English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Genotype networks are a method used in systems biology to study the"innovability" of a set of genotypes having the same phenotype. In the pastthey have been applied to determine the genetic heterogeneity, and stability tomutations, of systems such as metabolic networks and RNA folds. Recently, theyhave been the base for re-conciliating the two neutralist and selectionistschools on evolution.  Here, we adapted the concept of genotype networks to the study of populationgenetics data, applying them to the 1000 Genomes dataset. We used networkscomposed of short haplotypes of Single Nucleotide Variants (SNV), and definedphenotypes as the presence or absence of a haplotype in a human population. Weused coalescent simulations to determine if the number of samples in the 1000Genomes dataset is large enough to represent the genetic variation of realpopulations. The result is a scan of how properties related to the geneticheterogeneity and stability to mutations are distributed along the humangenome. We found that genes involved in acquired immunity, such as some HLA andMHC genes, tend to have the most heterogeneous and connected networks; and wehave also found that there is a small, but significant difference betweennetworks of coding regions and those of non-coding regions, suggesting thatcoding regions are both richer in genotype diversity, and more stable tomutations. Together, the work presented here may constitute a starting pointfor applying genotype networks to study genome variation, as larger datasets ofnext-generation data will become availa

Human Genome Variation and the concept of Genotype Networks