Biomedical subjects

Stefan Palm

Publications and source records attributed to Stefan Palm.

5 recordsLinked to original sources

PubMed2025

Genetic Adaptation to Brackish Water and Spawning Season in European Cisco.

How species adapt to diverse environmental conditions is essential for understanding evolution and the maintenance of biodiversity. The European cisco (Coregonus albula) is a salmonid that occurs in both fresh and brackish water, and this together with the presence of sympatric spring- and autumn-spawning lacustrine populations provides an opportunity for studying the genetics of adaptation in relation to salinity and timing of reproduction. Here, we present a high-quality reference genome of the European cisco based on PacBio HiFi long read sequencing and HiC-directed scaffolding. We generated low-coverage whole-genome sequencing data from 336 individuals across 12 population samples to explore population structure and genetics of ecological adaptation. We found a major subdivision between two groups of populations most likely reflecting colonisation from different glacial refugia. Within the two major groups, we detected further genetic differentiation between spring- and autumn-spawning populations and between populations from freshwater lakes, rivers and brackish water (Bothnian Bay). A genome-wide screen for genetic differentiation among populations identified a set of outlier SNPs strongly correlated with spawning timing and salinity. Several of the genes associated with spawning time, including BHLHE40, TIMELESS and CPT1A, have previously been shown to have a role in circadian rhythm biology. As many as 17 loci were associated with genetic differentiation between populations reproducing in fresh and brackish water. This study provides insights into the genomic basis of ecological adaptation in European cisco with implications for sustainable fishery management.

Animals↗

PubMed2006

Power for detecting genetic divergence: differences between statistical methods and marker loci.

Information on statistical power is critical when planning investigations and evaluating empirical data, but actual power estimates are rarely presented in population genetic studies. We used computer simulations to assess and evaluate power when testing for genetic differentiation at multiple loci through combining test statistics or P values obtained by four different statistical approaches, viz. Pearson's chi-square, the log-likelihood ratio G-test, Fisher's exact test, and an F(ST)-based permutation test. Factors considered in the comparisons include the number of samples, their size, and the number and type of genetic marker loci. It is shown that power for detecting divergence may be substantial for frequently used sample sizes and sets of markers, also at quite low levels of differentiation. The choice of statistical method may be critical, though. For multi-allelic loci such as microsatellites, combining exact P values using Fisher's method is robust and generally provides a high resolving power. In contrast, for few-allele loci (e.g. allozymes and single nucleotide polymorphisms) and when making pairwise sample comparisons, this approach may yield a remarkably low power. In such situations chi-square typically represents a better alternative. The G-test without Williams's correction frequently tends to provide an unduly high proportion of false significances, and results from this test should be interpreted with great care. Our results are not confined to population genetic analyses but applicable to contingency testing in general.

Alleles↗

PubMed2005

Spatial genetic structure of northern pike (Esox lucius) in the Baltic Sea.

The genetic relationships among 337 northern pike (Esox lucius) collected from the coastal zone of the central Baltic region and the Finnish islands of Aland were analysed using five microsatellite loci. Spatial structure was delineated using both traditional F-statistics and individually based approaches including spatial autocorrelation analysis. Our results indicate that the observed genotypic distribution is incompatible with that of a single, panmictic population. Isolation by distance appears important for shaping the genetic structure of pike in this region resulting in a largely continuous genetic change over the study area. Spatial autocorrelation analysis (Moran's I) of individual pairwise genotypic data show significant positive genetic correlation among pike collected within geographical distances of less than c. 100-150 km (genetic patch size). We suggest that the genetic patch size may be used as a preliminary basis for identifying management units for pike in the Baltic Sea.

Animals↗

PubMed2005

Genetic population structure of fishes: implications for coastal zone management.

The pattern for distribution of genetic variation within and between populations is referred to as the genetic population structure of the species. To avoid depletion of genetic resources sustainable management should be based on knowledge of this structure. We discuss key aspects of genetic population structure in the context of identifying biological units for fisheries management, suggesting three basic types of structuring: distinct populations; continuous change; and no differentiation. The type of structure determines how units for genetically sustainable management are to be identified. We also review what is currently known regarding the genetic population structure of fishes exploited in the Swedish part of the Baltic Sea, and conclude that sufficient genetic information is lacking for most of the species. This is a serious problem, particularly considering that populations of several commercially exploited fishes are declining and some exhibit recruitment problems. For six species, Atlantic herring, Atlantic salmon, brown trout, European eel, turbot, and pike, sufficient genetic data are available to provide at least basic information on genetic structure and genetic units for biologically sustainable use. Current management practices do not sufficiently consider these data.

Animals↗

PubMed2002

[Risk Management: concepts and chances for public health].

BACKGROUND: Errors are a common problem in medicine and occur as a result of a complex process involving many contributing factors. Medical errors significantly reduce the safety margin for the patient and contribute additional costs in health care delivery. SYSTEM APPROACH: In most cases adverse events cannot be attributed to a single underlying cause. Therefore an effective risk management strategy must follow a system approach, which is based on counting and analysis of near misses. The development of defenses against the undesired effects of errors should be the main focus rather than asking the question "Who blundered?". Analysis of near misses (which in this context can be compared to indicators) offers several methodological advantages as compared to the analysis of errors and adverse events. Risk management is an integral element of quality management.

Computer Simulation↗