1371/journal.pgen.1009493
Statistical modeling and machine learning methods development in Population Genetics

Developing novel statistical methods is of critical value in the application of population genetics in anthropological research, as the quality and quantity of available data are rapidly changing.  Many studies since the 2010s have revealed candidate genes in worldwide populations being adaptively introgressed from archaic hominins, while recently studies also have suggested that recessive deleterious variants private to donor populations can create heterosis upon admixture. Without a beneficial mutation, this process can lead to signatures similar to adaptive introgression, and it was not clear whether heterosis can change the detection of current statistical methods for adaptive introgression.

In one of my recent articles, we find that signals of adaptive introgression remain robust in most previously identified candidate genes in modern humans, with the exception of two genes (HLA and HYAL2). And it turns out their susceptibility to high false positive rates are predominantly contributed by two factors: high exon density and low recombination rate, simultaneously. Overall, recessive deleterious variants affect the power of statistical methods detecting adaptive introgression and should be included in the null models, which is especially important for studying organisms with compact genomic structures.

Currently, I am working on the development of a novel machine learning method called MaLAdapt to detect genome-wide adaptive introgression. Leveraging information from a large number of population genetic summary statistics, this method is especially powerful at detecting adaptive introgression with mild beneficial effects, including selection on standing archaic variation, and is robust to confounding mechanisms such as non-introgressed selection sweeps, heterosis, and demographic mis-specifications. MaLAdapt reveals novel adaptive introgression candidate regions in all non-African populations that were previously undetected, and the preprint of this work showing full results will become available in late-2021.
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Reference:
​1. Zhang et al., The impact of recessive deleterious variants on signals of adaptive introgression in human populations, GENETICS 2020 vol. 215 no. 3 799-812
2. Zhang et al., MaLAdapt - A machine learning-based method for detecting adaptive introgression in modern humans. In prep
Complex traits and polygenic risk prediction in recently admixed human populations

In recent years, studies have made significant progress in understanding the polygenic basis and local adaptations of a wide range of complex traits and common genetic diseases. In one of my side projects during PhD, I applied the polygenic score and the Qst/Fst method to worldwide modern and ancient human populations for detecting selection signals on a number of anthropometric traits, as an attempt to extend our understanding on the polygenic adaptation on human height in modern Europeans. However, the reliability of the clear signal of positive selection on height, as well as the interpretation of GWAS-based analyses in general, were vehemently challenged by the failure of replicating the signals in newly released UK biobank data. It was revealed that the previous evidences were strongly confounded by population stratification. Furthermore, multiple studies also suggested poor transferability of polygenic scores across populations, especially in diverse, admixed populations.

Funded by an NIH K99/R00 award, over the next 3-5 years I will use a mixed approach to systematically study how recent admixture in human population influenced the genetic architecture of complex traits. Leveraging empirical genomic patterns and extensive simulations, I will develop non-additive models to improve polygenic risk predictions, with a special focus on underrepresented diverse human populations that experienced recent admixtures.

Reference:
1. Berg, Zhang, Coop. Polygenic Adaptation has Impacted the Evolution of Multiple Anthropometric Traits. biorXiv, 2018
2. Berg, Harpak, ... Zhang, ... Pritchard, Coop. Reduced Signal for Polygenic Adaptation of Height in UK Biobank. eLife, 2019.
Non-human Primates and Zoonotic Malaria

During the first two decades of the 21st century, two malaria parasites had been confirmed to be naturally transmissible between humans and macaques in Southeast Asia, in contrast to the previous belief that Plasmodium parasites are highly host-specific. It was suspected that the occurrence of zoonotic malaria was due to close proximity between humans and wild animals, however the exact prevalence of zoonotic parasites in macaque populations was unclear.

​In my PhD research, I led a pioneering project to characterize the epidemiology of zoonotic malaria in their natural hosts long-tailed macaques (Macaca fascicularis) in Southeast Asia. I reported infections in their Laotian population for the first time, which enabled public health organizations in related area to target prevention acts in human population under threat of infection. I further investigated the demographic histories of the long-tailed macaque populations, and showed strikingly distinct malaria susceptibilities among individuals driven by previously unknown admixture with rhesus macaques (Macaca mulatta).  Revealing the association between susceptibility and admixture had effectively prevented misuse of research animals with unclear ancestry in critical anti-malaria medical research. This project also had shed light on future identification of vital genes under selection in human and non-human primates, which may reveal candidate regions for precision medicine and personalized treatment.

Reference:
1. Zhang et al., Distribution and prevalence of malaria parasites among long-tailed macaques (Macaca fascicularis) in regional populations across Southeast Asia. Malaria Journal, 2016
2. Zhang et al., Ancestry, Plasmodium cynomolgi prevalence and rhesus macaque admixture in cynomolgus macaques (Macaca fascicularis) bred for export in Chinese breeding farms. Journal of Medical Primatology, 2017
3. Zhang et al., Genetic Characterization of a Captive Colony of Pigtailed Macaques (Macaca nemestrina). Journal of American Association for Laboratory Animal Science, 2017