Genotyping marker density reduction is not an effective approach in long-term prediction-based breeding of cross-pollinated crops

Reductions of genotyping marker density have been extensively evaluated as potential strategies to reduce the genotyping costs of genomic selection (GS). Low-density marker panels are appealing in GS because they entail lower multicollinearity and computational time-consumption and allow more individuals to be genotyped for the same cost. However, statistical models used in GS are usually evaluated with empirical data, using "static" training sets and populations. This may be adequate for making predictions during a breeding program's initial cycles, but not for the long term. Moreover, to the best of our knowledge, no GS models consider the effect of dominance, which is particularly important for breeding outcomes in cross-pollinated crops. Hence, dominance effects are an important and unexplored issue in GS for long-term programs involving allogamous species. To address it, we employed two approaches: analysis of empirical maize datasets and simulations of long-term breeding applying phenotypic and genomic recurrent selection (intrapopulation and reciprocal schemes). In both schemes, we simulated twenty breeding cycles and assessed the effect of marker density reduction on the population mean, the best crosses, additive variance, selective accuracy, and response to selection with models (additive, additive-dominant, general (GCA), and specific combining ability (SCA)). Our results indicate that marker reduction based on linkage disequilibrium levels provides useful predictions only within a cycle, as accuracy significantly decreases over cycles. In the long-term, high-marker density provides the best responses to selection. The model to be used depends on the breeding scheme: additive for intrapopulation and additive-dominant or SCA for reciprocal.

205 Runs of homozygosity and analysis of inbreeding depression

Pedigree information was traditionally used to assess inbreeding. Availability of high-density marker panels provides an alternative to assess inbreeding, particularly in the presence of incomplete and error-prone pedigrees. Assessment of autozygosity across chromosomal segments using runs of homozygosity (ROH) is emerging as a valuable tool to estimate inbreeding due to its general flexibility and ability to quantify chromosomal contribution to genome-wide inbreeding. Unfortunately, identifying ROH segments is sensitive to the parameters used during the search process. These parameters are heuristically set, leading to significant variation in the results. The minimum length required to identify a ROH segment has major effects on the estimation of inbreeding, yet it is arbitrarily set. Understanding the rise, purging, and the effects of deleterious mutations requires the ability to discriminate between ancient and recent inbreeding. However, thresholds to discriminate between short and long ROH segments are largely unknown. To address these questions, an inbred Hereford cattle population of 785 animals genotyped for 30,220 SNPs was used. A search algorithm to approximate mutation loads was used to determine the minimum length of ROH segments. It consisted of finding genome segments with significant differences in trait means between animals with high and low autozygosity intervals at certain threshold values. The minimum length was around 1 Mb for weaning and yearling weights and ADG, and 2.5 Mb for birth weight. Using a model-based clustering algorithm, a mixture of three Gaussian distributions was clearly separable, resulting in three classes of short (< 6.16 Mb), medium (6.16–12.57 Mb), and long (>12.27 Mb) ROH segments, representing ancient, intermediate, and recent inbreeding. Contribution of ancient, intermediate and recent to genome-wide inbreeding was 37.4%, 40.1% and 22.5%, respectively. Inbreeding depression analyses showed a greater damaging effect of recent inbreeding, likely due to purging of old highly deleterious haplotypes.

Assessment of a white matter reference region for 11C-UCB-J PET quantification

11C-UCB-J is a positron emission tomography (PET) radioligand that has been used in humans for synaptic vesicle glycoprotein 2A (SV2A) imaging and as a potential synaptic density marker. The centrum semiovale (CS) is a proposed reference region for noninvasive quantification of 11C-UCB-J, due to negligible concentrations of SV2A in this region in baboon brain assessed by in vitro methods. However, in displacement scans with SV2A-specific drug levetiracetam in humans, a decrease in 11C-UCB-J concentration was observed in the CS, consistent with some degree of specific binding. The current study aims to validate the CS as a reference region by (1) optimizing CS region of interest (ROI) to minimize spill-in from gray matter with high radioactivity concentrations; (2) investigating convergence of CS ROI values using ordered subset expectation maximization (OS-EM) reconstruction, and (3) comparing baseline CS volume of distribution ( VT) to nondisplaceable uptake in gray matter, VND. Improving ROI definition and increasing OS-EM iterations during reconstruction decreased the difference between CS VT and VND. However, even with these corrections, CS VT overestimated VND by ∼35–40%. These measures showed significant correlation, suggesting that, though biased, the CS may be a useful estimate of nondisplaceable uptake, allowing for noninvasive quantification for SV2A PET.

Immunohistochemical expression of GRP78 in relation to angiogenesis markers VEGF-a and CD31 and other histopathological parameters in NSCLC.

e20500 Background: Neovascularization is essential for the growth and progression of tumor tissues. GRP78 is frequently overexpressed in various types of cancers and has been suggested as a proangiogenic factor. Methods: In order to evaluate GRP78 expression and its role in angiogenesis of non-small cell lung cancer (NSCLC), paraffin-embedded NSCLC tissue samples (66 adenocarcinoma and 24 squamous cell carcinoma) were retrospectively collected from 90 patients who underwent surgical resection between 2008 and 2015; and did not receive chemotherapy or radiotherapy prior to surgery. Then we performed immunohistochemistry to examine GRP78 expression and we analyzed the relationships between GRP78 and the angiogenesis marker VEGF-A and the microvessel density marker (MVD) CD31. Additionally, we analyzed the association of GRP78 with clinicopathological characteristics of the patients. Results: Strong GRP78 expression was evident in about 86% of the tumor tissues (77/90). There was significant difference in GRP78 expression between poorly-differentiated and well-differentiated tumors (OR = 0.023, 95% CI = 0.001-0.419, p = 0.011). Moreover, there was a statistically significant association between VEGF-A and CD31 (χ² = 12.00, p = 0.001). Indeed, CD31 and VEGF-A expression significantly associated with histological type. Among the tissues expressing high CD31, approximately 86% of them were adenocarcinoma (χ² = 5.009, p = 0.025); and among the tissues expressing positive VEGF-A, about 79% were adenocarcinoma tissues (χ² = 6.545, p = 0.021). Conclusions: Strong GRP78 may be related to good prognosis of NSCLC. Nevertheless, further studies investigating large number of samples of all histological subtypes are required.