Jean-Baptiste Cazier

Molecular genetics of the transcription factor GLIS3 identifies its dual function in beta cells and neurons.

The GLIS family zinc finger 3 isoform (GLIS3) is a risk gene for Type 1 and Type 2 diabetes, glaucoma and Alzheimers disease endophenotype. We identified GLIS3 binding sites in insulin secreting cells (INS1) (FDR q<0.05; enrichment range 1.40-9.11 fold) sharing the motif wrGTTCCCArTAGs, which were enriched in genes involved in neuronal function and autophagy and in risk genes for metabolic and neuro-behavioural diseases. We confirmed experimentally Glis3-mediated regulation of the expression of genes involved in autophagy and neuron function in INS1 and neuronal PC12 cells. Naturally-occurring coding polymorphisms in Glis3 in the Goto-Kakizaki rat model of type 2 diabetes were associated with increased insulin production in vitro and in vivo, suggestive alteration of autophagy in PC12 and INS1 and abnormal neurogenesis in hippocampus neurons. Our results support biological pleiotropy of GLIS3 in pathologies affecting β-cells and neurons and underline the existence of trans‑nosology pathways in diabetes and its co-morbidities.

Transcriptome Profiling in Rat Inbred Strains and Experimental Cross Reveals Discrepant Genetic Architecture of Genome-Wide Gene Expression

To test the impact of genetic heterogeneity on cis- and trans-mediated mechanisms of gene expression regulation, we profiled the transcriptome of adipose tissue in 20 inbred congenic strains derived from diabetic Goto–Kakizaki (GK) rats and Brown–Norway (BN) controls, which contain well-defined blocks (1–183 Mb) of genetic polymorphisms, and in 123 genetically heterogeneous rats of an (GK × BN)F2 offspring. Within each congenic we identified 73–1351 differentially expressed genes (DEGs), only 7.7% of which mapped within the congenic blocks, and which may be regulated in cis. The remainder localized outside the blocks, and therefore must be regulated in trans. Most trans-regulated genes exhibited approximately twofold expression changes, consistent with monoallelic expression. Altered biological pathways were replicated between congenic strains sharing blocks of genetic polymorphisms, but polymorphisms at different loci also had redundant effects on transcription of common distant genes and pathways. We mapped 2735 expression quantitative trait loci (eQTL) in the F2 cross, including 26% predominantly cis-regulated genes, which validated DEGs in congenic strains. A hotspot of >300 eQTL in a 10 cM region of chromosome 1 was enriched in DEGs in a congenic strain. However, many DEGs among GK, BN and congenic strains did not replicate as eQTL in F2 hybrids, demonstrating distinct mechanisms of gene expression when alleles segregate in an outbred population or are fixed homozygous across the entire genome or in short genomic regions. Our analysis provides conceptual advances in our understanding of the complex architecture of genome expression and pathway regulation, and suggests a prominent impact of epistasis and monoallelic expression on gene transcription.

Harnessing genomics to improve outcomes for women with cancer in India: key priorities for research

Cumulatively, breast, cervical, ovarian, and uterine cancer account for more than 70% of cancers in women in India. Distinct differences in the clinical presentation of women with cancer suggest underlying differences in cancer biology and genetics. The peak age of onset of breast and ovarian cancer appears to be a decade earlier in India (age 45-50 years) than in high-income countries (age >60 years). Understanding these differences through research to develop diagnosis, screening, prevention, and treatment frameworks that ar e specific to the Indian population are critical and essential to improving womens health in India. Since the sequencing of the human genome in 2001, applications of advanced technologies, such as massively parallel sequencing, have transformed the understanding of the genetic and environmental drivers of cancer. How can advanced technologies be harnessed to provide health-care solutions at a scale and to a budget suitable for a country of 1·2 billion people? What research programmes are necessary to answer questions specific to India, and to build capacity for innovative solutions using these technologies? In order to answer these questions, we convened a workshop with key stakeholders to address these issues. In this Series paper, we highlight challenges in tackling the growing cancer burden in India, discuss ongoing genomics research and developments in infrastructure, and suggest key priorities for future research in cancer in India.

Novel putative drugs and key initiating genes for neurodegenerative disease determined using network-based genetic integrative analysis: MORTEZAEI et al.

Understanding the genetic causes of neurodegenerative disease (ND) can be useful for their prevention and treatment. Among the genetic variations responsible for ND, heritable germline variants have been discovered in genome‐wide association studies (GWAS), and nonheritable somatic mutations have been discovered in sequencing projects. Distinguishing the important initiating genes in ND and comparing the importance of heritable and nonheritable genetic variants for treating ND are important challenges. In this study, we analysed GWAS results, somatic mutations and drug targets of ND from large databanks by performing directed network‐based analysis considering a randomised network hypothesis testing procedure. A disease‐associated biological network was created in the context of the functional interactome, and the nonrandom topological characteristics of directed‐edge classes were interpreted. Hierarchical network analysis indicated that drug targets tend to lie upstream of somatic mutations and germline variants. Furthermore, using directed path length information and biological explanations, we provide information on the most important genes in these created node classes and their associated drugs. Finally, we identified nine germline variants overlapping with drug targets for ND, seven somatic mutations close to drug targets from the hierarchical network analysis and six crucial genes in controlling other genes from the network analysis. Based on these findings, some drugs have been proposed for treating ND via drug repurposing. Our results provide new insights into the therapeutic actionability of GWAS results and somatic mutations for ND. The interesting properties of each node class and the existing relationships between them can broaden our knowledge of ND.