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Srs2 and Sgs1–Top3 Suppress Crossovers during Double-Strand Break Repair in Yeast

Overview of attention for article published in Cell, November 2003
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Article details
Title
Srs2 and Sgs1–Top3 Suppress Crossovers during Double-Strand Break Repair in Yeast
Published in
Cell, November 2003
DOI 10.1016/s0092-8674(03)00886-9
Pubmed ID
Authors
Abstract

Very few gene conversions in mitotic cells are associated with crossovers, suggesting that these events are regulated. This may be important for the maintenance of genetic stability. We have analyzed the relationship between homologous recombination and crossing-over in haploid budding yeast and identified factors involved in the regulation of crossover outcomes. Gene conversions unaccompanied by a crossover appear 30 min before conversions accompanied by exchange, indicating that there are two different repair mechanisms in mitotic cells. Crossovers are rare (5%), but deleting the BLM/WRN homolog, SGS1, or the SRS2 helicase increases crossovers 2- to 3-fold. Overexpressing SRS2 nearly eliminates crossovers, whereas overexpression of RAD51 in srs2Delta cells almost completely eliminates the noncrossover recombination pathway. We suggest Sgs1 and its associated topoisomerase Top3 remove double Holliday junction intermediates from a crossover-producing repair pathway, thereby reducing crossovers. Srs2 promotes the noncrossover synthesis-dependent strand-annealing (SDSA) pathway, apparently by regulating Rad51 binding during strand exchange.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 263 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 8 3%
United Kingdom 4 2%
Russia 1 <1%
Japan 1 <1%
France 1 <1%
Spain 1 <1%
Switzerland 1 <1%
Canada 1 <1%
Unknown 245 93%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 83 32%
Researcher 62 24%
Student > Master 21 8%
Professor > Associate Professor 19 7%
Professor 12 5%
Other 30 11%
Unknown 36 14%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 119 45%
Biochemistry, Genetics and Molecular Biology 83 32%
Immunology and Microbiology 3 1%
Psychology 3 1%
Medicine and Dentistry 3 1%
Other 14 5%
Unknown 38 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 April 2019.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from Cell
#12,611
of 17,168 outputs
Outputs of similar age
#20,195
of 57,110 outputs
Outputs of similar age from Cell
#53
of 66 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 17,168 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 59.1. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 57,110 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.