Accounting for genomic pre-selection in national BLUP evaluations in dairy cattle

<p>Abstract</p> <p>Background</p> <p>In future Best Linear Unbiased Prediction (BLUP) evaluations of dairy cattle, genomic selection of young sires will cause evaluation biases and loss of accuracy once the selected ones get progeny.</p> <p>Methods</p> <p>To avoid such bias in the estimation of breeding values, we propose to include information on all genotyped bulls, including the culled ones, in BLUP evaluations. Estimated breeding values based on genomic information were converted into genomic pseudo-performances and then analyzed simultaneously with actual performances. Using simulations based on actual data from the French Holstein population, bias and accuracy of BLUP evaluations were computed for young sires undergoing progeny testing or genomic pre-selection. For bulls pre-selected based on their genomic profile, three different types of information can be included in the BLUP evaluations: (1) data from pre-selected genotyped candidate bulls with actual performances on their daughters, (2) data from bulls with both actual and genomic pseudo-performances, or (3) data from all the genotyped candidates with genomic pseudo-performances. The effects of different levels of heritability, genomic pre-selection intensity and accuracy of genomic evaluation were considered.</p> <p>Results</p> <p>Including information from all the genotyped candidates, i.e. genomic pseudo-performances for both selected and culled candidates, removed bias from genetic evaluation and increased accuracy. This approach was effective regardless of the magnitude of the initial bias and as long as the accuracy of the genomic evaluations was sufficiently high.</p> <p>Conclusions</p> <p>The proposed method can be easily and quickly implemented in BLUP evaluations at the national level, although some improvement is necessary to more accurately propagate genomic information from genotyped to non-genotyped animals. In addition, it is a convenient method to combine direct genomic, phenotypic and pedigree-based information in a multiple-step procedure.</p

Co- and post-translational translocation through the protein-conducting channel:analogous mechanisms at work?

Many proteins are translocated across, or integrated into, membranes. Both functions are fulfilled by the 'translocon/translocase', which contains a membrane-embedded proteinconducting channel (PCC) and associated soluble factors that drive translocation and insertion reactions using nucleotide triphosphates as fuel. This perspective focuses on reinterpreting existing experimental data in light of a recently proposed PCC model comprising a front-to-front dimer of SecY or Sec61 heterotrimeric complexes. In this new framework, we propose (i) a revised model for SRP-SR-mediated docking of the ribosome-nascent polypeptide to the PCC; (ii) that the dynamic interplay between protein substrate, soluble factors and PCC controls the opening and closing of a transmembrane channel across, and/or a lateral gate into, the membrane; and (iii) that co-and post-translational translocation, involving the ribosome and SecA, respectively, not only converge at the PCC but also use analogous mechanisms for coordinating protein translocation

QTL analysis and genomic selection using RADseq derived markers in Sitka spruce: the potential utility of within family data

Sitka spruce (Picea sitchensis (Bong.) Carr) is the most common commercial plantation species in Britain and a breeding programme based on traditional lines has been in operation since the early 1960s. Rotation lengths of 40-years have led breeders to adopt a process of indirect selection at younger ages based on traits well correlated with final selection, but still the generation interval is unlikely to reduce much below twenty years. Recent successful developments with genomic selection in animal breeding have led tree breeders to consider the application of this technology. In this study a RAD sequence assay was developed as a means of investigating the potential of molecular breeding in a non-model species. DNA was extracted from nearly 500 clonally replicated trees growing in a single full-sibling family at one site in Britain. The technique proved successful in identifying 132 QTLs for 5-year bud-burst and 2 QTLs for 6-year height. In addition, the accuracy of predicting phenotypes by genomic selection was strikingly high at 0.62 and 0.59 respectively. Sensitivity analysis with 200 offspring found only a slight fall in correlation values (0.54 and 0.38) although when the training population reduced to 50 offspring predictive values fell further (0.33 and 0.25). This proved an encouraging first investigation into the potential use of genomic selection in the breeding of Sitka spruce. The authors investigate how problems associated with effective population size and linkage disequilibrium can be avoided and suggest a practical way of incorporating genomic selection into a dynamic breeding programme

SecA, a remarkable nanomachine

Biological cells harbor a variety of molecular machines that carry out mechanical work at the nanoscale. One of these nanomachines is the bacterial motor protein SecA which translocates secretory proteins through the protein-conducting membrane channel SecYEG. SecA converts chemically stored energy in the form of ATP into a mechanical force to drive polypeptide transport through SecYEG and across the cytoplasmic membrane. In order to accommodate a translocating polypeptide chain and to release transmembrane segments of membrane proteins into the lipid bilayer, SecYEG needs to open its central channel and the lateral gate. Recent crystal structures provide a detailed insight into the rearrangements required for channel opening. Here, we review our current understanding of the mode of operation of the SecA motor protein in concert with the dynamic SecYEG channel. We conclude with a new model for SecA-mediated protein translocation that unifies previous conflicting data