Abstract

BackgroundApple (Malus x domestica Borkh.) is one of the most important fruit tree crops of temperate areas, with great economic and cultural value. Apple cultivars can be maintained for centuries in plant collections through grafting, and some are thought to date as far back as Roman times. Molecular markers provide a means to reconstruct pedigrees and thus shed light on the recent history of migration and trade of biological materials. The objective of the present study was to identify relationships within a set of over 1400 mostly old apple cultivars using whole-genome SNP data (~ 253 K SNPs) in order to reconstruct pedigrees.ResultsUsing simple exclusion tests, based on counting the number of Mendelian errors, more than one thousand parent-offspring relations and 295 complete parent-offspring families were identified. Additionally, a grandparent couple was identified for the missing parental side of 26 parent-offspring pairings. Among the 407 parent-offspring relations without a second identified parent, 327 could be oriented because one of the individuals was an offspring in a complete family or by using historical data on parentage or date of recording. Parents of emblematic cultivars such as ‘Ribston Pippin’, ‘White Transparent’ and ‘Braeburn’ were identified. The overall pedigree combining all the identified relationships encompassed seven generations and revealed a major impact of two Renaissance cultivars of French and English origin, namely ‘Reinette Franche’ and ‘Margil’, and one North-Eastern Europe cultivar from the 1700s, ‘Alexander’. On the contrary, several older cultivars, from the Middle Ages or the Roman times, had no, or only single, identifiable offspring in the set of studied accessions. Frequent crosses between cultivars originating from different European regions were identified, especially from the nineteenth century onwards.ConclusionsThe availability of over 1400 apple genotypes, previously filtered for genetic uniqueness and providing a broad representation of European germplasm, has been instrumental for the success of this large pedigree reconstruction. It enlightens the history of empirical selection and recent breeding of apple cultivars in Europe and provides insights to speed-up future breeding and selection.

Highlights

  • Apple (Malus x domestica Borkh.) is one of the most important fruit tree crops of temperate areas, with great economic and cultural value

  • For the 3655 pairings with a PI_HAT value greater than 0.4, the distribution of Mendelian errors (ME) ranged from 0 to 9376 with a distinct gap around 600 (Fig. 1). This gap was a total of 1181 pairings deemed to be parent-offspring relations, of which 184 pairings were from two small segregating populations, each containing 46 progenies and their parents

  • We found documented dates for 22 individuals inferred as offspring in the potential grandparents-parent-offspring groups, and the dates were consistent with the proposed orientation

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Summary

Introduction

Apple (Malus x domestica Borkh.) is one of the most important fruit tree crops of temperate areas, with great economic and cultural value. Molecular markers provide a means to reconstruct pedigrees and shed light on the recent history of migration and trade of biological materials. Information about pedigrees is strategic for a wide range of uses, from animal and plant breeding to the study of human or wildlife genetics. Pedigree knowledge is essential for estimating heritabilities and genetic correlations of economically interesting traits [1]. Whilst markers alone can provide precise estimates of some genetic parameters [2], pedigree information makes it possible to account for background similarity due to shared parents [3]. Pedigree knowledge is useful to trace history of migrations or exchanges at very recent time scales, for humans and for the biological material they convey. Pedigree knowledge and accuracy is instrumental to assemble balanced sets representing important breeding parents with the purpose of detecting and validating QTLs using the Pedigree Based Analysis approach [6,7,8]

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