Factors related to the voluntary interruption of pregnancy in Spain

Introduction: The voluntary interruption of pregnancy (VIP) is a complex process, influenced both by health and psychosocial factors, which in turn affect the health and well-being of the women. The objective of this study is to determine the factors related to the voluntary interruption of pregnancy in Spain, in women with more than one interruption, according to their origin. Methods: A cross-sectional study of the VIP episodes carried out at the request of the women themselves in Spain during 2018. The factors related to repeat VIPs are described according to the origin of the women, estimating the crude and adjusted prevalence odds ratio (OR). Results: The highest rates of VIP occurred in women aged 20 to 24 years. The probability of a second VIP, both in Spanish women and those of foreign origin, increased with age, with the size of the population (> 50,000 inhabitants), and with dependent children. Conclusions: All women should have the possibility of planning their reproductive life, for which they have the right to have access to adequate information, to effective contraceptive methods, and to be able to interrupt an unplanned pregnancy with all the guarantees of quality, confidentiality and safety.S

Codes and data for "Using genomic tools to maintain diversity and fitness in conservation programmes"

Files included in file DryaData.tar.gz : BigPopMSD.f90, genotiposCGD.dat, OCgen_ranmat.f90, OCroh_ranmat.f90, DistFreqsSeg_overReps.f90, genotiposMukai.dat, OCmol_ranmat.f90. Genotype data: genotiposCGD.dat and genotiposMukai.dat are obtained after 10000 generations of mutation-selection-drift with BigPopMSD.f90 for the CGD and the Mukai scenarios, respectively. Population size is kept constant at 1000 diploid individuals (500 females and 500 males), and the genome is assumed to have 20 chromosomes of 1 Morgan each. Every chromosome includes 2000 neutral loci, 1000 selected loci and 1000 marker loci, all of them biallelic. For the CGD scenario, the parameters used are lambda is 0.03, beta is 2.3, mean s is 0.264, and mean h is 0.2. For the Mukai scenario, the parameters used are lambda equals 0.5, beta 1, mean s is 0.05, and mean h equals 0.3. BigPopMSD.f90 generates the base population. OCgen_ranmat.f90 performs 10 generations of optimal contributions for population management with random matings between the individuals who contribute. Contributions are calculated to optimise genealogical coancestry, which is calculated assuming the founder individuals are unrelated. The number of replicates is 100, but can be varied, as well as the population size during management. OCmol_ranmat.f90 performs 10 generations of optimal contributions for population management with random matings between the individuals who contribute. Contributions are calculated to optimise molecular coancestry, calculated as identity by state (see Toro et al 2002, Conservation Genetics). The number of replicates is 100, but can be varied, as well as the population size during management. OCroh_ranmat.f90 performs 10 generations of optimal contributions for population management with random matings between the individuals who contribute. Contributions are calculated to optimise IBD-based coancestry, calculated as the proportion of the genome that is identical by descent between individuals. It is calculated by looking only at marker loci, and it requires a minimum length of a segment for it to be considered identical by descent. The number of replicates is 100, but can be varied, as well as the population size during management. DistFreqsSeg_overReps.f90 analyses replicates from the base population to calculate the average number of markers segregating and the average number of runs of homozygosity in the base population. Note that the codes sometimes assume reading from a file not in the same directory. OC...f90 all read from file ../genotipos_1.dat but that can be easily changed to whichever genotypes you want to read. Should you have any issues, contact angeles.decara AT gmai

Data from: An evaluation of the methods to estimate effective population size from measures of linkage disequilibrium

In 1971, John Sved derived an approximate relationship between linkage disequilibrium and effective population size for an ideal finite population. This seminal work was extended by Sved and Feldman (1973) and Weir and Hill (1980) who derived additional equations with the same purpose. These equations yield useful estimates of effective population size, as they require a single sample in time. As these estimates of effective population size are now commonly used on a variety of genomic data, from arrays of single nucleotide polymorphisms to whole genome data, some authors have investigated their bias through simulation studies and proposed corrections for different mating systems. However, the cause of the bias remains elusive. Here we show the problems of using linkage disequilibrium as a statistical measure and, analogously, the problems in estimating effective population size from such measure. For that purpose, we compare three commonly used approaches with a transition probability based method that we develop here. It provides an exact computation of linkage disequilibrium. We show here that the bias in the estimates of linkage disequilibrium and effective population size are partly due to low frequency markers, tightly linked markers or to a small total number of crossovers per generation. These biases, however, do not decrease when increasing sample size or using unlinked markers. Our results show the issues of such measures of effective population based on linkage disequilibrium, and suggest which of the method here studied should be used in empirical studies as well as the optimal distance between markers for such estimates

An evaluation of the methods to estimate effective population size from measures of linkage disequilibrium

International audienceThe effective population size N e is defined as the number of individuals in an idealized population that give rise to the same loss of heterozygosity, inbreeding or variance in allelic frequencies as the studied population (Caballero, 1994). It is a crucial parameter in evolutionary and conservation genetics, commonly used to estimate the conservation status of a species. There are many ways to estimate N e depending on the available data. For instance, we can use the variance of allelic frequencies at multiple markers, or if we have samples taken at different times, we can measure the rate of increase in inbreeding (Wang, 2005). Sved (1971) derived an expression to infer N e from linkage dis-equilibrium (LD), which is convenient as it only requires one sample in time from several markers and individuals. Given the increasing number of single nucleotide polymorphism (SNP) data available, such data are now commonly used to infer N e from LD. Further approaches have been developed to infer current or ancestral effective Abstract In 1971, John Sved derived an approximate relationship between linkage disequilib-rium (LD) and effective population size for an ideal finite population. This seminal work was extended by Sved and Feldman (Theor Pop Biol 4, 129, 1973) and Weir and Hill (Genetics 95, 477, 1980) who derived additional equations with the same purpose. These equations yield useful estimates of effective population size, as they require a single sample in time. As these estimates of effective population size are now commonly used on a variety of genomic data, from arrays of single nucleotide polymorphisms to whole genome data, some authors have investigated their bias through simulation studies and proposed corrections for different mating systems. However, the cause of the bias remains elusive. Here, we show the problems of using LD as a statistical measure and, analogously, the problems in estimating effective population size from such measure. For that purpose, we compare three commonly used approaches with a transition probability-based method that we develop here. It provides an exact computation of LD. We show here that the bias in the estimates of LD and effective population size are partly due to low-frequency markers, tightly linked markers or to a small total number of crossovers per generation. These biases, however, do not decrease when increasing sample size or using unlinked markers. Our results show the issues of such measures of effective population based on LD and suggest which of the method here studied should be used in empirical studies as well as the optimal distance between markers for such estimates

Data from: Purging deleterious mutations in conservation programmes: combining optimal contributions with inbred matings

Conservation programmes aim at minimising the loss of genetic diversity, which allows populations to adapt to potential environmental changes. This can be achieved by calculating how many offspring every individual should contribute to the next generation to minimise global coancestry. However, an undesired consequence of this strategy is that it maintains deleterious mutations, compromising the viability of the population. In order to avoid this, optimal contributions could be combined with inbred matings, to expose and eliminate recessive deleterious mutations by natural selection in a process known as purging. Although some populations that have undergone purging experienced reduced inbreeding depression, this effect is not consistent across species. Whether purging by inbred matings is efficient in conservation programmes depends on the balance between the loss of diversity, the initial decrease in fitness and the reduction in mutational load. Here we perform computer simulations to determine whether managing a population by combining optimal contributions with inbred matings improves its long-term viability while keeping reasonable levels of diversity. We compare the management based on genealogical information with management based on molecular data to calculate coancestries. In the scenarios analysed, inbred matings never led to higher fitness and usually maintained lower diversity than random or minimum coancestry matings. Replacing genealogical with molecular coancestry can maintain a larger genetic diversity but can also lead to a lower fitness. Our results are strongly dependent on the mutational model assumed for the trait under selection, the population size during management and the reproductive rate

Dryad_data.tar

Four sets of genotypes used for population management, for populations of 1000 diploid individuals with 20 chromosomes of 1 Morgan each. For S=100 (1000), each chromosome has 2000 neutral loci, 100 (1000) selected loci and 1000 markers. Each row is one individual, and within row the two alleles per position

Artificial selection with traditional or genomic relationships: consequences in coancestry and genetic diversity

Estimated breeding values (EBVs) are traditionally obtained from pedigree information. However, EBVs from high-density genotypes can have higher accuracy than EBVs from pedigree information. At the same time, it has been shown that EBVs from genomic data lead to lower increases in inbreeding compared with traditional selection based on genealogies. Here we evaluate the performance with BLUP selection based on genealogical coancestry with three different genome-based coancestry estimates: (1) an estimate based on shared segments of homozygosity, (2) an approach based on SNP-by-SNP count corrected by allelic frequencies, and (3) the identity by state methodology. We evaluate the effect of different population sizes, different numberof genomic markers, and several heritability values for a quantitative trait. The performance of the different measures of coancestry in BLUP is evaluated in the true breeding values after truncation selection and also in terms of coancestry and diversity maintained.Accordingly, cross-performances were also carried out, that is, how prediction based on genealogical records impacts the three other measures of coancestry and inbreeding, and viceversa. Our results show that the genetic gains are very similar for allfour coancestries, but the genomic-based methods are superior to using genealogical coancestries in terms of maintainingdiversity measured as observed heterozygosity. Furthermore, the measure of coancestry based on shared segments of the genome seems to provide slightly better results on some scenarios, and the increase in inbreeding and loss in diversity is only slightly larger than the other genomic selection methods in those scenarios. Our results shed light on genomic selection versus traditional genealogical-based BLUP and make the case to manage the population variability using genomic information to preserve the future success of selection programmes

Dryad_data.tar

Four sets of genotypes used for population management, for populations of 1000 diploid individuals with 20 chromosomes of 1 Morgan each. For S=100 (1000), each chromosome has 2000 neutral loci, 100 (1000) selected loci and 1000 markers. Each row is one individual, and within row the two alleles per position

Supergene evolution triggered by the introgression of a chromosomal inversion

International audienc