Genetic architecture behind developmental and seasonal control of tree growth and wood properties in Norway spruce

Genetic control of tree growth and wood formation varies depending on the age of the tree and the time of the year. Single-locus, multi-locus, and multi-trait genome-wide association studies (GWAS) were conducted on 34 growth and wood property traits in 1,303 Norway spruce individuals using exome capture to cover similar to 130K single-nucleotide polymorphisms (SNPs). GWAS identified associations to the different wood traits in a total of 85 gene models, and several of these were validated in a progenitor population. A multilocus GWAS model identified more SNPs associated with the studied traits than single-locus or multivariate models. Changes in tree age and annual season influenced the genetic architecture of growth and wood properties in unique ways, manifested by non-overlapping SNP loci. In addition to completely novel candidate genes, SNPs were located in genes previously associated with wood formation, such as cellulose synthases and a NAC transcription factor, but that have not been earlier linked to seasonal or age-dependent regulation of wood properties. Interestingly, SNPs associated with the width of the year rings were identified in homologs of Arabidopsis thaliana BARELY ANY MERISTEM 1 and rice BIG GRAIN 1, which have been previously shown to control cell division and biomass production. The results provide toots for future Norway spruce breeding and functional studies

Complex genetic architecture underlying the plasticity of maize agronomic traits

Phenotypic plasticity is the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant to future agriculture under a changing climate. Here we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a diverse maize population planted at five sites with distinct environmental conditions. We found that latitude -related environmental factors were the main drivers of across-site variation in flowering time traits but not in plant architecture or yield traits. For the 23 traits, we detected 109 quantitative trait loci (QTLs), 29 for mean values, 66 for plasticity, and 14 for both parameters, and 80% of the QTLs interacted with latitude. The effects of several QTLs changed in magnitude or sign, driving variation in phenotypic plasticity. We experimentally validated one plastic gene, ZmTPS14.1, whose effect was likely mediated by the compen-sation effect of ZmSPL6 from a downstream pathway. By integrating genetic diversity, environmental vari-ation, and their interaction into a joint model, we could provide site-specific predictions with increased accuracy by as much as 9.9%, 2.2%, and 2.6% for days to tassel, plant height, and ear weight, respectively. This study revealed a complex genetic architecture involving multiple alleles, pleiotropy, and genotype-by -environment interaction that underlies variation in the mean and plasticity of maize complex traits. It provides novel insights into the dynamic genetic architecture of agronomic traits in response to changing environments, paving a practical way toward precision agriculture

Graph pangenome captures missing heritability and empowers tomato breeding

Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits(1,2). The solution to this problem is to identify all causal genetic variants and to measure their individual contributions(3,4). Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used forgenome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding

The Chinese pine genome and methylome unveil key features of conifer evolution

Conifers dominate the world's forest ecosystems and are the most widely planted tree species. Their giant and complex genomes present great challenges for assembling a complete reference genome for evolutionary and genomic studies. We present a 25.4-Gb chromosome-level assembly of Chinese pine (Pinus tabuliformis) and revealed that its genome size is mostly attributable to huge intergenic regions and long introns with high transposable element (TE) content. Large genes with long introns exhibited higher expressions levels. Despite a lack of recent whole-genome duplication, 91.2% of genes were duplicated through dispersed duplication, and expanded gene families are mainly related to stress responses, which may underpin conifers' adaptation, particularly in cold and/or arid conditions. The reproductive regulation network is distinct compared with angiosperms. Slow removal of TEs with high-level methylation may have contributed to genomic expansion. This study provides insights into conifer evolution and resources for advancing research on conifer adaptation and development

Dissecting the Genetic Regulation of Yeast Growth Plasticity in Response to Environmental Changes

Variable individual responses to environmental changes, such as phenotype plasticity, are heritable, with some genotypes being robust and others plastic. This variation for plasticity contributes to variance in complex traits as genotype-by-environment interactions (G x E). However, the genetic basis of this variability in responses to the same external stimuli is still largely unknown. In an earlier study of a large haploid segregant yeast population, genotype-by-genotype-by-environment interactions were found to make important contributions to the release of genetic variation in growth responses to alterations of the growth medium. Here, we explore the genetic basis for heritable variation of different measures of phenotype plasticity in the same dataset. We found that the central loci in the environmentally dependent epistatic networks were associated with overall measures of plasticity, while the specific measures of plasticity identified a more diverse set of loci. Based on this, a rapid one-dimensional genome-wide association (GWA) approach to overall plasticity is proposed as a strategy to efficiently identify key epistatic loci contributing to the phenotype plasticity. The study thus provided both analytical strategies and a deeper understanding of the complex genetic regulation of phenotype plasticity in yeast growth

Understanding the genetic basis of complex traits

Recent advances in genetics and genomics have provided numerous opportunities to study the genetic basis of complex traits. Nevertheless, dissecting the genetic basis of complex traits is still challenged by the complex genetic architecture, in which many genes are involved, and many have small contributions to phenotypic variation, interactions with other genes or environmental factors. The aim of this thesis is to evaluate the genetic basis of the complex traits by exploring available genomic resources and analytical approaches. Four studies included in this thesis explore: the genetic basis of global transcriptome variation in natural population (Study I); the genetic basis of 8-week body weight in artificial selected chicken lines (Study II); the genetic basis of flowering time variation for Arabidopsis thaliana sampled from a wide range of ecological conditions (Study III and Study IV). Findings from this thesis show that the genetic architecture of complex traits involves many polymorphisms with variable effect sizes. Some of those polymorphisms are multi-allelic and have interactions with each other and environmental factors at the same time. The presence of many alleles with minor contributions to phenotypic variation in natural and artificially selected population demonstrates that response to natural and artificial selection has been achieved by polygenic adaptation. Furthermore, population-specific large-effect loci with long-range LD to QTL in functionally related pathways indicate that emergence and fixation of loci with large effects and co-evolution of loci in the related pathway is contributing to the local adaptation of Arabidopsis thaliana. Overall, this thesis shows the complexity of complex trait genetics and provides a few insights into study designs and analysis approaches for understanding the genetic basis of complex traits

Understanding the genetic basis of complex traits

Recent advances in genetics and genomics have provided numerous opportunities to study the genetic basis of complex traits. Nevertheless, dissecting the genetic basis of complex traits is still challenged by the complex genetic architecture, in which many genes are involved, and many have small contributions to phenotypic variation, interactions with other genes or environmental factors. The aim of this thesis is to evaluate the genetic basis of the complex traits by exploring available genomic resources and analytical approaches. Four studies included in this thesis explore: the genetic basis of global transcriptome variation in natural population (Study I); the genetic basis of 8-week body weight in artificial selected chicken lines (Study II); the genetic basis of flowering time variation for Arabidopsis thaliana sampled from a wide range of ecological conditions (Study III and Study IV). Findings from this thesis show that the genetic architecture of complex traits involves many polymorphisms with variable effect sizes. Some of those polymorphisms are multi-allelic and have interactions with each other and environmental factors at the same time. The presence of many alleles with minor contributions to phenotypic variation in natural and artificially selected population demonstrates that response to natural and artificial selection has been achieved by polygenic adaptation. Furthermore, population-specific large-effect loci with long-range LD to QTL in functionally related pathways indicate that emergence and fixation of loci with large effects and co-evolution of loci in the related pathway is contributing to the local adaptation of Arabidopsis thaliana. Overall, this thesis shows the complexity of complex trait genetics and provides a few insights into study designs and analysis approaches for understanding the genetic basis of complex traits

Understanding the genetic basis of complex traits

Recent advances in genetics and genomics have provided numerous opportunities to study the genetic basis of complex traits. Nevertheless, dissecting the genetic basis of complex traits is still challenged by the complex genetic architecture, in which many genes are involved, and many have small contributions to phenotypic variation, interactions with other genes or environmental factors. The aim of this thesis is to evaluate the genetic basis of the complex traits by exploring available genomic resources and analytical approaches. Four studies included in this thesis explore: the genetic basis of global transcriptome variation in natural population (Study I); the genetic basis of 8-week body weight in artificial selected chicken lines (Study II); the genetic basis of flowering time variation for Arabidopsis thaliana sampled from a wide range of ecological conditions (Study III and Study IV). Findings from this thesis show that the genetic architecture of complex traits involves many polymorphisms with variable effect sizes. Some of those polymorphisms are multi-allelic and have interactions with each other and environmental factors at the same time. The presence of many alleles with minor contributions to phenotypic variation in natural and artificially selected population demonstrates that response to natural and artificial selection has been achieved by polygenic adaptation. Furthermore, population-specific large-effect loci with long-range LD to QTL in functionally related pathways indicate that emergence and fixation of loci with large effects and co-evolution of loci in the related pathway is contributing to the local adaptation of Arabidopsis thaliana. Overall, this thesis shows the complexity of complex trait genetics and provides a few insights into study designs and analysis approaches for understanding the genetic basis of complex traits

Genome annotation for N.tabacum

Genome annotation for N.tabacum</p

3.annotation.zip

Genome annotation for N.sylvestris</p