Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data.

The estimation of haplotype structure and frequencies provides crucial information about the composition of genomes. Techniques, such as single-individual haplotyping, aim to reconstruct individual haplotypes from diploid genome sequencing data. However, our focus is distinct. We address the challenge of reconstructing haplotype structure and frequencies from pooled sequencing samples where multiple individuals are sequenced simultaneously. A frequentist method to address this issue has recently been proposed. In contrast to this and other methods that compute point estimates, our proposed Bayesian hierarchical model delivers a posterior that permits us to also quantify uncertainty. Since matching permutations in both haplotype structure and corresponding frequency matrix lead to the same reconstruction of their product, we introduce an order-preserving shrinkage prior that ensures identifiability with respect to permutations. For inference, we introduce a blocked Gibbs sampler that enforces the required constraints. In a simulation study, we assessed the performance of our method. Furthermore, by using our approach on two distinct sets of real data, we demonstrate that our Bayesian approach can reconstruct the dominant haplotypes in a challenging, high-dimensional set-up.

Phase-type distributions in mathematical population genetics: An emerging framework.

A phase-type distribution is the time to absorption in a continuous- or discrete-time Markov chain. Phase-type distributions can be used as a general framework to calculate key properties of the standard coalescent model and many of its extensions. Here, the 'phases' in the phase-type distribution correspond to states in the ancestral process. For example, the time to the most recent common ancestor and the total branch length are phase-type distributed. Furthermore, the site frequency spectrum follows a multivariate discrete phase-type distribution and the joint distribution of total branch lengths in the two-locus coalescent-with-recombination model is multivariate phase-type distributed. In general, phase-type distributions provide a powerful mathematical framework for coalescent theory because they are analytically tractable using matrix manipulations. The purpose of this review is to explain the phase-type theory and demonstrate how the theory can be applied to derive basic properties of coalescent models. These properties can then be used to obtain insight into the ancestral process, or they can be applied for statistical inference. In particular, we show the relation between classical first-step analysis of coalescent models and phase-type calculations. We also show how reward transformations in phase-type theory lead to easy calculation of covariances and correlation coefficients between e.g. tree height, tree length, external branch length, and internal branch length. Furthermore, we discuss how these quantities can be used for statistical inference based on estimating equations. Providing an alternative to previous work based on the Laplace transform, we derive likelihoods for small-size coalescent trees based on phase-type theory. Overall, our main aim is to demonstrate that phase-type distributions provide a convenient general set of tools to understand aspects of coalescent models that are otherwise difficult to derive. Throughout the review, we emphasize the versatility of the phase-type framework, which is also illustrated by our accompanying R-code. All our analyses and figures can be reproduced from code available on GitHub.

Haplotype based testing for a better understanding of the selective architecture.

BACKGROUND: The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies. RESULTS: Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits. CONCLUSIONS: Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios.

Development and evaluation of an animal health and welfare monitoring system for veterinary supervision of pullet farms.

Regular welfare monitoring throughout rearing of pullets may help to identify problems early and take counteractions timely, which helps in guaranteeing good welfare. The aims of our observational study were (i) to establish and test a welfare monitoring system that can be used during (short) routine veterinary and technical staff visits for pullet flocks, (ii) to use the monitoring system to investigate variability between flocks and (iii) to analyse factors that potentially affect pullets' body weight, uniformity in body weight and mortality. The developed monitoring system tries to minimise the time required while not losing important information. Age-specific recording sheets comprise animal-based indicators of welfare and relevant environmental factors (housing, management, care) to allow for identifying causes of problems and targeted action. Finally, the system was implemented in a cross-sectional study and data collected in 100 flocks (67 organic, 33 conventional) on 28 rearing farms in Austria. Linear mixed models were used to identify factors influencing body weight, uniformity and mortality, both including all flocks (A) and only organic flocks (O) and a linear regression model with all flocks to investigate associations within animal-based indicators. High variability was found between flocks in animal-based indicators. Body weight was higher when the pre-rearing period was shorter (p ≤ 0.001, A&O), with higher intensities of light (p = 0.012, O), with only one compared to more stockpersons (p ≤ 0.007, A&O), with a higher number of flock visits per day (p ≤ 0.018, A&O), and a lower avoidance distance (p = 0.034, A). Body weight uniformity increased, with age and decreased with the duration of the light period (p = 0.046, A), and, amongst others, was higher on organic farms (farming type; p = 0.041). The latter may reflect a more uniform level of welfare due to a lower stocking density and lowered effects of social competition. Within organic flocks mortality was lower if pullets had access to a covered veranda (p = 0.025) resulting in an overall lower stocking density inside the barn, while in the model including all farms mortality was higher in cases where a disease had been diagnosed. We conclude that our monitoring system can easily be implemented in regular veterinary and technical staff visits, but could also be used by the farmers'. Several easy-to-record animal-based indicators of animal welfare could be analysed more frequently to increase early detection of problems. Implementation of such a routine-based monitoring system with easy-to-assess animal-based parameters and input measures can contribute to better animal health and welfare in pullets.

Using fecal immmunochemical cartridges for gut microbiome analysis within a colorectal cancer screening program.

The colorectal cancer (CRC) screening program B-PREDICT is an invited two-stage screening project using a fecal immunochemical test (FIT) for initial screening followed by a colonoscopy for those with a positive FIT. Since the gut microbiome likely plays a role in the etiology of CRC, microbiome-based biomarkers in combination with FIT could be a promising tool for optimizing CRC screening. Therefore, we evaluated the usability of FIT cartridges for microbiome analysis and compared it to Stool Collection and Preservation Tubes. Corresponding FIT cartridges as well as Stool Collection and Preservation Tubes were collected from participants of the B-PREDICT screening program to perform 16S rRNA gene sequencing. We calculated intraclass correlation coefficients (ICCs) based on center log ratio transformed abundances and used ALDEx2 to test for significantly differential abundant taxa between the two sample types. Additionally, FIT and Stool Collection and Preservation Tube triplicate samples were obtained from volunteers to estimate variance components of microbial abundances. FIT and Preservation Tube samples produce highly similar microbiome profiles which cluster according to subject. Significant differences between the two sample types can be found for abundances of some bacterial taxa (e.g. 33 genera) but are minor compared to the differences between the subjects. Analysis of triplicate samples revealed slightly worse repeatability of results for FIT than for Preservation Tube samples. Our findings indicate that FIT cartridges are appropriate for gut microbiome analysis nested within CRC screening programs.

Waves Out of the Korean Peninsula and Inter- and Intra-Species Replacements in Freshwater Fishes in Japan.

The Japanese archipelago is located at the periphery of the continent of Asia. Rivers in the Japanese archipelago, separated from the continent of Asia by about 17 Ma, have experienced an intermittent exchange of freshwater fish taxa through a narrow land bridge generated by lowered sea level. As the Korean Peninsula and Japanese archipelago were not covered by an ice sheet during glacial periods, phylogeographical analyses in this region can trace the history of biota that were, for a long time, beyond the last glacial maximum. In this study, we analyzed the phylogeography of four freshwater fish taxa, Hemibarbus longirostris, dark chub Nipponocypris temminckii, Tanakia ssp. and Carassius ssp., whose distributions include both the Korean Peninsula and Western Japan. We found for each taxon that a small component of diverse Korean clades of freshwater fishes migrated in waves into the Japanese archipelago to form the current phylogeographic structure of biota. The replacements of indigenous populations by succeeding migrants may have also influenced the phylogeography.

Multiple haplotype reconstruction from allele frequency data.

Because haplotype information is of widespread interest in biomedical applications, effort has been put into their reconstruction. Here, we propose an efficient method, called haploSep, that is able to accurately infer major haplotypes and their frequencies just from multiple samples of allele frequency data. Even the accuracy of experimentally obtained allele frequencies can be improved by re-estimating them from our reconstructed haplotypes. From a methodological point of view, we model our problem as a multivariate regression problem where both the design matrix and the coefficient matrix are unknown. Compared to other methods, haploSep is very fast, with linear computational complexity in the haplotype length. We illustrate our method on simulated and real data focusing on experimental evolution and microbial data.

Gentle interactions with restrained and free-moving cows: Effects on the improvement of the animal-human relationship.

The animal-human relationship is essential for farm animal welfare and production. Generally, gentle tactile and vocal interactions improve the animal-human relationship in cattle. However, cows that are fearful of humans avoid their close presence and touch; thus, the animal-human relationship first has to be improved to a point where the animals accept stroking before their perception of the interactions and consequently the animal-human relationship can become positive. We tested whether the animal-human relationship of cows fearful of humans is improved more effectively by gentle interactions during restraint, allowing physical contact from the beginning, or if the gentle interactions are offered while the animals are free to move, giving them more control over the situation and thus probably a higher level of agency and a more positive perception of the interactions. Thirty-six dairy cows (median avoidance distance 1.6 m) were assigned to three treatments (each n = 12): gentle vocal and tactile interactions during restraint in the feeding rack (LOCK); gentle vocal and, if possible, tactile interactions while free in the barn (FREE); routine management without additional interactions (CON). Treatments were applied for 3 min per cow on 10 d per fortnight for 6 weeks (i.e., three periods). Avoidance and approach behaviour towards humans was tested before the start of the treatment period, and then at 2-week intervals. The recorded variables were reduced to one score by Principal Component Analysis. The resulting relationship score (higher values implying a better relationship with humans) increased in all groups; the increase was stronger in FREE than in CON, with the increase in LOCK being not significantly different from the other treatment groups. Thus, we recommend that gentle interactions with cows should take place while they are unrestrained, if possible.

Talking to Cows: Reactions to Different Auditory Stimuli During Gentle Human-Animal Interactions.

The quality of the animal-human relationship and, consequently, the welfare of animals can be improved by gentle interactions such as stroking and talking. The perception of different stimuli during these interactions likely plays a key role in their emotional experience, but studies are scarce. During experiments, the standardization of verbal stimuli could be increased by using a recording. However, the use of a playback might influence the perception differently than "live" talking, which is closer to on-farm practice. Thus, we compared heifers' (n = 28) reactions to stroking while an experimenter was talking soothingly ("live") or while a recording of the experimenter talking soothingly was played ("playback"). Each animal was tested three times per condition and each trial comprised three phases: pre-stimulus, stimulus (stroking and talking) and post-stimulus. In both conditions, similar phrases with positive content were spoken calmly, using long low-pitched vowels. All tests were video recorded and analyzed for behaviors associated with different affective states. Effects on the heifers' cardiac parameters were assessed using analysis of heart rate variability. Independently of the auditory stimuli, longer durations of neck stretching occurred during stroking, supporting our hypothesis of a positive perception of stroking. Observation of ear positions revealed longer durations of the "back up" position and less ear flicking and changes of ear positions during stroking. The predicted decrease in HR during stroking was not confirmed; instead we found a slightly increased mean HR during stroking with a subsequent decrease in HR, which was stronger after stroking with live talking. In combination with differences in HRV parameters, our findings suggest that live talking might have been more pleasurable to the animals and had a stronger relaxing effect than "playback." The results regarding the effects of the degree of standardization of the stimulus on the variability of the data were inconclusive. We thus conclude that the use of recorded auditory stimuli to promote positive affective states during human-animal interactions in experimental settings is possible, but not necessarily preferable.

Effects of Different Stroking Styles on Behaviour and Cardiac Parameters in Heifers.

Gentle animal-human interactions, such as stroking, can promote positive emotions and thus welfare in cattle. While previous studies showed that stroking at the ventral neck elicited the most positive reactions in cows, intra-specific allogrooming in cattle includes different body regions and is probably guided partly by the receiver. Thus, we compared heifers' (n = 28) reactions to stroking with the experimenter either reactively responding to perceived momentary preferences of the heifers or exclusively stroking the ventral neck. Independently of the stroking style, longer durations of neck stretching and contact occurred during stroking, supporting our hypothesis of a positive perception of stroking. We did not confirm the predicted decrease in heart rate and increase in heart rate variability, but instead found a slightly increased mean heart rate during stroking. The different stroking styles elicited differences in the heifers' ear positions: "reactive" stroking led to longer durations of low ear positions during stroking, while during "ventral neck" stroking, the duration of back up increased. However, no other behaviours differed significantly between different stroking styles, indicating that the exact manner of stroking applied in our treatments seemed to be less important in the promotion of positive affective states in cattle through gentle human-animal interactions.

The Effects of Play Behavior, Feeding, and Time of Day on Salivary Concentrations of sIgA in Calves.

The focus of animal welfare science has shifted over the last decades from efforts to avoid negative states to ways of allowing animals the experience of positive emotions. They may influence physiological processes in farmed animals, potentially providing health benefits; in addition, the physiological changes might be used as indicators of emotional states. We investigated calves' salivary secretory immunoglobulin A (sIgA) concentrations with regard to a possible circadian rhythm and two situations that elicit positive emotions. Ten saliva samples of 14 calves were taken on two consecutive days; within the course of a day we observed a significant decline in salivary sIgA concentrations at 14:00 h. Further, we probed the animals before and after milk feeding and, contrarily to our prediction, detected lower sIgA concentrations 5 min after feeding than 15 min before. A probable explanation might be an increase in salivary flow rate caused by milk ingestion. We also took samples before and after we stimulated play behavior in calves. There was no significant difference in sIgA concentrations between samples taken before and after play. Although there was a significant correlation between the change in sIgA concentrations and the amount of play behavior shown, the correlation depended on an unexpected decrease of sIgA in animals that played little, and thus, does not support our hypothesis. In general, the data showed a large variability that might arise from different factors that are difficult to standardize in animals. Thus, the use of salivary sIgA concentrations as a marker of positive emotions in calves is not supported conclusively by the present data.

Benchmarking software tools for detecting and quantifying selection in evolve and resequencing studies.

BACKGROUND: The combination of experimental evolution with whole-genome resequencing of pooled individuals, also called evolve and resequence (E&R) is a powerful approach to study the selection processes and to infer the architecture of adaptive variation. Given the large potential of this method, a range of software tools were developed to identify selected SNPs and to measure their selection coefficients. RESULTS: In this benchmarking study, we compare 15 test statistics implemented in 10 software tools using three different scenarios. We demonstrate that the power of the methods differs among the scenarios, but some consistently outperform others. LRT-1, CLEAR, and the CMH test perform best despite LRT-1 and the CMH test not requiring time series data. CLEAR provides the most accurate estimates of selection coefficients. CONCLUSION: This benchmark study will not only facilitate the analysis of already existing data, but also affect the design of future data collections.

The impact of poly-A microsatellite heterologies in meiotic recombination.

Meiotic recombination has strong, but poorly understood effects on short tandem repeat (STR) instability. Here, we screened thousands of single recombinant products with sperm typing to characterize the role of polymorphic poly-A repeats at a human recombination hotspot in terms of hotspot activity and STR evolution. We show that the length asymmetry between heterozygous poly-A's strongly influences the recombination outcome: a heterology of 10 A's (9A/19A) reduces the number of crossovers and elevates the frequency of non-crossovers, complex recombination products, and long conversion tracts. Moreover, the length of the heterology also influences the STR transmission during meiotic repair with a strong and significant insertion bias for the short heterology (6A/7A) and a deletion bias for the long heterology (9A/19A). In spite of this opposing insertion-/deletion-biased gene conversion, we find that poly-A's are enriched at human recombination hotspots that could have important consequences in hotspot activation.

LDJump: Estimating variable recombination rates from population genetic data.

As recombination plays an important role in evolution, its estimation and the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating population recombination rates based on genotyping or sequence data that involves a sequential multiscale change point estimator. Our method also permits demography to be taken into account. It uses several summary statistics within a regression model fitted on suitable scenarios. Our proposed method is accurate, computationally fast, and provides a parsimonious solution by ensuring a type I error control against too many changes in the recombination rate. An application to human genome data suggests a good congruence between our estimated and experimentally identified hotspots. Our method is implemented in the R-package LDJump, which is freely available at https://github.com/PhHermann/LDJump.

An omnibus test for the global null hypothesis.

Global hypothesis tests are a useful tool in the context of clinical trials, genetic studies, or meta-analyses, when researchers are not interested in testing individual hypotheses, but in testing whether none of the hypotheses is false. There are several possibilities how to test the global null hypothesis when the individual null hypotheses are independent. If it is assumed that many of the individual null hypotheses are false, combination tests have been recommended to maximize power. If, however, it is assumed that only one or a few null hypotheses are false, global tests based on individual test statistics are more powerful (e.g. Bonferroni or Simes test). However, usually there is no a priori knowledge on the number of false individual null hypotheses. We therefore propose an omnibus test based on cumulative sums of the transformed p-values. We show that this test yields an impressive overall performance. The proposed method is implemented in an R-package called omnibus.

Caregiving and Caregiver Burden in Dementia Home Care: Results from the Prospective Dementia Registry (PRODEM) of the Austrian Alzheimer Society.

BACKGROUND: Comprehensive studies on caregiver burden (CB) of persons caring for dementia patients differ methodologically and show variable results. OBJECTIVE: Analysis of known and hypothesized factors of CB in home care of dementia patients. METHODS: Multicenter longitudinal study comprising 585 persons caring mostly for Alzheimer's disease patients (age median 77.25 years, Mini-Mental State Examination raw score median 23) using the Zarit Caregiver Burden Interview (CBI). Known patient-related determinants of CB were studied, such as dementia severity (Clinical Dementia Rating, CDR), neuropsychological deficits (CERAD-Plus), neuropsychiatric symptoms (Neuropsychiatric Inventory, NPI), disability (Disability Assessment for Dementia, DAD), dependency (Dependency Scale, DS), and moreover, unclarified potential factors (age, sex, education of patients; age, sex, occupational status of the caregivers; family relationship). Psychological and somatic effects of CB were analyzed (factor analysis). RESULTS: Caregiver age was median 61. Female caregivers prevailed (67.8%). Median CBI sum score (CBIss) was 16 at baseline. After two years, CBIss was 22 and 37% of the caregivers reported mild to moderate (CBIss 21-40), 16.8% moderate to severe or severe (≥41), and 46.2% absent to little CB (CBIss ≤ 20). CB correlated positively with NPI, CDR, DS scores, disability (DAD), years of education of the patients, and proximity of patient and caregiver sex (female), and negatively with caregiver age. Caregivers reported restrictions of time, health problems, and negative emotions. CONCLUSION: The findings are applicable to identify persons at risk for substantial CB and its consequences. There is demand for personal, psychological, and medical support of caregivers and increasing male participation.

Approximate maximum likelihood estimation for population genetic inference.

In many population genetic problems, parameter estimation is obstructed by an intractable likelihood function. Therefore, approximate estimation methods have been developed, and with growing computational power, sampling-based methods became popular. However, these methods such as Approximate Bayesian Computation (ABC) can be inefficient in high-dimensional problems. This led to the development of more sophisticated iterative estimation methods like particle filters. Here, we propose an alternative approach that is based on stochastic approximation. By moving along a simulated gradient or ascent direction, the algorithm produces a sequence of estimates that eventually converges to the maximum likelihood estimate, given a set of observed summary statistics. This strategy does not sample much from low-likelihood regions of the parameter space, and is fast, even when many summary statistics are involved. We put considerable efforts into providing tuning guidelines that improve the robustness and lead to good performance on problems with high-dimensional summary statistics and a low signal-to-noise ratio. We then investigate the performance of our resulting approach and study its properties in simulations. Finally, we re-estimate parameters describing the demographic history of Bornean and Sumatran orang-utans.

Quantifying Selection with Pool-Seq Time Series Data.

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies.

The long zinc finger domain of PRDM9 forms a highly stable and long-lived complex with its DNA recognition sequence.

PR domain containing protein 9 (PRDM9) is a meiosis-specific, multi-domain protein that regulates the location of recombination hotspots by targeting its DNA recognition sequence for double-strand breaks (DSBs). PRDM9 specifically recognizes DNA via its tandem array of zinc fingers (ZnFs), epigenetically marks the local chromatin by its histone methyltransferase activity, and is an important tether that brings the DNA into contact with the recombination initiation machinery. A strong correlation between PRDM9-ZnF variants and specific DNA motifs at recombination hotspots has been reported; however, the binding specificity and kinetics of the ZnF domain are still obscure. Using two in vitro methods, gel mobility shift assays and switchSENSE, a quantitative biophysical approach that measures binding rates in real time, we determined that the PRDM9-ZnF domain forms a highly stable and long-lived complex with its recognition sequence, with a dissociation halftime of many hours. The ZnF domain exhibits an equilibrium dissociation constant (K D) in the nanomolar (nM) range, with polymorphisms in the recognition sequence directly affecting the binding affinity. We also determined that alternative sequences (15-16 nucleotides in length) can be specifically bound by different subsets of the ZnF domain, explaining the binding plasticity of PRDM9 for different sequences. Finally, longer binding targets are preferred than predicted from the numbers of ZnFs contacting the DNA. Functionally, a long-lived complex translates into an enzymatically active PRDM9 at specific DNA-binding sites throughout meiotic prophase I that might be relevant in stabilizing the components of the recombination machinery to a specific DNA target until DSBs are initiated by Spo11.

Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution.

The effective population size ([Formula: see text]) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term [Formula: see text] They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to [Formula: see text] Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of [Formula: see text] which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate [Formula: see text] estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide [Formula: see text] estimates, we extend our method using a recursive partitioning approach to estimate [Formula: see text] locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their [Formula: see text] estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest.