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  • Oxford University Press (OUP)  (2)
  • 2000-2004  (2)
  • 1
    In: Genetics, Oxford University Press (OUP), Vol. 155, No. 3 ( 2000-07-01), p. 1369-1378
    Abstract: For many species several similar QTL mapping populations have been produced and analyzed independently. Joint analysis of such data could be used to increase power to detect QTL and evaluate population differences. In this study, data were collated on almost 3000 pigs from seven different F2 crosses between Western commercial breeds and either the European wild boar or the Chinese Meishan breed. Genotypes were available for 31 markers on chromosome 4 (on average 8.3 markers per population). Data from three traits common to all populations (birth weight, mean backfat depth at slaughter or end of test, and growth rate from birth to slaughter or end of test) were analyzed for individual populations and jointly. A QTL influencing birth weight was detected in one individual population and in the combined data, with no significant interaction of the QTL effect with population. A QTL affecting backfat that had a significantly greater effect in wild boar than in Meishan crosses was detected. Some evidence for a QTL affecting growth rate was detected in all populations, with no significant differences between populations. This study is the largest F2 QTL analysis achieved in a livestock species and demonstrates the potential of joint analysis.
    Type of Medium: Online Resource
    ISSN: 1943-2631
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2000
    detail.hit.zdb_id: 1477228-0
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2002
    In:  Genetics Vol. 161, No. 2 ( 2002-06-01), p. 905-914
    In: Genetics, Oxford University Press (OUP), Vol. 161, No. 2 ( 2002-06-01), p. 905-914
    Abstract: Controlling the false discovery rate (FDR) has been proposed as an alternative to controlling the genomewise error rate (GWER) for detecting quantitative trait loci (QTL) in genome scans. The objective here was to implement FDR in the context of regression interval mapping for multiple traits. Data on five traits from an F2 swine breed cross were used. FDR was implemented using tests at every 1 cM (FDR1) and using tests with the highest test statistic for each marker interval (FDRm). For the latter, a method was developed to predict comparison-wise error rates. At low error rates, FDR1 behaved erratically; FDRm was more stable but gave similar significance thresholds and number of QTL detected. At the same error rate, methods to control FDR gave less stringent significance thresholds and more QTL detected than methods to control GWER. Although testing across traits had limited impact on FDR, single-trait testing was recommended because there is no theoretical reason to pool tests across traits for FDR. FDR based on FDRm was recommended for QTL detection in interval mapping because it provides significance tests that are meaningful, yet not overly stringent, such that a more complete picture of QTL is revealed.
    Type of Medium: Online Resource
    ISSN: 1943-2631
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2002
    detail.hit.zdb_id: 1477228-0
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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