PMID- 23386628
OWN - NLM
STAT- MEDLINE
DCOM- 20131031
LR  - 20211021
IS  - 1537-1719 (Electronic)
IS  - 0737-4038 (Print)
IS  - 0737-4038 (Linking)
VI  - 30
IP  - 5
DP  - 2013 May
TI  - Inference of natural selection from interspersed genomic elements based on 
      polymorphism and divergence.
PG  - 1159-71
LID - 10.1093/molbev/mst019 [doi]
AB  - Complete genome sequences contain valuable information about natural selection, 
      but this information is difficult to access for short, widely scattered noncoding 
      elements such as transcription factor binding sites or small noncoding RNAs. 
      Here, we introduce a new computational method, called Inference of Natural 
      Selection from Interspersed Genomically coHerent elemenTs (INSIGHT), for 
      measuring the influence of natural selection on such elements. INSIGHT uses a 
      generative probabilistic model to contrast patterns of polymorphism and 
      divergence in the elements of interest with those in flanking neutral sites, 
      pooling weak information from many short elements in a manner that accounts for 
      variation among loci in mutation rates and coalescent times. The method is able 
      to disentangle the contributions of weak negative, strong negative, and positive 
      selection based on their distinct effects on patterns of polymorphism and 
      divergence. It obtains information about divergence from multiple outgroup 
      genomes using a general statistical phylogenetic approach. The INSIGHT model is 
      efficiently fitted to genome-wide data using an approximate expectation 
      maximization algorithm. Using simulations, we show that the method can accurately 
      estimate the parameters of interest even in complex demographic scenarios, and 
      that it significantly improves on methods based on summary statistics describing 
      polymorphism and divergence. To demonstrate the usefulness of INSIGHT, we apply 
      it to several classes of human noncoding RNAs and to GATA2-binding sites in the 
      human genome.
FAU - Gronau, Ilan
AU  - Gronau I
AD  - Department of Biological Statistics and Computational Biology, Cornell 
      University, USA.
FAU - Arbiza, Leonardo
AU  - Arbiza L
FAU - Mohammed, Jaaved
AU  - Mohammed J
FAU - Siepel, Adam
AU  - Siepel A
LA  - eng
GR  - R01 GM102192/GM/NIGMS NIH HHS/United States
GR  - GM102192/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20130205
PL  - United States
TA  - Mol Biol Evol
JT  - Molecular biology and evolution
JID - 8501455
RN  - 9007-49-2 (DNA)
SB  - IM
MH  - DNA/genetics
MH  - *Evolution, Molecular
MH  - Genetic Variation/genetics
MH  - Genetics, Population
MH  - Humans
MH  - Phylogeny
MH  - Polymorphism, Genetic/*genetics
MH  - Regulatory Sequences, Nucleic Acid/genetics
MH  - Selection, Genetic/*genetics
PMC - PMC3697874
EDAT- 2013/02/07 06:00
MHDA- 2013/11/01 06:00
PMCR- 2014/05/01
CRDT- 2013/02/07 06:00
PHST- 2013/02/07 06:00 [entrez]
PHST- 2013/02/07 06:00 [pubmed]
PHST- 2013/11/01 06:00 [medline]
PHST- 2014/05/01 00:00 [pmc-release]
AID - mst019 [pii]
AID - 10.1093/molbev/mst019 [doi]
PST - ppublish
SO  - Mol Biol Evol. 2013 May;30(5):1159-71. doi: 10.1093/molbev/mst019. Epub 2013 Feb 
      5.