Temporal changes in the gene expression heterogeneity during brain development and aging

Cells in largely non-mitotic tissues such as the brain are prone to stochastic (epi-)genetic alterations that may cause increased variability between cells and individuals over time. Although increased interindividual heterogeneity in gene expression was previously reported, whether this process starts during development or if it is restricted to the aging period has not yet been studied. The regulatory dynamics and functional significance of putative aging-related heterogeneity are also unknown. Here we address these by a meta-analysis of 19 transcriptome datasets from three independent studies, covering diverse human brain regions. We observed a significant increase in inter-individual heterogeneity during aging (20 + years) compared to postnatal development (0 to 20 years). Increased heterogeneity during aging was consistent among different brain regions at the gene level and associated with lifespan regulation and neuronal functions. Overall, our results show that increased expression heterogeneity is a characteristic of aging human brain, and may influence aging-related changes in brain functions

Variation and Functional Impact of Neanderthal Ancestry in Western Asia

Neanderthals contributed genetic material to modern humans via multiple admixture events. Initial admixture events presumably occurred in Western Asia shortly after humans migrated out of Africa. Despite being a focal point of admixture, earlier studies indicate lower Neanderthal introgression rates in some Western Asian populations as compared with other Eurasian populations. To better understand the genome-wide and phenotypic impact of Neanderthal introgression in the region, we sequenced whole genomes of nine present-day Europeans. Africans, and the Western Asian Druze at high depth, and analyzed available whole genome data from various other populations, including 16 genomes from present-day Turkey. Our results confirmed previous observations that contemporary Western Asian populations, on an average, have lower levels of Neanderthal-introgressed DNA relative to other Eurasian populations. Modern Western Asians also show comparatively high variability in Neanderthal ancestry, which may be attributed to the complex demographic history of the region. We further replicated the previously described depletion of putatively functional sequences among Neanderthal-introgressed haplotypes. Still, we find dozens of common Neanderthalintrogressed haplotypes in the Turkish sample associated with human phenotypes, including anthropometric and metabolic traits, as well as the immune response. One of these haplotypes is unusually long and harbors variants that affect the expression of members of the CCR gene family and are associated with celiac disease. Overall, our results paint a complex first picture of the genomic impact of Neanderthal introgression in the Western Asian populations

Archaeogenomic analysis of the first steps of Neolithization in Anatolia and the Aegean

The Neolithic transition in west Eurasia occurred in two main steps: the gradual development of sedentism and plant cultivation in the Near East and the subsequent spread of Neolithic cultures into the Aegean and across Europe after 7000 cal BCE. Here, we use published ancient genomes to investigate gene flow events in west Eurasia during the Neolithic transition. We confirm that the Early Neolithic central Anatolians in the ninth millennium BCE were probably descendants of local hunter-gatherers, rather than immigrants from the Levant or Iran. We further study the emergence of post-7000 cal BCE north Aegean Neolithic communities. Although Aegean farmers have frequently been assumed to be colonists originating from either central Anatolia or from the Levant, our findings raise alternative possibilities: north Aegean Neolithic populations may have been the product of multiple westward migrations, including south Anatolian emigrants, or they may have been descendants of local Aegean Mesolithic groups who adopted farming. These scenarios are consistent with the diversity of material cultures among Aegean Neolithic communities and the inheritance of local forager know-how. The demographic and cultural dynamics behind the earliest spread of Neolithic culture in the Aegean could therefore be distinct from the subsequent Neolithization of mainland Europe.WoSScopu

Computational studies on ageing and age-related diseases

Age is the major risk factor for a variety of non-communicable diseases. As life expectancy increases, ageing poses significant challenges to the individual, society, and healthcare systems. Ageing is a complex process involving multiple interconnected cellular and organismal phenotypes. Thus, understanding the molecular mechanisms and finding potential interventions is challenging and requires systems-level approaches. In this PhD I have addressed three main questions about ageing, using high-throughput data and computational methods. My first study considers interindividual heterogeneity in gene expression during ageing. Previous studies had suggested that phenotype, epigenome and gene expression become more heterogeneous with age. However, the list of genes and pathways reported as heterogeneous in late age showed differences in the literature and did not resolve whether the increase in heterogeneity is a time-dependent process starting at birth or is restricted to the ageing period (i.e. after 20 years of age). Using different data pre-processing steps and heterogeneity measures on the same transcriptome dataset, we have shown that the inconsistency in the literature could reflect technical issues as well as biological variability. Next, applying a meta-analysis scheme that relies on consistent results across multiple datasets to increase reproducibility, we have shown that the increase in inter-individual heterogeneity starts after the age of 20. Moreover, the genes that become more heterogeneous during ageing have a higher number of transcriptional regulators (miRNAs and transcription factors) and are associated with known longevity pathways. My second study focuses on the link between ageing and age-related diseases. Many diseases show age-dependency, but the molecular nature of this relationship is not fully understood. Using UK Biobank data, I have characterised 116 common diseases based on their age-of-onset profiles and genetic associations. I first showed diseases following the same age-of-onset distribution are genetically more similar, and this similarity could not be explained by disease categories, co-occurrences, or causal relationships. Two groups of diseases showed age-dependent profiles, starting to become more prevalent after the ages of 20 and 40 respectively. They both showed an association with known ageing-related genes but had different functional and evolutionary profiles. I found support for the two evolutionary genetic theories of ageing, mutation accumulation, and antagonistic pleiotropy, using the variants linked to diseases with different age-of-onsets. I also identified some drugs that could be repurposed to target multiple conditions and potentially decrease the need for polypharmacy in the elderly. Finally, I followed a systems-level approach to identify drugs that can target ageing in the human brain. Using transcriptome datasets from multiple brain regions, I first identified the gene expression changes that can characterise ageing. Then, compared with the drug-perturbed gene expression profiles in the Connectivity Map, I identified 24 drugs that are significantly associated with the ageing signature. Some of these drugs may function as anti-ageing drugs by reversing the detrimental changes that occur during ageing, others by mimicking the cellular defence mechanisms. The drugs that we identified included a significant number of already identified pro-longevity drugs, indicating that the method can discover de novo drugs that ameliorate ageing