Design of reference populations for genomic selection in crossbreeding programs

Background

In crossbreeding programs, genomic selection offers the opportunity to make efficient use of information on crossbred (CB) individuals in the selection of purebred (PB) candidates. In such programs, reference populations often contain genotyped PB animals, although the breeding objective is usually more focused on CB performance. The question is what would be the benefit of including a larger proportion of CB individuals in the reference population.

Methods

In a deterministic simulation study, we evaluated the benefit of including various proportions of CB animals in a reference population for genomic selection of PB animals in a crossbreeding program. We used a pig breeding scheme with selection for a moderately heritable trait and a size of 6000 for the reference population.

Results

Applying genomic selection to improve the performance of CB individuals, with a genetic correlation between PB and CB performance (r_PC) of 0.7, selection accuracy of PB candidates increased from 0.49 to 0.52 if the reference population consisted of PB individuals, it increased to 0.55 if the reference population consisted of the same number of CB individuals, and to 0.60 if the size of the CB reference population was twice that of the reference population for each PB line. The advantage of using CB rather than PB individuals increased linearly with the proportion of CB individuals in the reference population. This advantage disappeared quickly if r_PC was higher or if the breeding objective put some emphasis on PB performance. The benefit of adding CB individuals to an existing PB reference population was limited for high r_PC.

Conclusions

Using CB rather than PB individuals in a reference population for genomic selection can provide substantial advantages, but only when correlations between PB and CB performances are not high and PB performance is not part of the breeding objective.     

AMIGO is an auxiliary subunit of the Kv2.1 potassium channel

Kv2.1 is a potassium channel α-subunit abundantly expressed throughout the brain. It is a main component of delayed rectifier current (I(K)) in several neuronal types and a regulator of excitability during high-frequency firing. Here we identify AMIGO (amphoterin-induced gene and ORF), a neuronal adhesion protein with leucine-rich repeat and immunoglobin domains, as an integral part of the Kv2.1 channel complex. AMIGO shows extensive spatial and temporal colocalization and association with Kv2.1 in the mouse brain. The colocalization of AMIGO and Kv2.1 is retained even during stimulus-induced changes in Kv2.1 localization. AMIGO increases Kv2.1 conductance in a voltage-dependent manner in HEK cells. Accordingly, inhibition of endogenous AMIGO suppresses neuronal I(K) at negative membrane voltages. In conclusion, our data indicate AMIGO as a function-modulating auxiliary subunit for Kv2.1 and thus provide new insights into regulation of neuronal excitability.     

Impact of global warming on the tree species composition of boreal forests in Finland and effects on emissions of isoprenoids

This study aims to identify how climate change may influence total emissions of monoterpene and isoprene from boreal forest canopies. The whole of Finland is assumed to experience an annual mean temperature (T) increase of 4 °C and a precipitation increase of 10% by the year 2100. This will increase forest resources throughout the country. At the same time, the proportions of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) in southern Finland (60°≤ latitude < 65°N) will be reduced from the current 40–50% to less than 10–20%, with increased dominance of birches (Betula pendula and Betula pubescens). In northern Finland (65°≤ latitude < 70°N), the proportions of Norway spruce and Scots pine will be balanced at a level of about 40% as the result of an increase in Norway spruce from the current 21% to 37% and a concurrent reduction in Scots pine from 63% to 40%. The proportion of birches is predicted to increase from the current 17% to 23%, but these will become the dominant species only on the most fertile sites. Total mean emissions of monoterpene by Scots pine will be reduced by 80% in southern Finland, but will increase by 62% in the north. Emissions from Norway spruce canopies will increase by 4% in the south but by 428% in the north, while those from birch canopies will increase by about 300% and 113%, respectively. Overall emissions of monoterpene over the whole country amount to about 950 kg km^?2 y^?1 under current temperature conditions and will increase by 17% to 1100 kg km^?2 y^?1 with elevated temperature and precipitation, mainly because of an increase at northern latitudes. Under current conditions, emissions of isoprene follow the spatial distribution of spruce canopies (the only isoprene‐emitting tree species that forms forests in Finland) with four times higher emissions in the south than in the north. The elevated temperature and the changes in the areal distribution of Norway spruce will result in increases in isoprene emissions of about 37% in southern Finland and 435% in northern Finland. Annual mean isoprene emissions from Norway spruce canopies over the whole country will increase by about 60% up to the year 2100.     

Bayesian variable selection in searching for additive and dominant effects in genome-wide data

Although complex diseases and traits are thought to have multifactorial genetic basis, the common methods in genome-wide association analyses test each variant for association independent of the others. This computational simplification may lead to reduced power to identify variants with small effect sizes and requires correcting for multiple hypothesis tests with complex relationships. However, advances in computational methods and increase in computational resources are enabling the computation of models that adhere more closely to the theory of multifactorial inheritance. Here, a Bayesian variable selection and model averaging approach is formulated for searching for additive and dominant genetic effects. The approach considers simultaneously all available variants for inclusion as predictors in a linear genotype-phenotype mapping and averages over the uncertainty in the variable selection. This leads to naturally interpretable summary quantities on the significances of the variants and their contribution to the genetic basis of the studied trait. We first characterize the behavior of the approach in simulations. The results indicate a gain in the causal variant identification performance when additive and dominant variation are simulated, with a negligible loss of power in purely additive case. An application to the analysis of high- and low-density lipoprotein cholesterol levels in a dataset of 3895 Finns is then presented, demonstrating the feasibility of the approach at the current scale of single-nucleotide polymorphism data. We describe a Markov chain Monte Carlo algorithm for the computation and give suggestions on the specification of prior parameters using commonly available prior information. An open-source software implementing the method is available at http://www.lce.hut.fi/research/mm/bmagwa/ and https://github.com/to-mi/.     

Automatically extracting functionally equivalent proteins from SwissProt

Background  

There is a frequent need to obtain sets of functionally equivalent homologous proteins (FEPs) from different species. While it is usually the case that orthology implies functional equivalence, this is not always true; therefore datasets of orthologous proteins are not appropriate. The information relevant to extracting FEPs is contained in databanks such as UniProtKB/Swiss-Prot and a manual analysis of these data allow FEPs to be extracted on a one-off basis. However there has been no resource allowing the easy, automatic extraction of groups of FEPs – for example, all instances of protein C.     

Monitoring of residues of ochratoxin A in blood and kidney of chicken using HPLC-FLD

Detoxification of ochratoxin A can be achieved by chemical or enzymatic hydrolyzation, the products of such reactions are ochratoxin α and phenylalanine. Ochratoxin α like ochratoxin A, is a fluorescing molecule, therefore sensitive analysis is possible at very low concentration levels. Methods have been established that make it possible to look for residues of ochratoxin A and its main metabolite ochratoxin α in blood and tissues at very low concentration levels. Plasma is extracted by the use of small amounts of chloroform; the extract is cleaned with water and afterwards evaporated to dryness]. The residue is re-dissolved and analysed by HPLC-FLD. Using this method a limit of detection of 0.5μg/l for both ochratoxin A and ochratoxin α can be reached.     

Plasma and Cerebrospinal Fluid Amino Acids in Epileptic Patients

Altered plasma and cerebrospinal fluid amino acid levels may be associated with human epilepsy. We studied three groups of patients, those with a generalized epileptic syndrome, juvenile myoclonic epilepsy, patients with refractory localization-related epilepsies, and patients with acute seizures (within 24 h). Plasma levels of amino acids were studied in all patient groups, as were those in the cerebrospinal fluid (CSF) of patients with acute seizures. After acute seizures, the amino acid changes in the CSF were limited to a reduction in the level of taurine, whereas the levels of most amino acids in plasma were decreased. On the other hand, levels of the excitatory amino acids glutamate and aspartate were increased. The most notable finding in the juvenile myoclonic epilepsy patients was an increase in glutamate level in the plasma. Our study supports the conception of an altered metabolism of glutamate in generalized epilepsies.