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- Backström, Niclas, et al.
(author)
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The recombination landscape of the zebra finch Taeniopygia guttata genome
- 2010
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In: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 20:4, s. 485-495
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Journal article (peer-reviewed)abstract
- Understanding the causes and consequences of variation in the rate of recombination is essential since this parameter is considered to affect levels of genetic variability, the efficacy of selection, and the design of association and linkage mapping studies. However, there is limited knowledge about the factors governing recombination rate variation. We genotyped 1920 single nucleotide polymorphisms in a multigeneration pedigree of more than 1000 zebra finches (Taeniopygia guttata) to develop a genetic linkage map, and then we used these map data together with the recently available draft genome sequence of the zebra finch to estimate recombination rates in 1 Mb intervals across the genome. The average zebra finch recombination rate (1.5 cM/Mb) is higher than in humans, but significantly lower than in chicken. The local rates of recombination in chicken and zebra finch were only weakly correlated, demonstrating evolutionary turnover of the recombination landscape in birds. The distribution of recombination events was heavily biased toward ends of chromosomes, with a stronger telomere effect than so far seen in any organism. In fact, the recombination rate was as low as 0.1 cM/Mb in intervals up to 100 Mb long in the middle of the larger chromosomes. We found a positive correlation between recombination rate and GC content, as well as GC-rich sequence motifs. Levels of linkage disequilibrium (LD) were significantly higher in regions of low recombination, showing that heterogeneity in recombination rates have left a footprint on the genomic landscape of LD in zebra finch populations.
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- Berlin Kolm, Sofia, et al.
(author)
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High-density linkage mapping and evolution of paralogs and orthologs in Salix and Populus
- 2010
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In: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 11:1, s. 129-
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Journal article (peer-reviewed)abstract
- BACKGROUND: Salix (willow) and Populus (poplar) are members of the Salicaceae family and they share many ecological as well as genetic and genomic characteristics. The interest of using willow for biomass production is growing, which has resulted in increased pressure on breeding of high yielding and resistant clones adapted to different environments. The main purpose of this work was to develop dense genetic linkage maps for mapping of traits related to yield and resistance in willow. We used the Populus trichocarpa genome to extract evenly spaced markers and mapped the orthologous loci in the willow genome. The marker positions in the two genomes were used to study genome evolution since the divergence of the two lineages some 45 mya. RESULTS: We constructed two linkage maps covering the 19 linkage groups in willow. The most detailed consensus map, S1, contains 495 markers with a total genetic distance of 2477 cM and an average distance of 5.0 cM between the markers. The S3 consensus map contains 221 markers and has a total genetic distance of 1793 cM and an average distance of 8.1 cM between the markers. We found high degree of synteny and gene order conservation between willow and poplar. There is however evidence for two major interchromosomal rearrangements involving poplar LG I and XVI and willow LG Ib, suggesting a fission or a fusion in one of the lineages, as well as five intrachromosomal inversions. The number of silent substitutions were three times lower (median: 0.12) between orthologs than between paralogs (median: 0.37 - 0.41). CONCLUSIONS: The relatively slow rates of genomic change between willow and poplar mean that the genomic resources in poplar will be most useful in genomic research in willow, such as identifying genes underlying QTLs of important traits. Our data suggest that the whole-genome duplication occurred long before the divergence of the two genera, events which have until now been regarded as contemporary. Estimated silent substitution rates were 1.28 x 10-9 and 1.68 x 10-9 per site and year, which are close to rates found in other perennials but much lower than rates in annuals.
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- Franck, Niclas, et al.
(author)
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Insulin-induced GLUT4 translocation to the plasma membrane is blunted in large compared with small primary fat cells isolated from the same individual
- 2007
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In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 50:8, s. 1716-1722
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Journal article (peer-reviewed)abstract
- Aims/hypothesis: Several studies have suggested that large fat cells are less responsive to insulin than small fat cells. However, in these studies, large fat cells from obese individuals were compared with smaller fat cells from leaner participants, in effect making it impossible to draw conclusions about whether there is a causal relationship between fat cell size and insulin sensitivity. We hypothesised that small fat cells might be more insulin-responsive than large adipocytes when obtained from the same individual. Materials and methods: We developed a method of sorting isolated primary human fat cells by using nylon filters of two different pore sizes. The cells were stained to visualise DNA, which allowed discrimination from artefacts such as lipid droplets. The sorted cells were left to recover overnight, since we had previously demonstrated that this is necessary for correct assessment of insulin response. Results: We found similar amounts of the insulin receptor (IR), IRS-1 and GLUT4 when we compared small and large adipocytes from the same volunteer by immunoblotting experiments using the same total cell volume from both cell populations. Activation of IR, IRS-1 and Akt1 (also known as protein kinase B) by insulin was similar in the two cell populations. However, immunofluorescence confocal microscopy of plasma membrane sheets did not reveal any increase in the amount of GLUT4 in the plasma membrane following insulin stimulation in the large fat cells, whereas we saw a twofold increase in the amount of GLUT4 in the small fat cells. Conclusions/interpretation: Our results support a causal relationship between the accumulation of large fat cells in obese individuals and reduced insulin responsiveness.
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- Gyllensten, Ulf B., et al.
(author)
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Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
- 2022
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In: Cancers. - : MDPI AG. - 2072-6694. ; 14:7
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Journal article (peer-reviewed)abstract
- Simple Summary Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4-7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort. Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
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