Comparative Transcriptomics Among Four White Pine Species

Baker, Ethan A G; Wegrzyn, Jill L.; Sezen, U. Uzay; Falk, Taylor; Maloney, Patricia E.; Vogler, Detlev R.; Delfino-Mix, Annette; Jensen, Camille; Mitton, Jeffry B.; Wright, Jessica W.; Knaus, Brian J.; Rai, Hardeep; Cronn, Richard; González-Ibeas, Daniel; Vasquez-Gross, Hans; Famula, Randi; Liu, Jun‐Jun; Kueppers, Lara M.; Neale, David B.

doi:10.1534/g3.118.200257

Cited by 31 publications

(24 citation statements)

References 67 publications

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“…The newly established transcriptome for P. cembra is similar to other published pine transcriptomes (e.g., Baker et al, ; Canales et al, ; Wachowiak, Trivedi, Perry, & Cavers, ) in terms of total size (69.4 Mbp), number of transcripts (40,468), number of genes (27,979), median transcript length (1,422 bp) and proportion of annotated transcripts (84%). Since our goal was to gain information for the largest possible gene space to design capture probes, we included multiple libraries consisting of various tissues of different life stages, individuals and treatments.…”

Section: Discussionsupporting

confidence: 76%

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga‐genome of Pinus cembra

Rellstab

Dauphin

Zoller

et al. 2019

Molecular Ecology Resources

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Despite decreasing sequencing costs, whole‐genome sequencing for population‐based genome scans for selection is still prohibitively expensive for organisms with large genomes. Moreover, the repetitive nature of large genomes often represents a challenge in bioinformatic and downstream analyses. Here, we use in‐depth transcriptome sequencing to design probes for exome capture in Swiss stone pine (Pinus cembra), a conifer with an estimated genome size of 29.3 Gbp and no reference genome available. We successfully applied around 55,000 self‐designed probes, targeting 25,000 contigs, to DNA pools of seven populations from the Swiss Alps and identified >160,000 SNPs in around 15,000 contigs. The probes performed equally well in pools of the closely related species Pinus sibirica; in both species, more than 70% of the targeted contigs were sequenced at a depth ≥40× (number of haplotypes in the pool). However, a thorough analysis of individually sequenced P. cembra samples indicated that a majority of the contigs (63%) represented multi‐copy genes. We therefore removed paralogous contigs based on heterozygote excess and deviation from allele balance. Without putatively paralogous contigs, allele frequencies of population pools represented accurate estimates of individually determined allele frequencies. We show that inferences of neutral and adaptive genetic variation may be biased when not accounting for such multi‐copy genes. Without individual genotype data, it would have been nearly impossible to recognize and deal with the problem of multi‐copy contigs. We advocate to put more emphasis on identifying paralogous loci, which will be facilitated by the establishment of additional high‐quality reference genomes.

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Section: Discussionsupporting

confidence: 76%

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga‐genome of Pinus cembra

Rellstab

Dauphin

Zoller

et al. 2019

Molecular Ecology Resources

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show abstract

“…The newly established transcriptome for P. cembra is similar to other published pine transcriptomes (e.g., Baker et al 2018; Wachowiak et al 2015) in terms of total size (69.4 Mbp), number of transcripts (40,468), number of genes (27,979), median transcript length (1422 bp), and proportion of annotated transcripts (84%). Since our goal was to gain information for the largest possible gene space to design capture probes, we included multiple libraries consisting of various tissues of different life stages, individuals, and treatments.…”

Section: Discussionsupporting

confidence: 66%

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga-genome ofPinus cembra

Rellstab

Dauphin

Zoller

et al. 2018

Preprint

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Despite decreasing sequencing costs, whole-genome sequencing for population-based genome scans for selection is still prohibitively expensive for organisms with large genomes. Moreover, the repetitive nature of large genomes often represents a challenge in bioinformatic and downstream analyses. Here we use in-depth transcriptome sequencing to design probes for exome capture in Swiss stone pine (Pinus cembra), a conifer with an estimated genome size of 29.3 Gbp and no reference genome available. We successfully applied around 55,000 self-designed probes, targeting 25,000 contigs, to DNA pools of seven populations from the Swiss Alps and identified > 140,000 SNPs in around 13,000 contigs. The probes performed equally well in pools of the closely related species Pinus sibirica; in both species, more than 70% of the targeted contigs were sequenced at a depth ≥ 40x, i.e. the number of haplotypes in the pool. However, a thorough analysis of individually sequenced P. cembra samples indicated that a majority of the contigs (63%) represented multi-copy genes. We therefore removed paralogous contigs based on heterozygote excess and deviation from allele balance. Without putatively paralogous contigs, allele frequencies of population pools represented accurate estimates of individually determined allele frequencies. Using population genetic and landscape genomic methods, we show that inferences of neutral and adaptive genetic variation may be biased when not accounting for such multi-copy genes. Future studies should therefore put more emphasis on identifying paralogous loci, which will be facilitated by the establishment of additional high-quality reference genomes.

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“…Although traditional breeding approaches currently are effective in screening five‐needle pine resistance to WPBR, the genetic dissection of complex phenotypic traits is still an obstacle. In recent years, genomic resources have been developed in a few five‐needle pines, including genome‐wide marker discovery (Liu et al ., ; Syring et al ., ), high‐density genetic maps (Jermstad et al ., ; Friedline et al ., ), transcriptome profiles (Lorenz et al ., ; Liu et al ., , ; Gonzalez‐Ibeas et al ., ; Baker et al ., ) and whole‐genome sequences (Stevens et al ., ). These genomics resources and tools open up a completely new avenue for the capture and use of genome‐wide variability in breeding programs; however, the genomic information available so far is still too limited to generate a sufficient foundation of knowledge required for the genetic improvement of five‐needle pines (Liu et al ., ).…”

Section: Discussionmentioning

confidence: 99%

Limber pine (Pinus flexilis James) genetic map constructed by exome‐seq provides insight into the evolution of disease resistance and a genomic resource for genomics‐based breeding

et al. 2019

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Limber pine (Pinus flexilis) is a keystone species of high-elevation forest ecosystems of western North America, but some parts of the geographic range have high infection and mortality from the non-native white pine blister rust caused by Cronartium ribicola. Genetic maps can provide essential knowledge for understanding genetic disease resistance as well as local adaptation to changing climates. Exome-seq was performed to construct high-density genetic maps in two seed families. Composite maps positioned 9612 unigenes across 12 linkage groups (LGs). Syntenic analysis of genome structure revealed that the majority of orthologs were positional orthologous genes (POGs) with localization on homologous LGs among conifer species. Gene ontology (GO) enrichment analysis showed relatively fewer constraints for POGs with putative roles in adaptation to environments and relatively more conservation for POGs with roles in basic cell function and maintenance. The mapped genes included 639 nucleotide-binding site leucine-rich repeat genes (NBS-LRRs), 290 receptor-like protein kinase genes (RLKs), and 1014 genes with potential roles in the defense response and induced systemic resistance to attack by pathogens. Orthologous loci for resistance to rust pathogens were identified and were co-positioned with multiple members of the R gene family, revealing the evolutionary pressure acting upon them. This high-density genetic map provides a genomic resource and practical tool for breeding and genetic conservation programs, with applications in genomewide association studies (GWASs), the characterization of functional genes underlying complex traits, and the sequencing and assembly of the full-length genomes of limber pine and related Pinus species.

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Comparative Transcriptomics Among Four White Pine Species

Cited by 31 publications

References 67 publications

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga‐genome of Pinus cembra

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga‐genome of Pinus cembra

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga-genome ofPinus cembra

Limber pine (Pinus flexilis James) genetic map constructed by exome‐seq provides insight into the evolution of disease resistance and a genomic resource for genomics‐based breeding

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