Quantitative Trait Loci Research Articles

GRABSEEDS: extraction of plant organ traits through image analysis

BackgroundPhenotyping of plant traits presents a significant bottleneck in Quantitative Trait Loci (QTL) mapping and genome-wide association studies (GWAS). Computerized phenotyping using digital images promises rapid, robust, and reproducible measurements of dimension, shape, and color traits of plant organs, including grain, leaf, and floral traits.ResultsWe introduce GRABSEEDS, which is specifically tailored to extract a comprehensive set of features from plant images based on state-of-the-art computer vision and deep learning methods. This command-line enabled tool, which is adept at managing varying light conditions, background disturbances, and overlapping objects, uses digital images to measure plant organ characteristics accurately and efficiently. GRABSEED has advanced features including label recognition and color correction in a batch setting.ConclusionGRABSEEDS streamlines the plant phenotyping process and is effective in a variety of seed, floral and leaf trait studies for association with agronomic traits and stress conditions. Source code and documentations for GRABSEEDS are available at: https://github.com/tanghaibao/jcvi/wiki/GRABSEEDS.

Genetic improvement of drought stress tolerance in maize, recent advancements and future research direction

Maize is an imperative crop around the globe, and it provides several essential nutrients to humans and animals. Environmental changes seriously affect growth and productivity. Drought stress is one of the most important abiotic stresses, reducing maize growth and yield and threatening global food security. For decades, breeders have been trying to improve maize's ability to counter the toxic effects of drought stress. Drought tolerance is controlled by many genes and it complicates molecular breeding. The use of conventional breeding methods limited the development of drought tolerance in maize because of the complex nature of this trait. Hence, maize breeders have shifted their focus towards improvement of drought tolerance in maize at molecular level. Different molecular tools like quantitative trait loci (QTL) mapping, genome-wide-association-studies (GWAS), transcriptome analysis, transcription factor (TFs) analysis, and CRISPR/Cas9 have played a vital role in gene’s identification and their use in molecular breeding. These genomic regions have been proven very effective, and more studies are being conducted to increase their efficiency; however, the improvement level is limited because of the complex genetic mechanism of drought tolerance. Different review articles have been published on this aspect; however, a comprehensive and updated overview of drought tolerance needs to be included. The current review highlights the role of diverse molecular techniques to improve drought tolerance in maize. This review article will enhance the interest of researchers working on the genetic improvement of maize.

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions.

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.

Genome-Wide Analysis Reveals Copy Number Variant Gene TGFBR3 Regulates Pig Back Fat Deposition.

BFT is closely related to meat quality and lean meat percentage in pigs. The BFT traits of European LW pigs significantly differ from those of Chinese indigenous fatty MZ pigs. CNV is a prevalent genetic variation that plays an important role in economically important traits in pigs. However, the potential contribution of CNV to BFT in LW and MZ pigs remains unclear. In this study, whole-genome CNV detection was performed using next-generation sequencing data from LW and MZ pigs, and transcriptome data from back fat tissue of 180-day-old LW and MZ pigs were integrated for expression quantitative trait loci (eQTL) analysis. We identified a copy number variation in the TGFBR3 gene associated with BFT, showing a dose effect between the genome and transcriptome levels of the TGFBR3 gene. In porcine preadipocytes, TGFBR3 expression continuously increased during differentiation. Knockdown of TGFBR3 using specific siRNA inhibited preadipocyte differentiation and proliferation. Our study provides insights into the genetic regulation of pork quality and offers a theoretical basis for improving carcass quality by modulating BFT in pigs.

Validation and identification of new QTLs for plant and fruit developmental and composition traits in eggplant under low N conditions

Enhancing plant adaptation to low input conditions is a fundamental goal for implementing sustainable agriculture. In the present study, two eggplant (Solanum melongena) accessions (MEL1 and MEL5), two introgression lines (ILs) derived from eggplant wild relatives S. dasyphyllum (IL-M1-D1) and S. insanum (IL-M5-I9), and a heterozygous version of this last IL (ILHet-M5-I9), along with hybrids among them were evaluated under low N (LN) conditions. IL-M1-D1 carries an introgressed fragment of 4.9 Mb in homozygosis from S. dasyphyllum on chromosome 2, while IL-M5-I9 and ILHet-M5-I9 carry an introgression of 21.5 Mb on chromosome 9 in homozygosis and heterozygosis, respectively, from S. insanum. Multiple quantitative trait loci (QTLs) for several traits of interest were associated with both introgressions under LN conditions in a previous study with segregating advanced backcrosses. Here we evaluated the performance of these materials for 22 agronomic and developmental traits under low N fertilization (LN) conditions. Hybrids with the ILs enabled the study of genetic background effects on QTLs expression. The materials evaluated showed a significant phenotypic variation, particularly within hybrids segregating for the introgression from S. insanum in chromosome 9. Statistical analysis revealed no significant differences among hybrids carrying or not the introgression on chromosome 2 of S. dasyphyllum, and only slight differences were observed between the IL-M1-D1 and its recurrent parent S. melongena MEL1, suggesting a limited impact of this introgression on chromosome 2 on the phenotype variation. However, the differences observed between IL-M5-I9 and its recurrent parent S. melongena MEL5, together with the association between genotypic and phenotypic variation in hybrids segregating for this introgression, allowed the identification of 13 QTLs on chromosome 9. These results successfully validated the previously identified QTLs for flavonol content in leaves, nitrogen balanced index, fruit mean weight, and nitrogen content in leaves and, also revealed nine new QTLs associated with the introgressed genomic region in chromosome 9. This study emphasizes the influence of environmental conditions, genotypes, and genetic backgrounds on the phenotypic expression of eggplant QTLs introgressed from wild relatives and highlights the importance of QTL validation. These findings contribute valuable insights for developing new eggplant cultivars for a more sustainable agriculture, particularly with adaptation to LN conditions.

Detection of Quantitative Trait Loci Associated with Alkaline Tolerance Using Recombinant Inbred Line Population Derived from Longdao5 × Zhongyouzao8 at Seedling Stage.

Salt-alkaline stress is one of the most stressful occurrences, causing negative effects on plant development and agricultural yield. Identifying and utilizing genes that affect alkaline tolerance is an excellent approach to accelerate breeding processes and meet the needs for remediating saline-alkaline soil. Here, we employed a mapping population of 176 recombinant inbred lines (RILs) produced from a cross between alkali-tolerant Longdao5 and alkali-sensitive Zhongyouzao8 to identify the quantitative trait loci (QTLs) determining alkali tolerance at the seedling stage. For the evaluation of alkali tolerance, the recovered seedling's average alkali tolerance index (ATI), root number (RN), root length (RL), seedling dry weight (SW), root dry weight (RW), and seedling height (SH) were assessed, together with their relative alkaline damage rate. Under alkaline stress, the ATI was substantially negative connected with the root number, seedling height, seedling dry weight, and root dry weight; however, it was considerably positive correlated with the relative alkaline damage rate of the root number and root dry weight. A total of 13 QTLs for the root number, root length, seedling height, seedling dry weight, root dry weight, and alkali tolerance index under alkaline stress were identified, which were distributed across chromosomes 1, 2, 3, 4, 5, 7, and 8. All of these QTLs formed two QTL clusters for alkali tolerance on chromosome 5 and chromosome 7, designated AT5 and AT7, respectively. Nine QTLs were identified for the relative alkaline damage rate of the root number, root length, seedling height, seedling dry weight, and root dry weight under alkali stress. These QTLs were located on chromosome 2, 4, 6, 7, 8, 9, and 12. In conclusion, these findings further strengthen our knowledge about rice's genetic mechanisms for alkaline tolerance. This research offers clues to accelerate breeding programs for new alkaline-tolerance rice varieties.

Genetic analysis of QTLs for lysine content in four maize DH populations

BackgroundLow levels of the essential amino acid lysine in maize endosperm is considered to be a major problem regarding the nutritional quality of food and feed. Increasing the lysine content of maize is important to improve the quality of food and feed nutrition. Although the genetic basis of quality protein maize (QPM) has been studied, the further exploration of the quantitative trait loci (QTL) underlying lysine content variation still needs more attention.ResultsEight maize inbred lines with increased lysine content were used to construct four double haploid (DH) populations for identification of QTLs related to lysine content. The lysine content in the four DH populations exhibited continuous and normal distribution. A total of 12 QTLs were identified in a range of 4.42–12.66% in term of individual phenotypic variation explained (PVE) which suggested the quantitative control of lysine content in maize. Five main genes involved in maize lysine biosynthesis pathways in the QTL regions were identified in this study.ConclusionsThe information presented will allow the exploration of candidate genes regulating lysine biosynthesis pathways and be useful for marker-assisted selection and gene pyramiding in high-lysine maize breeding programs.

Identification of genetic association between mitochondrial dysfunction and knee osteoarthritis through integrating multi-omics: a summary data-based Mendelian randomization study

ObjectiveAssociation between mitochondrial dysfunction and osteoarthritis (OA) has been consistently investigated, yet their genetic association remains obscure. In this study, mitochondrial-related genes were used as instrumental variables to proxy for mitochondrial dysfunction, and summary data of knee OA (KOA) were used as outcome to examine their genetic association.MethodsWe obtained 1136 mitochondrial-related genes from the human MitoCarta3.0 database. Genetic proxy instruments for mitochondrial-related genes from studies of corresponding gene expression (n = 31,684) and protein (n = 35,559) quantitative trait locus (eQTLs and pQTLs), respectively. Aggregated data for KOA (62,497 KOA cases and 333,557 controls) were extracted from the largest OA genome-wide association study (GWAS). We integrated QTL data with KOA GWAS data to estimate their genetic association using summary data-based Mendelian randomization analysis (SMR). Additionally, we implemented Bayesian colocalization analysis to reveal whether suggestive mitochondrial-related genes and KOA were driven by a same genetic variant. Finally, to validate the primary findings, replication study (24,955 cases and 378,169 controls) and multi-SNP-based SMR (SMR-multi) test was performed.ResultsThrough SMR analysis, we found that the expression levels of 2 mitochondrial-related genes were associated with KOA risk. Specifically, elevated gene expression levels of the IMMP2L (odds ratio [OR] = 1.056; 95% confidence interval [CI] = 1.030–1.082; P-FDR = 0.004) increased the risk of KOA. Conversely, increased gene expression levels of AKAP10 decreased the risk of KOA (OR = 0.955; 95% CI, 0.934–0.977; P-FDR = 0.019). Colocalization analysis demonstrated that AKAP10 (PP.H4 = 0.84) and IMMP2L (PP.H4 = 0.91) shared the same genetic variant with KOA. In addition, consistent results were found in replication study and SMR-multi test, further demonstrating the reliability of our findings.ConclusionsIn summary, our analyses revealed the genetic association between mitochondrial dysfunction proxied by mitochondrial-related genes and KOA, providing new insight into potential pathogenesis of KOA. Furthermore, these identified candidate genes offer the possibility of clinical drug target development for KOA.Key points• This is the first SMR study to explore the genetic association between mitochondrial dysfunction proxied by mitochondrial-related genes and KOA.• Sufficient evidence to support genetic association between the expression levels of AKAP10 and IMMP2L, and KOA• Our MR analysis may provide novel new insight into potential pathogenesis of KOA.• These identified candidate genes offer the possibility of clinical drug target development for KOA

Direct targets of MEF2C are enriched for genes associated with schizophrenia and cognitive function and are involved in neuron development and mitochondrial function.

Myocyte Enhancer Factor 2C (MEF2C) is a transcription factor that plays a crucial role in neurogenesis and synapse development. Genetic studies have identified MEF2C as a gene that influences cognition and risk for neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia (SCZ). Here, we investigated the involvement of MEF2C in these phenotypes using human-derived neural stem cells (NSCs) and glutamatergic induced neurons (iNs), which represented early and late neurodevelopmental stages. For these cellular models, MEF2C function had previously been disrupted, either by direct or indirect mutation, and gene expression assayed using RNA-seq. We integrated these RNA-seq data with MEF2C ChIP-seq data to identify dysregulated direct target genes of MEF2C in the NSCs and iNs models. Several MEF2C direct target gene-sets were enriched for SNP-based heritability for intelligence, educational attainment and SCZ, as well as being enriched for genes containing rare de novo mutations reported in ASD and/or developmental disorders. These gene-sets are enriched in both excitatory and inhibitory neurons in the prenatal and adult brain and are involved in a wide range of biological processes including neuron generation, differentiation and development, as well as mitochondrial function and energy production. We observed a trans expression quantitative trait locus (eQTL) effect of a single SNP at MEF2C (rs6893807, which is associated with IQ) on the expression of a target gene, BNIP3L. BNIP3L is a prioritized risk gene from the largest genome-wide association study of SCZ and has a function in mitophagy in mitochondria. Overall, our analysis reveals that either direct or indirect disruption of MEF2C dysregulates sets of genes that contain multiple alleles associated with SCZ risk and cognitive function and implicates neuron development and mitochondrial function in the etiology of these phenotypes.

Early exposure to phosphorus starvation induces genetically determined responses in Sorghum bicolor roots

Key message We identified novel physiological and genetic responses to phosphorus starvation in sorghum diversity lines that augment current knowledge of breeding for climate-smart crops in Europe.Phosphorus (P) deficiency and finite P reserves for fertilizer production pose a threat to future global crop production. Understanding root system architecture (RSA) plasticity is central to breeding for P-efficient crops. Sorghum is regarded as a P-efficient and climate-smart crop with strong adaptability to different climatic regions of the world. Here we investigated early genetic responses of sorghum RSA to P deficiency in order to identified genotypes with interesting root phenotypes and responses under low P. A diverse set of sorghum lines (n = 285) was genotyped using DarTSeq generating 12,472 quality genome wide single-nucleotide polymorphisms. Root phenotyping was conducted in a paper-based hydroponic rhizotron system under controlled greenhouse conditions with low and optimal P nutrition, using 16 RSA traits to describe genetic and phenotypic variability at two time points. Genotypic and phenotypic P-response variations were observed for multiple root traits at 21 and 42 days after germination with high broad sense heritability (0.38–0.76). The classification of traits revealed four distinct sorghum RSA types, with genotypes clustering separately under both low and optimal P conditions, suggesting genetic control of root responses to P availability. Association studies identified quantitative trait loci in chromosomes Sb02, Sb03, Sb04, Sb06 and Sb09 linked with genes potentially involved in P transport and stress responses. The genetic dissection of key factors underlying RSA responses to P deficiency could enable early identification of P-efficient sorghum genotypes. Genotypes with interesting RSA traits for low P environments will be incorporated into current sorghum breeding programs for later growth stages and field-based evaluations.

Identification of novel drug targets for osteoarthritis by integrating genetics and proteomes from blood

BackgroundOsteoarthritis (OA) is a degenerative osteoarticular disease, involving genetic predisposition. How the risk variants confer the risk of OA through their effects on proteins remains largely unknown. Therefore, we aimed to discover new and effective drug targets for OA and its subtypes.MethodsA proteome-wide association study (PWAS) was performed based on OA and its subtypes genome-wide association studies (GWAS) summary datasets and the protein quantitative trait loci (pQTL) data. Subsequently, Mendelian randomization (MR) and colocalization analysis was conducted to estimate the associations between protein and OA risk. The replication analysis was performed in an independent dataset of human plasma pQTL data.ResultsThe abundance of seven proteins was causally related to OA, two proteins to knee OA and six proteins to hip OA, respectively. We replicated 2 of these proteins using an independent pQTL dataset. With the further support of colocalization, and higher ECM1 level was causally associated with a higher risk of OA and hip OA. Higher PCSK1 level was causally associated with a lower risk of OA. And higher levels of ITIH1, EFEMP1, and ERLEC1 were associated with decreased risk of hip OA.ConclusionOur study provides new insights into the genetic component of protein abundance in OA and a promising therapeutic target for future drug development.

Proteome-wide Mendelian randomization identified potential drug targets for migraine

BackgroundMigraine is a highly prevalent and complex neurovascular disease. However, the currently available therapeutic drugs often fall to adequately meet clinical needs due to limited effectiveness and numerous undesirable side effects. This study aims to identify putative novel targets for migraine treatment through proteome-wide Mendelian randomization (MR).MethodsWe utilized MR to estimate the causal effects of plasma proteins on migraine and its two subtypes, migraine with aura (MA) and without aura (MO). This analysis integrated plasma protein quantitative trait loci (pQTL) data with genome-wide association studies (GWAS) findings for these migraine phenotypes. Moreover, we conducted a phenome-wide MR assessment, enrichment analysis, protein–protein interaction networks construction, and mediation MR analysis to further validate the pharmaceutical potential of the identified protein targets.ResultsWe identified 35 protein targets for migraine and its subtypes (p < 8.04 × 10–6), with prioritized targets showing minimal side effects. Phenome-wide MR identified novel protein targets—FCAR, UBE2L6, LATS1, PDCD1LG2, and MMP3—that have no major disease side effects and interacted with current acute migraine medication targets. Additionally, MMP3, PDCD1LG2, and HBQ1 interacted with current preventive migraine medication targets. The causal effects of plasma protein on migraine were partly mediated by plasma metabolites (proportion of mediation from 3.8% to 21.0%).ConclusionsA set of potential protein targets for migraine and its subtypes were identified. These proteins showed rare side effects and were responsible for biological mechanisms involved in migraine pathogenesis, indicating priority for the development of migraine treatments.

Pleiotropic Quantitative Trait Loci (QTL) Mining for Regulating Wheat Processing Quality- and Yield-Related Traits.

To investigate the genetic basis of processing quality- and yield-related traits in bread wheat (Triticum aestivum L., AABBDD), a systematic analysis of wheat processing quality- and yield-related traits based on genome-wide association studies (GWASs) of 285 regional test lines of wheat from Hebei province, China, was conducted. A total of 87 quantitative trait loci (QTL), including twenty-one for water absorption (WA), four for wet gluten content, eight for grain protein content, seventeen for dough stability time (DST), thirteen for extension area (EA), twelve for maximum resistance (MR), five for thousand-grain weight (TGW), one for grain length, and six for grain width were identified. These QTL harbored 188 significant single-nucleotide polymorphisms (SNPs). Twenty-five SNPs were simultaneously associated with multiple traits. Notably, the SNP AX-111015470 on chromosome 1A was associated with DST, EA, and MR. SNPs AX-111917292 and AX-109124553 on chromosome 5D were associated with wheat WA and TGW. Most processing quality-related QTL and seven grain yield-related QTL identified in this study were newly discovered. Among the surveyed accessions, 18 rare superior alleles were identified. This study identified significant QTL associated with quality-related and yield-related traits in wheat, and some of them showed pleiotropic effects. This study will facilitate molecular designs that seek to achieve synergistic improvements of wheat quality and yield.

Genome-wide association study of bacterial blight resistance in soybean.

Bacterial blight caused by Pseudomonas syringae pv. glycines (Psg) is a widespread foliar disease. Although four Resistance to Pseudomonas syringae pv. glycinea (Rpg) 1 ~ 4 (Rpg1~4) genes that have been observed to segregate in a Mendelian pattern have been reported to confer resistance to Psg in soybean, the genetic basis of quantitative resistance to bacterial blight in soybean remains unclear. In the present study, the Psg resistance of two soybean association panels consisting of 573 and 213 lines, respectively, were phenotyped in multiple environments in 2014 - 2016. Genome-wide association study (GWAS) were performed using 2 models FarmCPU and BLINK to identify Psg resistance loci. A total of 40 soybean varieties with high level of Psg resistance were identified, and 14 quantitative trait loci (QTLs) were detected on 12 soybean chromosomes. These QTLs were identified for the first time. The majority of the QTLs were only detected in one or the other association panels, while qRPG-18-1 was detected in both association panels for at least one growing season. A total of 46 candidate Psg resistance genes were identified from the qRpg_13_1, qRPG-15-1, and qRPG-18-1 loci based on gene function annotation. In addition, we found the genomic region covering rpg1-b and rpg1-r harbored the synteny with a genomic region on chromosome 15, and identified 16 nucleotide binding site - leucine-rich repeat (NBS-LRR) genes as the candidate Psg resistance genes from the synteny blocks. This study provides new information for dissecting the genetic control of Psg resistance in soybean.

Multi-locus genome-wide association study for grain yield and drought tolerance indices in sorghum accessions.

Drought is a significant factor that causes yield loss in essential cereal crops such as sorghum [Sorghum bicolor (L.) Moench], necessitating the development of drought-tolerant varieties adaptable to various water conditions. This study aimed to pinpoint drought-tolerant sorghum lines and genomic regions for tolerance by utilizing 216 sorghum accessions in stressed and non-stressed environments at two locations. Genetic diversity was evident among accessions in terms of grain yield under different watering regimes. Drought stress indices such as the stress tolerance index, mean productivity, geometric mean productivity, harmonic mean productivity, yield stability index, and yield index were identified as effective measures for selecting drought-tolerant sorghum. Cluster analysis classified genotypes into four groups based on their association with grain yield, highlighting Acc. #28546 and Acc. #216739 as highly drought tolerant across environments. This study identified 32 and 22 quantitative trait nucleotides (QTNs) for drought indices and grain yield under stress and non-stress conditions, respectively, at two locations, with five common QTNs linked to multiple drought indices. Colocation analysis revealed that these QTNs were associated with known stay-green-related quantitative trait loci (QTLs), and 47 putative genes near these QTNs potentially influenced drought tolerance traits. It is suggested that accession selection considers multiple indices for robust evaluation. Understanding the identified genes and their functions provides insights into the genetic mechanisms governing plant responses to drought stress, offering prospects for developing improved drought-resistant sorghum varieties through further genetic research.

Yellow Dwarf Virus Resistance in Barley: Phenotyping, Remote Imagery, and Virus-Vector Characterization.

Yellow dwarf viruses (YDVs) spread by aphids are some of the most economically important barley (Hordeum vulgare) virus-vector complexes worldwide. Detection and control of these viruses are critical components in the production of barley, wheat, and numerous other grasses of agricultural importance. Genetic control of plant diseases is often preferable to chemical control to reduce the environmental and economic cost of foliar insecticides. Accordingly, the objectives of this work were to (i) screen a barley population for resistance to YDVs under natural infection using phenotypic assessment of disease symptoms, (ii) implement drone imagery to further assess resistance and test its utility as a disease screening tool, (iii) identify the prevailing virus and vector types in the experimental environment, and (iv) perform a genome-wide association study to identify genomic regions associated with measured traits. Significant genetic differences were found in a population of 192 barley inbred lines regarding their YDV symptom severity, and symptoms were moderately to highly correlated with grain yield. The YDV severity measured with aerial imaging was highly correlated with on-the-ground estimates (r = 0.65). Three aphid species vectoring three YDV species were identified with no apparent genotypic influence on their distribution. A quantitative trait locus impacting YDV resistance was detected on chromosome 2H, albeit undetected using aerial imaging. However, quantitative trait loci for canopy cover and mean normalized difference vegetation index were successfully mapped using the drone. This work provides a framework for utilizing drone imagery in future resistance breeding efforts for YDVs in cereals and grasses, as well as in other virus-vector disease complexes.

Polygenic, autosomal, and stable spirotetramat resistance in Chrysoperla carnea resulting in increased fitness.

Green lacewing, Chrysoperla carnea (Stephens) is a generalist predator used as a biological control agent in agro ecosystems. In order to use chemical and biological control in an integrated way, it is advantageous to know about natural enemy resistance response to a selected chemical. To determine C. carnea spirotetramat resistance potential, a population collected from the field was selected in the laboratory. Then we determined how spirotetramat resistance was inherited and how much it impacts the fitness of C. carnea. After eighteen selections with spirotetramat, the selected population (Spiro-Sel) of C. carnea had a 47-fold of resistance when compared to an UNSEL population. Inheritance results showed that spirotetramat resistance was inherited as an autosomal, incompletely dominant and polygenic trait. The values of effective dominance decreased from 0.87 (incomplete dominant) to 0.00 (complete recessive) as the concentration of spirotetramat increased from 625 mg/L to 10000 mg/L. The Spiro-Sel strain had no cross resistance to chlorfenapyr (1.10-fold), deltamethrin (1.26-fold) and chlorpyrifos (1.27-fold). After 7 generations without selection pressure resistance to all experimental insecticides in the Spiro-Sel strain was stable. Fitness data of the Spiro-Sel, Cross A, Cross B, UNSEL and susceptible strains of C. carnea showed that spirotetramat resistance increased the fitness of the selected green lacewing population. Life history parameters like fecundity, net reproductive rate, and relative fitness of the Spiro-Sel strain significantly increased when compared to the susceptible or unselected strains of C. carnea. These findings show that C. carnea is a perfect candidate for integrated pest management (IPM) programmes that combine biological control methods with selective pesticide applications to manage a variety of insect pests. Additionally, it would reduce the possibility of pests developing pesticide resistance despite repeated applications. It would be an excellent choice for widespread releases and be effective in most spray programs.

QTL mapping and epistatic interactions for improved seed oil quality in safflower

QTL mapping and epistatic interactions for improved seed oil quality in safflower

QTL Mapping and Candidate Gene Analysis for Wax Trait of Stem and Leaf in Durum Wheat (Triticum turgidum L. ssp. durum (Desf.))

QTL Mapping and Candidate Gene Analysis for Wax Trait of Stem and Leaf in Durum Wheat (Triticum turgidum L. ssp. durum (Desf.))

Fish Genomics and Its Application in Disease‐Resistance Breeding

ABSTRACTGlobal aquaculture production has been rising for several decades, with up to 76% of the total production from fish. However, the problem of fish diseases is becoming more and more prominent in today's context of pursuing sustainable aquaculture. Since the first fish genome assembly reported in 2002, genomic approaches have been successfully implemented in fish breeding to enhance disease resistance and reduce economic losses caused by diverse fish diseases. Here, we present a review of the current progress in fish genomics and its application in disease‐resistance breeding. First, assembly data for all publicly available fish genomes were curated and statistical analysis of these data were performed. Subsequently, genomics‐assisted breeding approaches (including quantitative trait loci mapping, genome‐wide association study, marker‐assisted selection, genomic selection, gene transfer, and genome editing) that have been applied in practical disease–resistance breeding programs are outlined. In addition, candidate genetic markers that could possibly be utilized in breeding were summarized. Finally, remaining challenges and further directions were discussed. In summary, this review provides insight into fish genomics and genomics‐assisted breeding of disease‐resistant fish varieties.