Genome-wide association study identified novel candidate loci affecting wood formation in Norway spruce

Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics underlying important wood quality traits in the species. We performed a functional genome-wide association study (GWAS) of 17 wood traits in Norway spruce using 178 101 single nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a Least Absolute Shrinkage and Selection Operator (LASSO-based) association mapping method using a functional multilocus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine a significant quantitative trait locus. The analysis provided 52 significant SNPs from 39 candidate genes, including genes previously implicated in wood formation and tree growth in spruce and other species. Our study represents a multilocus GWAS for complex wood traits in Norway spruce. The results advance our understanding of the genetics influencing wood traits and identifies candidate genes for future functional studies.Peer reviewe

Design and evaluation of a large sequence-capture probe set and associated SNPs for diploid and haploid samples of Norway spruce (<i>Picea abies</i>)

AbstractMassively parallel sequencing has revolutionized the field of genetics by providing comparatively high-resolution insights into whole genomes for large number of species so far. However, whole-genome resequencing of many conspecific individuals remains cost-prohibitive for most species. This is especially true for species with very large genomes with extensive genomic redundancy, such as the genomes of coniferous trees. The genome assembly for the conifer Norway spruce (Picea abies) was the first published draft genome assembly for any gymnosperm. Our goal was to develop a dense set of genome-wide SNP markers for Norway spruce to be used for assembly improvement and population studies. From 80,000 initial probe candidates, we developed two partially-overlapping sets of sequence capture probes: one developed against 56 haploid megagametophytes, to aid assembly improvement; and the other developed against 6 diploid needle samples, to aid population studies. We focused probe development within genes, as delineated via the annotation of ~67,000 gene models accompanying P. abies assembly version 1.0. The 31,277 probes developed against megagametophytes covered 19,268 gene models (mean 1.62 probes/model). The 40,018 probes developed against diploid tissue covered 26,219 gene modules (mean 1.53 probes/model). Analysis of read coverage and variant quality around probe sites showed that initial alignment of captured reads should be done against the whole genome sequence, rather than a subset of probe-containing scaffolds, to overcome occasional capture of sequences outside of designed regions. All three probe sets, anchored to the P. abies 1.0 genome assembly and annotation, are available for download.</jats:p

An Ultra-Dense Haploid Genetic Map for Evaluating the Highly Fragmented Genome Assembly of Norway Spruce (Picea abies)

Norway spruce (Picea abies (L.) Karst.) is a conifer species of substanital economic and ecological importance. In common with most conifers, the P. abies genome is very large (∼20 Gbp) and contains a high fraction of repetitive DNA. The current P. abies genome assembly (v1.0) covers approximately 60% of the total genome size but is highly fragmented, consisting of >10 million scaffolds. The genome annotation contains 66,632 gene models that are at least partially validated (www.congenie.org), however, the fragmented nature of the assembly means that there is currently little information available on how these genes are physically distributed over the 12 P. abies chromosomes. By creating an ultra-dense genetic linkage map, we anchored and ordered scaffolds into linkage groups, which complements the fine-scale information available in assembly contigs. Our ultra-dense haploid consensus genetic map consists of 21,056 markers derived from 14,336 scaffolds that contain 17,079 gene models (25.6% of the validated gene models) that we have anchored to the 12 linkage groups. We used data from three independent component maps, as well as comparisons with previously published Picea maps to evaluate the accuracy and marker ordering of the linkage groups. We demonstrate that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors as they contain genetic markers that map to different regions within or between linkage groups. We further evaluate the utility of the genetic map for the conifer research community by using an independent data set of unrelated individuals to assess genome-wide variation in genetic diversity using the genomic regions anchored to linkage groups. The results show that our map is sufficiently dense to enable detailed evolutionary analyses across the P. abies genome

An Ultra-Dense Haploid Genetic Map for Evaluating the Highly Fragmented Genome Assembly of Norway Spruce <i>(Picea abies</i>)

Abstract Norway spruce (Picea abies (L.) Karst.) is a conifer species of substanital economic and ecological importance. In common with most conifers, the P. abies genome is very large (∼20 Gbp) and contains a high fraction of repetitive DNA. The current P. abies genome assembly (v1.0) covers approximately 60% of the total genome size but is highly fragmented, consisting of &amp;gt;10 million scaffolds. The genome annotation contains 66,632 gene models that are at least partially validated (www.congenie.org), however, the fragmented nature of the assembly means that there is currently little information available on how these genes are physically distributed over the 12 P. abies chromosomes. By creating an ultra-dense genetic linkage map, we anchored and ordered scaffolds into linkage groups, which complements the fine-scale information available in assembly contigs. Our ultra-dense haploid consensus genetic map consists of 21,056 markers derived from 14,336 scaffolds that contain 17,079 gene models (25.6% of the validated gene models) that we have anchored to the 12 linkage groups. We used data from three independent component maps, as well as comparisons with previously published Picea maps to evaluate the accuracy and marker ordering of the linkage groups. We demonstrate that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors as they contain genetic markers that map to different regions within or between linkage groups. We further evaluate the utility of the genetic map for the conifer research community by using an independent data set of unrelated individuals to assess genome-wide variation in genetic diversity using the genomic regions anchored to linkage groups. The results show that our map is sufficiently dense to enable detailed evolutionary analyses across the P. abies genome.</jats:p

An ultra-dense haploid genetic map for evaluating the highly fragmented genome assembly of Norway spruce<i>(Picea abies)</i>

AbstractNorway spruce (Picea abies(L.) Karst.) is a conifer species of substanital economic and ecological importance. In common with most conifers, theP. abiesgenome is very large (∼20 Gbp) and contains a high fraction of repetitive DNA. The currentP. abiesgenome assembly (v1.0) covers approximately 60% of the total genome size but is highly fragmented, consisting of &gt;10 million scaffolds. The genome annotation contains 66,632 gene models that are at least partially validated (www.congenie.org), however, the fragmented nature of the assembly means that there is currently little information available on how these genes are physically distributed over the 12P. abieschromosomes. By creating an ultra-dense genetic linkage map, we anchored and ordered scaffolds into linkage groups, which complements the fine-scale information available in assembly contigs. Our ultra-dense haploid consensus genetic map consists of 21,056 markers derived from 14,336 scaffolds that contain 17,079 gene models (25.6% of the validated gene models) that we have anchored to the 12 linkage groups. We used data from three independent component maps, as well as comparisons with previously publishedPiceamaps to evaluate the accuracy and marker ordering of the linkage groups. We demonstrate that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors as they contain genetic markers that map to different regions within or between linkage groups. We further evaluate the utility of the genetic map for the conifer research community by using an independent data set of unrelated individuals to assess genome-wide variation in genetic diversity using the genomic regions anchored to linkage groups. The results show that our map is sufficiently dense to enable detailed evolutionary analyses across theP. abiesgenome.</jats:p

Supplemental Material for Bernhardsson et al., 2019

Supplementary information to "An ultra-dense haploid genetic map for evaluating the highly fragmented genome assembly of Norway spruce (Picea abies)

Genome-wide association study (GWAS) identified candidate loci affecting wood formation in Norway spruce

Abstract Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics underlying important wood quality traits in the species. We performed a functional genome‐wide association study (GWAS) of 17 wood traits in Norway spruce using 178 101 single nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a Least Absolute Shrinkage and Selection Operator (LASSO‐based) association mapping method using a functional multilocus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine a significant quantitative trait locus. The analysis provided 52 significant SNPs from 39 candidate genes, including genes previously implicated in wood formation and tree growth in spruce and other species. Our study represents a multilocus GWAS for complex wood traits in Norway spruce. The results advance our understanding of the genetics influencing wood traits and identifies candidate genes for future functional studies

The EKiTE network (epidemiology in kidney transplantation - a European validated database): an initiative epidemiological and translational European collaborative research

BACKGROUND: Kidney transplantation is considered to be the treatment of choice for people with end-stage renal disease (ESRD). However, due to the shortage of available organs and the increase in the ESRD prevalence in Europe, it is essential to improve transplantation outcomes by studying the related prognostic factors. Today, there is no European registry collecting data to perform such clinical epidemiology studies. MAIN BODY: Entitled EKiTE, for European cohort for Kidney Transplantation Epidemiology, this prospective and multicentric cohort includes patients from Spanish (Barcelona), Belgian (Leuven), Norwegian (Oslo) and French (Paris Necker, Lyon, Nantes, Nancy, Montpellier, Nice and Paris Saint Louis) transplantation centers and currently contains 13,394 adult recipients of kidney (only) transplantation from 2005 and updated annually. A large set of parameters collected from transplantation until graft failure or death with numbers of post-transplantation outcomes. The long-term follow-up and the collected data enable a wide range of possible survival and longitudinal analyses. CONCLUSION: EKiTE is a multicentric cohort aiming to better assess the natural history of the ESRD in European kidney transplant recipients and perform benchmarking of clinical practices. The data are available for clinical epidemiology studies and open for external investigators upon request to the scientific council. Short-term perspectives are to extend EKITE network to other European countries and collect additional parameters in respect of the common thesaurus.status: publishe