Evidence map›Paper›PMID 20624300›Full record

ArticleBMC genomics2010

Mining non-model genomic libraries for microsatellites: BAC versus EST libraries and the generation of allelic richness.

Christopher K Ellison, Kerry L Shaw

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Christopher K EllisonDepartment of Neurobiology and Behavior, Cornell University, Ithaca, NY 14850, USA. cke7@cornell.edu
Kerry L Shaw
Cornell University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSimple sequence repeats (SSRs) are tandemly repeated sequence motifs common in genomic nucleotide sequence that often harbor significant variation in repeat number. Frequently used as molecular markers, SSRs are increasingly identified via in silico approaches. Two common classes of genomic resources that can be mined are bacterial artificial chromosome (BAC) libraries and expressed sequence tag (EST) libraries.

results288 SSR loci were screened in the rapidly radiating Hawaiian swordtail cricket genus Laupala. SSRs were more densely distributed and contained longer repeat structures in BAC library-derived sequence than in EST library-derived sequence, although neither repeat density nor length was exceptionally elevated despite the relatively large genome size of Laupala. A non-random distribution favoring AT-rich SSRs was observed. Allelic diversity of SSRs was positively correlated with repeat length and was generally higher in AT-rich repeat motifs.

conclusionThe first large-scale survey of Orthopteran SSR allelic diversity is presented. Selection contributes more strongly to the size and density distributions of SSR loci derived from EST library sequence than from BAC library sequence, although all SSRs likely are subject to similar physical and structural constraints, such as slippage of DNA replication machinery, that may generate increased allelic diversity in AT-rich sequence motifs. Although in silico approaches work well for SSR locus identification in both EST and BAC libraries, BAC library sequence and AT-rich repeat motifs are generally superior SSR development resources for most applications.

Indexed as

Chromosomes, Artificial, BacterialExpressed Sequence TagsGenomic LibraryMicrosatellite RepeatsMinisatellite RepeatsAllelesAnimalsData MiningGryllidae

Identifiers

PMID20624300
PMCPMC2996956
OpenAlexW1974334580

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.