Person:
Arief, V.N.

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Arief
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V.N.
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Arief, V.N.
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0000-0002-3980-1716

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2013 - 201922020 - 20221
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Now showing 1 - 3 of 3
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    Visualising the pattern of long-term genotype performance by leveraging a genomic prediction model
    (Wiley, 2022) Arief, V.N.; Delacy, I.H.; Payne, T.S.; Basford, K.E.
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    A genomic selection index applied to simulated and real data
    (Genetics Society of America, 2015) Cerón-Rojas, J.J.; Crossa, J.; Arief, V.N.; Basford, K.E.; Rutkoski, J.; Jarquin, D.; Alvarado Beltrán, G.; Beyene, Y.; Semagn, K.; Delacy, I.H.
    A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors have proposed a GSI; however, they have not used simulated or real data to validate the GSI theory and have not explained how to estimate the GSI selection response and the GSI expected genetic gain per selection cycle for the unobserved traits after the first selection cycle to obtain information about the genetic gains in each subsequent selection cycle. In this paper, we develop the theory of a GSI and apply it to two simulated and four real data sets with four traits. Also, we numerically compare its efficiency with that of the phenotypic selection index (PSI) by using the ratio of the GSI response over the PSI response, and the PSI and GSI expected genetic gain per selection cycle for observed and unobserved traits, respectively. In addition, we used the Technow inequality to compare GSI vs. PSI efficiency. Results from the simulated data were confirmed by the real data, indicating that GSI was more efficient than PSI per unit of time.
    Publication
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    Using molecular marker order to compare genetic structure in plant populations undergoing selection
    (UCLA Department of Statistics, 2013) Arief, V.N.; Delacy, I.H.; Wenzl, P.; Dreisigacker, S.; Crossa, J.; Dieters, M.; Basford, K.E.
    Many ecological studies compare the genetic structure of populations undergoing natu- ral or artificial selection across different environments. High-throughput molecular markers are now commonly used for these comparisons and provide information on the adapta- tion of the populations to their environments. The genetic structure reflects the history of selection, mutation, migration, and the reproductive breeding system of the populations in their environments. This can be investigated by comparing the ordering of markers obtained from the population with that provided by a recombination or physical map. In populations undergoing selection many genes (markers) have low or zero frequency and commonly used disequilibrium coefficients become unstable under these conditions. A method is presented for ordering bi-allelic markers for populations of self-fertilizing plant species which consist of mixtures of related homozygous genotypes. This provides stable pairwise marker similarity measures even when marker frequencies are low, identification of marker combinations that reflect phenomena that cause differentiation (such as selection and migration), and genetic information on the adaptation of the populations to the environments. The method is illustrated using data from a plant breeding program and inferences are made about accumulation of desirable genes (such as for disease resistance).
    Publication