Biology subjects

Ge, X. J.

Publications and source records attributed to Ge, X. J..

7 recordsLinked to original sources

bioRxiv2026

The Human Pleiotropic Map of GWAS Associations and Therapeutic Implications

Genetic support for drug targets substantially increases clinical success rates, establishing genome-wide association studies (GWAS) as central to therapeutic hypothesis generation. However, the same genetic evidence that reveals causal gene-disease relationships simultaneously exposes organism-level safety liabilities--a dimension requiring principled, genome-wide quantification. Here we systematically analyse 100,526 GWAS to yield 789,453 credible sets and gene prioritisations for 15,641 genes, with discovery showing no saturation as GWAS expand and increase diversity. We find that 64% of GWAS-implicated genes are pleiotropic, associated with traits across multiple diseases and showing a non-linear relationship between the degree of pleiotropy and clinical success. Highly pleiotropic genes--concentrated in immune, inflammatory, and oncogenic signalling programmes--are enriched in safety-terminated clinical programmes, mouse lethal knockouts, and cancer driver genes, establishing gene-level pleiotropy as a potential measure of genetically-informed organism-level safety liability. Protein-altering variant (PAV) support amplifies therapeutic signal (OR = 6.0), yet PAV targets show higher average pleiotropy, introducing a competing safety liability. Combining PAV support with intermediate pleiotropy (2-5 therapeutic areas) resolves this tension, yielding OR = 10.3 and relative success = 4.8--a profile already satisfied by 52 approved therapies. As GWAS continue to expand in scale and resolution, these findings lay the groundwork for increasingly sophisticated target discovery strategies that yield safer and more effective therapeutic hypotheses.

genomics↗

bioRxiv2024

2500 Years of Human Betaherpesvirus 6A and 6B Evolution Revealed by Ancient DNA

Human betaherpesviruses 6A and 6B are double-stranded DNA viruses, specialised in infecting humans and are best known as the main causative pathogens of the common childhood infection "sixth disease". Despite only being discovered in the 1980s, these viruses are speculated to have a much longer and more complex history within the human population than available modern data make clear. The viruses are carried by large fractions of the human population and can integrate into the human genome, leading to a wide range of clinical manifestations of varied severity. Here, we present the first nine full and two partial ancient genomes of HHV-6A and 6B, dating as far back as the Italian Iron Age (ca. 1100-600 BCE). We demonstrate that large fractions of the current HHV-6 diversity were already well established in the human population by the 14th century CE. Our data suggests that HHV-6B integrated into the human genome at the latest before the 1st-6th century CE, with two integrated clades being populated by ancient DNA genomes in our phylogeny, which further supports that they originated from likely much older ancient founder events. Additionally, we show that all known inherited chromosomally integrated (ici-)HHV-6A clades were already represented in European historical populations, confirming that ici-HHV-6A no longer integrates into the human germline within populations of European ancestry and likely endogenized in early human history. Finally, our results demonstrate the unique suitability of archaeological remains and ancient DNA for the study of the evolution of integrated viruses in human populations.

evolutionary biology↗

bioRxiv2023

ClipperQTL: ultrafast and powerful eGene identification method

A central task in expression quantitative trait locus (eQTL) analysis is to identify cis-eGenes (henceforth "eGenes"), i.e., genes whose expression levels are regulated by at least one local genetic variant. Among the existing eGene identification methods, FastQTL is considered the gold standard but is computationally expensive as it requires thousands of permutations for each gene. Alternative methods such as eigenMT and TreeQTL have lower power than FastQTL. In this work, we propose ClipperQTL, which reduces the number of permutations needed from thousands to 20 for data sets with large sample sizes (> 450) by using the contrastive strategy developed in Clipper; for data sets with smaller sample sizes, it uses the same permutation-based approach as FastQTL. We show that ClipperQTL performs as well as FastQTL and runs about 500 times faster if the contrastive strategy is used and 50 times faster if the conventional permutation-based approach is used. The R package ClipperQTL is available at https://github.com/heatherjzhou/ClipperQTL.

genetics↗

bioRxiv2023

Medieval social landscape through the genetic history of Cambridgeshire before and after the Black Death

The extent of the devastation of the Black Death pandemic (1346-53) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at local scale in the context of the social stratification of medieval communities. Here we study 275 newly reported ancient genomes from later medieval and post-medieval Cambridgeshire, from individuals buried before, during, and after the Black Death. The majority of individuals examined had local genetic ancestries. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. Accounting for the genetic component for height accentuates the disparities between social groups in stature estimated from long bones, as a proxy for health and the quality of life. While we detect long-term shifts in local genetic ancestry in Cambridgeshire that either pre- or postdate the Black Death, we find no evidence of major changes in genetic ancestry nor, in contrast to recent claims, higher differentiation of immune loci between cohorts living before and after the Black Death.

genetics↗

bioRxiv2022

Wilcoxon rank-sum test still outperforms dearseq after accounting for the normalization impact in semi-synthetic RNA-seq data simulation

In this response to the correspondence by Hejblum et al. [1], we clarify the reasons why we ran the Wilcoxon rank-sum test on the semi-synthetic RNA-seq samples without normalization, and why we could only run dearseq with its built-in normalization, in our published study [2]. We also argue that no normalization should be performed on the semi-synthetic samples. Hence, for a fairer method comparison and using the updated dearseq package by Hejblum et al., we re-run the six differential expression methods (DESeq2, edgeR, limma-voom, dearseq, NOISeq, and the Wilcoxon rank-sum test) without normalizing the semi-synthetic samples, i.e., under the "No normalization" scheme in [1]. Our updated results show that the Wilcoxon rank-sum test is still the best method in terms of false discovery rate (FDR) control and power performance under all settings investigated.

bioinformatics↗

bioRxiv2020

Phenotypic plasticity, population structure and adaptation in a young weed species with a worldwide distribution

The colonization success of a species depends on phenotypic plasticity, adaptive potential and population structure. Assessing their relative contributions during a colonization process is challenging, and a large-scale experiment had yet to be done. In this study, we attempted to tease apart their effects on the fitness of one of the most common plant on Earth, the shepherds purse (Capsella bursa-pastoris), a self-fertilizing and allopolyploid weed, with a worldwide distribution. The overarching goal is to eventually understand how the shepherds purse extensive distribution range was established so rapidly. To do so, we carried out three common gardens, located in Europe, Asia and North America, and measured several life-history traits on field-collected accessions belonging to three distinct genetic clusters (Middle East, Europe, and Asia). Our experiment showed that (i) the success of C. bursa-pastoris is mainly due to its high degree of phenotypic plasticity; and (ii), genetic cluster effect reflected a classic pattern observed in core vs marginal populations, with the Middle Eastern cluster (putative core population) outperforming the European and Asian clusters. This study therefore revealed, in a model species, different relative contributions of plasticity and adaptation to fitness, depending on the population and the time since colonization occurred.

evolutionary biology↗

bioRxiv2018

Local adaptation and maladaptation during the worldwide range expansion of a self-fertilizing plant

Species having experienced rapid range expansion represent unique opportunities to evaluate the dynamics of adaptation during colonization of new environments. We investigated the consequences of range expansion on local adaptation of a successful worldwide colonizer, the shepherds purse Capsella bursa-pastoris. This species is an annual weed that originated recently in Eurasia and has now broadly colonized both temperate and subtropical areas. We assessed the performance, genetic diversity, and phenology of field-collected accessions belonging to three distinct genetic clusters of decreasing age (Middle East, Europe and Asia) in three common gardens in Europe, Asia and North America. To understand the genetic basis of local adaptation in this species, we also tested for correlation between SNP allele frequencies and environmental factors in Europe and Asia. Overall, we showed that patterns of local adaptation depended on population history: some older populations were weakly adapted to local conditions while those closer to the front of the colonization wave, far from the origin of the species, were maladapted whatever the common gardens. Altogether, our results have important consequences for the understanding of the evolution and adaptation of self-fertilizing plant during range expansion.

evolutionary biology↗