Molecular genetic analysis of U.S. and Chinese soybean ancestral lines

Zenglu Li, Lijuan Qiu, Jeffery A. Thompson, Molly M. Welsh, Randall L. Nelson

Research output: Contribution to journalArticle

Abstract

Most of the U.S. soybean [Glycine max (L.) Merr.] ancestral lines were introduced from China, but nothing is known of the genetic relationships among the ancestors of modern U.S. and Chinese cultivars. The objectives of this research were to measure the variation among the major ancestors of U.S. and Chinese cultivars, to establish the genetic relationships among these U.S. and Chinese soybean ancestral lines, and to determine the relationship between geographical origin and genetic diversity. Genomic DNA from these lines was characterized by random amplified polymorphic DNA (RAPD) with 35 selected decamer primers. On the basis of the presence or absence of amplified DNA fragments, simple matching coefficients were used to calculate genetic similarities between pairs of lines. Cluster analyses generally separated the ancestral gene pools of the USA and China. Clusters reflected the geographical origin of the lines. Large differences exist between northern U.S. and Chinese ancestral lines and central and southern Chinese ancestral lines. The pattern of diversity found within the U.S. and Chinese ancestors can aid breeders in selecting parental lines to more efficiently exploit the diversity found in these two major gene pools.

Original languageEnglish (US)
Pages (from-to)1330-1336
Number of pages7
JournalCrop Science
Volume41
Issue number4
DOIs
StatePublished - Jan 1 2001

ASJC Scopus subject areas

  • Agronomy and Crop Science

Fingerprint Dive into the research topics of 'Molecular genetic analysis of U.S. and Chinese soybean ancestral lines'. Together they form a unique fingerprint.

  • Cite this

    Li, Z., Qiu, L., Thompson, J. A., Welsh, M. M., & Nelson, R. L. (2001). Molecular genetic analysis of U.S. and Chinese soybean ancestral lines. Crop Science, 41(4), 1330-1336. https://doi.org/10.2135/cropsci2001.4141330x