| 1. |
- Bernhardsson, Carolina, et al.
(författare)
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An Ultra-Dense Haploid Genetic Map for Evaluating the Highly Fragmented Genome Assembly of Norway Spruce (Picea abies)
- 2019
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Ingår i: G3. - : Genetics Society of America. - 2160-1836. ; 9:5, s. 1623-1632
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Tidskriftsartikel (refereegranskat)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 (similar to 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 (), 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.
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| 2. |
- Bernhardsson, Carolina, et al.
(författare)
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Variant Calling Using Whole Genome Resequencing and Sequence Capture for Population and Evolutionary Genomic Inferences in Norway Spruce (Picea Abies)
- 2020
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Ingår i: The Spruce Genome. - Switzerland : Springer Nature. - 9783030210014 - 9783030210007 ; , s. 9-36
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Bokkapitel (refereegranskat)abstract
- Advances in next-generation sequencing methods and the development of new statistical and computational methods have opened up possibilities for large-scale, high-quality genotyping in most organisms. Conifer genomes are large and are known to contain a high fraction of repetitive elements and this complex genome structure has bearings for approaches that aim to use next-generation sequencing methods for genotyping. In this chapter, we provide a detailed description of a workflow for variant calling using next-generation sequencing in Norway spruce (Picea abies). The workflow starts with raw sequencing reads and proceeds through read mapping to variant calling and variant filtering. We illustrate the pipeline using data derived from both whole-genome resequencing data and reduced representation sequencing. We highlight possible problems and pitfalls of using next-generation sequencing data for genotyping stemming from the complex genome structure of conifers and how those issues can be mitigated or eliminated.
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| 3. |
- Wang, Xi, 1990-, et al.
(författare)
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Demography and Natural Selection Have Shaped Genetic Variation in the Widely Distributed Conifer Norway Spruce (Picea abies)
- 2020
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Ingår i: Genome Biology and Evolution. - : Oxford University Press. - 1759-6653. ; 12:2, s. 3803-3817
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Tidskriftsartikel (refereegranskat)abstract
- Under the neutral theory, species with larger effective population size are expected to harbor higher genetic diversity. However, across a wide variety of organisms, the range of genetic diversity is orders of magnitude more narrow than the range of effective population size. This observation has become known as Lewontin's paradox and although aspects of this phenomenon have been extensively studied, the underlying causes for the paradox remain unclear. Norway spruce (Picea abies) is a widely distributed conifer species across the northern hemisphere, and it consequently plays a major role in European forestry. Here, we use whole-genome resequencing data from 35 individuals to perform population genomic analyses in P. abies in an effort to understand what drives genome-wide patterns of variation in this species. Despite having a very wide geographic distribution and an corresponding enormous current population size, our analyses find that genetic diversity of P. abies is low across a number of populations (pi = 0.0049 in Central-Europe, pi = 0.0063 in Sweden-Norway, pi = 0.0063 in Finland). To assess the reasons for the low levels of genetic diversity, we infer the demographic history of the species and find that it is characterized by several reoccurring bottlenecks with concomitant decreases in effective population size can, at least partly, provide an explanation for low polymorphism we observe in P. abies. Further analyses suggest that recurrent natural selection, both purifying and positive selection, can also contribute to the loss of genetic diversity in Norway spruce by reducing genetic diversity at linked sites. Finally, the overall low mutation rates seen in conifers can also help explain the low genetic diversity maintained in Norway spruce.
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| 4. |
- Wang, Xi, 1990-, et al.
(författare)
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Quantifying adaptive evolution and the effects of natural selection across the Norway spruce genome
- 2023
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Ingår i: Molecular Ecology. - : John Wiley & Sons. - 0962-1083 .- 1365-294X. ; 32:19, s. 5288-5304
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Tidskriftsartikel (refereegranskat)abstract
- Detecting natural selection is one of the major goals of evolutionary genomics. Here, we sequence whole genomes of 34 Picea abies individuals and quantify the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we show that negative selection is very limited in coding regions, while positive selection is rare in coding regions but very strong in non-coding regions, suggesting the great importance of regulatory changes in evolution of Norway spruce. Additionally, we found a positive correlation between adaptive rate with recombination rate and a negative correlation between adaptive rate and gene density, suggesting a widespread influence from Hill-Robertson interference to efficiency of protein adaptation in P. abies. Finally, the distinct population statistics between genomic regions under either positive or balancing selection with that under neutral regions indicated impact from selection to genomic architecture of Norway spruce. Further gene ontology enrichment analysis for genes located in regions identified as undergoing either positive or long-term balancing selection also highlighted specific molecular functions and biological processes in that appear to be targets of selection in Norway spruce.
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| 5. |
- Wang, Xi, 1990-
(författare)
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The roles of demography and natural selection in shaping genome-wide variation of Norway spruce
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Understanding the relative contribution of genetic drift, natural selection, and mutation to genetic variation, and quantifying adaptive evolution and the effects of natural selection in species are enduring goals of evolutionary genetics. Norway spruce (Picea abies) is one of the most important conifer species that dominates from both an ecological and economical point of view in many boreal ecosystems. Recently published reference genome of Norway spruce makes it possible to perform population genomic studies to understand the basis of genetic variation and evolutionary effects of natural selection in P. abies by using next-generation sequencing (NGS) data. We create an ultra-dense genetic linkage map for Norway spruce using sequence capture data. The 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 (LGs). We also demonstrate, however, that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors. By performing population genetic analyses using the genomic regions anchored to LGs, our genetic linkage map is sufficiently dense to enable detailed evolutionary analyses across the P. abies genome.In order to understand how different evolutionary forces have shaped patterns of nucleotide diversity in Norway spruce, we perform population genomic analyses using whole-genome resequencing data. We find that genetic diversity is low across a number of populations in spite of a very wide geographic distribution of P. abies. The demographic history of several reoccurring bottlenecks with concomitant decreases in effective population size, the recurrent natural selection (both purifying and positive selection), and the low overall mutation rates seen in conifers, together make contribute to the loss of genome-wide nucleotide diversity in Norway spruce.We quantify adaptive evolution and the effects of natural selection across the Norway spruce whole genome. The results show that negative selection is very limited in coding regions, while positive selection is rare in coding regions but very strong in non-coding regions, suggesting the great importance of regulatory changes in evolutionary history of P. abies. We further find a positive correlation between adaptive rate with recombination rate and a negative correlation between adaptive rate and gene density, suggesting a widespread influence from Hill-Robertson interference to efficiency of protein adaptation in P. abies. The distinct population statistics between genomic regions under either positive or balancing selection with that under neutral regions indicate impact from natural selection to genomic architecture of Norway spruce.
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