Winter wheat yield improvement by genetic gain across different provinces in China

The replacement of winter wheat varieties has contributed significantly to yield improvement worldwide,with remarkable progress in China.Drawing on two sets of data,production yield from the National Bureau of Statistics of China and experimental yield from literature,this study aims to(1)illustrate the increasing patterns of production yield among different provinces from 1978 to 2018 in China,(2)explore the genetic gain in yield and yield relevant traits through the variety replacement based on experimental yield from 1937 to 2016 in China,and(3)compare the yield gap between experimental yield and production yield.The results show that both the production and experimental yields significantly increased along with the variety replacement.The national annual yield increase ratio for the production yield was 1.67%from 1978 to 2018,varying from 0.96%in Sichuan Province to 2.78%in Hebei Province;such ratio for the experimental yield was 1.13%from 1937 to 2016.The yield gap between experimental and production yields decreased from the 1970s to the 2010s.This study reveals significant increases in some yield components consequent to variety replacement,including thousand-grain weight,kernel number per spike,and grain number per square meter;however,no change is shown in spike number per square meter.The biomass and harvest index consistently and significantly increased,whereas the plant height decreased significantly.

Genetically modified pigs:Emerging animal models for hereditary hearing loss

Hereditary hearing loss(HHL),a genetic disorder that impairs auditory function,significantly affects quality of life and incurs substantial economic losses for society.To investigate the underlying causes of HHL and evaluate therapeutic outcomes,appropriate animal models are necessary.Pigs have been extensively used as valuable large animal models in biomedical research.In this review,we highlight the advantages of pig models in terms of ear anatomy,inner ear morphology,and electrophysiological characteristics,as well as recent advancements in the development of distinct genetically modified porcine models of hearing loss.Additionally,we discuss the prospects,challenges,and recommendations regarding the use pig models in HHL research.Overall,this review provides insights and perspectives for future studies on HHL using porcine models.

A dual-RPA based lateral flow strip for sensitive,on-site detection of CP4-EPSPS and Cry1Ab/Ac genes in genetically modified crops

Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.

Genetic pathways in cerebral palsy:a review of the implications for precision diagnosis and understanding disease mechanisms

Ce rebral palsy is a diagnostic term utilized to describe a group of permanent disorders affecting movement and posture.Patients with cerebral palsy are often only capable of limited activity,resulting from non-progressive disturbances in the fetal or neonatal brain.These disturbances severely impact the child’s daily life and impose a substantial economic burden on the family.Although cerebral palsy encompasses various brain injuries leading to similar clinical outcomes,the unde rstanding of its etiological pathways remains incomplete owing to its complexity and heterogeneity.This review aims to summarize the current knowledge on the genetic factors influencing cerebral palsy development.It is now widely acknowledged that genetic mutations and alterations play a pivotal role in cerebral palsy development,which can be further influenced by environmental fa ctors.Des pite continuous research endeavors,the underlying fa ctors contributing to cerebral palsy remain are still elusive.However,significant progress has been made in genetic research that has markedly enhanced our comprehension of the genetic factors underlying cerebral palsy development.Moreove r,these genetic factors have been categorized based on the identified gene mutations in patients through clinical genotyping,including thrombosis,angiogenesis,mitochondrial and oxidative phosphorylation function,neuronal migration,and cellular autophagy.Furthermore,exploring targeted genotypes holds potential for precision treatment.In conclusion,advancements in genetic research have substantially improved our understanding of the genetic causes underlying cerebral palsy.These breakthroughs have the potential to pave the way for new treatments and therapies,consequently shaping the future of cerebral palsy research and its clinical management.The investigation of cerebral palsy genetics holds the potential to significantly advance treatments and management strategies.By elucidating the underlying cellular mechanisms,we can develop to rgeted interventions to optimize outcomes.A continued collaboration between researchers and clinicians is imperative to comprehensively unravel the intricate genetic etiology of cerebral palsy.

An efficient method for constructing a random insertional mutant library for forward genetics in Nannochloropsis oceanica

Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.

Genetic Diversity of Jute Mallow (Corchorus spp.) Accessions Based on ISSR Markers

Jute mallow is a nutritious leafy vegetable. The leaves are rich in proteins, vitamins and essential amino acids. Molecular characterization of Jute mallow with focus on improvement of leaf yield is scarcely reported. In the present study, inter sequence simple repeats (ISSR) molecular markers were employed to assess genetic diversity and relationships of 83 accessions of Jute mallow from different parts of Africa and Asia conserved at the World Vegetable Center East and Southern Africa. A total of 89 bands were amplified by 8 ISSR primers. Number of polymorphic bands per primer ranged from 2 to 6 with an average of 2.75 bands per primer. Polymorphic information content (PIC) values ranged from 0.390 to 0.760 with average of 0.53. Average Nei’s gene diversity (h) and Shannon’s information index (I) were 0.335 and 0.494 respectively. The highest pairwise genetic distance was 0.431 observed in a population from East Africa accessions. PC1 and PC2 axis explained 21.69% and 11.66% of the total variation respectively. UPGMA cluster analysis grouped the accessions into six main clusters at genetic similarity coefficient of 0.53 as standard value for classification. These results have important implications for jute mallow breeding and conservation.

LociScan,a tool for screening genetic marker combinations for plant variety discrimination

To reduce the cost and increase the efficiency of plant genetic marker fingerprinting for variety discrimination,it is desirable to identify the optimal marker combinations.We describe a marker combination screening model based on the genetic algorithm(GA)and implemented in a software tool,Loci Scan.Ratio-based variety discrimination power provided the largest optimization space among multiple fitness functions.Among GA parameters,an increase in population size and generation number enlarged optimization depth but also calculation workload.Exhaustive algorithm afforded the same optimization depth as GA but vastly increased calculation time.In comparison with two other software tools,Loci Scan accommodated missing data,reduced calculation time,and offered more fitness functions.In large datasets,the sample size of training data exerted the strongest influence on calculation time,whereas the marker size of training data showed no effect,and target marker number had limited effect on analysis speed.

Genetic Diversity in Cowpea (Vigna unguiculata (L.) Walp) under Two Growing Conditions*

This study explores the use of genetic variability for advancing the genetic improvement of Cowpea (Vigna unguiculata (L.) Walp), particularly in response to insect infestation stress. Over a period spanning 2015 to 2017, forty accessions of cowpeas were evaluated to determine their variability under both insecticide spray and no insecticide spray conditions at the Teachings and Research Farms, Federal University of Agriculture, Abeokuta. The experimental design was a randomized complete block design in three replicates. The accessions were evaluated for plant height, leaf length, leaf width, number of days of 50% flowering, number of pods per plant, pod length, number of seeds per plant, 100-seed weight, and seed yield. Data collected were subjected to principal component and single linkage cluster analyses. Principal axis I (PCA1) accounted for 39% and 35% under insecticide spray and no insecticide spray respectively to the total variation in the accessions. Plant height with a factor score of 0.38, leaf length (0.41), number of leaves (0.37), and 100-seed, weight (0.30) was related to PCAI under insecticide spray while leaf width (0.32). Pod length (0.37) and number of seeds/plant (0.38) were significant to PCA1 under no insecticide spray. Notably, accessions such as SAMPEA6, SAMPEA10, IFE-Brown, and IFE-BPE exhibited consistent performance across both conditions, while others displayed condition-specific attributes. For instance, NGB1063, NGB1152, and NGB1093 demonstrated distinct traits under insecticide spray, while NGB1146 and NGB1124 exhibited notable characteristics under no insecticide spray conditions. Therefore, identifying these forty accessions with desirable traits hold promise for future genetic improvement efforts of cowpea cultivation in Nigeria and beyond.

Genetic and Agronomic Parameter Estimates of Growth, Yield and Related Traits of Maize (Zea mays L.) under Different Rates of Nitrogen Fertilization

This study evaluated the genetic and agronomic parameter estimates of maize under different nitrogen rates. The trial was established at the Njala Agricultural Research Centre experimental site during 2021 and 2022 in a split block design with three maize varieties (IWCD2, 2009EVDT, and DMR-ESR-Yellow) and seven nitrogen (0, 30, 60, 90, 120, 150 and 180 kg∙N∙ha−1) rates. Findings showed that cob diameter and anthesis silking time (ASI) had intermediate heritability, ASI had high genetic advance, ASI and grain yield had high genotypic coefficient of variation (GCV), while traits with high phenotypic coefficient of variation (PCV) were plant height, ASI, grain yield, number of kernel per cob, number of kernel rows, ear length, and ear height. The PCV values were higher than GCV, indicating the influence of the environment in the studied traits. Nitrogen rates and variety significantly (p < 0.05) influenced grain yield production. Mean grain yields and economic parameter estimates increased with increasing nitrogen rates, with the 30 and 180 kg∙N∙ha−1 plots exhibiting the lowest and highest grain yields of 1238 kg∙ha−1 and 2098 kg∙ha−1, respectively. Variety and nitrogen effects on partial factor productivity (PFPN), agronomic efficiency (AEN), net returns (NR), value cost ratio (VCR) and marginal return (MR) indicated that these parameters were significantly affected (p < 0.05) by these factors. The highest PFPN (41.3 kg grain kg−1∙N) and AEN (29.4 kg grain kg−1∙N) were obtained in the 30 kg∙N∙ha−1 plots, while the highest VCR (2.8) and MR (SLL 1.8 SLL−1 spent on N) were obtained in the 180 kg∙N∙ha−1. The significant influence of variety and nitrogen on traits suggests that increasing yields and maximizing profits require use of appropriate nitrogen fertilization and improved farming practices that could be exploited for increased productivity of maize.

Age-specific heterogeneity of genetic susceptibility to cardiovascular disease might have opposite outcomes depending on the presence of prediabetes

Examining age-specific heterogeneity of susceptibility to cardiovascular disease is also essential in individuals without prediabetes to determine its relative size and direction compared to those with prediabetes.Of particular interest,age-specific heterogeneity in genetic susceptibility may exhibit opposite directions depending on the presence or absence of prediabetes.

Population genomic data reveal low genetic diversity,divergence and local adaptation among threatened Reeves's Pheasant(Syrmaticus reevesii)

Population genomic data could provide valuable information for conservation efforts;however,limited studies have been conducted to investigate the genetic status of threatened pheasants.Reeves’s Pheasant(Syrmaticus reevesii)is facing population decline,attributed to increases in habitat loss.There is a knowledge gap in understanding the genomic status and genetic basis underlying the local adaptation of this threatened bird.Here,we used population genomic data to assess population structure,genetic diversity,inbreeding patterns,and genetic divergence.Furthermore,we identified candidate genes linked with adaptation across the current distribution of Reeves’s Pheasant.The present study assembled the first de novo genome sequence of Reeves’s Pheasant and annotated 19,458 genes.We also sequenced 30 individuals from three populations(Dabie Mountain,Shennongjia,Qinling Mountain)and found that there was clear population structure among those populations.By comparing with other threatened species,we found that Reeves’s Pheasants have low genetic diversity.Runs of homozygosity suggest that the Shennongjia population has experienced serious inbreeding.The demographic history results indicated that three populations experienced several declines during the glacial period.Local adaptative analysis among the populations identified 241 candidate genes under directional selection.They are involved in a large variety of processes,including the immune response and pigmentation.Our results suggest that the three populations should be considered as three different conservation units.The current study provides genetic evidence for conserving the threatened Reeves’s Pheasant and provides genomic resources for global biodiversity management.

Population genomic analysis reveals key genetic variations and the driving force for embryonic callus induction capability in maize

Genetic transformation has been an effective technology for improving the agronomic traits of maize.However,it is highly reliant on the use of embryonic callus(EC)and shows a serious genotype dependence.In this study,we performed genomic sequencing for 80 core maize germplasms and constructed a high-density genomic variation map using our newly developed pipeline(MQ2Gpipe).Based on the induction rate of EC(REC),these inbred lines were categorized into three subpopulations.The low-REC germplasms displayed more abundant genetic diversity than the high-REC germplasms.By integrating a genome-wide selective signature screen and region-based association analysis,we revealed 95.23 Mb of selective regions and 43 REC-associated variants.These variants had phenotypic variance explained values ranging between 21.46 and 49.46%.In total,103 candidate genes were identified within the linkage disequilibrium regions of these REC-associated loci.These genes mainly participate in regulation of the cell cycle,regulation of cytokinesis,and other functions,among which MYB15 and EMB2745 were located within the previously reported QTL for EC induction.Numerous leaf area-associated variants with large effects were closely linked to several REC-related loci,implying a potential synergistic selection of REC and leaf size during modern maize breeding.

Genetic variants in C1GALT1 are associated with gastric cancer risk by influencing immune infiltration

Core 1 synthase glycoprotein-N-acetylgalactosamine 3-β-galactosyltransferase 1(C1GALT1)is known to play a critical role in the development of gastric cancer,but few studies have elucidated associations between genetic variants in C1GALT1 and gastric cancer risk.By using the genome-wide association study data from the database of Genotype and Phenotype(dbGAP),we evaluated such associations with a multivariable logistic regression model and identified that the rs35999583 G>C in C1GALT1 was associated with gastric cancer risk(odds ratio,0.83;95% confidence interval[CI],0.75-0.92;P=3.95×10^(-4)).C1GALT1 mRNA expression levels were significantly higher in gastric tumor tissues than in normal tissues,and gastric cancer patients with higher C1GALT1 mRNA levels had worse overall survival rates(hazards ratio,1.33;95%CI,1.05-1.68;P_(log-rank)=1.90×10^(-2)).Furthermore,we found that C1GALT1 copy number differed in various immune cells and that C1GALT1 mRNA expression levels were positively correlated with the infiltrating levels of CD4^(+)T cells and macrophages.These results suggest that genetic variants of C1GALT1 may play an important role in gastric cancer risk and provide a new insight for C1GALT1 into a promising predictor of gastric cancer susceptibility and immune status.

Inbreeding and genetic load in a pair of sibling grouse species:Tetrastes sewersowi and T.bonasia

Genetic load and inbreeding are recognized as important factors to be considered in conservation programs.Elevated levels of both can increase the risk of population extinction by negatively impacting fitness-related characters in many species of plants and animals,including humans(inbreeding depression).Genomic tech-niques are increasingly used in measuring and understanding genetic load and inbreeding and their importance in evolution and conservation.We used whole genome resequencing data from two sibling grouse species in subarctic Eurasia to quantify both.We found a large range of inbreeding measured as FROH(fraction of runs of homozygosity)in individuals from different populations of Chinese Grouse(Tetrastes sewerzowi)and Hazel Grouse(T.bonasia).FROH estimated from genome-wide runs of homozygosity(ROH)ranged from 0.02 to 0.24 among Chinese Grouse populations and from 0.01 to 0.44 in Hazel Grouse.Individuals from a population of Chinese Grouse residing in the Qilian mountains and from the European populations of Hazel Grouse(including samples from Sweden,Germany and Northeast Poland)were the most inbred(FROH ranged from 0.10 to 0.23 and 0.11 to 0.44,respectively).These levels are comparable to other highly inbred populations of birds.Hazel Grouse from northern China and Chinese Grouse residing in the Qinghai-Tibetan Plateau showed relatively lower inbreeding levels.Comparisons of the ratio between deleterious missense mutations and synonymous mutations revealed higher levels in Chinese Grouse as compared to Hazel Grouse.These results are possibly explained by higher fixation rates,mutational melt down,in the range-restricted Chinese Grouse compared to the wide-ranging Hazel Grouse.However,when we compared the relatively more severe class of loss-of-function muta-tions,Hazel Grouse had slightly higher levels than Chinese Grouse,a result which may indicate that purifying selection(purging)has been more efficient in Chinese Grouse on this class of mutations.

Protocol of Investigation on Sudden Death at Autopsy, Including Molecular, Genetic and Toxicology Testing

The role of the autopsy: 1) Whether the death is ascribable to a natural or unnatural cause and when natural, if cardiac or extra-cardiac;2) The nosology of the cardiac diseases and the mechanism of cardiac death, whether arrhythmic or mechanical;3) If the cardiac disease is inherited, screening and counselling of the next of kin is required. About 30% of sudden deaths is ascribable to genetically determined morbid entities, mostly transmissible with the autosomal dominant pattern of inheritance, so that 50% of the first degree relatives are genetically affected (“carriers”) and exposed at risk;4) If toxic or illicit drug abuse was involved.

MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algor

Metallic alloys for a given application are usually designed to achieve the desired properties by devising experimentsbased on experience, thermodynamic and kinetic principles, and various modeling and simulation exercises.However, the influence of process parameters and material properties is often non-linear and non-colligative. Inrecent years, machine learning (ML) has emerged as a promising tool to dealwith the complex interrelation betweencomposition, properties, and process parameters to facilitate accelerated discovery and development of new alloysand functionalities. In this study, we adopt an ML-based approach, coupled with genetic algorithm (GA) principles,to design novel copper alloys for achieving seemingly contradictory targets of high strength and high electricalconductivity. Initially, we establish a correlation between the alloy composition (binary to multi-component) andthe target properties, namely, electrical conductivity and mechanical strength. Catboost, an ML model coupledwith GA, was used for this task. The accuracy of the model was above 93.5%. Next, for obtaining the optimizedcompositions the outputs fromthe initial model were refined by combining the concepts of data augmentation andPareto front. Finally, the ultimate objective of predicting the target composition that would deliver the desired rangeof properties was achieved by developing an advancedMLmodel through data segregation and data augmentation.To examine the reliability of this model, results were rigorously compared and verified using several independentdata reported in the literature. This comparison substantiates that the results predicted by our model regarding thevariation of conductivity and evolution ofmicrostructure and mechanical properties with composition are in goodagreement with the reports published in the literature.

Bridging the gap in cardiac mass diagnosis:Advanced imaging,genetic associations,and biomarkers

In this editorial we comment on the article by Huffaker et al published in a recent issue of the World Journal of Clinical Cases.We focus on cardiac tumors linked to genetic syndromes and the differential diagnosis of cardiac masses.As cardiomyocytes lack the ability to actively divide,primary cardiac tumors are extremely rare across all ethnicities and age groups.Once they occur,these tumors are often associated with genetic mutations and,occasionally,genetic syndromes.This underscores the importance of considering genetic mutations and syndromes when encountering these cases.The more common growths in the heart are thrombi and vegetations,which can mimic tumors,further making the differential diagnosis challenging.Among the imaging techniques,contrast-enhanced cardiac magnetic resonance imaging has the highest sensitivity for differential diagnosis.To aid in the differential diagnosis of cardiac masses,especially thrombi,appropriate utilization of biomarkers(i.e.D-dimer level)may provide pivotal clinical implications.Employing a multidisciplinary approach that integrates personal history,epidemiological insights,imaging findings,genetic markers,and biomarkers is therefore critical in the diagnostic process of cardiac masses.

Progress in clinical diagnosis and treatment of colorectal cancer with rare genetic variants

Targeted therapy is crucial for advanced colorectal cancer(CRC) positive for genetic drivers. With advances in deep sequencing technology and new targeted drugs, existing standard molecular pathological detection systems and therapeutic strategies can no longer meet the requirements for careful management of patients with advanced CRC. Thus, rare genetic variations require diagnosis and targeted therapy in clinical practice. Rare gene mutations, amplifications, and rearrangements are usually associated with poor prognosis and poor response to conventional therapy. This review summarizes the clinical diagnosis and treatment of rare genetic variations, in genes including erb-b2 receptor tyrosine kinase 2(ERBB2), B-Raf proto-oncogene, serine/threonine kinase(BRAF), ALK receptor tyrosine kinase/ROS proto-oncogene 1, receptor tyrosine kinase(ALK/ROS1), neurotrophic receptor tyrosine kinases(NTRKs), ret proto-oncogene(RET), fibroblast growth factor receptor 2(FGFR2), and epidermal growth factor receptor(EGFR), to enhance understanding and identify more accurate personalized treatments for patients with rare genetic variations.