Molecular evolution of the hyaluronan synthase 2 gene in mammals: implications for adaptations to the subterranean niche and cancer resistance

The naked mole-rat (NMR) Heterocephalus glaber is a unique and fascinating mammal exhibiting many unusual adaptations to a subterranean lifestyle. The recent discovery of their resistance to cancer and exceptional longevity has opened up new and important avenues of research. Part of this resistance to cancer has been attributed to the fact that NMRs produce a modified form of hyaluronan—a key constituent of the extracellular matrix—that is thought to confer increased elasticity of the skin as an adaptation for living in narrow tunnels. This so-called high molecular mass hyaluronan (HMM-HA) stems from two apparently unique substitutions in the hyaluronan synthase 2 enzyme (HAS2). To test whether other subterranean mammals with similar selection pressures also show molecular adaptation in their HAS2 gene, we sequenced the HAS2 gene for 11 subterranean mammals and closely related species, and combined these with data from 57 other mammals. Comparative screening revealed that one of the two putatively important HAS2 substitutions in the NMR predicted to have a significant effect on hyaluronan synthase function was uniquely shared by all African mole-rats. Interestingly, we also identified multiple other amino acid substitutions in key domains of the HAS2 molecule, although the biological consequences of these for hyaluronan synthesis remain to be determined. Despite these results, we found evidence of strong purifying selection acting on the HAS2 gene across all mammals, and the NMR remains unique in its particular HAS2 sequence. Our results indicate that more work is needed to determine whether the apparent cancer resistance seen in NMR is shared by other members of the African mole-rat clade.National Research Foundation (South Africa

Neocortex expansion is linked to size variations in gene families with chemotaxis, cell–cell signalling and immune response functions in mammals

Increased brain size is thought to have played an important role in the evolution of mammals and is a highly variable trait across lineages. Variations in brain size are closely linked to corresponding variations in the size of the neocortex, a distinct mammalian evolutionary innovation. The genomic features that explain and/or accompany variations in the relative size of the neocortex remain unknown. By comparing the genomes of 28 mammalian species, we show that neocortical expansion relative to the rest of the brain is associated with variations in gene family size (GFS) of gene families that are significantly enriched in biological functions associated with chemotaxis, cell–cell signalling and immune response. Importantly, we find that previously reported GFS variations associated with increased brain size are largely accounted for by the stronger link between neocortex expansion and variations in the size of gene families. Moreover, genes within these families are more prominently expressed in the human neocortex during early compared with adult development. These results suggest that changes in GFS underlie morphological adaptations during brain evolution in mammalian lineage

A multidimensional systems biology analysis of cellular senescence in aging and disease.

BACKGROUND: Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of aging and has been linked to aging-related diseases. Many genes play a role in cellular senescence, yet a comprehensive understanding of its pathways is still lacking. RESULTS: We develop CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes driving cellular senescence, and perform various integrative analyses. Genes inducing cellular senescence tend to be overexpressed with age in human tissues and are significantly overrepresented in anti-longevity and tumor-suppressor genes, while genes inhibiting cellular senescence overlap with pro-longevity and oncogenes. Furthermore, cellular senescence genes are strongly conserved in mammals but not in invertebrates. We also build cellular senescence protein-protein interaction and co-expression networks. Clusters in the networks are enriched for cell cycle and immunological processes. Network topological parameters also reveal novel potential cellular senescence regulators. Using siRNAs, we observe that all 26 candidates tested induce at least one marker of senescence with 13 genes (C9orf40, CDC25A, CDCA4, CKAP2, GTF3C4, HAUS4, IMMT, MCM7, MTHFD2, MYBL2, NEK2, NIPA2, and TCEB3) decreasing cell number, activating p16/p21, and undergoing morphological changes that resemble cellular senescence. CONCLUSIONS: Overall, our work provides a benchmark resource for researchers to study cellular senescence, and our systems biology analyses reveal new insights and gene regulators of cellular senescence

Captive reptile mortality rates in the home and implications for the wildlife trade

The trade in wildlife and keeping of exotic pets is subject to varying levels of national and international regulation and is a topic often attracting controversy. Reptiles are popular exotic pets and comprise a substantial component of the live animal trade. High mortality of traded animals raises welfare concerns, and also has implications for conservation if collection from the wild is required to meet demand. Mortality of reptiles can occur at any stage of the trade chain from collector to consumer. However, there is limited information on mortality rates of reptiles across trade chains, particularly amongst final consumers in the home. We investigated mortality rates of reptiles amongst consumers using a specialised technique for asking sensitive questions, additive Randomised Response Technique (aRRT), as well as direct questioning (DQ). Overall, 3.6% of snakes, chelonians and lizards died within one year of acquisition. Boas and pythons had the lowest reported mortality rates of 1.9% and chameleons had the highest at 28.2%. More than 97% of snakes, 87% of lizards and 69% of chelonians acquired by respondents over five years were reported to be captive bred and results suggest that mortality rates may be lowest for captive bred individuals. Estimates of mortality from aRRT and DQ did not differ significantly which is in line with our findings that respondents did not find questions about reptile mortality to be sensitive. This research suggests that captive reptile mortality in the home is rather low, and identifies those taxa where further effort could be made to reduce mortality rate

GiSAO.db: a database for ageing research

<p>Abstract</p> <p>Background</p> <p>Age-related gene expression patterns of <it>Homo sapiens </it>as well as of model organisms such as <it>Mus musculus</it>, <it>Saccharomyces cerevisiae</it>, <it>Caenorhabditis elegans </it>and <it>Drosophila melanogaster </it>are a basis for understanding the genetic mechanisms of ageing. For an effective analysis and interpretation of expression profiles it is necessary to store and manage huge amounts of data in an organized way, so that these data can be accessed and processed easily.</p> <p>Description</p> <p>GiSAO.db (Genes involved in senescence, apoptosis and oxidative stress database) is a web-based database system for storing and retrieving ageing-related experimental data. Expression data of genes and miRNAs, annotation data like gene identifiers and GO terms, orthologs data and data of follow-up experiments are stored in the database. A user-friendly web application provides access to the stored data. KEGG pathways were incorporated and links to external databases augment the information in GiSAO.db. Search functions facilitate retrieval of data which can also be exported for further processing.</p> <p>Conclusions</p> <p>We have developed a centralized database that is very well suited for the management of data for ageing research. The database can be accessed at <url>https://gisao.genome.tugraz.at</url> and all the stored data can be viewed with a guest account.</p

A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

<p>Abstract</p> <p>Background</p> <p>The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes), for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties.</p> <p>Results</p> <p>The main patterns discovered by the classification methods are as follows: (a) the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b) the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO) annotations; (c) GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d) interaction with the XRCC5 (Ku80) protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e) DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related.</p> <p>Conclusions</p> <p>The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.</p

Myotis rufoniger genome sequence and analyses: M-rufoniger&apos;s genomic feature and the decreasing effective population size of Myotis bats

Myotis rufoniger is a vesper bat in the genus Myotis. Here we report the whole genome sequence and analyses of the M. rufoniger. We generated 124 Gb of short-read DNA sequences with an estimated genome size of 1.88 Gb at a sequencing depth of 66x fold. The sequences were aligned to M. brandtii bat reference genome at a mapping rate of 96.50% covering 95.71% coding sequence region at 10x coverage. The divergence time of Myotis bat family is estimated to be 11.5 million years, and the divergence time between M. rufoniger and its closest species M. davidii is estimated to be 10.4 million years. We found 1,239 function-altering M. rufoniger specific amino acid sequences from 929 genes compared to other Myotis bat and mammalian genomes. The functional enrichment test of the 929 genes detected amino acid changes in melanin associated DCT, SLC45A2, TYRP1, and OCA2 genes possibly responsible for the M. rufoniger&apos;s red fur color and a general coloration in Myotis. N6AMT1 gene, associated with arsenic resistance, showed a high degree of function alteration in M. rufoniger. We further confirmed that the M. rufoniger also has batspecific sequences within FSHB, GHR, IGF1R, TP53, MDM2, SLC45A2, RGS7BP, RHO, OPN1SW, and CNGB3 genes that have already been published to be related to bat&apos;s reproduction, lifespan, flight, low vision, and echolocation. Additionally, our demographic history analysis found that the effective population size of Myotis clade has been consistently decreasing since similar to 30k years ago. M. rufoniger&apos;s effective population size was the lowest in Myotis bats, confirming its relatively low genetic diversity

A Review of Supervised Machine Learning Applied to Ageing Research

Broadly speaking, supervised machine learning is the computational task of learning correlations between variables in annotated data (the training set), and using this information to create a predictive model capable of inferring annotations for new data, whose annotations are not known. Ageing is a complex process that affects nearly all animal species. This process can be studied at several levels of abstraction, in different organisms and with different objectives in mind. Not surprisingly, the diversity of the supervised machine learning algorithms applied to answer biological questions reflects the complexities of the underlying ageing processes being studied. Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to review these works, to discuss their main findings and weaknesses. In summary, the main findings of the reviewed papers are: the link between specific types of DNA repair and ageing, ageing-related proteins tend to be highly connected and seem to play a central role in molecular pathways; ageing/longevity is linked with autophagy and apoptosis, nutrient receptor genes, and copper and iron ion transport. Additionally, several biomarkers of ageing were found by machine learning. Despite some interesting machine learning results, we also identified a weakness of current works on this topic: only one of the reviewed papers has corroborated the computational results of machine learning algorithms through wet-lab experiments. In conclusion, supervised machine learning has contributed to advance our knowledge and has provided novel insights on ageing, yet future work should have a greater emphasis in validating the predictions