Background: Pinus sylvestris, P. mugo, P. uliginosa and P. uncinata are closely related but phenotypically and ecologically very distinct European pine species providing an excellent study system for analysis of the genetic basis of adaptive variation and speciation. For comparative genomic analysis of the species, transcriptome sequence was generated for 17 samples collected across the European distribution range using Illumina paired-end sequencing technology.
Results: De novo transcriptome assembly of a reference sample of P. sylvestris contained 40968 unigenes, of which fewer than 0.5% were identified as putative retrotransposon sequences. Based on gene annotation approaches, 19659 contigs were identified and assigned to unique genes covering a broad range of gene ontology categories. About 80% of the reads from each sample were successfully mapped to the reference transcriptome of P. sylvestris. Single nucleotide polymorphisms were identified in 22041-24096 of the unigenes providing a set of ~220-262 k SNPs identified for each species. Very similar levels of nucleotide polymorphism were observed across species (π=0.0044-0.0053) and highest pairwise nucleotide divergence (0.006) was found between P. mugo and P. sylvestris at a common set of unigenes.
Conclusions: The study provides whole transcriptome sequence and a large set of SNPs to advance population and association genetic studies in pines. Our study demonstrates that transcriptome sequencing can be a very useful approach for development of novel genomic resources in species with large and complex genomes.
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http://dx.doi.org/10.1186/s12864-015-1401-z | DOI Listing |
Oncogene
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Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, USA.
Lung cancer is one of the most frequently diagnosed cancers in the US. African-American (AA) men are more likely to develop lung cancer with higher incidence and mortality rates than European-American (EA) men. Herein, we report high-confidence alternative splicing (AS) events from high-throughput, high-depth total RNA sequencing of lung tumors and non-tumor adjacent tissues (NATs) in two independent cohorts of patients with adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Ecology and Silviculture, Faculty of Forestry, University of Agriculture in Krakow, 29 Listopada 46 Str, Krakow, 31-425, Poland.
Tree species through aboveground biomass and roots are a key factors influencing the quality and quantity of soil organic matter. Our study aimed to determine the stability of soil organic matter in Luvisols under the influence of five different tree species. The study areas were located 25 km north of Krakow, in southern Poland.
View Article and Find Full Text PDFInsects
December 2024
School of Biological and Environmental Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK.
The large pine weevil ( L.) is a major pest in European and Asian coniferous forests, particularly in managed plantations where clear-felling practices create ideal conditions for its population growth. Traditional management practices involving synthetic insecticides have limited efficacy in terms of reducing pest populations and pose environmental risks.
View Article and Find Full Text PDFStacks (Portland)
November 2024
Vincent Wildlife Trust, Ledbury HR8 1EP, Herefordshire, UK.
The successful onset of recovery of the European pine marten () in some parts of Britain through range expansion and, more recently translocation for reintroductions, has resulted in a strong interest in reintroduction projects throughout the country. However, the geographic scope and conservation goals of these initiatives are often local and lack consideration of how they fit within the wider context of national-scale pine marten conservation. Here, we aim to maximize conservation benefit strategically at a national level by developing a simple, transparent, and transferable framework based on landscape modelling methods and spatially explicit population viability analyses.
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