Phytoplasma effector SAP54 induces indeterminate leaf-like flower development in Arabidopsis plants

Phytoplasmas are insect-transmitted bacterial plant pathogens that cause considerable damage to a diverse range of agricultural crops globally. Symptoms induced in infected plants suggest that these phytopathogens may modulate developmental processes within the plant host. We report herein that Aster Yellows phytoplasma strain Witches' Broom (AY-WB) readily infects the model plant Arabidopsis (Arabidopsis thaliana) ecotype Columbia, inducing symptoms that are characteristic of phytoplasma infection, such as the production of green leaf-like flowers (virescence and phyllody) and increased formation of stems and branches (witches' broom). We found that the majority of genes encoding secreted AY-WB proteins (SAPs), which are candidate effector proteins, are expressed in Arabidopsis and the AY-WB insect vector Macrosteles quadrilineatus (Hemiptera; Cicadellidae). To identify which of these effector proteins induce symptoms of phyllody and virescence, we individually expressed the effector genes in Arabidopsis. From this screen, we have identified a novel AY-WB effector protein, SAP54, that alters floral development, resulting in the production of leaf-like flowers that are similar to those produced by plants infected with this phytoplasma. This study offers novel insight into the effector profile of an insect-transmitted plant pathogen and reports to our knowledge the first example of a microbial pathogen effector protein that targets flower development in a host.     

Predominant genera of fecal microbiota in children with atopic dermatitis are not altered by intake of probiotic bacteria Lactobacillus acidophilus NCFM and Bifidobacterium animalis subsp. lactis Bi-07

The effect of probiotic bacteria Lactobacillus acidophilus NCFM and Bifidobacterium lactis Bi-07 on the composition of the Lactobacillus group, Bifidobacterium and the total bacterial population in feces from young children with atopic dermatitis was investigated. The study included 50 children randomized to intake of one of the probiotic strain or placebo. Microbial composition was characterized by denaturing gradient gel electrophoresis, quantitative PCR and, in a subset of subjects, by pyrosequencing of the 16S rRNA gene. The core population of the Lactobacillus group was identified as Lactobacillus gasseri, Lactobacillus fermentum, Lactobacillus oris, Leuconostoc mesenteroides, while the bifidobacterial community included Bifidobacterium adolescentis, Bifidobacterium bifidum, Bifidobacterium longum and Bifidobacterium catenulatum. The fecal numbers of L. acidophilus and B. lactis increased significantly after intervention, indicating survival of the ingested bacteria. The levels of Bifidobacterium correlated positively (P=0.03), while the levels of the Lactobacillus group negatively (P=0.01) with improvement of atopic eczema evaluated by the Severity Scoring of Atopic Dermatitis index. This correlation was observed across the whole study cohort and not attributed to the probiotic intake. The main conclusion of the study is that administration of L. acidophilus NCFM and B. lactis Bi-07 does not affect the composition and diversity of the main bacterial populations in feces.     

Concordance analysis for QTL detection in dairy cattle: a case study of leg morphology

Background

The present availability of sequence data gives new opportunities to narrow down from QTL (quantitative trait locus) regions to causative mutations. Our objective was to decrease the number of candidate causative mutations in a QTL region. For this, a concordance analysis was applied for a leg conformation trait in dairy cattle. Several QTL were detected for which the QTL status (homozygous or heterozygous for the QTL) was inferred for each individual. Subsequently, the inferred QTL status was used in a concordance analysis to reduce the number of candidate mutations.

Methods

Twenty QTL for rear leg set side view were mapped using Bayes C. Marker effects estimated during QTL mapping were used to infer the QTL status for each individual. Subsequently, polymorphisms present in the QTL regions were extracted from the whole-genome sequences of 71 Holstein bulls. Only polymorphisms for which the status was concordant with the QTL status were kept as candidate causative mutations.

Results

QTL status could be inferred for 15 of the 20 QTL. The number of concordant polymorphisms differed between QTL and depended on the number of QTL statuses that could be inferred and the linkage disequilibrium in the QTL region. For some QTL, the concordance analysis was efficient and narrowed down to a limited number of candidate mutations located in one or two genes, while for other QTL a large number of genes contained concordant polymorphisms.

Conclusions

For regions for which the concordance analysis could be performed, we were able to reduce the number of candidate mutations. For part of the QTL, the concordant analyses narrowed QTL regions down to a limited number of genes, of which some are known for their role in limb or skeletal development in humans and mice. Mutations in these genes are good candidates for QTN (quantitative trait nucleotides) influencing rear leg set side view.     

Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers

Background

Although the X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. In this study, we presented a method for computing genomic relationships using X chromosome markers, investigated the accuracy of imputation from a low density (7K) to the 54K SNP (single nucleotide polymorphism) panel, and compared the accuracy of genomic prediction with and without using X chromosome markers.

Methods

The impact of considering X chromosome markers on prediction accuracy was assessed using data from Nordic Holstein bulls and different sets of SNPs: (a) the 54K SNPs for reference and test animals, (b) SNPs imputed from the 7K to the 54K SNP panel for test animals, (c) SNPs imputed from the 7K to the 54K panel for half of the reference animals, and (d) the 7K SNP panel for all animals. Beagle and Findhap were used for imputation. GBLUP (genomic best linear unbiased prediction) models with or without X chromosome markers and with or without a residual polygenic effect were used to predict genomic breeding values for 15 traits.

Results

Averaged over the two imputation datasets, correlation coefficients between imputed and true genotypes for autosomal markers, pseudo-autosomal markers, and X-specific markers were 0.971, 0.831 and 0.935 when using Findhap, and 0.983, 0.856 and 0.937 when using Beagle. Estimated reliabilities of genomic predictions based on the imputed datasets using Findhap or Beagle were very close to those using the real 54K data. Genomic prediction using all markers gave slightly higher reliabilities than predictions without X chromosome markers. Based on our data which included only bulls, using a G matrix that accounted for sex-linked relationships did not improve prediction, compared with a G matrix that did not account for sex-linked relationships. A model that included a polygenic effect did not recover the loss of prediction accuracy from exclusion of X chromosome markers.

Conclusions

The results from this study suggest that markers on the X chromosome contribute to accuracy of genomic predictions and should be used for routine genomic evaluation.     

Mortality after Parental Death in Childhood: A Nationwide Cohort Study from Three Nordic Countries

Background

Bereavement by spousal death and child death in adulthood has been shown to lead to an increased risk of mortality. Maternal death in infancy or parental death in early childhood may have an impact on mortality but evidence has been limited to short-term or selected causes of death. Little is known about long-term or cause-specific mortality after parental death in childhood.

Methods and Findings

This cohort study included all persons born in Denmark from 1968 to 2008 (n = 2,789,807) and in Sweden from 1973 to 2006 (n = 3,380,301), and a random sample of 89.3% of all born in Finland from 1987 to 2007 (n = 1,131,905). A total of 189,094 persons were included in the exposed cohort when they lost a parent before 18 years old. Log-linear Poisson regression was used to estimate mortality rate ratio (MRR). Parental death was associated with a 50% increased all-cause mortality (MRR = 1.50, 95% CI 1.43–1.58). The risks were increased for most specific cause groups and the highest MRRs were observed when the cause of child death and the cause of parental death were in the same category. Parental unnatural death was associated with a higher mortality risk (MRR = 1.84, 95% CI 1.71–2.00) than parental natural death (MRR = 1.33, 95% CI 1.24–1.41). The magnitude of the associations varied according to type of death and age at bereavement over different follow-up periods. The main limitation of the study is the lack of data on post-bereavement information on the quality of the parent-child relationship, lifestyles, and common physical environment.

Conclusions

Parental death in childhood or adolescence is associated with increased all-cause mortality into early adulthood. Since an increased mortality reflects both genetic susceptibility and long-term impacts of parental death on health and social well-being, our findings have implications in clinical responses and public health strategies. Please see later in the article for the Editors'' Summary     

A 660-Kb Deletion with Antagonistic Effects on Fertility and Milk Production Segregates at High Frequency in Nordic Red Cattle: Additional Evidence for the Common Occurrence of Balancing Selection in Livestock

In dairy cattle, the widespread use of artificial insemination has resulted in increased selection intensity, which has led to spectacular increase in productivity. However, cow fertility has concomitantly severely declined. It is generally assumed that this reduction is primarily due to the negative energy balance of high-producing cows at the peak of lactation. We herein describe the fine-mapping of a major fertility QTL in Nordic Red cattle, and identify a 660-kb deletion encompassing four genes as the causative variant. We show that the deletion is a recessive embryonically lethal mutation. This probably results from the loss of RNASEH2B, which is known to cause embryonic death in mice. Despite its dramatic effect on fertility, 13%, 23% and 32% of the animals carry the deletion in Danish, Swedish and Finnish Red Cattle, respectively. To explain this, we searched for favorable effects on other traits and found that the deletion has strong positive effects on milk yield. This study demonstrates that embryonic lethal mutations account for a non-negligible fraction of the decline in fertility of domestic cattle, and that associated positive effects on milk yield may account for part of the negative genetic correlation. Our study adds to the evidence that structural variants contribute to animal phenotypic variation, and that balancing selection might be more common in livestock species than previously appreciated.     

Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle

Background

The advent of low cost next generation sequencing has made it possible to sequence a large number of dairy and beef bulls which can be used as a reference for imputation of whole genome sequence data. The aim of this study was to investigate the accuracy and speed of imputation from a high density SNP marker panel to whole genome sequence level. Data contained 132 Holstein, 42 Jersey, 52 Nordic Red and 16 Brown Swiss bulls with whole genome sequence data; 16 Holstein, 27 Jersey and 29 Nordic Reds had previously been typed with the bovine high density SNP panel and were used for validation. We investigated the effect of enlarging the reference population by combining data across breeds on the accuracy of imputation, and the accuracy and speed of both IMPUTE2 and BEAGLE using either genotype probability reference data or pre-phased reference data. All analyses were done on Bovine autosome 29 using 387,436 bi-allelic variants and 13,612 SNP markers from the bovine HD panel.

Results

A combined breed reference population led to higher imputation accuracies than did a single breed reference. The highest accuracy of imputation for all three test breeds was achieved when using BEAGLE with un-phased reference data (mean genotype correlations of 0.90, 0.89 and 0.87 for Holstein, Jersey and Nordic Red respectively) but IMPUTE2 with un-phased reference data gave similar accuracies for Holsteins and Nordic Red. Pre-phasing the reference data only lead to a minor decrease in the imputation accuracy, but gave a large improvement in computation time. Pre-phasing with BEAGLE was substantially faster than pre-phasing with SHAPEIT2 (2.5 hours vs. 52 hours for 242 individuals), and imputation with pre-phased data was faster in IMPUTE2 than in BEAGLE (5 minutes vs. 50 minutes per individual).

Conclusion

Combining reference populations across breeds is a good option to increase the size of the reference data and in turn the accuracy of imputation when only few animals are available. Pre-phasing the reference data only slightly decreases the accuracy but gives substantial improvements in speed. Using BEAGLE for pre-phasing and IMPUTE2 for imputation is a fast and accurate strategy.     

Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg⁻¹ was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg⁻¹ at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg⁻¹ was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha⁻¹ and in the top 1 m there was 120 t SOC ha⁻¹. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.     

Tissue MicroRNAs as Predictors of Outcome in Patients with Metastatic Colorectal Cancer Treated with First Line Capecitabine and Oxaliplatin with or without Bevacizumab

Purpose

We tested the hypothesis that expression of microRNAs (miRNAs) in cancer tissue can predict effectiveness of bevacizumab added to capecitabine and oxaliplatin (CAPEOX) in patients with metastatic colorectal cancer (mCRC).

Experimental Design

Patients with mCRC treated with first line CAPEOX and bevacizumab (CAPEOXBEV): screening (n = 212) and validation (n = 121) cohorts, or CAPEOX alone: control cohort (n = 127), were identified retrospectively and archival primary tumor samples were collected. Expression of 754 miRNAs was analyzed in the screening cohort using polymerase chain reaction (PCR) arrays and expression levels were related to time to disease progression (TTP) and overall survival (OS). Significant miRNAs from the screening study were analyzed in all three cohorts using custom PCR arrays. In situ hybridization (ISH) was done for selected miRNAs.

Results

In the screening study, 26 miRNAs were significantly correlated with outcome in multivariate analyses. Twenty-two miRNAs were selected for further study. Higher miR-664-3p expression and lower miR-455-5p expression were predictive of improved outcome in the CAPEOXBEV cohorts and showed a significant interaction with bevacizumab effectiveness. The effects were strongest for OS. Both miRNAs showed high expression in stromal cells. Higher expression of miR-196b-5p and miR-592 predicted improved outcome regardless of bevacizumab treatment, with similar effect estimates in all three cohorts.

Conclusions

We have identified potentially predictive miRNAs for bevacizumab effectiveness and additional miRNAs that could be related to chemotherapy effectiveness or prognosis in patients with mCRC. Our findings need further validation in large cohorts, preferably from completed randomized trials.