Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Protein–RNA interactions are central to the regulation of gene expression. Emerging technologies for pinpointing these interactions, both in large complexes and between individual proteins and RNA, are discussed. Methods for analysing these data are also considered.
The increased availability of reference genomes and the ability to obtain resequencing data in larger quantities are changing the capabilities of crop comparative genomics. Insights into the genetic basis of domestication and agriculturally important traits are emerging, and improved genomic tools have implications for crop breeders and evolutionary biologists.
There is considerable interest in exploring whether environmental factors, including chemicals and dietary components, can alter epigenomes. Environmentally induced changes in epigenetic marks are important in the development of several species, such as plants and insects; whether they influence human disease will be an area for future research.
Computer simulations can be valuable components of studies in many fields, including population genetics, evolutionary biology, genetic epidemiology and ecology. The recent increase in the available range of software packages is now making simulation an accessible option for researchers with limited bioinformatics experience.
Many organisms have evolved dosage compensation mechanisms to normalize gene expression levels when copy numbers of sex chromosomes and autosomes are unequal. This Review discusses how multiple epigenetic processes fine-tune the twofold upregulation of gene expression across the entire male X chromosome ofDrosophila melanogaster.
This Review presents arguments for and against each of two main models for the genetic basis of complex traits. It concludes that the infinitesimal model is essentially correct, but that rare, large-effect alleles also make an essential contribution to disease risk.
