Consensus Map Research Articles

A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes.

Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.

A consensus map for quality traits in durum wheat based on genome-wide association studies and detection of ortho-meta QTL across cereal species.

The present work focused on the identification of durum wheat QTL hotspots from a collection of genome-wide association studies, for quality traits, such as grain protein content and composition, yellow color, fiber, grain microelement content (iron, magnesium, potassium, selenium, sulfur, calcium, cadmium), kernel vitreousness, semolina, and dough quality test. For the first time a total of 10 GWAS studies, comprising 395 marker-trait associations (MTA) on 57 quality traits, with more than 1,500 genotypes from 9 association panels, were used to investigate consensus QTL hotspots representative of a wide durum wheat genetic variation. MTA were found distributed on all the A and B genomes chromosomes with minimum number of MTA observed on chromosome 5B (15) and a maximum of 45 on chromosome 7A, with an average of 28 MTA per chromosome. The MTA were equally distributed on A (48%) and B (52%) genomes and allowed the identification of 94 QTL hotspots. Synteny maps for QTL were also performed in Zea mays, Brachypodium, and Oryza sativa, and candidate gene identification allowed the association of genes involved in biological processes playing a major role in the control of quality traits.

Delineating meta-quantitative trait loci for anthracnose resistance in common bean (Phaseolus vulgaris L.).

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, is one of the devastating disease affecting common bean production and productivity worldwide. Several quantitative trait loci (QTLs) for anthracnose resistance have been identified. In order to make use of these QTLs in common bean breeding programs, a detailed meta-QTL (MQTL) analysis has been conducted. For the MQTL analysis, 92 QTLs related to anthracnose disease reported in 18 different earlier studies involving 16 mapping populations were compiled and projected on to the consensus map. This meta-analysis led to the identification of 11 MQTLs (each involving QTLs from at least two different studies) on 06 bean chromosomes and 10 QTL hotspots each involving multiple QTLs from an individual study on 07 chromosomes. The confidence interval (CI) of the identified MQTLs was found 3.51 times lower than the CI of initial QTLs. Marker-trait associations (MTAs) reported in published genome-wide association studies (GWAS) were used to validate nine of the 11 identified MQTLs, with MQTL4.1 overlapping with as many as 40 MTAs. Functional annotation of the 11 MQTL regions revealed 1,251 genes including several R genes (such as those encoding for NBS-LRR domain-containing proteins, protein kinases, etc.) and other defense related genes. The MQTLs, QTL hotspots and the potential candidate genes identified during the present study will prove useful in common bean marker-assisted breeding programs and in basic studies involving fine mapping and cloning of genomic regions associated with anthracnose resistance in common beans.

Construction of a high-density genetic linkage map and QTL mapping for growth traits in gynogenetic brown-marbled grouper (Epinephelus fuscoguttatus)

High-density genetic linkage maps based on single nucleotide polymorphisms (SNPs) are essential for quantitative trait loci (QTL) mapping, trait-related gene identification, marker-assisted selection (MAS), genome assembly, and comparative genomic analysis in aquaculture fish species. Haploid (or gynogenesis) is an excellent germplasm target for mapping genetic linkage maps and MAS breeding. In this study, the high-density genetic linkage map of gynogenetic brown-marbled grouper (Epinephelus fuscoguttatus) based on genotyping by sequencing (GBS) technology was constructed using one F1 gynogenetic family composed of 164 gynogens and their female parents. A high-density linkage map of gynogenetic brown-marbled grouper was constructed with 19,301 SNPs located in 24 linkage groups (LGs). The genetic length of the consensus map was 2343.72 cM, with an average genetic length of 97.655 cM and an average marker interval of 0.12 cM. QTL mapping analysis revealed forty QTLs for body mass and ten phenotypic traits in 9 LGs. Multiple loci were found to be shared on LG3, LG8, LG11, LG16 and LG23, and several important growth-related candidate genes (e.g., mrc1, adgrb3, zbtb38 and adcy3), were identified within QTL regions. These vital SNPs and candidate genes may serve as useful genomic tools for marker-assisted selective breeding. Coupled breeding of MAS and artificial gynogenesis could provide a powerful method for genetic improvement in grouper breeding.

Tracking Wheat Variety and Origin by the Shape Analysis of the Volatiles Fingerprint of Wheat Kernels and Wheat Beers

The Volatile Organic Compounds (VOCs) of common wheat of different origin (variety and altitude of cultivation) and craft wheat beers produced by using the wheat themselves were analyzed by SPME GC-MS. The VOCs of wheat kernels and wheat beers were compared, and 14 common flavor-active compounds were identified. Principal component analysis was used to describe changes in the profile of common volatiles induced by beer processing. A unifying approach by Generalized Procrustes analysis (GPA), which considers the overall characteristics of the datasets, permitted linking the VOCs of wheat to those of beers and to define a common flavor pattern. Despite the beer processing deeply affecting the overall volatilome profile, a consensus map permitted to clearly classify the VOCs profile of five out of six samples. This work revealed that differences in wheat VOCs induced by wheat variety and cultivation site were reflected in different beer aromatic profiles, highlighting the importance of origin on the wheat and beers’ flavor. This unifying approach to flavor analysis by GPA could be of help in sight of a certification of origin, since it may contribute not only to the definition of wheat origin but also of the “terroir” of wheat beer thereof.

The use of wheatgrass (<i>Thinopyrum intermedium</i>) in breeding

Wheatgrass (Th. intermedium) has been traditionally used in wheat breeding for obtaining wheat-wheatgrass hybrids and varieties with introgressions of new genes for economically valuable traits. However, in the 1980s in the United States wheatgrass was selected from among perennial plant species as having promise for domestication and the development of dual-purpose varieties for grain (as an alternative to perennial wheat) and hay. The result of this work was the creation of the wheatgrass varieties Kernza (The Land Institute, Kansas) and MN-Clearwater (University of Minnesota, Minnesota). In Omsk State Agrarian University, the variety Sova was developed by mass selection of the most winter-hardy biotypes with their subsequent combination from the population of wheatgrass obtained from The Land Institute. The average grain yield of the variety Sova is 9.2 dt/ha, green mass is 210.0 dt/ ha, and hay is 71.0 dt/ha. Wheatgrass is a crop with a large production potential, benef icial environmental properties, and valuable grain for functional food. Many publications show the advantages of growing the Kernza variety compared to annual crops in reducing groundwater nitrate contamination, increasing soil carbon sequestration, and reducing energy and economic costs. However, breeding programs for domestication of perennial crops are very limited in Russia. This paper presents an overview of main tasks faced by breeders, aimed at enhancing the yield and cultivating wheatgrass eff iciency as a perennial grain and fodder crop. To address them, both traditional and modern biotechnological and molecular cytogenetic approaches are used. The most important task is to transfer target genes of Th. intermedium to modern wheat varieties and decrease the level of chromatin carrying undesirable genes of the wild relative. The f irst consensus map of wheatgrass containing 10,029 markers was obtained, which is important for searching for genes and their introgressions to the wheat genome. The results of research on the nutritional and technological properties of wheatgrass grain for the development of food products as well as the differences in the quality of wheatgrass grain and wheat grain are presented.

Investigating the Impact of the Social Media Branding on Purchase Intention in the African Context

Start-ups play an important role in providing job opportunities and promoting economic development. Social media enables start-ups to reach customers at a more affordable cost than traditional channels. The present study aims to explore the possibility of using social media for African start-ups as a marketing and branding tool and to investigate the effects of social media branding on African consumers’ purchase behaviours. Multiple studies were conducted. First, two case studies of African start-ups were made to obtain feasible business models of social media branding. Then, a qualitative pilot study was conducted to explore the consensus map of social media branding from the consumers’ perspective. Finally, a model was established and verified by employing a quantitative approach. Six constructs of trust, interaction, social support, information sharing, brand relationship, and brand engagement are identified. Among them, trust plays a crucial role in the context of African markets. By using SEM testing, the present study reveals that brand relationship and brand engagement act as mediators between social media branding factors and consumers’ purchase intentions. In Africa, the idea of branding via social media is appealing for start-ups due to the emergence and growth of various social media platforms. The present study provides an overall view of social media branding for African start-ups, including business models, consumer engagement, and consumer experience. The insights and suggestions will be beneficial for African start-ups and will contribute to the African business literature.

Mapping odorant sensitivities reveals a sparse but structured representation of olfactory chemical space by sensory input to the mouse olfactory bulb.

In olfactory systems, convergence of sensory neurons onto glomeruli generates a map of odorant receptor identity. How glomerular maps relate to sensory space remains unclear. We sought to better characterize this relationship in the mouse olfactory system by defining glomeruli in terms of the odorants to which they are most sensitive. Using high-throughput odorant delivery and ultrasensitive imaging of sensory inputs, we imaged responses to 185 odorants presented at concentrations determined to activate only one or a few glomeruli across the dorsal olfactory bulb. The resulting datasets defined the tuning properties of glomeruli - and, by inference, their cognate odorant receptors - in a low-concentration regime, and yielded consensus maps of glomerular sensitivity across a wide range of chemical space. Glomeruli were extremely narrowly tuned, with ~25% responding to only one odorant, and extremely sensitive, responding to their effective odorants at sub-picomolar to nanomolar concentrations. Such narrow tuning in this concentration regime allowed for reliable functional identification of many glomeruli based on a single diagnostic odorant. At the same time, the response spectra of glomeruli responding to multiple odorants was best predicted by straightforward odorant structural features, and glomeruli sensitive to distinct odorants with common structural features were spatially clustered. These results define an underlying structure to the primary representation of sensory space by the mouse olfactory system.

Meta-QTL for morphological traits and pharmaceutical alkaloids in periwinkle (Catharanthus roseus (L.) ‘G. Don’)

ABSTRACT Meta-analysis is a powerful method used to discern reliable genomic regions associated with quantitative traits. The objective of this study was to use a meta-QTL (MQTL) analysis method to identify the most reliable and accurate QTL controlling morphological traits and terpenoid indole alkaloids (TIAs); serpentine (S), vinblastine (VB), ajmalicine (A) and vincristine (VC) in Catharanthus roseus. A quantitative trait loci (QTL) database containing 40 QTLs retrieved from two individual mapping studies associated with 13 phytochemical and morphological traits. The results of projection of 40 putative QTLs on to the consensus genetic map showed that 18 MQTLs had a 25.88% reduction in confidence interval (CI) on C. roseus chromosomes. Co-localisation results suggested that leaves TAL and serpentine in roots (SR) with 50% and 60% frequencies were the most common QTLs associated with vindoline (V) and catharanthine (C). The MQTL.LG1.5, MQTL.LG2.2, MQTL.LG1.1, MQTL.LG1.2, MQTL.LG1.7 and MQTL.LG3.3 were the most important MQTLs and the most reliable chromosome regions for refining genetic control of the tested traits in C. roseus. The consensus map provided information for the identification of the QTL-dense genomic regions that will assist in improving the efficiency of genomic and marker-assisted selection (MAS) in pharmacological researches.

Predicting distributions of blacklegged ticks (Ixodes scapularis), Lyme disease spirochetes (Borrelia burgdorferi sensu stricto) and human Lyme disease cases in the eastern United States

Lyme disease is the most commonly reported vector-borne disease in the United States (US), with approximately 300,000 -to- 40,000 cases reported annually. The blacklegged tick, Ixodes scapularis, is the primary vector of the Lyme disease-causing spirochete, Borrelia burgdorferi sensu stricto, in high incidence regions in the upper midwestern and northeastern US. Using county-level records of the presence of I. scapularis or presence of B. burgdorferi s.s. infected host-seeking I. scapularis, we generated habitat suitability consensus maps based on an ensemble of statistical models for both acarological risk metrics. Overall accuracy of these suitability models was high (AUC = 0.76 for I. scapularis and 0.86 for B. burgdorferi s.s. infected-I. scapularis). We sought to compare which acarological risk metric best described the distribution of counties reporting high Lyme disease incidence (≥10 confirmed cases/100,000 population) by setting the models to a fixed omission rate (10%). We compared the percent of high incidence counties correctly classified by the two models. The I. scapularis consensus map correctly classified 53% of high and low incidence counties, while the B. burgdorferi s.s. infected-I. scapularis consensus map classified 83% correctly. Counties classified as suitable by the B. burgdorferi s.s. map showed a 91% overlap with high Lyme disease incidence counties with over a 38-fold difference in Lyme disease incidence between high- and low-suitability counties. A total of 288 counties were classified as highly suitable for B. burgdorferi s.s., but lacked records of infected-I. scapularis and were not classified as high incidence. These counties were considered to represent a leading edge for B. burgdorferi s.s. infection in ticks and humans. They clustered in Illinois, Indiana, Michigan, and Ohio. This information can aid in targeting tick surveillance and prevention education efforts in counties where Lyme disease risk may increase in the future.

Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.).

In wheat, multiple disease resistance meta-QTLs (MDR-MQTLs) and underlying candidate genes for the three rusts were identified which may prove useful for development of resistant cultivars. Rust diseases in wheat are a major threat to global food security. Therefore, development of multiple disease-resistant cultivars (resistant to all three rusts) is a major goal in all wheat breeding programs worldwide. In the present study, meta-QTLs and candidate genes for multiple disease resistance (MDR) involving all three rusts were identified using 152 individual QTL mapping studies for resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR). From these 152 studies, a total of 1,146 QTLs for resistance to three rusts were retrieved, which included 368 QTLs for LR, 291 QTLs for SR, and 487 QTLs for YR. Of these 1,146 QTLs, only 718 QTLs could be projected onto the consensus map saturated with 2, 34,619 markers. Meta-analysis of the projected QTLs resulted in the identification of 86 MQTLs, which included 71 MDR-MQTLs. Ten of these MDR-MQTLs were referred to as the 'Breeders' MQTLs'. Seventy-eight of the 86 MQTLs could also be anchored to the physical map of the wheat genome, and 54 MQTLs were validated by marker-trait associations identified during earlier genome-wide association studies. Twenty MQTLs (including 17 MDR-MQTLs) identified in the present study were co-localized with 44 known R genes. In silico expression analysis allowed identification of several differentially expressed candidate genes (DECGs) encoding proteins carrying different domains including the following: NBS-LRR, WRKY domains, F-box domains, sugar transporters, transferases, etc. The introgression of these MDR loci into high-yielding cultivars should prove useful for developing high yielding cultivars with resistance to all the three rusts.

Using ZMET to explore consumers’ cognitive model in virtual reality: take the tourism experience as an example

ABSTRACT Due to its growing application in various industries as a marketing tool, the travel industry is increasingly perceiving the potential of virtual reality (VR) in the tourism arena. Although VR has been widely discussed in practice management research, there is, however, little knowledge on how VR technology can be applied in themed tourism environments. Hence, in this study, we use the Zaltman Metaphor Elicitation Technique (ZMET) to empirically study how visitors express their inner values and meanings through VR-themed tourism. We invited 26 respondents to participate in a VR-themed tourism experience, and we organized our results based on three key themes. First, characteristics of VR-themed tourism such as ‘freedom of virtual reality’, ‘escapism of virtual reality’ and ‘anxiety of virtual reality’ were summarized. Second, an objective consensus map was created using the ‘conservative’, ‘average’ and ‘optimistic’ calculation procedures. Third, we determined the relevance of the integrated linking constructs. We found that ‘imagination’ and ‘fantasy dream’ have the highest relevance value, followed by ‘illusion’ and ‘illusionary situation’. These themes could thus provide new insights into the possible intertwined integration and complexity of ‘virtual’ and ‘physical’ issues that may arise when tourists experience VR-themed tourism.

The construction of a high-density consensus genetic map for soybean based on SNP markers derived from genotyping-by-sequencing.

Genetic linkage maps are used to localize markers on the genome based on the recombination frequency. Most often, these maps are based on the segregation observed within a single biparental population of limited size (n<300) where relatively few recombination events are sampled and in which some genomic regions are monomorphic because both parents carry the same alleles. Together, these two limitations affect both the resolution and extent of genome coverage of such maps. Consensus genetic maps overcome the limitations of individual genetic maps by merging the information from multiple segregating populations derived from a greater diversity of parental combinations, thus increasing the number of recombination events and reducing the number of monomorphic regions. The aim of this study was to construct a high-density consensus genetic map for single nucleotide polymorphism (SNP) markers obtained through a genotyping-by-sequencing (GBS) approach. Individual genetic maps were generated from six F4:5 mapping populations (n=278-365), totaling 1857 individuals. The six linkage maps were then merged to produce a consensus map comprising a total of 16 311 mapped SNPs that jointly cover 99.5% of the soybean genome with only two gaps larger than 10 cM. Compared to previous soybean consensus maps, it offers a more extensive and uniform coverage.

Consensus genetic map and QTLs for morphological and agronomical traits in mungbean using DArT markers.

Mungbean is an important but understudied food legume compared with other major grain crops. Genetic studies through development of high-through put markers, linkage map construction and QTL analysis can accelerate and improve the efficiency of mining for genes for breeding in this crop. This study used four mungbean F5 recombinant inbred lines (RILs) from crosses of two wild types (ACC 1, ACC 87) and two cultivars (Berken, Kiloga) and DArT markers to construct individual and consensus linkage maps and to identify QTLs associated with 54 traits in mungbean. The number of polymorphic DArT markers identified among the four RIL populations varied from 1062 to 2013. The individual maps covered the lengths of 629.7-883.5cM, comprising 672-981 DArT markers and 15-19 linkage groups (LG) with average distance between markers of 0.9-1.2cM. The consensus map had the total length of 795.3cM, comprising 1539 DArT markers and resolved 11 LGs with an average inter-marker distance of 0.65cM. Sixty-two QTLs were identified for 39 traits across 10 LGs of the consensus map. Major QTLs were identified for two special traits, late flowering inherited from ACC 1 (6 QTLs, PVE of 11.2-29.9%) and perenniality inherited from ACC 87 (3 QTLs, PVE of 17.4-22.6%) in separate population analysis. Number of congruent QTLs across four mungbean populations and the consensus map was 18 for 13 traits. These results illustrated the high efficiency of DArT marker application in mungbean genetic dissection and suggested the future potential employment of identified QTLs for mungbean improvement.

Potential Distribution of Invasive Boxwood Blight Pathogen (Calonectriapseudonaviculata) as Predicted by Process-Based and Correlative Models.

Simple SummaryKnowledge of where invasive species could potentially establish (potential distribution) is critical to prioritizing and addressing biological invasion threats. In this study, we predicted the potential distribution of Calonectria pseudonaviculata (Cps), an invasive fungal pathogen that blights boxwood, an iconic landscape plant, major evergreen nursery crop, and keystone forest species. We used climate data, presence records from Europe and western Asia, and multiple modeling approaches to predict the potential distribution of Cps at regional and global scales and to explore the roles of temperature and moisture in shaping its distribution. Model predictions were validated using an independent presence record dataset. A consensus map of model predictions revealed that Cps could potentially spread and establish well beyond its currently invaded range in Europe, western Asia, New Zealand, United States and Canada. These include a number of not-yet-invaded areas in eastern and southern Europe, North America, and many regions of the world where boxwood is native. This knowledge informs policymakers and other stakeholders in these areas on the need for implementing a strict phytosanitary protocol for risk mitigation of accidental introduction, having an effective surveillance for early detection, and developing a recovery plan for the pathogen when accidental introductions occur.Boxwood blight caused by Cps is an emerging disease that has had devastating impacts on Buxus spp. in the horticultural sector, landscapes, and native ecosystems. In this study, we produced a process-based climatic suitability model in the CLIMEX program and combined outputs of four different correlative modeling algorithms to generate an ensemble correlative model. All models were fit and validated using a presence record dataset comprised of Cps detections across its entire known invaded range. Evaluations of model performance provided validation of good model fit for all models. A consensus map of CLIMEX and ensemble correlative model predictions indicated that not-yet-invaded areas in eastern and southern Europe and in the southeastern, midwestern, and Pacific coast regions of North America are climatically suitable for Cps establishment. Most regions of the world where Buxus and its congeners are native are also at risk of establishment. These findings provide the first insights into Cps global invasion threat, suggesting that this invasive pathogen has the potential to significantly expand its range.

A meta-analysis of low temperature tolerance QTL in maize

BackgroundCold injury is one of the most important limiting factors for maize production in mid-high latitude regions in the world. A total of 314 QTLs for maize low temperature tolerance have been identified in different populations using different statistical methods. However, few identical QTLs have been identified in different research studies. ResultsA consensus map of QTLs related to maize low temperature tolerance was constructed, based on the public genetic map, IBM2 2008 Neighbors as a reference map, along with a set of 314 QTLs reported in the literature over the past 20 years. A total of 187 QTLs were projected onto the IBM2 2008 Neighbors by software BioMercator. Forty-seven consensus QTLs were detected. The confidence interval at all sites ranged from 0.04 cM to 102.73 cM, and the proportion of the phenotypic variance associated with each of them ranged from 3.32% to 20.11%. Major chromosomal sites were identified on Chr.6 (MQTL29, MQTL30, and MQTL31). ConclusionsThis study provides further insights into the genetic basis of maize low temperature tolerance. Moreover, the MQTLs reported here could be harnessed for functional marker development and candidate gene mining of maize low temperature tolerance.How to cite: Yu T, Zhang J, Cao J, et al. A meta-analysis of low temperature tolerance QTL in maize. Electron J Biotechnol 2022;58. https://doi.org/10.1016/j.ejbt.2022.05.002

Construction of an ultra-high-density consensus genetic map and analysis of recombination rate variation in Sorghum bicolor

Abstract. Satrio RD, Nikmah IA, Fendiyanto MH, Pratami MP, Awwanah M, Sari NIP, Farah N, Nurhadiyanta. 2022. Construction of an ultra-high-density consensus genetic map and analysis of recombination rate variation in Sorghum bicolor. Asian J Agric 6: 47-54. Sorghum is one of the most widely grown cereal crops on a global scale. A consensus map is a method for combining genetic information from multiple populations, and it is an effective way to increase genome coverage and marker density. This study constructed a consensus map by combining publicly available marker data from four mapping populations. A total of 3449 non-redundant polymorphic markers at the nucleotide level were used to construct a single consensus map on 10 sorghum chromosomes. This study generated an ultra-high-density sorghum consensus map consisting of a large number of markers spanning 1571.68 cM and averaging one marker per 0.46 cM. Due to the high density of the markers, it is only 0.06% of the markers had an interval greater than 5 cM. The rates of local recombination were estimated using a set of all markers genetic and physical positions along each of the 10 chromosomes. The analysis of the recombination rate on 10 sorghum chromosomes revealed that it decreased as the centromere position was getting closer. The consensus map generated in this study can be used to integrate information related to sorghum genetic resources and QTLs to the genome sequence, thereby accelerating the discovery of novel potential genes in sorghum.

Unravelling consensus genomic regions associated with quality traits in wheat using meta-analysis of quantitative trait loci.

Meta-analysis in wheat for three major quality traits identified 110 meta-QTL (MQTL) with reduced confidence interval (CI). Five GWAS validated MQTL (viz., 1A.1, 1B.2, 3B.4, 5B.2, and 6B.2), each involving more than 20 initial QTL and reduced CI (95%) (< 2cM), were selected for quality breeding programmes. Functional characterization including candidate gene mining and expression analysis discovered 44 high confidence candidate genes associated with quality traits. A meta-analysis of quantitative trait loci (QTL) associated with dough rheology properties, nutritional traits, and processing quality traits was conducted in wheat. For this purpose, as many as2458 QTL were collected from 50 interval mapping studies published during 2013-2020. Of the total QTL, 1126 QTL were projected onto the consensus map saturated with 249,603 markers which led to the identification of 110 meta-QTL (MQTL). These MQTL exhibited an 18.84-fold reduction in the average CI compared to the average CI of the initial QTL (ranging from 14.87 to 95.55cM with an average of 40.35cM). Of the 110, 108 MQTL were physically anchored to the wheat reference genome, including 51 MQTL verified with marker-trait associations (MTAs) reported from earlier genome-wide association studies. Candidate gene (CG) mining allowed the identification of 2533 unique gene models from the MQTL regions. In-silico expression analysis discovered 439 differentially expressed gene models with > 2 transcripts per million expressions in grains and related tissues, which also included 44 high-confidence CGs involved in the various cellular and biochemical processes related to quality traits. Nine functionally characterized wheat genes associated with grain protein content, high-molecular-weight glutenin, and starch synthase enzymes were also found to be co-localized with some of the MQTL. Synteny analysis between wheat and rice MQTL regions identified 23 wheat MQTL syntenic to 16 rice MQTL associated with quality traits. Furthermore, 64 wheat orthologues of 30 known rice genes were detected in 44 MQTL regions. Markers flanking the MQTL identified in the present study can be used for marker-assisted breeding and as fixed effects in the genomic selection models for improving the prediction accuracy during quality breeding. Wheat orthologues of rice genes and other CGs available from MQTLs can be promising targets for further functional validation and to better understand the molecular mechanism underlying the quality traits in wheat.

Robust Bayesian fusion of continuous segmentation maps.

The fusion of probability maps is required when trying to analyse a collection of image labels or probability maps produced by several segmentation algorithms or human raters. The challenge is to weight the combination of maps correctly, in order to reflect the agreement among raters, the presence of outliers and the spatial uncertainty in the consensus. In this paper, we address several shortcomings of prior work in continuous label fusion. We introduce a novel approach to jointly estimate a reliable consensus map and to assess the presence of outliers and the confidence in each rater. Our robust approach is based on heavy-tailed distributions allowing local estimates of raters performances. In particular, we investigate the Laplace, the Student's t and the generalized double Pareto distributions, and compare them with respect to the classical Gaussian likelihood used in prior works. We unify these distributions into a common tractable inference scheme based on variational calculus and scale mixture representations. Moreover, the introduction of bias and spatial priors leads to proper rater bias estimates and control over the smoothness of the consensus map. Finally, we propose an approach that clusters raters based on variational boosting, and thus may produce several alternative consensus maps. Our approach was successfully tested on MR prostate delineations and on lung nodule segmentations from the LIDC-IDRI dataset.

A High-Density Genetic Map and QTL Fine Mapping for Growth- and Sex-Related Traits in Red Swamp Crayfish (Procambarus clarkii).

Red swamp crayfish (Procambarus clarkii) is a commercially important species in global aquaculture and most successfully invasive freshwater shrimp in China. In order to determine the genetic basis of growth- and sex-related traits, a high-density genetic linkage map was constructed using 2b-RAD sequencing technology in a full-sib family. The consensus map contains 4,878 SNP markers assigned to 94 linkage groups (LGs) and spanned 6,157.737 cM with an average marker interval of 1.26 cM and 96.93% genome coverage. The quantitative trait locus (QTL) mapping for growth and sex traits was performed for the first time. QTL mapping uncovers 28 QTLs for growth-related traits in nine LGs, explaining 7.9–14.4% of the phenotypic variation, and identifies some potential candidate growth-related genes such as mih, lamr, golgb1, nurf301, and tbcd1 within the QTL intervals. A single major locus for sex determination was revealed in LG20 that explains 59.3–63.7% of the phenotypic variations. Some candidate sex-related genes, such as vps4bl, ssrf, and acot1, were identified in the QTL intervals and found to be differentially expressed in the muscle tissues between the females and the males. Furthermore, the identified SNPs were revealed to be female heterozygotes, suggesting that red swamp crayfish might have the female heterogametic ZZ/ZW sex determination system. The present study provides a valuable resource for marker-assisted selection and genetic improvement and for further genetic and genomic research in red swamp crayfish.