Different models of genetic variation and their effect on genomic evaluation

Background

The theory of genomic selection is based on the prediction of the effects of quantitative trait loci (QTL) in linkage disequilibrium (LD) with markers. However, there is increasing evidence that genomic selection also relies on "relationships" between individuals to accurately predict genetic values. Therefore, a better understanding of what genomic selection actually predicts is relevant so that appropriate methods of analysis are used in genomic evaluations.

Methods

Simulation was used to compare the performance of estimates of breeding values based on pedigree relationships (Best Linear Unbiased Prediction, BLUP), genomic relationships (gBLUP), and based on a Bayesian variable selection model (Bayes B) to estimate breeding values under a range of different underlying models of genetic variation. The effects of different marker densities and varying animal relationships were also examined.

Results

This study shows that genomic selection methods can predict a proportion of the additive genetic value when genetic variation is controlled by common quantitative trait loci (QTL model), rare loci (rare variant model), all loci (infinitesimal model) and a random association (a polygenic model). The Bayes B method was able to estimate breeding values more accurately than gBLUP under the QTL and rare variant models, for the alternative marker densities and reference populations. The Bayes B and gBLUP methods had similar accuracies under the infinitesimal model.

Conclusions

Our results suggest that Bayes B is superior to gBLUP to estimate breeding values from genomic data. The underlying model of genetic variation greatly affects the predictive ability of genomic selection methods, and the superiority of Bayes B over gBLUP is highly dependent on the presence of large QTL effects. The use of SNP sequence data will outperform the less dense marker panels. However, the size and distribution of QTL effects and the size of reference populations still greatly influence the effectiveness of using sequence data for genomic prediction.     

THE BOOK CORNER

In order to increase the yield of prothrombin complex concentrates (PCCs) and to reduce their associated thrombotic risks, the influence of washing conditions on the yield, purity, and balance of coagulation factors (FII, FVII, FIX, and FX), and inhibitor proteins (PC, PS, PZ, and AT [antithrombin]) in PCCs was investigated by orthogonal testing, in which three variables (sodium citrate, NaCl, and pH) and their three levels were selected. It was found that AT yield and purity were extraordinarily low, and at lower NaCl content, the general yield, purity, and balance were higher, lower, and better, respectively; however, the results became contrary at higher NaCl. Moreover, within the investigated levels, NaCl was the first determinant for the yield except AT and the purity except FVII, PC, PS, and AT. Sodium citrate was the first determinant for AT yield and FVII, PS, and AT purity. The yield except FII, PS, and AT decreased and the purity except PC increased with increase of sodium citrate content. Just for PC purity, pH was the first determinant. The effect with pH fluctuation on the yield and purity was characteristically unobvious. The outcome undoubtedly supplies the guidance to further improve PCCs.     

英国多克隐花植物保护区森林土壤和凋落叶特性及其与真菌的关系

报道了英国独特的真菌保护区里真菌的生态学和生物多样性,而该保护区内有关物种构成的数据自1994年就开始进行收集了。关于真菌的生态学相互关系以及它们在总的生态系统功能中的作用可以作为生物多样性数据的补充。5~8月期间,在8块覆盖着不同植被（山毛榉,桦树,桦栎山毛榉,禾本科植物）实验区里,研究了森林凋落叶和叶本层土壤的特性和构成,测量了细菌种群数量和真菌的生物量（针对麦角固醇而言）。用相关分析和分段回归建模方法,结合可通过并行研究采集到的原生动物和线虫数据,得到了一系列结果。这些结果强调了某些因素的复杂性,这些因素影响着森林土壤和森林凋落叶中真菌生物量空间可变性的时间动态。大多数的相互作用看起来是瞬时的,在解释环境观测记录时应该对这一点给予充分考虑。最后,解释了若干具体关系,给出了进一步研究的方向,讨论了对整个生态系统功能研究的必要性。     

Analysis of the extracellular matrix vesicle proteome in mineralizing osteoblasts

Many key processes central to bone formation and homeostasis require the involvement of osteoblasts, cells responsible for accumulation and mineralization of the extracellular matrix (ECM). During this complex and only partially understood process, osteoblasts generate and secrete matrix vesicles (MVs) into the ECM to initiate mineralization. Although they are considered an important component of mineralization process, MVs still remain a mystery. To better understand their function and biogenesis, a proteomic analysis of MVs has been conducted. MVs were harvested by two sample preparation approaches and mass spectrometry was utilized for protein identification. A total of 133 proteins were identified in common from the two MV preparations, among which were previously known proteins, such as annexins and peptidases, along with many novel proteins including a variety of enzymes, osteoblast-specific factors, ion channels, and signal transduction molecules, such as 14-3-3 family members and Rab-related proteins. To compare the proteome of MV with that of the ECM we conducted a large-scale proteomic analysis of collagenase digested mineralizing osteoblast matrix. This analysis resulted in the identification of 1,327 unique proteins. A comparison of the proteins identified from the two MV preparations with the ECM analysis revealed 83 unique, non-redundant proteins identified in all three samples. This investigation represents the first systematic proteomic analysis of MVs and provides insights into both the function and origin of these important mineralization-regulating vesicles.     

A tetravalent bispecific TandAb (CD19/CD3), AFM11, efficiently recruits T cells for the potent lysis of CD19+ tumor cells

To harness the potent tumor-killing capacity of T cells for the treatment of CD19⁺ malignancies, we constructed AFM11, a humanized tetravalent bispecific CD19/CD3 tandem diabody (TandAb) consisting solely of Fv domains. The molecule exhibits good manufacturability and stability properties. AFM11 has 2 binding sites for CD3 and 2 for CD19, an antigen that is expressed from early B cell development through differentiation into plasma cells, and is an attractive alternative to CD20 as a target for the development of therapeutic antibodies to treat B cell malignancies. Comparison of the binding and cytotoxicity of AFM11 with those of a tandem scFv bispecific T cell engager (BiTE) molecule targeting the same antigens revealed that AFM11 elicited more potent in vitro B cell lysis. Though possessing high affinity to CD3, the TandAb mediates serial-killing of CD19⁺ cells with little dependence of potency or efficacy upon effector:target ratio, unlike the BiTE. The advantage of the TandAb over the BiTE was most pronounced at lower effector:target ratios. AFM11 mediated strictly target-dependent T cell activation evidenced by CD25 and CD69 induction, proliferation, and cytokine release, notwithstanding bivalent CD3 engagement. In a NOD/scid xenograft model, AFM11 induced dose-dependent growth inhibition of Raji tumors in vivo, and radiolabeled TandAb exhibited excellent localization to tumor but not to normal tissue. After intravenous administration in mice, half-life ranged from 18.4 to 22.9 h. In a human ex vivo B-cell chronic lymphocytic leukemia study, AFM11 exhibited substantial cytotoxic activity in an autologous setting. Thus, AFM11 may represent a promising therapeutic for treatment of CD19⁺ malignancies with an advantageous safety risk profile and anticipated dosing regimen.     

Using an evolutionary algorithm and parallel computing for haplotyping in a general complex pedigree with multiple marker loci

Background  

Haplotype reconstruction is important in linkage mapping and association mapping of quantitative trait loci (QTL). One widely used statistical approach for haplotype reconstruction is simulated annealing (SA), implemented in SimWalk2. However, the algorithm needs a very large number of sequential iterations, and it does not clearly show if convergence of the likelihood is obtained.     

Failure to Use Cubicles and Concentrate Dispenser by Heifers after Transfer from Rearing Accommodation to Milking Herd

Thirty-three dairy farms in the Norwegian counties of ?stfold and Akershus in which cubicle sheds had been in use for at least one year and with a herd size of less than 60 cows, were contacted and asked to participate in a study. The study focused on heifers' use of cubicles and concentrate dispenser just after being transferred from rearing accommodation to the milking herd. For each heifer, the farmer recorded cubicle use once nightly between 9 and 11 pm. The daily amount of concentrate released in the dispenser and the allotted daily ration were also recorded. The recording period was 15 consecutive days for cubicle use and 7 days for concentrate dispenser use. Cubicle refusal behaviour, i.e. lying outside the cubicles, was analysed by logistic regression using rearing accommodation of heifers, herd size, heifer age, and housing layout as independent variables, and herd as a clustering variable. On Day 2 after transfer, 34% of the heifers were showing cubicle refusal behaviour (N = 340). By Day 15 this percentage had dropped to 23. Cubicle refusal was lower throughout the whole period among heifers which used the cubicles on the 3 first days after transfer compared to those which did not. This tendency could also be detected several months later. The analysis showed cubicle refusal to be significantly associated with rearing accommodation (OR = 6.1, c.i._95%OR = 1.5–24.3, P = 0.01) and cubicle layout in the shed (OR = 0.2, c.i._95%OR = 0.0–0.7, P = 0.01). None of the tested variables were found to be significant for failure to use the concentrate dispenser, a behaviour which was less frequent than cubicle refusal. However, 8 percent of the heifers did not visit the dispenser at all throughout the 7 days of observation.     

Changes in Triphasic Mechanical Properties of Proteoglycan-Depleted Articular Cartilage Extracted from Osmotic Swelling Behavior Monitored Using High-Frequency Ultrasound

This study aims to obtain osmosis-induced swelling strains of normal and proteoglycan (PG) depleted articular cartilage using an ultrasound system and to investigate the changes in its mechanical properties due to the PG depletion using a layered triphasic model. The swelling strains of 20 cylindrical cartilage-bone samples collected from different bovine patellae were induced by decreasing the concentration of bath saline and monitored by the ultrasound system. The samples were subsequently digested by a trypsin solution for approximately 20 min to deplete proteoglycans, and the swelling behaviors of the digested samples were measured again. The bi-layered triphasic model proposed in our previous study (Wang et al., J Biomech Eng-Trans ASME 2007; 129: 413-422) was used to predict the layered aggregate modulus Hafrom the data of depth-dependent swelling strain, fixed charge density and water content. It was found that the region near the bone, for the normal specimens, had a significantly higher aggregate modulus (Ha₁= 20.6±18.2 MPa) in comparison with the middle zone and the surface layer (Ha₂= 7.8±14.5 MPa and Ha₃= 3.6±3.2 MPa, respectively) (p < 0.001). The normalized thickness of the deep layer h₁ was 0.68±0.20. After the trypsin digestion, the parametric values decreased to Ha₁ = 13.6±9.6 MPa, Ha₂ = 6.7±11.5 MPa, Ha₃ = 2.7±3.2 MPa, and h₁ = 0.57±0.28. Other models were also used to analyze data and the results were compared. This study showed that high-frequency ultrasound measurement combined with the triphasic modeling was capable of nondestructively quantifying the alterations in the layered mechanical properties of the proteoglycan-depleted articular cartilage.     

Mathematical design of prokaryotic clone-based microarrays

Background  

Clone-based microarrays, on which each spot represents a random genomic fragment, are a good alternative to open reading frame-based microarrays, especially for microorganisms for which the complete genome sequence is not available. Since the generation of a genomic DNA library is a random process, it is beforehand uncertain which genes are represented. Nevertheless, the genome coverage of such an array, which depends on different variables like the insert size and the number of clones in the library, can be predicted by mathematical approaches. When applying the classical formulas that determine the probability that a certain sequence is represented in a DNA library at the nucleotide level, massive amounts of clones would be necessary to obtain a proper coverage of the genome.