The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes

Background

The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values.

Methods

Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated.

Results

The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy.

Conclusions

An animal''s relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.     

Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation

Background

Genomic predictions can be applied early in life without impacting selection candidates. This is especially useful for meat quality traits in sheep. Carcass and novel meat quality traits were predicted in a multi-breed sheep population that included Merino, Border Leicester, Polled Dorset and White Suffolk sheep and their crosses.

Methods

Prediction of breeding values by best linear unbiased prediction (BLUP) based on pedigree information was compared to prediction based on genomic BLUP (GBLUP) and a Bayesian prediction method (BayesR). Cross-validation of predictions across sire families was used to evaluate the accuracy of predictions based on the correlation of predicted and observed values and the regression of observed on predicted values was used to evaluate bias of methods. Accuracies and regression coefficients were calculated using either phenotypes or adjusted phenotypes as observed variables.

Results and conclusions

Genomic methods increased the accuracy of predicted breeding values to on average 0.2 across traits (range 0.07 to 0.31), compared to an average accuracy of 0.09 for pedigree-based BLUP. However, for some traits with smaller reference population size, there was no increase in accuracy or it was small. No clear differences in accuracy were observed between GBLUP and BayesR. The regression of phenotypes on breeding values was close to 1 for all methods, indicating little bias, except for GBLUP and adjusted phenotypes (regression = 0.78). Accuracies calculated with adjusted (for fixed effects) phenotypes were less variable than accuracies based on unadjusted phenotypes, indicating that fixed effects influence the latter. Increasing the reference population size increased accuracy, indicating that adding more records will be beneficial. For the Merino, Polled Dorset and White Suffolk breeds, accuracies were greater than for the Border Leicester breed due to the smaller sample size and limited across-breed prediction. BayesR detected only a few large marker effects but one region on chromosome 6 was associated with large effects for several traits. Cross-validation produced very similar variability of accuracy and regression coefficients for BLUP, GBLUP and BayesR, showing that this variability is not a property of genomic methods alone. Our results show that genomic selection for novel difficult-to-measure traits is a feasible strategy to achieve increased genetic gain.     

Pseudomonas syringae pv. actinidiae (PSA) isolates from recent bacterial canker of kiwifruit outbreaks belong to the same genetic lineage

Intercontinental spread of emerging plant diseases is one of the most serious threats to world agriculture. One emerging disease is bacterial canker of kiwi fruit (Actinidia deliciosa and A. chinensis) caused by Pseudomonas syringae pv. actinidiae (PSA). The disease first occurred in China and Japan in the 1980s and in Korea and Italy in the 1990s. A more severe form of the disease broke out in Italy in 2008 and in additional countries in 2010 and 2011 threatening the viability of the global kiwi fruit industry. To start investigating the source and routes of international transmission of PSA, genomes of strains from China (the country of origin of the genus Actinidia), Japan, Korea, Italy and Portugal have been sequenced. Strains from China, Italy, and Portugal have been found to belong to the same clonal lineage with only 6 single nucleotide polymorphisms (SNPs) in 3,453,192 bp and one genomic island distinguishing the Chinese strains from the European strains. Not more than two SNPs distinguish each of the Italian and Portuguese strains from each other. The Japanese and Korean strains belong to a separate genetic lineage as previously reported. Analysis of additional European isolates and of New Zealand isolates exploiting genome-derived markers showed that these strains belong to the same lineage as the Italian and Chinese strains. Interestingly, the analyzed New Zealand strains are identical to European strains at the tested SNP loci but test positive for the genomic island present in the sequenced Chinese strains and negative for the genomic island present in the European strains. Results are interpreted in regard to the possible direction of movement of the pathogen between countries and suggest a possible Chinese origin of the European and New Zealand outbreaks.     

Predictive modeling of Pseudomonas syringae virulence on bean using gradient boosted decision trees

Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P. syringae isolates are assigned pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P. syringae isolates on common bean (Phaseolus vulgaris). This collection includes P. syringae phylogroup 2 (PG2) bean isolates (pathovar syringae) that cause bacterial spot disease and P. syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then used gradient boosting machine learning to predict each strain’s virulence on bean based on whole genome k-mers, type III secreted effector k-mers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study strengthens the hypothesis that P. syringae PG2 strains have evolved a different lifestyle than other P. syringae strains as reflected in their lower level of host specificity. It also acts as a proof-of-principle to demonstrate the power of machine learning for predicting host specific adaptation.     

Integrin switching modulates adhesion dynamics and cell migration

When cells are stimulated to move, for instance during development, wound healing or angiogenesis, they undergo changes in the turnover of their cell-matrix adhesions. This is often accompanied by alterations in the expression profile of integrins—the extracellular matrix receptors that mediate anchorage within these adhesions. Here, we discuss how a shift in expression between two different types of integrins that bind fibronectin can have dramatic consequences for cell-matrix adhesion dynamics and cell motility.Key words: integrin, fibronectin, migration, cytoskeleton, dynamicsCells attach to the extracellular matrix (ECM) that surrounds them in specialized structures termed “cell-matrix adhesions.” These come in different flavors including “focal complexes” (small adhesions found in membrane protrusions of spreading and migrating cells), “focal adhesions” (larger adhesions connected by F-actin stress fibers that are derived from focal complexes in response to tension), “fibrillar adhesions” (elongated adhesions associated with fibronectin matrix assembly), and proteolytically active adhesions termed “podosomes” or “invadopodia” found in osteoclasts, macrophages and certain cancer cells. Common to all these structures is the local connection between ECM proteins outside- and the actin cytoskeleton within the cell through integrin transmembrane receptors. The intracellular linkage to filamentous actin is indirect through proteins that concentrate in cell-matrix adhesions such as talin, vinculin, tensin, parvins and others.¹Cell migration is essential for embryonic development and a number of processes in the adult, including immune cell homing, wound healing, angiogenesis and cancer metastasis. In moving cells, cell-matrix adhesion turnover is spatiotemporally controlled.² New adhesions are made in the front and disassembled in the rear of cells that move along a gradient of motogenic factors or ECM proteins. This balance between formation and breakdown of cell-matrix adhesions is important for optimal cell migration. Several mechanisms regulate the turnover of cell-matrix adhesions. Proteolytic cleavage of talin has been identified as an important step in cell-matrix adhesion disassembly³ and FAK and Src family kinases are required for cell-matrix adhesion turnover and efficient cell migration.^4,5 Besides regulating phospho-tyrosine-mediated protein-protein interactions within cell-matrix adhesions, the FAK/Src complex mediates signaling downstream of integrins to Rho GTPases, thus controlling cytoskeletal organization.^6,7 The transition from a stationary to a motile state could involve (local) activation of such mechanisms.Interestingly, conditions of increased cell migration (development, wound healing, angiogenesis, cancer metastasis) are accompanied by shifts in integrin expression with certain integrins being lost and others gained. Most ECM proteins can be recognized by various different integrins. For instance, the ECM protein, fibronectin (Fn) can be recognized by nine different types of integrins and most of these bind to the Arg-Gly-Asp (RGD) motif in the central cell-binding domain. Thus, cell-matrix adhesions formed on Fn contain a mixture of different integrins and shifts in expression from one class of Fn-binding integrins to another will alter the receptor composition of such adhesions. This may provide an alternative means to shift from stationary to motile.Indeed, we have found that the type of integrins used for binding to Fn strongly affects cell migration. We made use of cells deficient in certain Fn-binding integrins and either restored their expression or compensated for their absence by overexpression of alternative Fn-binding integrins. This allowed us to compare in a single cellular background cell-matrix adhesions containing α5β1 to those containing αvβ3. Despite the fact that these integrins support similar levels of adhesion to Fn, only α5β1 was found to promote a contractile, fibroblastic morphology with centripetal orientation of cell-matrix adhesions⁸ (Fig. 1). Moreover, RhoA activity is high in the presence of α5β1 and these cells move in a random fashion with a speed of around 25 mm/h. By contrast, in cells using αvβ3 instead, adhesions distribute across the ventral surface, RhoA activity is low, and these cells move with similar speed but in a highly persistent fashion.^8,9 Finally, photobleaching experiments using GFP-vinculin and GFP-paxillin demonstrated that cell-matrix adhesions containing α5β1 are highly dynamic whereas adhesions containing αvβ3 are more static.⁹Open in a separate windowFigure 1Immunofluorescence images. GE11 cells, epithelial β1 knockout cells derived from mouse embryos chimeric for the integrin β1 subunit endogenously express various av integrins, including low levels of αvβ3 and αvβ5. Ectopic expression of β1 leads to expression of α5β1 and induced α5β1-mediated adhesion to Fn (left image) whereas ectopic expression of β3 (in the β1 null background) leads to strong expression of αvβ3 and induced αvβ3-mediated adhesion to Fn (right image). Adhesions containing either α5β1 or αvβ3 show distinct distribution and dynamics (paxillin; green) and cause different F-actin organization (phalloidin; red). Cartoons: Differences in cell-matrix adhesion dynamics may be explained by differential binding of soluble Fn molecules (blue) or different molecular determinants of the interaction with immobilized Fn (red). See text for details.It has been observed that α5β1 and αvβ3 use different recycling routes. Interfering with Rab4-mediated recycling of αvβ3 causes increased Rab11-mediated recycling of α5β1 to the cell surface. In agreement with our findings, the shift to α5β1 leads to increased Rho-ROCK activity and reduced persistence of migration.¹⁰ One possible explanation for the different types of migration promoted by these two Fn-binding integrins might involve different signaling and/or adaptor proteins interacting with specific amino acids in their cytoplasmic tails. However, this appears not to be the case: α5β1 in which the cytoplasmic tails of α5 or β1 are replaced by those of αv or β3, respectively, behaves identical to wild type α5β1: it promotes a fibroblast-like morphology with centripetal orientation of cell-matrix adhesions and it drives a non-persistent mode of migration.^8,11 Together, these findings point to differences between α5β1 and αvβ3 integrins in the mechanics of their interaction with Fn, which apparently modulates intracellular signaling pathways in control of cell-matrix adhesion dynamics and cell migration.How might this work? It turns out that although α5β1 and αvβ3 similarly support cell adhesion to immobilized (stretched) Fn, only α5β1 efficiently binds soluble, folded (“inactive”) Fn.¹¹ We have proposed that such interactions with soluble Fn molecules (possibly secreted by the cell itself) may weaken the interaction with the immobilized ligand thereby causing enhanced cell-matrix adhesion dynamics in the presence of α5β1,¹¹ (Fig. 1). Preferential binding of soluble Fn by α5β1 could be explained by differences in accessibility of the RGD binding pocket between α5β1 (more exposed) and αvβ3 (more hidden) as suggested by others.¹² If this is the case, immobilization (“stretching”) of Fn apparently leads to reorientation of the RGD motif in such a way that it is easily accessed by both integrins.The issue is considerably complicated by the fact that other recognition motifs are present in the Fn central cell-binding domain. In addition to the RGD sequence in the tenth Fn type 3 repeat (IIIFn10), binding of α5β1, but not αvβ3, also depends on the PHSRN “synergy” sequence in IIIFn9.^13–15 The relative contribution of these motifs is controversial and there is structural data pointing either towards a model in which IIIFn9 interacts with α5β1 or towards a model in which IIIFn9 exerts long-range electrostatic steering resulting in a higher affinity interaction without contacting the integrin.^16,17 Cell adhesion studies have suggested that an interaction of α5β1 with the synergy region stabilizes the binding to RGD.^14,18 Such a two-step interaction may facilitate binding to full length, folded Fn for instance by altering the tilt angle between IIIFn9 and IIIFn10 leading to optimal exposure of the RGD loop, perhaps explaining why αvβ3 (which may not interact with the synergy site) poorly binds soluble Fn.Others have shown that the RGD motif alone is sufficient for mechanical coupling of αvβ3 to Fn whereas the synergy region is required to provide mechanical strength to the α5β1-Fn bond.¹⁹ It appears that the interaction of α5β1 with Fn is particularly dynamic with various conformations of α5β1 interacting with different Fn binding surfaces, including the RGD and synergy sequences as well as other regions in IIIFn9. Thus, besides the above model based on differential binding to soluble Fn molecules, differences in the complexity and dynamics of interactions with immobilized Fn that determine functional binding strength could also underlie the different dynamics of cell-matrix adhesions containing either α5β1 or αvβ3 (Fig. 1).Precisely how mechanical differences in receptor-ligand interactions result in such remarkably distinct cellular responses is poorly understood. In addition to effects on cell-matrix adhesion dynamics and cytoskeletal organization it is also associated with different activities of Rho GTPases, indicating that mechanical differences between these two integrins must translate into differential activation of intracellular signaling pathways.^8,9,11 Possibly, different adhesion dynamics due to distinct mechanisms of receptor-ligand interaction result in different patterns of F-actin organization, which, in turn, affects the formation of signaling platforms. It is also possible that differences in the extent of integrin clustering have an impact on the conformation of one or more cytoplasmic components of the cell-matrix adhesions containing either α5β1 or αvβ3. This could lead to hiding or exposing binding sites for signaling molecules (e.g., upstream regulators of Rho GTPases) or substrates. Whatever the mechanism involved, altering the integrin composition of cell-matrix adhesions through shifts in integrin expression as observed during development, angiogenesis, wound healing and cancer progression may be a driving force in the enhanced cell migration that characterizes those processes.     

An adenosine kinase mutation in baby hamster kidney cells causing increased sensitivity to adenosine

A class of aravinosyladenine (araA)-resistant mutants of baby hamster kidney (BHK 21/C13) cells exhibits multiple phenotypes: resistance to araA and deoxyadenosine, extreme sensitivity to adenosine (Ado) and varying degrees of deficiency in adenosine kinase (AK) activity. One of these Ado^s/araA^r strains, ara-S10d, was isolated without mutagenesis and was shown to possess about 59% level of the wild-type AK activity. The AK from ara-S10d had an altered K_m and pH optimum and was stimulated by K⁺ cations. A number of Ado^s to Ado^r revertants were isolated from araS10d, and in all of the 7 examined, the AK activity was reduced to a nondetectable level. The altered kinetic parameters of the AK enzyme in ara-S10d cells suggest a mutation of the AK gene that leads to the synthesis of an altered enzyme. The loss of AK activity in the Ado^r revertants suggests an association of the enhanced Ado sensitivity to the AK mutation.     

Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.     

BtcA,A Class IA Type III Chaperone,Interacts with the BteA N-Terminal Domain through a Globular/Non-Globular Mechanism

Bordetella pertussis, the etiological agent of “whooping cough” disease, utilizes the type III secretion system (T3SS) to deliver a 69 kDa cytotoxic effector protein, BteA, directly into the host cells. As with other T3SS effectors, prior to its secretion BteA binds BtcA, a 13.9 kDa protein predicted to act as a T3SS class IA chaperone. While this interaction had been characterized for such effector-chaperone pairs in other pathogens, it has yet to be fully investigated in Bordetella. Here we provide the first biochemical proof that BtcA is indeed a class IA chaperone, responsible for the binding of BteA''s N-terminal domain. We bring forth extensive evidence that BtcA binds its substrate effector through a dual-interface binding mechanism comprising of non-globular and bi-globular interactions at a moderate micromolar level binding affinity. We demonstrate that the non-globular interactions involve the first 31 N-terminal residues of BteA287 and their removal leads to destabilization of the effector-chaperone complex and lower binding affinities to BtcA. These findings represent an important first step towards a molecular understanding of BteA secretion and cell entry.