Person:
Bradbury, P.

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Bradbury
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Bradbury, P.
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0000-0003-3825-8480

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2011 - 201932020 - 20241
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    Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel
    (Oxford University Press, 2024) LaPorte, M.F.; Suwarno, W.B.; Hannok, P.; Koide, A.; Bradbury, P.; Crossa, J.; Palacios-Rojas, N.; Diepenbrock, C.
    Publication
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    Novel methods to optimize genotypic imputation for low-coverage, next- generation sequence data in crops plants
    (CSSA, 2014) Swarts, K.; Huihui Li; Romero Navarro, J.A.; Dong An; Romay, M.C.; Hearne, S.; Acharya, C.B.; Glaubitz, J.C.; Mitchell, S.; Elshire, R.; Buckler, E.; Bradbury, P.
    Publication
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    High-resolution genetic mapping of maize pan-genome sequence anchors
    (Nature Research, 2015) Fei Lu; Romay, M.C.; Glaubitz, J.C.; Bradbury, P.; Elshire, R.; Wang, T.; Yu Li; Yongxiang Li; Semagn, K.; Xuecai Zhang; Hernandez, A.; Mikel, M.A.; Soifer, I.; Barad, O.; Buckler, E.
    In addition to single-nucleotide polymorphisms, structural variation is abundant in many plant genomes. The structural variation across a species can be represented by a ‘pan-genome’, which is essential to fully understand the genetic control of phenotypes. However, the pan-genome’s complexity hinders its accurate assembly via sequence alignment. Here we demonstrate an approach to facilitate pan-genome construction in maize. By performing 18 trillion association tests we map 26 million tags generated by reduced representation sequencing of 14,129 maize inbred lines. Using machine-learning models we select 4.4 million accurately mapped tags as sequence anchors, 1.1 million of which are presence/absence variations. Structural variations exhibit enriched association with phenotypic traits, indicating that it is a significant source of adaptive variation in maize. The ability to efficiently map ultrahigh-density pan-genome sequence anchors enables fine characterization of structural variation and will advance both genetic research and breeding in many crops.
    Publication
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    Joint QTL linkage mapping for multiple-cross mating design sharing one common parent
    (Public Library of Science, 2011) Huihui Li; Bradbury, P.; Ersoz, E.; Buckler, E.; Jiankang Wang
    Nested association mapping (NAM) is a novel genetic mating design that combines the advantages of linkage analysis and association mapping. This design provides opportunities to study the inheritance of complex traits, but also requires more advanced statistical methods. In this paper, we present the detailed algorithm of a QTL linkage mapping method suitable for genetic populations derived from NAM designs. This method is called joint inclusive composite interval mapping (JICIM). Simulations were designed on the detected QTL in a maize NAM population and an Arabidopsis NAM population so as to evaluate the efficiency of the NAM design and the JICIM method. Fifty-two QTL were identified in the maize population, explaining 89% of the phenotypic variance of days to silking, and nine QTL were identified in the Arabidopsis population, explaining 83% of the phenotypic variance of flowering time. Simulations indicated that the detection power of these identified QTL was consistently high, especially for large-effect QTL. For rare QTL having significant effects in only one family, the power of correct detection within the 5 cM support interval was around 80% for 1-day effect QTL in the maize population, and for 3-day effect QTL in the Arabidopsis population. For smaller-effect QTL, the power diminished, e.g., it was around 50% for maize QTL with an effect of 0.5 day. When QTL were linked at a distance of 5 cM, the likelihood of mapping them as two distinct QTL was about 70% in the maize population. When the linkage distance was 1 cM, they were more likely mapped as one single QTL at an intermediary position. Conclusions Because it takes advantage of the large genetic variation among parental lines and the large population size, NAM is a powerful multiple-cross design for complex trait dissection. JICIM is an efficient and specialty method for the joint QTL linkage mapping of genetic populations derived from the NAM design.
    Publication