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Plant Genomics - Advancing Our Understanding of Plants Plant genomics has made significant progress in recent years, enabling researchers to identify genes and genomic regions responsible for plant growth, development, and stress response. Genome editing technologies such as CRISPR/Cas9 have revolutionized the field of plant genomics and provided researchers with powerful tools to precisely modify plant genomes. [Extracted from the article]

The main goal of this article is to examine in detail an area of the grammar where standard Romanian, a Balkan Sprachbund language of the Romance phylum, and the Romance dialects of Southern Italy (here we used the dialect of Ragusa, in South-East Sicily) appear to converge, namely differential object marking (DOM). When needed, additional observations from non-Romance Balkan languages were also taken into account. Romanian and Ragusa use a prepositional strategy for differential marking, in a conjunctive system of semantic specifications, of which one is normally humanness/animacy. However, despite these unifying traits, this paper also focuses on important loci of divergence, some of which have generally been ignored in the previous literature. For example, Ragusa does not easily permit clitic doubling and shows differences in terms of binding possibilities and positions of direct objects, two traits that set it aside from both Romanian and non-Romance Balkan languages; additionally, as opposed to Romanian, its prepositional DOM strategy cannot override humanness/animacy. The comparative perspective we adopt allow us to obtain an in-depth picture of differential marking in the Balkan and Romance languages. [ABSTRACT FROM AUTHOR]

Transcriptome-wide association studies (TWAS) goal is to better understand the etiology of diseases and develop preventative and therapeutic approaches by examining the connections between genetic variants and phenotypes while overcoming the limitations of the genome-wide association study (GWAS). It is a valuable complement to GWAS, reducing the negative effects of multiple tests and enabling a more thorough investigation of gene expression patterns in various tissues. A systematic review is presented in this paper to identify articles that utilize TWAS to understand the genetic factors behind complex diseases. A detailed selection process was carried out using standard PRISMA criteria to select relevant articles for the review. Twenty-five articles passed the inclusion criteria and were selected for additional review. The studies cover a diverse range of disorders, including Tourette's syndrome, Alzheimer's disease, rheumatoid arthritis, and major depression. Leveraging gene expression data from different tissues and populations, these investigations successfully identified novel genes and pathways associated with the studied conditions. The collective findings highlight the transformative impact of integrative genomics in advancing our understanding of complex diseases, providing insights into potential therapeutic targets, and laying the foundation for precision medicine approaches. [ABSTRACT FROM AUTHOR]

Currently, the control of rhizosphere selection on farms has been applied to achieve enhancements in phenotype, extending from improvements in single root characteristics to the dynamic nature of entire crop systems. Several specific signals, regulatory elements, and mechanisms that regulate the initiation, morphogenesis, and growth of new lateral or adventitious root species have been identified, but much more work remains. Today, phenotyping technology drives the development of root traits. Available models for simulation can support all phenotyping decisions (root trait improvement). The detection and use of markers for quantitative trait loci (QTLs) are effective for enhancing selection efficiency and increasing reproductive genetic gains. Furthermore, QTLs may help wheat breeders select the appropriate roots for efficient nutrient acquisition. Single-nucleotide polymorphisms (SNPs) or alignment of sequences can only be helpful when they are associated with phenotypic variation for root development and elongation. Here, we focus on major root development processes and detail important new insights recently generated regarding the wheat genome. The first part of this review paper discusses the root morphology, apical meristem, transcriptional control, auxin distribution, phenotyping of the root system, and simulation models. In the second part, the molecular genetics of the wheat root system, SNPs, TFs, and QTLs related to root development as well as genome editing (GE) techniques for the improvement of root traits in wheat are discussed. Finally, we address the effect of omics strategies on root biomass production and summarize existing knowledge of the main molecular mechanisms involved in wheat root development and elongation. [ABSTRACT FROM AUTHOR]

Physiological disorders impact the yield and quality of marketable fruit in tomato. Puffy fruit caused by cavities inside the locule can be problematic for processing and fresh market quality. In this paper, we used a recombinant inbred line (RIL) and three derived processing tomato populations to map and validate quantitative trait loci (QTLs) for fruit puffiness across environments. Binary interval mapping was used for mapping the incidence of fruit puffiness, and non-parametric interval mapping and parametric composite interval mapping were used for mapping severity. Marker–trait regressions were carried out to validate putative QTLs in subsequent crosses. QTLs were detected on chromosome (Chr) 1, 2, and 4. Only the QTL on Chr 1 was validated in progeny from subsequent crosses. This QTL explained up to 22.5% of the variance in the percentage of puffy fruit, with a significant interaction between loci on Chr 2 and 4, increasing the percentage of puffy fruit by an additional 15%. The allele responsible for puffy fruit on Chr 1 was inherited from parent FG02-188 and was dominant towards increased incidence and severity. Marker-assisted selection (MAS) for the QTL on Chr 1 was as efficient as genomic selection (GS) in reducing the incidence and severity of puffy fruit, despite the potential contribution of other loci. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) is a fundamental crop essential for both human and animal consumption. Addressing the challenge of enhancing wheat yield involves sophisticated applications of molecular genetics and genomic techniques. This review synthesizes current research identifying and characterizing pivotal genes that impact traits such as grain size, number, and weight, critical factors influencing overall yield. Key genes including TaSPL17, ABP7, TaGNI, TaCKX6, TaGS5, TaDA1, WAPO1, TaRht1, TaTGW-7A, TaGW2, TaGS5-3A, TaSus2-2A, TaSus2-2B, TaSus1-7A, and TaSus1-7B are examined for their roles in these traits. The review also explores genes responsive to environmental changes, which are increasingly significant under current climate variability. Multi-trait regulatory genes and quantitative trait loci (QTLs) that contribute to these traits are discussed, highlighting their dual influences on grain size and yield. Furthermore, the paper underscores the utility of emerging technologies such as CRISPR/Cas9, Case13, and multi-omics approaches. These innovations are instrumental for future discoveries and are poised to revolutionize wheat breeding by enabling precise genetic enhancements. Facing unprecedented challenges from climate change, the identification and utilization of these candidates is crucial. This review aims to be a comprehensive resource for researchers, providing an integrative understanding of complex traits in wheat and proposing new avenues for research and crop improvement strategies. [ABSTRACT FROM AUTHOR]

Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer's disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3'-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing. This paper unveils the complexity of human immune cell splicing, highlighting cell-specific isoforms and establishing connections between alternative splicing and complex traits. These findings have implications for understanding diseases and the evolution of the genome. [ABSTRACT FROM AUTHOR]

Background: Researchers have long studied the regulatory processes of genes to uncover their functions. Gene regulatory network analysis is one of the popular approaches for understanding these processes, requiring accurate identification of interactions among the genes to establish the gene regulatory network. Advances in genome-wide association studies and expression quantitative trait loci studies have led to a wealth of genomic data, facilitating more accurate inference of gene–gene interactions. However, unknown confounding factors may influence these interactions, making their interpretation complicated. Mendelian randomization (MR) has emerged as a valuable tool for causal inference in genetics, addressing confounding effects by estimating causal relationships using instrumental variables. In this paper, we propose a new statistical method, MR-GGI, for accurately inferring gene–gene interactions using Mendelian randomization. Results: MR-GGI applies one gene as the exposure and another as the outcome, using causal cis-single-nucleotide polymorphisms as instrumental variables in the inverse-variance weighted MR model. Through simulations, we have demonstrated MR-GGI's ability to control type 1 error and maintain statistical power despite confounding effects. MR-GGI performed the best when compared to other methods using the F1 score on the DREAM5 dataset. Additionally, when applied to yeast genomic data, MR-GGI successfully identified six clusters. Through gene ontology analysis, we have confirmed that each cluster in our study performs distinct functional roles by gathering genes with specific functions. Conclusion: These findings demonstrate that MR-GGI accurately inferences gene–gene interactions despite the confounding effects in real biological environments. [ABSTRACT FROM AUTHOR]

Transcriptional cis-regulatory modules, e.g., enhancers, control the time and location of metazoan gene expression. While changes in enhancers can provide a powerful force for evolution, there is also significant deep conservation of enhancers for developmentally important genes, with function and sequence characteristics maintained over hundreds of millions of years of divergence. Not well understood, however, is how the overall regulatory composition of a locus evolves, with important outstanding questions such as how many enhancers are conserved vs. novel, and to what extent are the locations of conserved enhancers within a locus maintained? We begin here to address these questions with a comparison of the respective single-minded (sim) loci in the two dipteran species Drosophila melanogaster (fruit fly) and Aedes aegypti (mosquito). sim encodes a highly conserved transcription factor that mediates development of the arthropod embryonic ventral midline. We identify two enhancers in the A. aegypti sim locus and demonstrate that they function equivalently in both transgenic flies and transgenic mosquitoes. One A. aegypti enhancer is highly similar to known Drosophila counterparts in its activity, location, and autoregulatory capability. The other differs from any known Drosophila sim enhancers with a novel location, failure to autoregulate, and regulation of expression in a unique subset of midline cells. Our results suggest that the conserved pattern of sim expression in the two species is the result of both conserved and novel regulatory sequences. Further examination of this locus will help to illuminate how the overall regulatory landscape of a conserved developmental gene evolves. Author summary: The expression patterns and roles of genes, especially those involved in core developmental processes, are often conserved over vast evolutionary distances. Paradoxically, the DNA sequences surrounding these genes, which contain the cis-regulatory sequences (enhancers) that regulate gene expression, tend to be highly diverged. The manner and extent to which enhancers are functionally conserved, and how the overall organization of regulatory sequences within a locus is preserved or restructured, is not well understood. In this paper, we investigate these questions by identifying enhancers controlling expression of a master nervous system regulatory gene named sim in the mosquito Aedes aegypti, and comparing their functions and locations to those in the well-characterized sim locus of the fruit fly Drosophila melanogaster. Our results suggest that the two species generate identical patterns of sim expression through a mix of conserved and novel regulatory sequences. Continued exploration of the sim locus in these two species will help to build a comprehensive picture of how a regulatory locus for a master developmental regulator has evolved. [ABSTRACT FROM AUTHOR]

Tocopherols are secondary metabolites synthesized through the shikimate biosynthetic pathway in the plastids of most plants. It is well known that α–Tocopherol (vitamin E) has many health benefits for humans and animals; therefore, it is highly used in human and animal diets. Tocopherols vary considerably in most crop (and plant) species and within cultivars of the same species depending on environmental and growth conditions; tocopherol content is a polygenic, complex traits, and its inheritance is poorly understood. The objective of this review paper was to summarize all identified quantitative trait loci (QTL) that control seed tocopherols and related contents identified in maize (Zea mays) during the past two decades (2002–2022). Candidate genes identified within these QTL regions are also discussed. The QTL described here, and candidate genes identified within these genomic regions could be used in breeding programs to develop maize cultivars with high, beneficial levels of seed tocopherol contents. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Genetic merit, or breeding values as referred to in livestock and crop breeding programs, is one of the keys to the successful selection of animals in commercial farming systems. The developments in statistical methods during the twentieth century and single nucleotide polymorphism (SNP) chip technologies in the twenty-first century have revolutionized agricultural production, by allowing highly accurate predictions of breeding values for selection candidates at a very early age. Nonetheless, for many breeding populations, realized accuracies of predicted breeding values (PBV) remain below the theoretical maximum, even when the reference population is sufficiently large, and SNPs included in the model are in sufficient linkage disequilibrium (LD) with the quantitative trait locus (QTL). This is particularly noticeable over generations, as we observe the so-called erosion of the effects of SNPs due to recombinations, accompanied by the erosion of the accuracy of prediction. While accurately quantifying the erosion at the individual SNP level is a difficult and unresolved task, quantifying the erosion of the accuracy of prediction is a more tractable problem. In this paper, we describe a method that uses the relationship between reference and target populations to calculate expected values for the accuracies of predicted breeding values for non-phenotyped individuals accounting for erosion. The accuracy of the expected values was evaluated through simulations, and a further evaluation was performed on real data. Results: Using simulations, we empirically confirmed that our expected values for the accuracy of PBV accounting for erosion were able to correctly determine the prediction accuracy of breeding values for non-phenotyped individuals. When comparing the expected to the realized accuracies of PBV with real data, only one out of the four traits evaluated presented accuracies that were significantly higher than the expected, approaching h 2 . Conclusions: We defined an index of genetic correlation between reference and target populations, which summarizes the expected overall erosion due to differences in allele frequencies and LD patterns between populations. We used this correlation along with a trait's heritability to derive expected values for the accuracy (R ) of PBV accounting for the erosion, and demonstrated that our derived E R | erosion is a reliable metric. [ABSTRACT FROM AUTHOR]

Improving barley grain quality is a major goal in barley breeding. In this study, a total of 35 papers focusing on quantitative trait loci (QTLs) mapping for barley quality traits published since 2000 were collected. Among the 454 QTLs identified in these studies, 349 of them were mapped onto high-density consensus maps, which were used for QTL meta-analysis. Through QTL metaanalysis, the initial QTLs were integrated into 41 meta-QTLs (MQTLs) with an average confidence interval (CI) of 1. 66 cM, which is 88.9% narrower than that of the initial QTLs. Among the 41 identified MQTLs, 25 were subsequently validated in publications using genome-wide association study (GWAS). From these 25 validated MQTLs, ten breeder’s MQTLs were selected. Synteny analysis comparing barley and wheat MQTLs revealed orthologous relationships between eight breeder’s MQTLs and 45 wheat MQTLs. Additionally, 17 barley homologs associated with rice quality traits were identified within the regions of the breeder’s MQTLs through comparative analysis. The findings of this study provide valuable insights for molecular marker-assisted breeding and the identification of candidate genes related to quality traits in barley. [ABSTRACT FROM AUTHOR]

Context. Several high-quality reference genomes for oat (Avena sativa L. and relatives) have been published, with the prospect of many additional whole-genome assemblies emerging in the near future. Aims. This has necessitated an effort by the International Oat Nomenclature Committee (IONC; all co-authors on this paper) to devise a universal system for naming oat genomes and subgenomes, chromosomes, genes, gene models and quantitative trait loci. Methods. We evaluated existing naming practices, recent data from oat whole-genome sequencing, and the newly published convention for wheat nomenclature. Key results. A framework for these rules has been posted on the GrainGenes database website (https://wheat.pw.usda.gov/GG3/oatnomenclature). The gene naming convention requires adoption of a numerical identifier for each genotype; we propose that these identifiers be assigned by contacting the GrainGenes curators, the curator of the Oat Newsletter, or a member of the IONC (as listed at the GrainGenes link above). Conclusions. We encourage oat researchers to refer to these resources, policies, procedures and conventions, adopting them as an international nomenclature standard. Implications. Adoption of these standards will facilitate communication and dissemination of oat research and allow programmatic access and data sharing across platforms, and will contribute to oat breeding and research worldwide. [ABSTRACT FROM AUTHOR]

This document is an editorial published in the journal Frontiers in Veterinary Science. It discusses the importance of environmental and genomic strategies for conservation and selection in small ruminants, such as sheep and goats. The editorial highlights the genetic diversity and adaptation of local breeds, as well as the need to preserve their unique traits and genetic variability. The document also mentions several research papers included in the journal's Research Topic, which cover various aspects of genetic differentiation, adaptation, and selection in small ruminants. Overall, the editorial emphasizes the importance of balancing conservation efforts with breeding programs to ensure the sustainability of small ruminant populations. [Extracted from the article]

This paper proposes and studies a discrete-time model for a sex-structured population with non-overlapping generations under density-dependent regulation of survival. The population is assumed to have genetic variety among individuals in terms of reproductive potential, controlled by a single autosomal diallelic locus. We consider a panmictic population with Mendelian inheritance rules. We examine the stability model and show that increasing the average value of reproductive potential destabilizes the population dynamics. The scenario of stability loss in fixed points via period doubling or Neimark–Sacker bifurcations depends on the intensity of the self-regulation. The growth rate at which the population survives and develops is shown to depend on the fitness of the genotypes and the secondary sex ratio. As a result, the asymptotic genetic composition of the population is determined by the values of the reproductive potentials of the heterozygote and homozygotes, the initial conditions, and the parameter describing the ratio of newborn females to males. With disruptive selection, the influence of external factors changing the current genetic composition of a population can alter the direction of evolution and lead to the extinction of a successful developing population or a gradual population recovery due to evolutionary rescue after a noticeable decline in its abundance. [ABSTRACT FROM AUTHOR]

This article reports the expression profiles of the three I TdDRF1 i gene transcripts, from durum wheat genotypes during different plant growth stages. The second group includes two other papers: one written by Arianna Latini et al. regarding functional genomics research into the expression profiles of a drought-responsive transcription factor gene I (DRF1) i of durum wheat in fields under full- and reduced-irrigation conditions. Now more than ever, the understanding of the genetics and evolution of the gene mechanisms and the networks of different molecular pathways acting on plant abiotic stress tolerance has an important role in the finding of new solutions and approaches mitigating the effects of global climate changes, thus contributing to a correct equilibrium among human needs, food security and human health and wellbeing. [Extracted from the article]

Background: Quantitative trait locus (QTL) analysis aims to locate and estimate the effects of the genes influencing quantitative traits and infer the relationship between gene variants and changes in phenotypic characteristics using statistical methods. Some methods have been developed to map QTLs of multiple traits in the case of no genotype error in a given dataset. However, practical genetic data that people use may contain some potential errors because of the limitations of biotechnology. Common genetic data correction methods can only reduce errors, but cannot calculate the degree of error. In this paper, we propose a QTL mapping strategy for multiple traits in the presence of genotype errors. Methods: The additive effect, dominant effect, recombination rate, error rate, and other parameters of QTLs can be simultaneously obtained using this new method in the framework of multiple-interval mapping. Results: Our simulation results show that the accuracy of parameter estimation can be improved by considering the errors of marker genotypes during the analysis of genetic data. Real data analysis also shows that the new method proposed in this paper can map the QTLs of multiple traits more accurately. [ABSTRACT FROM AUTHOR]

Biotic stress is one of the major threats to stable rice production. Climate change affects the shifting of pest outbreaks in time and space. Genetic improvement of biotic stress resistance in rice is a cost-effective and environment-friendly way to control diseases and pests compared to other methods such as chemical spraying. Fast deployment of the available and suitable genes/alleles in local elite varieties through marker-assisted selection (MAS) is crucial for stable high-yield rice production. In this review, we focused on consolidating all the available cloned genes/alleles conferring resistance against rice pathogens (virus, bacteria, and fungus) and insect pests, the corresponding donor materials, and the DNA markers linked to the identified genes. To date, 48 genes (independent loci) have been cloned for only major biotic stresses: seven genes for brown planthopper (BPH), 23 for blast, 13 for bacterial blight, and five for viruses. Physical locations of the 48 genes were graphically mapped on the 12 rice chromosomes so that breeders can easily find the locations of the target genes and distances among all the biotic stress resistance genes and any other target trait genes. For efficient use of the cloned genes, we collected all the publically available DNA markers (~500 markers) linked to the identified genes. In case of no available cloned genes yet for the other biotic stresses, we provided brief information such as donor germplasm, quantitative trait loci (QTLs), and the related papers. All the information described in this review can contribute to the fast genetic improvement of biotic stress resistance in rice for stable high-yield rice production. [ABSTRACT FROM AUTHOR]

Copyright of Genetika (0534-0012) is the property of Serbian Genetics Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The potential yield of maize (Zea mays L.) and other major crops is curtailed by several biotic, abiotic, and socio-economic constraints. Parasitic weeds, Striga spp., are major constraints to cereal and legume crop production in sub-Saharan Africa (SSA). Yield losses reaching 100% are reported in maize under severe Striga infestation. Breeding for Striga resistance has been shown to be the most economical, feasible, and sustainable approach for resource-poor farmers and for being environmentally friendly. Knowledge of the genetic and genomic resources and components of Striga resistance is vital to guide genetic analysis and precision breeding of maize varieties with desirable product profiles under Striga infestation. This review aims to present the genetic and genomic resources, research progress, and opportunities in the genetic analysis of Striga resistance and yield components in maize for breeding. The paper outlines the vital genetic resources of maize for Striga resistance, including landraces, wild relatives, mutants, and synthetic varieties, followed by breeding technologies and genomic resources. Integrating conventional breeding, mutation breeding, and genomic-assisted breeding [i.e., marker-assisted selection, quantitative trait loci (QTL) analysis, next-generation sequencing, and genome editing] will enhance genetic gains in Striga resistance breeding programs. This review may guide new variety designs for Striga-resistance and desirable product profiles in maize. [ABSTRACT FROM AUTHOR]

Migraine—a painful, throbbing headache disorder—is the most common complex brain disorder, yet its molecular mechanisms remain unclear. Genome-wide association studies (GWAS) have proven successful in identifying migraine risk loci; however, much work remains to identify the causal variants and genes. In this paper, we compared three transcriptome-wide association study (TWAS) imputation models—MASHR, elastic net, and SMultiXcan—to characterise established genome-wide significant (GWS) migraine GWAS risk loci, and to identify putative novel migraine risk gene loci. We compared the standard TWAS approach of analysing 49 GTEx tissues with Bonferroni correction for testing all genes present across all tissues (Bonferroni), to TWAS in five tissues estimated to be relevant to migraine, and TWAS with Bonferroni correction that took into account the correlation between eQTLs within each tissue (Bonferroni-matSpD). Elastic net models performed in all 49 GTEx tissues using Bonferroni-matSpD characterised the highest number of established migraine GWAS risk loci (n = 20) with GWS TWAS genes having colocalisation (PP4 > 0.5) with an eQTL. SMultiXcan in all 49 GTEx tissues identified the highest number of putative novel migraine risk genes (n = 28) with GWS differential expression at 20 non-GWS GWAS loci. Nine of these putative novel migraine risk genes were later found to be at and in linkage disequilibrium with true (GWS) migraine risk loci in a recent, more powerful migraine GWAS. Across all TWAS approaches, a total of 62 putative novel migraine risk genes were identified at 32 independent genomic loci. Of these 32 loci, 21 were true risk loci in the recent, more powerful migraine GWAS. Our results provide important guidance on the selection, use, and utility of imputation-based TWAS approaches to characterise established GWAS risk loci and identify novel risk gene loci. [ABSTRACT FROM AUTHOR]

Transcriptome analysis revealed that I OsERF83 i regulates drought response genes, which are related to the transporter, lignin biosynthesis, terpenoid synthesis, cytochrome P450 family, and abiotic stress-related genes. This Special Issue, "Drought-Stress Induced Physiological and Molecular Changes in Plants", presents twelve excellent articles, ten research papers and two reviews, that discuss the latest findings that elucidate the molecular basis of how plants adapt to drought stress. Soil drought is one of the major abiotic stresses that inhibits the growth, development, and yield of crops all over the world. TFs play a significant role in signal transduction that spans the perception of a stress signal and the expression of stress responsive genes. [Extracted from the article]

SUMMARY Bulk segregation analysis (BSA) utilizes a strategy of pooling individuals with extreme phenotypes to conduct economical and rapidly linked marker screening or quantitative trait locus (QTL) mapping. With the development of next‐generation sequencing (NGS) technology in the past 10 years, BSA methods and technical systems have been gradually developed and improved. At the same time, the ever‐decreasing costs of sequencing accelerate NGS‐based BSA application in different species, including eukaryotic yeast, grain crops, economic crops, horticultural crops, trees, aquatic animals, and insects. This paper provides a landscape of BSA methods and reviews the BSA development process in the past decade, including the sequencing method for BSA, different populations, different mapping algorithms, associated region threshold determination, and factors affecting BSA mapping. Finally, we summarize related strategies in QTL fine mapping combining BSA. Significance Statement: This paper provides a landscape of BSA methods in the next‐generation sequencing (NGS) era and a guideline to select a proper method for bulk segregation analysis mapping design. In addition, quantitative trait locus fine mapping strategies are summarized for researchers in the field. [ABSTRACT FROM AUTHOR]

In this paper, we have carefully investigated the clinical phenotype and genotype of patients with Johanson-Blizzard syndrome (JBS) with diabetes mellitus as the main manifestation. Retinal vessel segmentation is an important tool for the detection of many eye diseases and plays an important role in the automated screening system for retinal diseases. A segmentation algorithm based on a multiscale attentional resolution network is proposed to address the problem of insufficient segmentation of small vessels and pathological missegmentation in existing methods. The network is based on the encoder-decoder architecture, and the attention residual block is introduced in the submodule to enhance the feature propagation ability and reduce the impact of uneven illumination and low contrast on the model. The jump connection is added between the encoder and decoder, and the traditional pooling layer is removed to retain sufficient vascular detail information. Two multiscale feature fusion methods, parallel multibranch structure, and spatial pyramid pooling are used to achieve feature extraction under different sensory fields. We collected the clinical data, laboratory tests, and imaging examinations of JBS patients, extracted the genomic DNA of relevant family members, and validated them by whole-exome sequencing and Sanger sequencing. The patient had diabetes mellitus as the main manifestation, with widened eye spacing, low flat nasal root, hypoplastic nasal wing, and low hairline deformities. Genetic testing confirmed the presence of a c.4463 T > C (p.Ile1488Thr) pure missense mutation in the UBR1 gene, which was a novel mutation locus, and pathogenicity analysis indicated that the locus was pathogenic. This patient carries a new UBR1 gene c.4463 T > C pure mutation, which improves the clinical understanding of the clinical phenotypic spectrum of JBS and broadens the genetic spectrum of the UBR1 gene. The experimental results showed that the method achieved 83.26% and 82.56% F1 values on CHASEDB1 and STARE standard sets, respectively, and 83.51% and 81.20% sensitivity, respectively, and its performance was better than the current mainstream methods. [ABSTRACT FROM AUTHOR]

Aims Vascular smooth muscle cells (SMCs) and their derivatives are key contributors to the development of atherosclerosis. However, studying changes in SMC gene expression in heterogeneous vascular tissues is challenging due to the technical limitations and high cost associated with current approaches. In this paper, we apply translating ribosome affinity purification sequencing to profile SMC-specific gene expression directly from tissue. Methods and results To facilitate SMC-specific translatome analysis, we generated SMCTRAP mice, a transgenic mouse line expressing enhanced green fluorescent protein (EGFP)-tagged ribosomal protein L10a (EGFP-L10a) under the control of the SMC-specific αSMA promoter. These mice were further crossed with the atherosclerosis model Ldlr−/−, ApoB100/100 to generate SMCTRAP−AS mice and used to profile atherosclerosis-associated SMCs in thoracic aorta samples of 15-month-old SMCTRAP and SMCTRAP-AS mice. Our analysis of SMCTRAP-AS mice showed that EGFP-L10a expression was localized to SMCs in various tissues, including the aortic wall and plaque. The TRAP fraction demonstrated high enrichment of known SMC-specific genes, confirming the specificity of our approach. We identified several genes, including Cemip , Lum , Mfge8 , Spp1 , and Serpina3 , which are known to be involved in atherosclerosis-induced gene expression. Moreover, we identified several novel genes not previously linked to SMCs in atherosclerosis, such as Anxa4 , Cd276 , inter-alpha-trypsin inhibitor-4 (Itih4), Myof , Pcdh11x , Rab31 , Serpinb6b , Slc35e4 , Slc8a3 , and Spink5. Among them, we confirmed the SMC-specific expression of Itih4 in atherosclerotic lesions using immunofluorescence staining of mouse aortic roots and spatial transcriptomics of human carotid arteries. Furthermore, our more detailed analysis of Itih4 showed its link to coronary artery disease through the colocalization of genome-wide association studies, splice quantitative trait loci (QTL), and protein QTL signals. Conclusion We generated a SMC-specific TRAP mouse line to study atherosclerosis and identified Itih4 as a novel SMC-expressed gene in atherosclerotic plaques, warranting further investigation of its putative function in extracellular matrix stability and genetic evidence of causality. [ABSTRACT FROM AUTHOR]

The development and viability of seedlings are crucial in overwintering cereals, as it can affect not only an adult plant physiological condition, but also the size and quality of future grain. Recent studies on the genetic control of morphological and yield-related traits have been focused on adult plants of wheat, barley, maize, and rice. However, there is insufficient research describing the genetic control of cereals in the seedling stage. To fill that gap, the winter triticale 'Hewo' × 'Magnat'-doubled haploid lines population was used to locate quantitative trait loci associated with selected traits measured at the seedling stage: the width and length of the first and second leaves, the leaf blade and leaf sheath lengths as well as the length-to-width ratio. Based on the genetic map for 'Hewo' × 'Magnat' DH population, main four loci, statistically significant (P < 0.05) and strongly associated with the second leaf length and width as well as their ratio were identified. Those regions were located on rye chromosomes 4R, 5R, and 6R with LOD value up to 20.35. In addition, candidate genes in localized regions were identified. The work also demonstrated correlations between the morphology of the second leaf, especially its length-to-width ratio, and the encoded proteins. As described in this paper, results are, to our knowledge, a first attempt to determine the genetic control of triticale seedlings and can provide a new insight on this field and become a reference for developing novel triticale varieties in breeding programmes. [ABSTRACT FROM AUTHOR]

Sweet sorghum is a cereal crop that can potentially serve as a source for bioethanol production. This study aims to analyse the genetic diversity of promising genotypes of sweet sorghum at the molecular level. The genetic material consisted of 12 sweet sorghum genotypes. The genetic diversity estimated using 59 SSRs markers showed a polymorphism value of 0.48 and the coefficient of genetic diversity was classified as moderate. The unweighted pair group method arithmetic average (UPGMA) analysis assigned the tested genotypes into three major clusters with a similarity coefficient level of 0.596. This indicates that the genetic similarity of the tested genotypes is moderate to high. Eight unique loci were identified with the SSRs markers in six genotypes, which are considered to control high sugar traits. [ABSTRACT FROM AUTHOR]

Introduction: Substantial links between autoimmune diseases have been shown by an increasing number of studies, and one hypothesis for this comorbidity is that there is a common genetic cause. Methods: In this paper, a large-scale cross-trait Genome-wide Association Studies (GWAS) was conducted to investigate the genetic overlap among rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease and type 1 diabetes. Results and discussion: Through the local genetic correlation analysis, 2 regions with locally significant genetic associations between rheumatoid arthritis and multiple sclerosis, and 4 regions with locally significant genetic associations between rheumatoid arthritis and type 1 diabetes were discovered. By cross-trait meta-analysis, 58 independent loci associated with rheumatoid arthritis and multiple sclerosis, 86 independent loci associated with rheumatoid arthritis and inflammatory bowel disease, and 107 independent loci associatedwith rheumatoid arthritis and type 1 diabeteswere identified with genome-wide significance. In addition, 82 common risk genes were found through genetic identification. Based on gene set enrichment analysis, it was found that shared genes are enriched in exposed dermal system, calf, musculoskeletal, subcutaneous fat, thyroid and other tissues, and are also significantly enriched in 35 biological pathways. To verify the association between diseases, Mendelian randomized analysis was performed, which shows possible causal associations between rheumatoid arthritis and multiple sclerosis, and between rheumatoid arthritis and type 1 diabetes. The common genetic structure of rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease and type 1 diabetes was explored by these studies, and it is believed that this important discovery will lead to new ideas for clinical treatment. [ABSTRACT FROM AUTHOR]

Quantitative Trait Loci (QTL) mapping has been thoroughly used in peanut genetics and breeding in spite of the narrow genetic diversity and the segmental tetraploid nature of the cultivated species. QTL mapping is helpful for identifying the genomic regions that contribute to traits, for estimating the extent of variation and the genetic action (i.e., additive, dominant, or epistatic) underlying this variation, and for pinpointing genetic correlations between traits. The aim of this paper is to review the recently published studies on QTL mapping with a particular emphasis on mapping populations used as well as traits related to kernel quality. We found that several populations have been used for QTL mapping including interspecific populations developed from crosses between synthetic tetraploids and elite varieties. Those populations allowed the broadening of the genetic base of cultivated peanut and helped with the mapping of QTL and identifying beneficial wild alleles for economically important traits. Furthermore, only a few studies reported QTL related to kernel quality. The main quality traits for which QTL have been mapped include oil and protein content as well as fatty acid compositions. QTL for other agronomic traits have also been reported. Among the 1261 QTL reported in this review, and extracted from the most relevant studies on QTL mapping in peanut, 413 (~33%) were related to kernel quality showing the importance of quality in peanut genetics and breeding. Exploiting the QTL information could accelerate breeding to develop highly nutritious superior cultivars in the face of climate change. [ABSTRACT FROM AUTHOR]

Importance: Multiple studies indicate a possible correlation between ADD3 rs2501577 and biliary atresia susceptibility; however, a conclusive determination has yet to be made. Objective: Investigate the role of ADD3 rs2501577 in biliary atresia susceptibility across diverse populations. Data sources: The study protocol has been registered on PROSPERO, an international platform for systematic review registration (PROSPERO ID: CRD42023384641). The following databases will be searched until February 1, 2023: PubMed, Embase, Cochrane, CBM, Web of Science, and CNKI. Study selection: Eight studies were selected from seven papers to assess the data. A total of 7651 participants were included, consisting of 1662 in the BA group and 5989 in the NC group. Data extraction and synthesis: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed while conducting the systematic reviews and meta-analyses. Two authors independently assessed the quality of the included studies using the Newcastle–Ottawa Quality Assessment Scale. The significance of the pooled odds ratio (OR) was evaluated with a Z test, and statistical heterogeneity across studies was assessed using the I2 and Q statistics. Publication bias was assessed using Egger's and Begg's tests. Main outcome(s) and measure(s): The primary study outcome was the development of biliary atresia. Subgroup analysis was performed based on race, region, and assessment of Hardy–Weinberg equilibrium (HWE). Results: The studies indicate that the ADD3 rs2501577 susceptibility locus increases the risk of developing biliary atresia, regardless of allelic, homozygote, dominant, and recessive gene inheritance models. Furthermore, ADD3 has been found to be associated with apoptosis, cell cycle, and cell damage repair based on functional analysis. Conclusions and relevance: The ADD3 rs2501577 polymorphic locus is associated with an increased risk of biliary atresia, particularly in Asian populations. This study recommends further investigation of the ADD3 rs2501577 locus in Asian populations to validate its role in the diagnosis of biliary atresia. [ABSTRACT FROM AUTHOR]

Introduction: Skeletal abnormalities and malocclusions have varied features that impact populations globally, impairing aesthetics and lowering life quality. The prevalence of the Skeletal Class III disease is the lowest among all angle malocclusions, with varied prevalence across nations. Environmental, genetic, and societal factors play a role in its numerous etiologies. In this study, we conducted a thorough search across the published data relating to quantitative trait loci (QTL) and the genes associated with Class III progression in humans, discussed these findings and their limitations, and proposed future directions and strategies for studying this phenotype. Methods: An inclusive search of published papers in the PubMed and Google Scholar search engines using the following terms: 1. Human skeletal Class III; 2. Genetics of Human skeletal Class III; 3. QTL mapping and gene associated with human skeletal Class III; 4. enriched skeletal Class-III-malocclusion-associated pathways. Results: Our search has found 53 genes linked with skeletal Class III malocclusion reported in humans, genes associated with epigenetics and phenomena, and the top 20 enriched pathways associated with skeletal Class III malocclusion. Conclusions: The human investigations yielded some contentious conclusions. We conducted a genome-wide association study (GWAS), an epigenetics-wide association study (EWAS), RNA-seq analysis, integrating GWAS and expression quantitative trait loci (eQTL), micro- and small-RNA, and long non-coding RNA analysis in tissues connected to skeletal Class III malocclusion phenotype in tissues connected with the skeletal phenotype. Finally, we invite regional, national, and international orthodontists and surgeons to join this effort by contributing human samples with skeletal Class III malocclusion following the accepted Helsinki ethical protocol to challenge these phenomena jointly. [ABSTRACT FROM AUTHOR]

This paper proposes the use of weighted multiple linear regression to estimate the triple3interaction (additive×additive×additive) of quantitative trait loci (QTLs) effects. The use of unweighted regression yielded an improvement (in absolute value) in the QTL×QTL×QTL interaction effects compared to assessment based on phenotypes alone in three cases (severe drought in 2010, control in 2012 and severe drought in 2012). In contrast, weighted regression yielded an improvement (in absolute value) in the evaluation of the aaagw parameter compared to aaap in five cases, with the exception of severe drought in 2012. The results show that by using weighted regression on marker observations, the obtained estimates are closer to the ones obtained by the phenotypic method. The coefficients of determination for the weighted regression model were significantly higher than for the unweighted regression and ranged from 46.2% (control in 2010) to 95.0% (control in 2011). Considering this, it is clear that a three-way interaction had a significant effect on the expression of quantitative traits. [ABSTRACT FROM AUTHOR]

Chickpea is a highly nutritious pulse crop with low digestible carbohydrates (40–60%), protein (15–22%), essential fats (4–8%), and a range of minerals and vitamins. The fatty acid composition of the seed adds value because fats govern the texture, shelf-life, flavor, aroma, and nutritional composition of chickpea-based food products. Therefore, the biofortification of essential fatty acids has become a nutritional breeding target for chickpea crop improvement programs worldwide. This paper examines global chickpea production, focusing on plant lipids, their functions, and their benefits to human health. In addition, this paper also reviews the chemical analysis of essential fatty acids and possible breeding targets to enrich essential fatty acids in chickpea (Cicer arietinum) biofortification. Biofortification of chickpea for essential fatty acids within safe levels will improve human health and support food processing to retain the quality and flavor of chickpea-based food products. Essential fatty acid biofortification is possible by phenotyping diverse chickpea germplasm over suitable locations and years and identifying the candidate genes responsible for quantitative trait loci mapping using genome-wide association mapping. [ABSTRACT FROM AUTHOR]

Introduction: The majority of peppers in the US for fresh market and processing are handpicked, and harvesting can account for 20-50% of production costs. Innovation in mechanical harvesting would increase availability; lower the costs of local, healthy vegetable products; and perhaps improve food safety and expand markets. Most processed peppers require removal of pedicels (stem and calyx) from the fruit, but lack of an efficient mechanical process for this operation has hindered adoption of mechanical harvest. In this paper, we present characterization and advancements in breeding green chile peppers for mechanical harvesting. Specifically, we describe inheritance and expression of an easy-destemming trait derived from the landrace UCD-14 that facilitates machine harvest of green chiles. Methods: A torque gauge was used for measuring bending forces similar to those of a harvester and applied to two biparental populations segregating for destemming force and rate. Genotyping by sequencing was used to generate genetic maps for quantitative trait locus (QTL) analyses. Results: A major destemming QTL was found on chromosome 10 across populations and environments. Eight additional population and/or environment-specific QTL were also identified. Chromosome 10 QTL markers were used to help introgress the destemming trait into jalapeño-type peppers. Low destemming force lines combined with improvements in transplant production enabled mechanical harvest of destemmed fruit at a rate of 41% versus 2% with a commercial jalapeńo hybrid. Staining for the presence of lignin at the pedicel/fruit boundary indicated the presence of an abscission zone and homologs of genes known to affect organ abscission were found under several QTL, suggesting that the easydestemming trait may be due to the presence and activation of a pedicel/fruit abscission zone. Conclusion: Presented here are tools to measure the easy-destemming trait, its physiological basis, possible molecular pathways, and expression of the trait in various genetic backgrounds. Mechanical harvest of destemmed mature green chile fruits was achieved by combining easy-destemming with transplant management. [ABSTRACT FROM AUTHOR]

Testing the existence of quantitative trait locus (QTL) effects is an important task in QTL mapping studies. In this paper, we assume the phenotype distributions from a location-scale distribution family, and consider to test the QTL effects in both location and scale in the backcross studies with double recombination occurring. Without equal scale assumption, the log-likelihood function is unbounded, which leads to the traditional likelihood ratio test being invalid. To deal with this problem, we propose a penalized likelihood ratio test (PLRT) for testing the QTL effects. The null limiting distribution of the PLRT is shown to be a supremum of a chi-square process. As a complement, we also investigate the null limiting distribution of the likelihood ratio test for the case with equal scale assumption. The limiting distributions of the two tests under local alternatives are also studied. Simulation studies are performed to evaluate the asymptotic results and a real-data example is given for illustration. [ABSTRACT FROM AUTHOR]

As one of the essential cereal crops, wheat provides 20% of the calories and proteins consumed by humans. Due to population expansion, dietary shift and climate change, it is challenging for wheat breeders to develop new varieties for meeting wheat production requirements. Marker-assisted selection (MAS) has distinct advantages over conventional selection in plant breeding, such as being time-saving, cost-effective and goal-oriented. This review makes attempts to give a description of different molecular markers: sequence tagged site (STS), simple sequence repeat (SSR), genotyping by sequencing (GBS), single nucleotide polymorphism (SNP) arrays, exome capture, Kompetitive Allele Specific PCR (KASP), cleaved amplified polymorphic sequence (CAPS), semi-thermal asymmetric reverse PCR (STARP) and genotyping by target sequencing (GBTS). We also summarize some quantitative trait loci (QTL)/genes as well as their linked markers, which are potentially useful in MAS. This paper provides updated information on some markers linked to critical traits and their potential applications in wheat breeding programs. [ABSTRACT FROM AUTHOR]

With the extensive application of high-dimensional heterogeneous data in various disciplines, sparse expectile regression is increasingly favoured by people. In this paper, we make use of the graphical structure among predictors node-by-node to improve the performance of parameter estimation, model selection and prediction in sparse expectile regression. A modified alternating direction method of multipliers (ADMM) algorithm with a linearization trick is proposed to implement the proposed method numerically, and the convergence of the algorithm is proved. Simulation studies are conducted to evaluate the finite-sample performance of the proposed method. We demonstrate the practicability of the proposed approach with a dataset of the expression quantitative trait locus mapping (eQTL) experiment in Rattus norvegicus. [ABSTRACT FROM AUTHOR]

Let $\mathbb {V}$ be a polarized variation of Hodge structure over a smooth complex quasi-projective variety $S$. In this paper, we give a complete description of the typical Hodge locus for such variations. We prove that it is either empty or equidistributed with respect to a natural differential form, the pull–push form. In particular, it is always analytically dense when the pull–push form does not vanish. When the weight is two, the Hodge numbers are $(q,p,q)$ and the dimension of $S$ is least $rq$ , we prove that the typical locus where the Picard rank is at least $r$ is equidistributed in $S$ with respect to the volume form $c_q^r$ , where $c_q$ is the $q$ th Chern form of the Hodge bundle. We obtain also several equidistribution results of the typical locus in Shimura varieties: a criterion for the density of the typical Hodge loci of a variety in $\mathcal {A}_g$ , equidistribution of certain families of CM points and equidistribution of Hecke translates of curves and surfaces in $\mathcal {A}_g$. These results are proved in the much broader context of dynamics on homogeneous spaces of Lie groups which are of independent interest. The pull–push form appears in this greater generality, we provide several tools to determine it, and we compute it in many examples. [ABSTRACT FROM AUTHOR]

The article discusses a comment made by Bourke et al. regarding the method described in Chen et al.'s paper on mapping quantitative trait loci (QTL) in autotetraploids. Chen et al. argue that their comment is correct based on facts and statistical principles. They explain that the method used in Bourke et al.'s paper lacks an essential component, which is genetic linkage analysis between QTLs and surrounding markers for QTL mapping in an outbred autotetraploid segregating population. Chen et al. also address the terminology and methodology used by Bourke et al., pointing out inconsistencies and inaccuracies. They conclude that their own method enables QTL mapping in autotetraploid species under a novel tetrasomic inheritance model and is based on rigorous scientific and statistical principles. [Extracted from the article]

A core problem in genetics is molecular quantitative trait locus (QTL) mapping, in which genetic variants associated with changes in the molecular phenotypes are identified. One of the most-studied molecular QTL mapping problems is expression QTL (eQTL) mapping, in which the molecular phenotype is gene expression. It is common in eQTL mapping to compute gene expression by aggregating the expression levels of individual isoforms from the same gene and then performing linear regression between SNPs and this aggregated gene expression level. However, SNPs may regulate isoforms from the same gene in different directions due to alternative splicing, or only regulate the expression level of one isoform, causing this approach to lose power. Here, we examine a broader question: which genes have at least one isoform whose expression level is regulated by genetic variants? In this study, we propose and evaluate several approaches to answering this question, demonstrating that "isoform-aware" methods—those that account for the expression levels of individual isoforms—have substantially greater power to answer this question than standard "gene-level" eQTL mapping methods. We identify settings in which different approaches yield an inflated number of false discoveries or lose power. In particular, we show that calling an eGene if there is a significant association between a SNP and any isoform fails to control False Discovery Rate, even when applying standard False Discovery Rate correction. We show that similar trends are observed in real data from the GEUVADIS and GTEx studies, suggesting the possibility that similar effects are present in these consortia. [ABSTRACT FROM AUTHOR]

[Display omitted] • Characterizing the heterogeneity of individual cognitive aging from a mitochondrial perspective. • Comprehensively assessing brain resilience through genetic metrics. • Individuals' levels of brain resilience were comprehensively measured by eight pathological characteristics. • The performance of PRS models could be efficiently improved by incorporating mitochondria-related loci. • Significant implications for the prevention and intervention of Alzheimer's disease. Identification of high-risk people for Alzheimer's disease (AD) is critical for prognosis and early management. Longitudinal epidemiologic studies have observed heterogeneity in the brain and cognitive aging. Brain resilience was described as above-expected cognitive function. The "resilience" framework has been shown to correlate with individual characteristics such as genetic factors and age. Besides, accumulative evidence has confirmed the association of mitochondria with the pathogenesis of AD. However, it is challenging to assess resilience through genetic metrics, in particular incorporating mitochondria-associated loci. In this paper, we first demonstrated that polygenic risk scores (PRS) could characterize individuals' resilience levels. Then, we indicated that mitochondria-associated loci could improve the performance of PRSs, providing more reliable measurements for the prevention and diagnosis of AD. The discovery (N = 1,550) and independent validation samples (N = 2,090) were used to construct nine types of PRSs containing mitochondria-related loci (PRSMT) from both biological and statistical aspects and combined them with known AD risk loci derived from genome-wide association studies (GWAS). Individuals' levels of brain resilience were comprehensively measured by linear regression models using eight pathological characteristics. It was found that PRSs could characterize brain resilience levels (e.g., Pearson correlation test P min = 7.96 × 10 - 9 ). Moreover, the performance of PRS models could be efficiently improved by incorporating a small number of mitochondria-related loci (e.g., Pearson correlation test P improved from 1.41 × 10 - 3 to 6.09 × 10 - 6 ). PRSs' ability to characterize brain resilience was validated. More importantly, by incorporating some mitochondria-related loci, the performance of PRSs in measuring brain resilience could be significantly improved. Our findings imply that mitochondria may play an important role in brain resilience, and targeting mitochondria may open a new door to AD prevention and therapy. [ABSTRACT FROM AUTHOR]

Expression quantitative trait locus (eQTL) analysis is a useful tool to identify genetic loci that are associated with gene expression levels. Large collaborative efforts such as the Genotype-Tissue Expression (GTEx) project provide valuable resources for eQTL analysis in different tissues. Most existing methods, however, either focus on one tissue at a time, or analyze multiple tissues to identify eQTLs jointly present in multiple tissues. There is a lack of powerful methods to identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. In this paper, we propose a novel statistical framework to improve the eQTL detection efficacy in the tissue of interest with auxiliary information from other tissues. This framework can enhance the power of the hypothesis test for eQTL effects by incorporating shared and specific effects from multiple tissues into the test statistics. We also devise data-driven and distributed computing approaches for efficient implementation of eQTL detection when the number of tissues is large. Numerical studies in simulation demonstrate the efficacy of the proposed method, and the real data analysis of the GTEx example provides novel insights into eQTL findings in different tissues. • Identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. • A novel mFDR-control procedure is proposed to maximize the mTPR. • Propose distributed computing approach for efficient eQTL detection. [ABSTRACT FROM AUTHOR]

Fungal pathogens Plasmopara viticola (Berk. & M.A. Curtis) Berl. & De Toni (downy mildew) and Erysiphe necator Schwein. (powdery mildew) represent the biggest threats for grape growers worldwide. Under suitable conditions, these pathogens can spread very quickly through vineyards and cause significant damage. The most ecological way to reduce the possibility of infection in vineyards is growing interspecific genotypes which are able to suppress these pathogens and stop the spread of infection. With this in mind, 9 international and 11 Czech grapevine genotypes were analysed in order to genotype the resistance loci present in them. As a tool a set of SSR markers linked to known loci of resistance to downy and powdery mildew was used. Namely, presence of four loci responsible for resistance to Plasmopara viticola (Rpv3, Rpv4, Rpv7, and Rpv10) and two for Erysiphe necator (Ren3 and Ren9) were analysed with respective SSR markers. By this way the degree of resistance gene pyramiding was newly assessed in all analysed cultivars and their perspectives in grapevine breeding are discussed. [ABSTRACT FROM AUTHOR]

Powdery mildew (PM) is a fungus that causes disease in both the field and the greenhouse. Utilizing resistant cultivars is the most effective approach of disease management. To develop insertion-deletion (InDel) markers associated to this trait, the whole genomes of the PM resistant line M17050 (P1) and the PM-susceptible line 28-1-1 (P2) were sequenced. A total of 1 200 InDels, with an average of 100 markers per chromosome, were arbitrarily chosen from the sequencing data for experimental validation. One hundred InDel markers were ultimately selected due to their informative genetic bands. Further, an F2 segregating population of melons generated from these two parents was inoculated by the PM pathogen. Based on bulk segregant analysis (BSA) using these 100 InDel markers, the powdery mildew resistance was associated with the genomic region LVpm12.1 on the melon chromosome 12. This region overlapped the previously described quantitative trait locus (QTL)-hotspot area carrying multiple PM-resistance QTLs. Moreover, conventional QTL mapping analysis was done, which located LVpm12.1 in the region between 22.72 and 23.34 Mb, where three highly polymorphic InDel markers MInDel89, MInDel92, and MInDel93 were detected. Therefore, these markers could be used to track this resistance locus in melon while the lines carrying this locus could be employed in PM melon resistance breeding programs after validation tests [ABSTRACT FROM AUTHOR]

Genetic diversity is referred to as any variation at the phenotypic, DNA or genomic level of an individual, population or species. The appraisal of diversity is important to understand its pattern and evolutionary relationships between germplasms or genotypes, which will aid in sampling the genetic resources in a more systematic manner for conservation and crop improvement. The present study employed 50 simple sequence repeat (SSR) markers linked to the yield and fibre quality/colour traits for estimating the genetic diversity in 33 cotton genotypes of diploid and tetraploid species differing in fibre colour. The diversity analysis was performed in GenAlEx (Ver. 6.41) and Powermarker (Ver. 3.25) while DARwin (Ver. 6.0.21) software was used to establish the phylogenetic relationships following neighbour- -joining (NJ) and unweighted pair group method with arithmetic (UPGMA) mean method. Markers generated 186 polymorphic loci as genotypic data with an average of 3.72 alleles and an average polymorphic information content (PIC) value of 0.59 per SSR locus. The NJ and UPGMA grouped 33 genotypes into three major clusters I, II and III consisting of 21 tetraploid Gossypium hirsutum, 10 G. arboreum coloured and 2 white cotton genotypes, respectively. In the PCA, the first two components (PC1 and PC2) explained 74.69% of the variation and the biplot plotted the 33 genotypes in three groups. The study established the diverse nature of 33 cotton genotypes based on their fibre colour and ploidy level. With confirmation of the prevalent genetic diversity, we suggest that hybridisation can be planned among diverse genotypes to unleash greater variation in the fibre colour or to derive superior cross combinations. [ABSTRACT FROM AUTHOR]