Genomewide predictions as a substitute for a portion of phenotyping in maize. Issue 1 (26th February 2020)

• Record Type: Journal Article
• Authors: Ames, Nicholas C.; Bernardo, Rex
• Is Part Of: Crop science. Volume 60:Issue 1(2020)
• Page Start: 181
• Page End: 189
• Publication Date: 2020-02-26
• Subjects: Crop science -- Periodicals; Cultures -- Périodiques; Cultures de plein champ -- Périodiques; Crop science; Nutzpflanzen; Zeitschrift; Pflanzenbau; Periodicals; 633
• DOI: 10.1002/csc2.20082
• Languages: English
• ISSNs: 0011-183X

Abstract

Abstract: When genomewide predictions are available, maize ( Zea mays L.) breeders may consider foregoing first‐year phenotyping of testcrosses or, at the very least, reducing the number of locations used in phenotyping. Our objectives were to determine the equivalency between genomewide predictions and the number of locations used in phenotyping, and the extent to which genomewide predictions can reduce subsequent phenotyping in maize. For each of 21 test populations, we constructed half‐sib training populations from prior biparental populations evaluated in multiple environments. Marker data were available for 2911 single nucleotide polymorphism markers. We estimated the number of locations ( L Eq ) for which the response to phenotypic selection was equal to the response to genomewide selection. The median analytical estimate of L Eq (cross‐validation estimate of L Eq in parentheses) was 1.1 (1) for yield, 1.8 (2) for moisture, and 3.0 (3) for test weight. The estimates of L Eq varied widely among the test populations. We estimated the response to selection for an index that combined genomewide predictions and phenotypic data from different numbers of predictor locations ( L P ). The improvement in the response when L P increased from 0 (genomewide selection) to 1 was greater than the improvement in the response when L P increased from 1 to 2. This result suggested that phenotyping even at a single location captured signals that genomewide prediction did not capture. The analysis herein is helpful in designing breeding schemes that achieve a balance between the amount of genetic gain and the time and cost required to achieve such gain.