title: Evolutionary profiling reveals the heterogeneous origins of classes of human disease genes: implications for modeling disease genetics in animals.
abstract: BACKGROUND
  The recent expansion of whole-genome sequence data available from diverse animal lineages provides an opportunity to investigate the evolutionary origins of specific classes of human disease genes. Previous studies have observed that human disease genes are of particularly ancient origin. While this suggests that many animal species have the potential to serve as feasible models for research on genes responsible for human disease, it is unclear whether this pattern has meaningful implications and whether it prevails for every class of human disease.
  
  
  RESULTS
  We used a comparative genomics approach encompassing a broad phylogenetic range of animals with sequenced genomes to determine the evolutionary patterns exhibited by human genes associated with different classes of disease. Our results support previous claims that most human disease genes are of ancient origin but, more importantly, we also demonstrate that several specific disease classes have a significantly large proportion of genes that emerged relatively recently within the metazoans and/or vertebrates. An independent assessment of the synonymous to non-synonymous substitution rates of human disease genes found in mammals reveals that disease classes that arose more recently also display unexpected rates of purifying selection between their mammalian and human counterparts.
  
  
  CONCLUSIONS
  Our results reveal the heterogeneity underlying the evolutionary origins of (and selective pressures on) different classes of human disease genes. For example, some disease gene classes appear to be of uncommonly recent (i.e., vertebrate-specific) origin and, as a whole, have been evolving at a faster rate within mammals than the majority of disease classes having more ancient origins. The novel patterns that we have identified may provide new insight into cases where studies using traditional animal models were unable to produce results that translated to humans. Conversely, we note that the larger set of disease classes do have ancient origins, suggesting that many non-traditional animal models have the potential to be useful for studying many human disease genes. Taken together, these findings emphasize why model organism selection should be done on a disease-by-disease basis, with evolutionary profiles in mind.
authors.affiliation: Computational and Statistical Genomics Branch, Division of Intramural Research, National Human Genome Research, National Institutes of Health, Bethesda, MD, 20892, USA. evan.maxwell@nih.gov.|Bioinformatics Program, Boston University, Boston, MA, 02215, USA. evan.maxwell@nih.gov.
authors.forename: Evan K
authors.initials: EK
authors.lastname: Maxwell
authors.affiliation: Computational and Statistical Genomics Branch, Division of Intramural Research, National Human Genome Research, National Institutes of Health, Bethesda, MD, 20892, USA. christine.schnitzler@nih.gov.
authors.forename: Christine E
authors.initials: CE
authors.lastname: Schnitzler
authors.affiliation: Department of Ecology and Evolutionary Biology, Rice University, Houston, Texas, 77005, USA. phavlak@medicine.tamhsc.edu.|Biomedical Informatics Core, College of Medicine, Texas A&M Health Science Center, Houston, Texas, 77030, USA. phavlak@medicine.tamhsc.edu.
authors.forename: Paul
authors.initials: P
authors.lastname: Havlak
authors.affiliation: Department of Ecology and Evolutionary Biology, Rice University, Houston, Texas, 77005, USA. nputnam@gmail.com.
authors.forename: Nicholas H
authors.initials: NH
authors.lastname: Putnam
authors.affiliation: Computational and Statistical Genomics Branch, Division of Intramural Research, National Human Genome Research, National Institutes of Health, Bethesda, MD, 20892, USA. nguyenan@mail.nih.gov.
authors.forename: Anh-Dao
authors.initials: AD
authors.lastname: Nguyen
authors.affiliation: Computational and Statistical Genomics Branch, Division of Intramural Research, National Human Genome Research, National Institutes of Health, Bethesda, MD, 20892, USA. travism@mail.nih.gov.
authors.forename: R Travis
authors.initials: RT
authors.lastname: Moreland
authors.affiliation: Computational and Statistical Genomics Branch, Division of Intramural Research, National Human Genome Research, National Institutes of Health, Bethesda, MD, 20892, USA. andy@mail.nih.gov.
authors.forename: Andreas D
authors.initials: AD
authors.lastname: Baxevanis
mesh_terms: D000818:Animals; D005075:Biological Evolution; D004194:Disease / Q000235:genetics*; D004195:Disease Models, Animal; D006801:Humans; D008957:Models, Genetic; D013045:Species Specificity