Revisiting protein heterozygosity in plants—nucleotide diversity in allozyme coding genes of conifer Pinus sylvestris

Abstract

Allozyme variation has been and continues to be a major source of information on the level of genetic variation among plant species. Deciphering the molecular basis of electrophoretic variation is essential for understanding the forces affecting the protein level variation. In this study, the relationship between allozyme heterozygosity and nucleotide diversity in plants is investigated among and within species. Allozyme and nucleotide diversity in 27 plant species was reviewed. At the multilocus level, the two methods are congruent: a clear correlation between the two measures of genetic diversity among plant species was observed, strengthening the view that effective population size is the major determinant of genome-wide diversity. Nucleotide diversity at six allozyme coding genes (6pgdB, aco, gdh, gotC, mdhA, and mdhB) in conifer Pinus sylvestris was investigated jointly with electrophoretic data. Single non-synonymous charge-changing mutations were found together with electrophoretic alleles that consequently were mutationally unique. Synonymous site nucleotide diversity (point estimate of θ W -0.009 per bp) and silent site divergence from Pinus pinaster at allozyme coding loci were at comparable levels with other loci in the species. Linkage disequilibrium was extensive compared to earlier estimates from P. sylvestris and other trees, spanning several kilobases. Allozyme coding genes had an excess of closely related haplotypes whose frequency has recently increased possibly as a result of partial selective sweeps or balancing selection, but complex demographic effects cannot be excluded.

The Evolutionary Genetics of the Genes Underlying Phenotypic Associations for Loblolly Pine (Pinus taeda, Pinaceae)

“…As shown repeatedly, linkage disequilibrium decays over physical distance quickly within coding regions (Neale and Savolainen 2004; but see Namroud et al 2010;Pyhäjärvi et al 2011), yet conifers appear to have extremely low recombination rates (Jaramillo-Correa et al 2010) and effective population sizes as estimated from estimates of Q are moderate (Savolainen and Pyhäjärvi 2007). The same pattern was observed here, as linkage disequilibrium decayed quite often within 500 bp to half its initial value.…”

The heterogeneous levels of linkage disequilibrium in white spruce genes and comparative analysis with other conifers

“…However, LD was generally higher in Douglas fir than in P. sylvestris. As argued by Pyhäjärvi et al (2011), pooling population samples with different frequencies might have contributed to inflate LD estimates in Douglas fir, although the population structure at nuclear and cpDNA markers is generally weak in P. menziesii var. menziesii (Eckert et al, 2009a;Wei et al, 2011).…”

“…However, the search for signatures of selection in these genes remained inconclusive (González-Martínez et al, 2006b). Only three studies examined LD in genes nearly completely sequenced in conifers; they all reported high levels of LD in some genes (Lepoittevin et al, 2008;Namroud et al, 2010;Pyhäjärvi et al, 2011). In Pinus pinaster, three genes coding for transcription factors from the HD-ZIP, LIM and MYB families exhibited high levels of LD (including the gene myb1 in complete LD over a distance of 1304 bp), as well as strong departures from SNM (Lepoittevin et al, 2008).…”

Extended Linkage Disequilibrium in Noncoding Regions in a Conifer, Cryptomeria japonica

“…INKAGE disequilibrium (LD) in the coding genes and their surrounding regions of conifers has been reported to extend to only several hundred to a few thousand base pairs [Brown et al (2004); Heuertz et al (2006); Pyhäjärvi et al (2007), but see Pyhäjärvi et al (2011) for LD extending to several kilobases]. This observation led to the conclusion that conifers are not suitable for finding associations with traits using a genomic scan (Neale and Savolainen 2004).…”

“…The slow Pyhäjärvi et al 2011). C. japonica is distantly related to these species (Chaw et al 2000), and the difference may be ascribed to differences in the species studied; however, a more plausible explanation would be the differences in the regions studied.…”