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Laboratory of Genetics
Overview: The mission of the Laboratory of Genetics (LG) is to understand the genetic and genomic determinants of aging.  The Laboratory investigates the genes and gene expression programs that govern the physiologic decline of aging (reduced strength, menopause, decreased ability to respond to nutrient imbalances, diminished immune function, etc) and the increased pathologies of the elderly (neurodegeneration, cardiovascular disease, diabetes, arthritis, obesity, cancer, etc).  The major areas of study underway in the LG are as follows:

The Human Genetics Section (HGS), headed by David Schlessinger, investigates cohorts of genes and mechanisms involved in the development of select non-renewable, and hence aging-prone, systems.  For example, to understand and ultimately try to compensate for loss of cells and tissues during aging, the Section studies the basis of skin appendage development and stability, and the genetic and genomic determination of the age of menopause.  The Section also performs complementary studies of genetic factors that determine aging-related traits, rates of aging, and diseases in a project studying the population on the island of Sardinia.
Within the Section, the Developmental Genomics and Aging Unit (DGAU) studies the transitions between immortal embryonic stem cells and mortal differentiating cells, a fundamental feature of the initiation of aging in metazoans.  The Unit investigates genes specifically activated and repressed during such transitions in mouse models where specific lineages are produced by the overexpression of individual master transcription factors.  These models provide a direct entrée to possibilities for regenerative medicine.

Another component of this Section, the Gene Recovery and Analysis Unit (GRAU), focuses on genes that show transcriptional and post-transcriptional regulation at a distance.  For example, the group investigates the regulation of regions of long repeated sequences, especially the rDNA chromosomal regions that determine the critical level of ribosomes.  The Unit also studies other examples of complex transcriptional control, including the regulation and function of a gene vital for placental homeostasis, PLAC1, which is specifically expressed in placenta and functions based on desmosome interactions.

The Genome Instability and Chromatin Remodeling Section (GICRS), led by Weidong Wang, focuses on three main projects: (1) protein complexes involved in genome instability diseases and the DNA damage response, (2) an RNA topoisomerase complex that works with the Fragile X syndrome protein (FMRP) to promote neuronal development, and (3) chromatin-remodeling complexes that regulate transcription, replication and repair.  The Section has a strong interest in nucleic acid remodeling complexes that play essential roles in DNA transcription, replication, and repair, as well as in mRNA translation.  Because many of these processes affect life span, and their defects can cause age-related disorders, genome instability syndromes, and cancer, the Section investigates if DNA and RNA remodeling complexes play crucial roles in maintaining normal aging and preventing premature aging disorders.  The team has used biochemical approaches to define targeted nucleic acid-remodeling complexes from mammalian cell extracts; using this method, they have successfully identified components of the Fanconi anemia core complex, Bloom syndrome complex, ATRX-syndrome complex, FANCM-MHF DNA remodeling complex, RNF8-FAAP20 ubiquitin cascade, several chromatin-remodeling complexes (BAF, PBAF, NURD), and Top3b-TDRD3 topoisomerase complexes.  Given that Top3b is the first RNA topoisomerase identified in eukaryotes, the group is working to elucidate how it functions with its partners, TDRD3 and FMRP (Fragile X syndrome proteins), to solve topological problems in RNA metabolism.  

The mission of the RNA Regulation Section (RRS), directed by Myriam Gorospe, is to investigate the post-transcriptional mechanisms that regulate gene expression in aging physiology and pathology.  The Section is particularly interested in mRNA processing, transport, turnover, and translation, as influenced by RNA-binding proteins (RBPs) and long and short noncoding RNAs (lncRNAs and microRNAs, respectively).  The general working hypothesis of the Section is that post-transcriptional gene regulatory processes directly impact upon the normal physiologic decline during aging as well as the aberrant gene expression programs in age-associated disease.  The group is testing this hypothesis in normal aging by analyzing the impact of RBPs and ncRNAs on age-associated inflammation, impaired muscle regeneration, cellular senescence, and declining responses to proliferative and metabolic stimuli.  The group is also testing the impact of RBPs and ncRNAs on the post-transcriptional gene regulatory processes that affect age-associated diseases such as diabetes, obesity, sarcopenia, neurodegeneration, and cancer.

The Image Informatics and Computational Biology Unit (IICBU), directed by Ilya Goldberg, is a core facility that develops pattern recognition software and data-driven analysis methods for biomedical imaging and clinical data.  The core uses these techniques to explore the progression of normal aging and age-related diseases.  Using the nematode as a model system to investigate the basic biology of aging, the core has shown that C. elegans ages by progressing through a series of discrete meta-stable states rather than a gradual continuous process.  The group is investigating the genetic and molecular mechanisms that define and potentially regulate the transitions between these states.  Machine-based pattern recognition can discern subtle differences between images, surpassing the sensitivity of even trained experts.  The core uses this property to detect subtle changes in the early stages of biological processes such as cell differentiation and in the onset of osteoarthritis.  The core also uses the sensitivity and reproducibility of machine-based pattern recognition to explore the value of these tools as diagnostic aids in medical imaging.

The Gene Expression and Genomics Unit (GEGU), under the direction of Kevin G. Becker, is a core facility that serves broadly the NIA-IRP by providing analysis of gene expression using microarrays, next-generation DNA sequencing, and RNA sequencing.  The service of the facility is provided in an interactive manner to meet the needs of each Principal Investigator and Laboratory.  The core facility carries out projects of different sizes using Illumina and Agilent gene expression arrays of multiple species including human, mouse, rat, fruit fly, and nematodes.  The service of the core often includes advising the user on experimental design, sample preparation, quality control of RNA or DNA samples, sample processing, and data extraction.  The core also assists the user in analyzing and mining the data, and in visualizing, interpreting, and archiving large-scale gene expression datasets in the context of a successful experiment.  This multi-leveled approach often requires extensive work with and training of fellows and students in other Laboratories in the details of complex gene expression studies.

The Human Statistical Genetics Unit (HSGU) is a core facility supervised by Jun Ding.  It focuses on developing statistical and computational tools for genetic studies and applying them to the analyses of aging-related traits and conditions.  Aging-related traits are complex and the risk of a disease is dictated by many genes and environmental factors.  The core combines genome-wide genotyping with powerful computational tools for correspondingly complex genetic analyses in whole populations or case-control studies.  The goal of the core is to add additional power with new algorithms to the analyses of variants involved in aging by allying genome-wide association studies (GWAS) with genome sequencing.  Concerning analysis tools, the core has three objectives: (1) to develop new programs to analyze mitochondrial (mt)DNA variation in next-generation sequencing studies, (2) to predict the gene inactivation status on the X chromosome, with application to GWAS including X-chromosome variants, and (3) to investigate the impact of genetic, phenotypic, and demographic information on the prediction of phenotypes using linear mixed models.  For experimental tests of the algorithms, the core capitalizes on the special advantages of the SardiNIA project to help in the assembly of mitochondrial sequence data, RNA-seq data, and multiple phenotypic data obtained from the founder Sardinia population.

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Updated: Friday April 08, 2016