Table of contents
October 2006 Vol 7 No 10
From the editors
p737 | doi:10.1038/nrg1963
Research Highlights
Stem cells: A recipe for reprogramming
p738 | doi:10.1038/nrg1977
Transcriptomics: Every transcript counts
p739 | doi:10.1038/nrg1973
RNA interference: RNAi misses the target
p739 | doi:10.1038/nrg1974
Evolution: Jump-starting speciation
p740 | doi:10.1038/nrg1975
Reproductive Biology: From worm sperm proteins to human infertility
p740 | doi:10.1038/nrg1976
In brief
Development | Gene function | Plant biology | Cancer genetics
p741 | doi:10.1038/nrg1978
Chromatin: Eukaryotic genomes in complete control
p742 | doi:10.1038/nrg1966
Ageing: Longevity mutations inhibit tumours
p742 | doi:10.1038/nrg1972
Evolution: Putting flower colour on the landscape
p743 | doi:10.1038/nrg1971
Human genetics: INDELible markers
p744 | doi:10.1038/nrg1965
In brief
Epigenetics | Technology | Population genetics | Development
p744 | doi:10.1038/nrg1979
Focus on: Statistical Analysis
Reviews
Computer programs for population genetics data analysis: a survival guide
Laurent Excoffier and Gerald Heckel
p745 | doi:10.1038/nrg1904
The increase in population genetics data has led to a parallel need for sophisticated analysis programs and packages. This article is intended as a guide to many of these statistical programs, to promote their more informed use.
Modern computational approaches for analysing molecular genetic variation data
Paul Marjoram and Simon Tavaré
p759 | doi:10.1038/nrg1961
The vast increase in the amount of molecular genetic data that are being generated, and the scale of their complexity, demand ever more sophisticated statistical analysis methods — this article surveys and compares these approaches, and the growing reliance on computational methodologies.
Genetic relatedness analysis: modern data and new challenges
Bruce S. Weir, Amy D. Anderson and Amanda B. Hepler
p771 | doi:10.1038/nrg1960
The concept of relatedness is central to many fields, from human linkage analysis to forensics to animal and plant breeding. This review covers the statistical framework for studying relatedness, its applications and the challenges that the field faces.
A tutorial on statistical methods for population association studies
David J. Balding
p781 | doi:10.1038/nrg1916
Identifying polymorphisms that are overrepresented in disease cases versus controls would seem to be a straightforward process, but genetic association studies are notoriously riddled with complex analysis problems. This article outlines these statistical issues and provides some guidance to overcoming them.
Reviews
Spreading of silent chromatin: inaction at a distance
Paul B. Talbert and Steven Henikoff
p793 | doi:10.1038/nrg1920
Several models have been proposed to explain the spreading of heterochromatin, including looping, sliding and oozing. A review of studies from diverse model eukaryotes allows the authors to evaluate the existing models and leads them to propose a common, ancestral mechanism for spreading.
Perspectives
Innovation
TAR cloning: insights into gene function, long-range haplotypes and genome structure and evolution
Natalay Kouprina and Vladimir Larionov
p805 | doi:10.1038/nrg1943
Transformation-associated recombination (TAR) cloning uses in vivo recombination in yeast to isolate large chromosomal segments from complex genomes. Although the principles of TAR cloning date back to the 1990s, recent modifications have opened up promising new applications of this technology.
Opinion
Genes, environment and the value of prospective cohort studies
Teri A. Manolio, Joan E. Bailey-Wilson and Francis S. Collins
p812 | doi:10.1038/nrg1919
Gene–environment interactions are key contributors to complex disease, but are hard to dissect in commonly used case–control designs. This article argues that large-scale prospective cohort studies, several of which are planned or under way, provide an essential alternative strategy.
Correspondence
Correspondence: Mining meiosis with genomic models
R. M. Ranganath and G. Venkatachalaiah
| doi:10.1038/nrg1614-c1
Erratum: Evolutionary genetics: High-resolution mutation mapping reveals parallel experimental evolution in yeast
| doi:10.1038/nrg1980