Biology subjects

Ferris, E.

Publications and source records attributed to Ferris, E..

7 recordsLinked to original sources

bioRxiv2024

Conserved Noncoding Cis-Elements Associated with Hibernation Modulate Metabolic and Behavioral Adaptations in Mice

Our study elucidates functional roles for conserved cis-elements associated with the evolution of mammalian hibernation. Genomic analyses found topologically associated domains (TADs) that disproportionately accumulated convergent genomic changes in hibernators, including the TAD for the Fat Mass & Obesity (Fto) locus. Some hibernation-linked cis-elements in this TAD form regulatory contacts with multiple neighboring genes. Knockout mice for these cis-elements exhibit Fto, Irx3, and Irx5 gene expression changes, impacting hundreds of genes downstream. Profiles of pre-torpor, torpor, and post-torpor phenotypes found distinct roles for each cis-element in metabolic control, while a high caloric diet uncovered different obesogenic effects. One cis-element promoting a lean phenotype influences foraging behaviors throughout life, affecting specific behavioral sequences. Thus, convergent evolution in hibernators pinpoints functional genetic mechanisms of mammalian metabolic control. One-sentence summaryDeletions of conserved cis-elements tied to hibernator evolution causes diverse metabolic traits in mice.

genomics↗

bioRxiv2024

Genomic Convergence in Hibernating Mammals Elucidates the Genetics of Metabolic Regulation in the Hypothalamus

Elucidating the genetic basis of mammalian metabolism could help define mechanisms central to health and disease. Here, we define conserved cis-regulatory elements (CREs) and programs for mammalian metabolic control. We delineate gene expression and chromatin responses in the mouse hypothalamus for 7 steps of the Fed-to-Fasted-to-Refed (FFR) response process. Comparative genomics of hibernating versus non-hibernating lineages then illuminates cis-elements showing convergent changes in hibernators. Hibernators accumulated loss-of-function effects for specific CREs regulating hypothalamic FFR responses. Multi-omics approaches pinpoint key CREs, genes, regulatory programs, and cell types in the divergence of hibernating and homeothermic lineages. The refeeding period after extended fasting is revealed as one critical period of chromatin remodeling with convergent genomic changes. This genetic framework is a step toward harnessing hibernator adaptations in medicine. One sentence summaryConvergent signals define cis-regulatory mechanisms behind food scarcity responses and hibernator-homeotherm divergence.

genomics↗

bioRxiv2020

Dopa decarboxylase is a genetic hub of parental control over offspring behavior

Dopa decarboxylase (DDC) regulates the synthesis of monoaminergic neurotransmitters and is linked to psychiatric and metabolic disorders. Ddc exhibits complex genomic imprinting effects that have not been functionally studied. Here, we investigate different noncanonical imprinting effects at the cellular level with a focus on Ddc. Using allele-specific reporter mice, we found Ddc exhibits dominant expression of the maternal allele in subpopulations of cells in 14 of 52 brain regions, and dominant paternal or maternal allele expression in adrenal cell subpopulations. Maternal versus paternal Ddc allele null mutations differentially affect offspring social, foraging and exploratory behaviors. Machine learning analyses of naturalistic foraging in Ddc-/+ and +/- offspring uncovered finite behavioral sequences controlled by the maternal versus paternal Ddc alleles. Additionally, parental Ddc genotype is revealed to affect behavior independent of offspring genotype. Thus, Ddc is a hub of maternal and paternal influence on behavior that mediates diverse imprinting and parental effects. HIGHLIGHTSO_LIDopa decarboxylase (Ddc) allelic expression resolved at the cellular level C_LIO_LICells differentially express maternal versus paternal Ddc alleles C_LIO_LIMaternal and paternal Ddc alleles control distinct behavioral sequences C_LIO_LIParental Ddc genotype affects offspring independent of mutation transmission C_LI eTOCAllelic reporter mice and machine learning analyses reveal dopa decarboxylase is affected by diverse imprinting and parental effects that shape finite behavioral sequences in sons and daughters.

neuroscience↗

bioRxiv2020

Elephant genomes reveal insights into differences in disease defense mechanisms between species

Disease susceptibility and resistance comprise important factors in conservation, particularly in elephants. To determine genetic mechanisms underlying disease resistance and other unique elephant traits, we estimated 862 and 1,017 potential regulatory elements in Asian and African elephants, respectively. These elements are significantly enriched in both species with differentially expressed genes involved in immunity pathways, including tumor-necrosis factor which plays a role in the response to elephant endotheliotropic herpesvirus (EEHV). Population genomics analyses indicate that amplified TP53 retrogenes are maintained by purifying selection and may contribute to cancer resistance in elephants, including less malignancies in African vs. Asian elephants. Positive selection scans across elephant genomes revealed genes that may control iconic elephant traits such as tusk development, memory, and somatic maintenance. Our study supports the hypothesis that interspecies variation in gene regulation contributes to differential inflammatory responses leading to increased infectious disease and cancer susceptibility in Asian versus African elephants. Genomics can inform functional immunological studies which may improve both conservation for elephants and human therapies.

evolutionary biology↗

bioRxiv2020

Rare protein coding variants implicate genes involved in risk of suicide death

Suicide death is a worldwide health crisis, claiming close to 800,000 lives per year. Recent evidence suggests that prediction and prevention challenges may be aided by discoveries of genetic risk factors. Here we focus on the role of rare (MAF <1%), putatively functional single nucleotide polymorphisms (SNPs) in suicide death using the large genetic resources available in the Utah Suicide Genetic Risk Study (USGRS). We conducted a single-variant association analysis of 30,377 rare putatively functional SNPs present on the PsychArray genotyping array in 2,672 USGRS suicides of non-Finnish European (NFE) ancestry and 51,583 publicly available NFE controls from gnomAD, with additional follow-up analyses using an independent control sample of 21,324 NFE controls from the Psychiatric Genomics Consortium. SNPs underwent rigorous quality control, and among SNPs meeting significance thresholds, we considered only those that were validated in sequence data. We identified five novel, high-impact, rare SNPs with significant associations with suicide death (SNAPC1, rs75418419; TNKS1BP1, rs143883793; ADGRF5, rs149197213; PER1, rs145053802; and ESS2, rs62223875). Both PER1 and SNAPC1 have other supporting gene-level evidence of suicide risk, and an association with bipolar disorder has been reported for PER1 and with schizophrenia for PER1, TNKS1BP1, and ESS2. Three genes (PER1, TNKS1BP1, and ADGRF5), with additional genes implicated by GWAS studies on suicidal behavior, showed significant enrichment in immune system, homeostatic and signal transduction processes. Pain, depression, and accidental trauma were the most prevalent phenotypes in electronic medical record data for the categories assessed. These findings suggest an important role for rare variants in suicide risk and provide new insights into the genetic architecture of suicide death. Furthermore, we demonstrate the added utility of careful assessment of genotyping arrays in rare variant discovery.

genetics↗

bioRxiv2018

Machine Learning Reveals Modules of Economic Behavior from Foraging Mice

Complex ethological behaviors could be constructed from modules that are discrete functional units of behavior with a genetic basis. Here, we test this idea for foraging, and develop a paradigm to dissect foraging patterns in mice. We uncover discrete behavioral modules linked to round trip excursions from the home. Machine learning reveals 59 modules across different genetic backgrounds and ages. Different modules develop at different ages and are linked to different aspects of economic behavior, including memory, reward, risk and effort responses. Crosses of distant mouse strains reveal that parental and genetic effects shape foraging differently, and parental effects grow stronger with age. Specific behavioral modules, genes and pathways are found to be sensitive to parental effects. One candidate gene, Magel2, is linked to Prader-Willi Syndrome and shaped the expression of discrete modules in an age-dependent manner. Our results reveal building blocks for normal and abnormal economic behavior patterns.\n\nHIGHLIGHTSO_LIIdentification of 59 economic behavior modules underlying foraging\nC_LIO_LIDiscrete modules are linked to memory, reward, risk and effort responses\nC_LIO_LIGenetic and parental effects shape foraging by changing module expression\nC_LIO_LIMagel2, a Prader-Willi Syndrome gene, affects specific modules at specific ages\nC_LI

neuroscience↗

bioRxiv2017

Identification of genome-wide significant shared genomic segments in large extended Utah families at high risk for completed suicide

Suicide is the 10th leading cause of death in the US. While environment has undeniable impact, evidence suggests genetic factors play a significant role in completed suicide. We linked a resource of >4,500 DNA samples from completed suicides obtained from the Utah Medical Examiner to genealogical records and medical records data available on over 8 million individuals. This linking has resulted in the identification of high-risk extended families (7-9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed Illumina PsychArray genotypes from suicide cases in 43 high-risk families, identifying 30 distinct shared genomic segments with genome-wide evidence (p=2.02E-07 to 1.30E-18) of segregation with completed suicide. The 207 genes implicated by the shared regions provide a focused set of genes for further study; 18 have been previously associated with suicide risk. While PsychArray variants do not represent exhaustive variation within the 207 genes, we investigated these for specific segregation within the high-risk families, and for association of variants with predicted functional impact in ~1300 additional Utah suicides unrelated to the discovery families. None of the limited PsychArray variants explained the high-risk family segregation; sequencing of these regions will be needed to discover segregating risk variants, which may be rarer or regulatory. However, additional association tests yielded four significant PsychArray variants (SP110, rs181058279; AGBL2, rs76215382; SUCLA2, rs121908538; APH1B, rs745918508), raising the likelihood that these genes confer risk of completed suicide.

genetics↗