A Classification of 148 U.S. Maize Inbreds: II. Validation of Cluster Analysis Based on RFLPs

Abstract

To be useful to breeders, classification of genotypes based on cluster analysis must provide meaningful groupings of the genotypes clustered. We evaluated a classification of 148 U.S. maize [Zea mays L.] inbreds resulting from cluster analysis based on restriction fragment length polymorphisms (RFLPs) to determine if it represented the true associations among the fines. Testing was aimed at the products of the two steps in cluster analysis: the proximity matrix containing estimates of relationship computed from the data and the phenogram displaying groups in the form of a tree diagram. The proximity matrix and a matrix of pedigree relationships were compared by the Hubert F statistic. Dissimilarities indicated in the phenogram were correlated with those defined in the proximity matrix. The grouping displayed in the phenogram was compared to that exhibited in phenograms resulting from three additional cluster analyses generated by different methods for computing proximities. These groupings were then compared to the expected grouping based on pedigree information. The patterns present in the proximity matrix were substantiated by pedigree information. Based on agreement between the phenogram and the proximity matrix, the phenogram depicted estimates of genetic relationship accurately. Inbreds were grouped similarly in the four classifications and the level of correspondence of inbred group assignments to the expected grouping based on available pedigree information was similar across classifications, suggesting that a natural grouping of the fines exists and was generally reflected in each classification. Therefore, the classification was judged to reasonably represent the true associations among the 148 maize inbreds. In addition, the advantages of a method to compute proximities by a formula proposed by Nei and Li were noted.