Biology subjects

Weigend, S.

Publications and source records attributed to Weigend, S..

5 recordsLinked to original sources

bioRxiv2025

In Ovo Sexing and Genotyping using PCR techniques: A Contribution to the 3R Principles in Chicken Breeding

Early sex determination and genotyping of chicken embryos is crucial for ethical and resource-efficient animal research, addressing concerns about surplus animals. We developed a reproducible workflow using whole genome amplification combined with Kompetitive Allele Specific PCR (KASP) and standard endpoint PCR to perform in ovo sexing and genotyping from embryonic day four (ED4/96h) onwards. The overall efficiency improved with embryonic age. Both standard PCR and KASP provided high success for sexing and genotyping (70-100% of samples yielding a result) and accuracy (92-100%) across multiple chicken lines, including a genetically modified line. Optimal reliability and hatchability were achieved when sampling at ED7. These PCR-based techniques enable precise early identification of sex and genotype, allowing selective removal of unwanted embryonated eggs before the assumed onset of nociception. This approach supports more humane and efficient practices in chicken breeding and research, contributing to the replacement, reduction and refinement (3R) principles in animal experimentation.

developmental biology↗

bioRxiv2020

Genetic diversity in global chicken breeds as a function of genetic distance to the wild populations

Migration of populations from their founder population is expected to cause a reduction in genetic diversity and facilitates population differentiation between the populations and their founder population as predicted by the theory of genetic isolation by distance. Consistent with that, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be well explained by their geographic expansion from the founders, which is correlated to the genetic differentiation. To investigate this in the chicken, we have estimated the relationship between the genetic diversity in 172 domesticated chicken populations and their genetic distances to wild populations. We have found a strong inverse relationship whereby 87.5% of the variation in the overall genetic diversity of domesticated chicken can be explained by the genetic distance to the wild populations. We also investigated if different types of SNPs and genes present similar patterns of genetic diversity as the overall genome. Among different SNP classes, the non-synonymous ones were the most deviating from the overall genome. However, the genetic distances to wild populations still explained more variation in domesticated chicken diversity in all SNP classes ranging from 81.7 to 88.7%. The genetic diversity seemed to change at a faster rate within the chicken in genes that are associated with transmembrane transport, protein transport and protein metabolic processes, and lipid metabolic processes. In general, such genes are flexible to be manipulated according to the population needs. On the other hand, genes which the genetic diversity hardly changes despite the genetic distance to the wild populations are associated with major functions e.g. brain development. Therefore, changes in the genes may be detrimental to the chickens. These results contribute to the knowledge of different evolutionary patterns of different functional genomic regions in the chicken. Author summaryThe chicken was first domesticated about 6000 B.C. in Asia from the jungle fowl. Following domestication, chickens were taken to different parts of the world mainly by humans. Evolutionary forces such as selection and genetic drift have shaped diversification within the chicken species. In addition, new breeds or strains have been developed from crossbreeding programs facilitated by man. These events, together with other breeding practices, have led to genomic alterations causing genetic differentiation between the domesticated chickens and their ancestral/wild population as well as manipulation of the genetic diversity within the domesticated chickens. We investigated the relationship between 172 domesticated chicken populations from different selection, breeding and management backgrounds and their genetic distance to the wild type chickens. We found that the genetic diversity within the populations decreases with the increasing genetic distances to the wild types. Human manipulation of chicken genetic diversity has more effect on the genetic differentiation than simple geographic separations (through migrations) do. We further found that some genes associated with vital functions show evolutionary constraints or persistent selection across the populations and do not comply with this relationship i.e. the genetic diversity within the populations is constant despite the change in the genetic distance to the wild types.

genetics↗

bioRxiv2019

How Array Design Affects SNP Ascertainment Bias

Single nucleotide polymorphisms (SNPs), genotyped with SNP arrays, have become a widely used marker type in population genetic analyses over the last 10 years. However, compared to whole genome re-sequencing data, arrays are known to lack a substantial proportion of globally rare variants and tend to be biased towards variants present in populations involved in the development process of the respective array. This affects population genetic estimators and is known as SNP ascertainment bias. We investigated factors contributing to ascertainment bias in array development by redesigning the Axiom Genome-Wide Chicken Array in silico and evaluating changes in allele frequency spectra and heterozygosity estimates in a stepwise manner. A sequential reduction of rare alleles during the development process was shown with main influencing factors being the identification of SNPs in a limited set of populations and a within-population selection of common SNPs when aiming for equidistant spacing. These effects were shown to be less severe with a larger discovery panel. Additionally, a generally massive overestimation of expected heterozygosity for the ascertained SNP sets was shown. This overestimation was 24% higher for populations involved in the discovery process than not involved populations in case of the original array. The same was observed after the SNP discovery step in the redesign. However, an unequal contribution of populations during the SNP selection can mask this effect but also adds uncertainty. Finally, we make suggestions for the design of specialized arrays for large scale projects where whole genome re-sequencing techniques are still too expensive.

genomics↗

bioRxiv2019

Improving imputation quality in BEAGLE for crop and livestock data

Imputation is one of the key steps in the preprocessing and quality control protocol of any genetic study. Most imputation algorithms were originally developed for the use in human genetics and thus are optimized for a high level of genetic diversity. Different versions of BEAGLE were evaluated on genetic datasets of doubled haploids of two European maize landraces, a commercial breeding line and a diversity panel in chicken, respectively, with different levels of genetic diversity and structure which can be taken into account in BEAGLE by parameter tuning. Especially for phasing BEAGLE 5.0 outperformed the newest version (5.1) which in turn also lead to improved imputation. Earlier versions were far more dependent on the adaption of parameters in all our tests. For all versions, the parameter ne (effective population size) had a major effect on the error rate for imputation of ungenotyped markers, reducing error rates by up to 98.5%. Further improvement was obtained by tuning of the parameters affecting the structure of the haplotype cluster that is used to initialize the underlying Hidden Markov Model of BEAGLE. The number of markers with extremely high error rates for the maize datasets were more than halved by the use of a flint reference genome (F7, PE0075 etc.) instead of the commonly used B73. On average, error rates for imputation of ungenotyped markers were reduced by 8.5% by excluding genetically distant individuals from the reference panel for the chicken diversity panel. To optimize imputation accuracy one has to find a balance between representing as much of the genetic diversity as possible while avoiding the introduction of noise by including genetically distant individuals.

genetics↗

bioRxiv2018

Dynamic changes in cerebral and peripheral markers of glutamatergic signaling across the human sleep-wake cycle

Both sleep and glutamatergic signaling in the brain are tightly controlled and homeostatically regulated. Sleep homeostasis is reliably reflected by predictable changes in brain electrical activity in waking and sleep, yet the underlying molecular mechanisms remain elusive. Current hypotheses posit that recovery sleep following prolonged waking restores efficient functioning of the brain, for example by keeping glutamatergic signaling in a homeostatic range. We recently provided evidence in humans and mice that metabotropic glutamate receptors of subtype-5 (mGluR5) contribute to the brains coping mechanisms with sleep deprivation. Here we combined in 31 healthy men, proton magnetic resonance spectroscopy to measure the levels of glutamate (Glu), GLX (glutamate-to-glutamine ratio) and GABA ({gamma}-amino-butyric-acid) in basal ganglia (BG) and dorsolateral prefrontal cortex, simultaneous positron emission tomography to quantify mGluR5 availability with the novel radioligand, [18F]PSS232, and quantification in blood plasma of the mGluR5-regulated proteins, fragile-X mental retardation protein (FMRP) and brain-derived neurotrophic factor (BDNF). All measurements were conducted at the same circadian time in baseline, following sleep deprivation and after recovery sleep. We found that Glu and GLX in BG (pall < 0.01), but not in prefrontal cortex, and the plasma concentration of FMRP (p < 0.02), were increased after sleep loss and tended to normalize following recovery sleep (pall < 0.1). Furthermore, a night without sleep enhanced whole-brain and striatal mGluR5 availability and was normalized by recovery sleep (pall < 0.05). By contrast, other brain metabolites and plasma BDNF levels were not altered. The findings demonstrate convergent changes in distinct markers of glutamatergic signaling across prolonged wakefulness and recovery sleep in humans. They warrant further studies to elucidate the underlying mechanisms that link the homeostatic regulation of sleep and glutamatergic system activity in health and disease.\n\nOne-sentence summarySleep-dependent recovery of wakefulness-induced changes in, cerebral glutamatergic signaling\n\nMajor subject areaNeuroscience; Human Biology & Medicine

neuroscience↗