A Picea abies Linkage Map Based on SNP Markers Identifies QTLs for Four Aspects of Resistance to Heterobasidion parviporum Infection

Abstract

A consensus linkage map of Picea abies, an economically important conifer, was constructed based on the segregation of 686 SNP markers in a F1 progeny population consisting of 247 individuals. The total length of 1889.2 cM covered 96.5% of the estimated genome length and comprised 12 large linkage groups, corresponding to the number of haploid P. abies chromosomes. The sizes of the groups (from 5.9 to 9.9% of the total map length) correlated well with previous estimates of chromosome sizes (from 5.8 to 10.8% of total genome size). Any locus in the genome has a 97% probability to be within 10 cM from a mapped marker, which makes the map suited for QTL mapping. Infecting the progeny trees with the root rot pathogen Heterobasidion parviporum allowed for mapping of four different resistance traits: lesion length at the inoculation site, fungal spread within the sapwood, exclusion of the pathogen from the host after initial infection, and ability to prevent the infection from establishing at all. These four traits were associated with two, four, four and three QTL regions respectively of which none overlapped between the traits. Each QTL explained between 4.6 and 10.1% of the respective traits phenotypic variation. Although the QTL regions contain many more genes than the ones represented by the SNP markers, at least four markers within the confidence intervals originated from genes with known function in conifer defence; a leucoanthocyanidine reductase, which has previously been shown to upregulate during H. parviporum infection, and three intermediates of the lignification process; a hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyltransferase, a 4-coumarate CoA ligase, and a R2R3-MYB transcription factor.

Different alleles of a gene encoding leucoanthocyanidin reductase (PaLAR3) influence resistance against the fungus Heterobasidion parviporum in Picea abies

“…Taken together, GQ03204_B13.1.1304 on LG 6 (Lind et al, 2014) appeared to be associated not only with reduced FGS in the QTL study, but also to the previously described PaLAR3 gene and (+) catechin, both associated with biotic stress responses in Picea spp. Thus, we selected locus GQ03204_B13.1.1304 and its associated gene PaLAR3 for analysis.…”

“…in conifers, is typically controlled by many loci, each with a relatively small effect (Quesada et al, 2010). The validated QTL, GQ03204_B13.1, is estimated to explain just under 5% of the phenotypic variation detected for FGS of H. parviporum in P. abies (Lind et al, 2014). Thus, a precise disease phenotyping is a critical step toward identifying and validating specific loci and alleles associated with quantitative disease resistance (Kayihan et al, 2005;Quesada et al, 2010), while careful experimental design and precision in the validation experiment is necessary to allow detection of effects of the QTL outside the original pedigree.…”

“…The genotype at locus GQ03204_B13.1 was determined by three SNPs (GQ03204_B13.1.64, GQ03204_B13.1.1304 and GQ03204_B13.1.1406) in 773 P. abies individuals, which were genotyped for a total of 1733 SNP sites, employing the Illumina GoldenGate assay used by Lind et al (2014). The 773 trees originated from 102 half-sib families collected from four populations in Sweden, Finland, and Russia.…”

“…In the first quantitative trait loci (QTL) study on P. abies resistance to H. parviporum, a member of the H. annosum s.l. species complex, Lind et al (2014) identified 13 QTLs that were associated with four traits related to host resistance. Four of the QTL regions were associated with the control of fungal growth in sapwood (FGS), which is a trait that reflects the trees capacity to protect its sapwood.…”

Genetics and Genomics of Tree Architecture

“…Similar examples of gene or miRNA atlas can be found in fruit trees, for their response to water stress (Bassett et al, 2014;Eldem et al, 2012) or during winter dormancy (Falavigna et al, 2014). These genomic resources combined with high-density genetic maps constructed for many forest tree species as in eucalyptus (Kullan et al, 2011;Neves, Mamani, Alfenas, Kirst, & Grattapaglia, 2011), maritime pine (Chancerelle et al, 2013), P. abies (Lind et al, 2014), Populus (Berlin, Lagercrantz, von Arnold, € Ost, & R€ onnberg-W€ astljung, 2010; Muchero et al, 2015), Cryptomeria japonica (Moriguchi et al, 2012), constitute a major basis to study the genetic determinants involved in the architectural development of trees. A recent study reported two high-resolution genetic maps constructed using a SNPs array genotyped on a large size pedigree , which has been useful to identify putative candidate genes underlying QTLs (Bartholomé, Mabiala, et al, 2015).…”