[Risk factors and sonographic findings associated with the type of placenta accreta spectrum disorders]

Objective: To evaluate the risk factors and sonographic findings of pregnancies complicated by placenta increta or placenta percreta. Methods: Totally, 2 219 cases were retrospectively analyzed from 20 tertiary hospitals in China from January 2011 to December 2015. The data were collected based on the original case records. All cases were divided into two groups, the placenta increta (PI) group (79.1%, 1 755/2 219) and the placenta percreta (PP) group (20.9%, 464/2 219) , according to the degree of placental implantation. The risk factors and sonographic findings of placenta increta or percreta were analyzed by uni-factor and logistic regression statistic methods. Results: The risk factors associated with the degree of placental implantation were age, gravida, previous abortion or miscarriage, previous cesarean sections, and placenta previa (all P<0.05), especially, previous cesarean sections (χ(2)=157.961) and placenta previa (χ(2)=91.759). Sonographic findings could be used to predict the degree of placental invasion especially the boundaries between placenta and uterine serosa, the boundary between placenta and myometrium, the disruption of the placental-uterine wall interface and loss of the normal retroplacental hypoechoic zone(all P<0.01). Conclusions: Previous cesarean sections and placenta previa are the main independent risk factors associated with the degree of placenta implantation. Ultrasound could be used to make a prenatal suggestive diagnosis of placenta accreta spectrum disorders.

Optical and physical mapping with local finishing enables megabase-scale resolution of agronomically important regions in the wheat genome

BACKGROUND

Numerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome.

RESULTS

Using chromosome 7A of wheat as a model, sequence-finished megabase-scale sections of this chromosome were established by combining a new independent assembly using a bacterial artificial chromosome (BAC)-based physical map, BAC pool paired-end sequencing, chromosome-arm-specific mate-pair sequencing and Bionano optical mapping with the International Wheat Genome Sequencing Consortium RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region.

CONCLUSIONS

Sufficient genome sequence information is shown to now be available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and that yield attributes are affected by five F-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.

MAGIC populations in crops: current status and future prospects

MAGIC populations present novel challenges and opportunities in crops due to their complex pedigree structure. They offer great potential both for dissecting genomic structure and for improving breeding populations. The past decade has seen the rise of multiparental populations as a study design offering great advantages for genetic studies in plants. The genetic diversity of multiple parents, recombined over several generations, generates a genetic resource population with large phenotypic diversity suitable for high-resolution trait mapping. While there are many variations on the general design, this review focuses on populations where the parents have all been inter-mated, typically termed Multi-parent Advanced Generation Intercrosses (MAGIC). Such populations have already been created in model animals and plants, and are emerging in many crop species. However, there has been little consideration of the full range of factors which create novel challenges for design and analysis in these populations. We will present brief descriptions of large MAGIC crop studies currently in progress to motivate discussion of population construction, efficient experimental design, and genetic analysis in these populations. In addition, we will highlight some recent achievements and discuss the opportunities and advantages to exploit the unique structure of these resources post-QTL analysis for gene discovery.

Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL

Background

Next-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL.

Results

We use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino acid alterations between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy.

Conclusions

The efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0665-6) contains supplementary material, which is available to authorized users.

ELF3 controls thermoresponsive growth in Arabidopsis

Plant development is highly responsive to ambient temperature, and this trait has been linked to the ability of plants to adapt to climate change. The mechanisms by which natural populations modulate their thermoresponsiveness are not known. To address this, we surveyed Arabidopsis accessions for variation in thermal responsiveness of elongation growth and mapped the corresponding loci. We find that the transcriptional regulator EARLY FLOWERING3 (ELF3) controls elongation growth in response to temperature. Through a combination of modeling and experiments, we show that high temperature relieves the gating of growth at night, highlighting the importance of temperature-dependent repressors of growth. ELF3 gating of transcriptional targets responds rapidly and reversibly to changes in temperature. We show that the binding of ELF3 to target promoters is temperature dependent, suggesting a mechanism where temperature directly controls ELF3 activity.

The surprising benefit of passive-aggressive behaviour at Christmas parties: being crowned king of the crackers

OBJECTIVE

To test the effects of technique and attitude in pulling Christmas crackers.

DESIGN, SETTING AND PARTICIPANTS

A binomial trial conducted at a Christmas-in-July dinner party involving five anonymous dinner guests, including two of the authors.

MAIN OUTCOME MEASURE

Number of wins achieved by different strategies, with a win defined as securing the larger portion of the cracker.

RESULTS

The previously "guaranteed" strategy for victory, employing a downwards angle towards the puller, failed to differentiate itself from random chance (win rate, 6/15; probability of winning, 0.40; 95% CI, 0.15-0.65). A novel passive-aggressive strategy, in which one individual just holds on without pulling, provided a significant advantage (win rate, 11/12; probability of winning, 0.92; 95% CI, 0.76-1.00).

CONCLUSION

The passive-aggressive strategy of failing to pull has a high rate of success at winning Christmas crackers; however, excessive adoption of this approach will result in a complete failure, with no winners at all.

Computationally efficient map construction in the presence of segregation distortion

We present a novel estimator for map construction in the presence of segregation distortion which is highly computationally efficient. For multi-parental designs this estimator outperforms methods that do not account for segregation distortion, at no extra computational cost. Inclusion of genetic markers exhibiting segregation distortion in a linkage map can result in biased estimates of genetic distance and distortion of map positions. Removal of distorted markers is hence a typical filtering criterion; however, this may result in exclusion of biologically interesting regions of the genome such as introgressions and translocations. Estimation of additional parameters characterizing the distortion is computationally slow, as it relies on estimation via the Expectation Maximization algorithm or a higher dimensional numerical optimisation. We propose a robust M-estimator (RM) capable of handling tens of thousands of distorted markers from a single linkage group. We show via simulation that for multi-parental designs the RM estimator can perform much better than uncorrected estimation, at no extra computational cost. We then apply the RM estimator to chromosome 2B in wheat in a multi-parent population segregating for the Sr36 introgression, a known transmission distorter. The resulting map contains over 700 markers, and is consistent with maps constructed from crosses which do not exhibit segregation distortion.

QTLs for tolerance of drought and breeding for tolerance of abiotic and biotic stress: an integrated approach

Background

The coupling of biotic and abiotic stresses leads to high yield losses in rainfed rice (Oryza sativa L.) growing areas. While several studies target these stresses independently, breeding strategies to combat multiple stresses seldom exist. This study reports an integrated strategy that combines QTL mapping and phenotypic selection to develop rice lines with high grain yield (GY) under drought stress and non-stress conditions, and tolerance of rice blast.

Methodology

A blast-tolerant BC₂F₃-derived population was developed from the cross of tropical japonica cultivar Moroberekan (blast- and drought-tolerant) and high-yielding indica variety Swarna (blast- and drought-susceptible) through phenotypic selection for blast tolerance at the BC₂F₂ generation. The population was studied for segregation distortion patterns and QTLs for GY under drought were identified along with study of epistatic interactions for the trait.

Results

Segregation distortion, in favour of Moroberekan, was observed at 50 of the 59 loci. Majority of these marker loci co-localized with known QTLs for blast tolerance or NBS-LRR disease resistance genes. Despite the presence of segregation distortion, high variation for DTF, PH and GY was observed and several QTLs were identified under drought stress and non-stress conditions for the three traits. Epistatic interactions were also detected for GY which explained a large proportion of phenotypic variance observed in the population.

Conclusions

This strategy allowed us to identify QTLs for GY along with rapid development of high-yielding purelines tolerant to blast and drought with considerably reduced efforts. Apart from this, it also allowed us to study the effects of the selection cycle for blast tolerance. The developed lines were screened at IRRI and in the target environment, and drought and blast tolerant lines with high yield were identified. With tolerance to two major stresses and high yield potential, these lines may provide yield stability in rainfed rice areas.

Selecting subsets of genotyped experimental populations for phenotyping to maximize genetic diversity

Selective phenotyping is a way of capturing the benefits of large population sizes without the need to carry out large-scale phenotyping and hence is a cost-effective means of capturing information about gene-trait relationships within a population. The diversity within the sample gives an indication of the efficiency of this information capture; less diversity implies greater redundancy of the genetic information. Here, we propose a method to maximize genetic diversity within the selected samples. Our method is applicable to general experimental designs and robust to common problems such as missing data and dominant markers. In particular, we discuss its application to multi-parent advanced generation intercross (MAGIC) populations, where, although thousands of lines may be genotyped as a large population resource, only hundreds may need to be phenotyped for individual studies. Through simulation, we compare our method to simple random sampling and the minimum moment aberration method. While the gain in power over simple random sampling for all tested methods is not large, our method results in a much more diverse sample of genotypes. This diversity can be applied to improve fine mapping resolution once a QTL region has been detected. Further, when applied to two wheat datasets from doubled haploid and MAGIC progeny, our method detects known QTL for small sample sizes where other methods fail.

Delay discounting, impulsiveness, and addiction severity in opioid-dependent patients

Individuals who abuse drugs show higher delay discounting (DD) rate and impulsiveness scores compared with controls; however, it is unclear if DD rate covaries with severity of the addiction or if an individual's discounting rate can be changed by effective substance abuse treatment. This study compared methadone maintenance treatment (MMT) patients (n = 30) who had not used illegal drugs for 2 years with drug-using MMT patients (n = 30) and controls (n = 25) in terms of addiction severity, DD rate, and impulsiveness. Methadone patients abstinent from illegal drugs scored significantly lower on a number of addiction severity measures than the drug-using methadone patients. In addition, both groups of MMT patients showed significantly higher rates of DD and impulsiveness than the control group; however, no differences in DD rate or impulsiveness were found between the groups of patients. Results suggest that DD rate and impulsiveness may not covary with indicators of addiction severity in MMT patients.

R/mpMap: a computational platform for the genetic analysis of multiparent recombinant inbred lines

Multiparent crosses of recombinant inbred lines provide opportunity to map markers and quantitative trait loci (QTL) with much greater resolution than is possible in biparental crosses. Realizing the full potential of these crosses requires computational tools capable of handling the increased statistical complexity of the analyses. R/mpMap provides a flexible and extensible environment, which interfaces easily with other packages to satisfy this demand. Functions in the package encompass simulation, marker map construction, haplotype reconstruction and QTL mapping. We demonstrate the easy-to-use features of mpMap through a simulated data example.

AVAILABILITY

www.cmis.csiro.au/mpMap.

The effect of a high-fat meal on postprandial arterial stiffness in men with obesity and type 2 diabetes

CONTEXT

Postprandial dysmetabolism is emerging as an important cardiovascular risk factor. Augmentation index (AIx) is a measure of systemic arterial stiffness and independently predicts cardiovascular outcome.

OBJECTIVE

The objective of this study was to assess the effect of a standardized high-fat meal on metabolic parameters and AIx in 1) lean, 2) obese nondiabetic, and 3) subjects with type 2 diabetes mellitus (T2DM).

DESIGN AND SETTING

Male subjects (lean, n = 8; obese, n = 10; and T2DM, n = 10) were studied for 6 h after a high-fat meal and water control. Glucose, insulin, triglycerides, and AIx (radial applanation tonometry) were measured serially to determine the incremental area under the curve (iAUC).

RESULTS

AIx decreased in all three groups after a high-fat meal. A greater overall postprandial reduction in AIx was seen in lean and T2DM compared with obese subjects (iAUC, 2251 +/- 1204, 2764 +/- 1102, and 1187 +/- 429% . min, respectively; P < 0.05). The time to return to baseline AIx was significantly delayed in subjects with T2DM (297 +/- 68 min) compared with lean subjects (161 +/- 88 min; P < 0.05). There was a significant correlation between iAUC AIx and iAUC triglycerides (r = 0.50; P < 0.05).

CONCLUSIONS

Obesity is associated with an attenuated overall postprandial decrease in AIx. Subjects with T2DM have a preserved, but significantly prolonged, reduction in AIx after a high-fat meal. The correlation between AIx and triglycerides suggests that postprandial dysmetabolism may impact on vascular dynamics. The markedly different response observed in the obese subjects compared with those with T2DM was unexpected and warrants additional evaluation.

Look before you leap: a new approach to mapping QTL

In this paper, we present an innovative and powerful approach for mapping quantitative trait loci (QTL) in experimental populations. This deviates from the traditional approach of (composite) interval mapping which uses a QTL profile to simultaneously determine the number and location of QTL. Instead, we look before we leap by employing separate detection and localization stages. In the detection stage, we use an iterative variable selection process coupled with permutation to identify the number and synteny of QTL. In the localization stage, we position the detected QTL through a series of one-dimensional interval mapping scans. Results from a detailed simulation study and real analysis of wheat data are presented. We achieve impressive increases in the power of QTL detection compared to composite interval mapping. We also accurately estimate the size and position of QTL. An R library, DLMap, implements the methods described here and is freely available from CRAN ( http://cran.r-project.org/ ).

Detecting haplotype effects in genomewide association studies

The analysis of genomewide association studies requires methods that are both computationally feasible and statistically powerful. Given the large-scale collection of single nucleotide polymorphisms (SNPs), it is desirable to explore the information contained in their interrelationships. In particular, utilizing haplotypes rather than individual SNPs and accounting for correlations of polymorphisms in adjustment for multiple testing can lead to increased power. We present a statistically powerful and numerically efficient method based on sliding windows of adjacent SNPs to detect haplotype-disease association in genomewide studies. This method consists of an efficient algorithm to calculate a proper likelihood-ratio statistic for any given window of SNPs, along with an accurate and efficient Monte Carlo procedure to adjust for multiple testing. Simulation studies using the HapMap data showed that the proposed method performs well in realistic situations. We applied the new method to a case-control study on rheumatoid arthritis and identified several loci worthy of further investigations.

Efficient association mapping of quantitative trait loci with selective genotyping

Selective genotyping (i.e., genotyping only those individuals with extreme phenotypes) can greatly improve the power to detect and map quantitative trait loci in genetic association studies. Because selection depends on the phenotype, the resulting data cannot be properly analyzed by standard statistical methods. We provide appropriate likelihoods for assessing the effects of genotypes and haplotypes on quantitative traits under selective-genotyping designs. We demonstrate that the likelihood-based methods are highly effective in identifying causal variants and are substantially more powerful than existing methods.

Interleukin-1 polymorphisms are associated with the inflammatory response in human muscle to acute resistance exercise

Inflammation appears to play an important role in the repair and regeneration of skeletal muscle after damage. We tested the hypothesis that the severity of the inflammatory response in muscle after an acute bout of resistance exercise is associated with single nucleotide polymorphisms (SNPs) previously shown to alter interleukin-1 (IL-1) activity. Using a double-blind prospective design, sedentary young men were screened (n = 100) for enrolment (n = 24) based upon having 1 of 4 haplotype patterns composed of five polymorphic sites in the IL-1 gene cluster: IL-1A (+4845), IL-1B (+3954), IL-1B (-511), IL-1B (-3737) and IL-1RN (+2018). Subjects performed a standard bout of resistance leg exercise and vastus lateralis biopsies were obtained pre-, and at 24, and 72 h post-exercise. Inflammatory marker mRNAs (IL-1beta, IL-6 and tumor necrosis factor-alpha (TNF-alpha)) and the number of CD68(+) macrophages were quantified. Considerable variation was observed in the expression of these gene products between subjects. At 72 h post-exercise, IL-1beta had increased in a number of subjects (n = 10) and decreased (n = 4) or did not change (n = 10) in others. Inflammatory responses were significantly associated with specific haplotype patterns and were also influenced by individual SNPs. Subjects with genotypes 1.1 at IL-1B (+3954) or 2.2 at IL-1B (-3737) had approximately a 2-fold higher median induction of several markers, but no increase in macrophages, suggesting that cytokine gene expression is elevated per macrophage. The IL-1RN (+2018) SNP maximized the response specifically within these groups and was associated with increased macrophage recruitment. This is the first report that IL-1 genotype is associated with the inflammation of skeletal muscle following acute resistance exercise that may potentially affect the adaptations to chronic resistance exercise.