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.

Rice Storage Proteins:Focus on Composition,Distribution,Genetic Improvement and Effects on Rice Quality

Rice storage proteins(RSPs)are plant proteins with high nutritional quality.As the second largest type of storage substance in rice,it is the main source of protein intake for people who consume rice as a staple food.The content and type of RSPs affect the appearance,processing quality and eating quality of rice.These effects involve the distribution of RSPs in rice grains as well as the interactions of RSPs with other components such as starch in rice grains.In the past two decades,some progress has been made in the genetic improvement of RSPs.However,the determination mechanism of protein content and composition in rice is still unclear,and the mechanism of the effect of RSPs on rice quality has not been elucidated.In this review,the composition,biosynthesis and distribution of RSPs,and quantitative trait loci mapping and cloning of RSP genes are summarized,the research progress of the influence of RSPs and their components on rice quality are reviewed,and the research directions in the future are proposed.

Harnessing male germline epigenomics for the genetic improvement in cattle

Sperm is essential for successful artificial insemination in dairy cattle,and its quality can be influenced by both epi-genetic modification and epigenetic inheritance.The bovine germline differentiation is characterized by epigenetic reprogramming,while intergenerational and transgenerational epigenetic inheritance can influence the offspring’s development through the transmission of epigenetic features to the offspring via the germline.Therefore,the selec-tion of bulls with superior sperm quality for the production and fertility traits requires a better understanding of the epigenetic mechanism and more accurate identifications of epigenetic biomarkers.We have comprehensively reviewed the current progress in the studies of bovine sperm epigenome in terms of both resources and biological discovery in order to provide perspectives on how to harness this valuable information for genetic improvement in the cattle breeding industry.

Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement

Background Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values(GEBV)to accelerate the speed of genetic improvement in domestic animals.But after multi-generation selection,the rate of inbreeding and the occurrence of homozygous harmful alleles might increase,which would reduce performance and genetic diversity.To mitigate the above problems,we can utilize genomic mating(GM)based upon optimal mate allocation to construct the best genotypic combinations in the next generation.In this study,we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population.These factors included:the algorithm used to derive inbreeding coefficients;the trait heritability(0.1,0.3 or 0.5);the kind of GM scheme(focused average GEBV or inbreeding);the approach for computing the genomic relationship matrix(by SNP or runs of homozygosity(ROH)).The outcomes were compared to three traditional mating schemes(random,positive assortative or negative assortative matings).In addition,the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population.Results Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain.The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs.The GROH-based GM schemes with the maximum genetic gain resulted in 0.9%-2.6%higher rates of genetic gainΔG,and 13%-83.3%lowerΔF than positive assortative mating regardless of heritability.The rates of inbreeding were always the fastest with positive assortative mating.Results from a purebred Large White pig population,confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes.Conclusion Compared with traditional mating schemes,genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population.Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs.

Genetic improvement of legume roots for adaption to acid soils

Acid soils occupy approximately 50% of potentially arable lands.Improving crop productivity in acid soils,therefore,will be crucial for ensuring food security and agricultural sustainability.High soil acidity often coexists with phosphorus(P) deficiency and aluminum(Al) toxicity,a combination that severely impedes crop growth and yield across wide areas.As roots explore soil for the nutrients and water required for plant growth and development,they also sense and respond to below-ground stresses.Within the terrestrial context of widespread P deficiency and Al toxicity pressures,plants,particularly roots,have evolved a variety of mechanisms for adapting to these stresses.As legumes,soybean(Glycine max) plants may acquire nitrogen(N) through symbiotic nitrogen fixation(SNF),an adaptation that can be useful for mitigating excessive N fertilizer use,either directly as leguminous crop participants in rotation and intercropping systems,or secondarily as green manure cover crops.In this review,we investigate legumes,especially soybean,for recent advances in our understanding of root-based mechanisms linked with root architecture modification,exudation and symbiosis,together with associated genetic and molecular strategies in adaptation to individual and/or interacting P and Al conditions in acid soils.We propose that breeding legume cultivars with superior nutrient efficiency and/or Al tolerance traits through genetic selection might become a potentially powerful strategy for producing crop varieties capable of maintaining or improving yields in more stressful soil conditions subjected to increasingly challenging environmental conditions.

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.

Genetic screening of liver cancer:State of the art

Liver cancer,primarily hepatocellular carcinoma,remains a global health challenge with rising incidence and limited therapeutic options.Genetic factors play a pivotal role in the development and progression of liver cancer.This state-of-the-art paper provides a comprehensive review of the current landscape of genetic screening strategies for liver cancer.We discuss the genetic underpinnings of liver cancer,emphasizing the critical role of risk-associated genetic variants,somatic mutations,and epigenetic alterations.We also explore the intricate interplay between environmental factors and genetics,highlighting how genetic screening can aid in risk stratification and early detection via using liquid biopsy,and advancements in high-throughput sequencing technologies.By synthesizing the latest research findings,we aim to provide a comprehensive overview of the state-of-the-art genetic screening methods for liver cancer,shedding light on their potential to revolutionize early detection,risk assessment,and targeted therapies in the fight against this devastating disease.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

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.

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.

Conservation genomic investigation of an endangered conifer,Thuja sutchuenensis,reveals low genetic diversity but also low genetic load

Endangered species generally have small populations with low genetic diversity and a high genetic load.Thuja sutchuenensis is an endangered conifer endemic to southwestern China.It was once considered extinct in the wild,but in 1999 was rediscovered.However,little is known about its genetic load.We collected 67 individuals from five wild,isolated T.sutchuenensis populations,and used 636,151 SNPs to analyze the level of genetic diversity and genetic load in T.sutchuenensis to delineate the conservation units of T.sutchuenensis,based on whole transcriptome sequencing data,as well as target capture sequencing data.We found that populations of T.sutchuenensis could be divided into three groups.These groups had low levels genetic diversity and were moderately genetically differentiated.Our findings also indicate that T.sutchuenensis suffered two severe bottlenecks around the Last Glaciation Period and Last Glacial Maximum.Among Thuja species,T.sutchuenensis presented the lowest genetic load and hence might have purged deleterious mutations efficiently through purifying selection.However,distribution of fitness effects analysis indicated a high extinction risk for T.sutchuenensis.Multiple lines of evidence identified three management units for T.sutchuenensis.Although T.sutchuenensis possesses a low genetic load,low genetic diversity,suboptimal fitness,and anthropogenic pressures all present an extinction risk for this rare conifer.This might also hold true for many endangered plant species in the mountains all over the world.

Genetic variation of circHIBADH enhances prostate cancer risk through regulating HNRNPA1-related RNA splicing

The current study aimed to investigate associations of circRNAs and related genetic variants with the risk of prostate cancer(PCa)as well as to elucidate biological mechanisms underlying the associations.We first compared expression levels of circRNAs between 25 paired PCa and adjacent normal tissues to identify riskassociated circRNAs by using the MiOncoCirc database.We then used logistic regression models to evaluate associations between genetic variants in candidate circRNAs and PCa risk among 4662 prostate cancer patients and 3114 healthy controls,and identified circHIBADH rs11973492 T>C as a significant risk-associated variant(odds ratio=1.20,95%confidence interval:1.08-1.34,P=7.06×10^(-4))in a dominant genetic model,which altered the secondary structure of the corresponding RNA chain.In the in silico analysis,we found that circHIBADH sponged and silenced 21 RNA-binding proteins(RBPs)enriched in the RNA splicing pathway,among which HNRNPA1 was identified and validated as a hub RBP using an external RNA-sequencing data as well as the in-house(four tissue samples)and publicly available single-cell transcriptomes.Additionally,we demonstrated that HNRNPA1 influenced hallmarks including MYC target,DNA repair,and E2F target signaling pathways,thereby promoting carcinogenesis.In conclusion,genetic variants in circHIBADH may act as sponges and inhibitors of RNA splicing-associated RBPs including HNRNPA1,playing an oncogenic role in PCa.

Genetic algorithm assisted meta-atom design for high-performance metasurface optics

Metasurfaces,composed of planar arrays of intricately designed meta-atom structures,possess remarkable capabilities in controlling electromagnetic waves in various ways.A critical aspect of metasurface design involves selecting suitable meta-atoms to achieve target functionalities such as phase retardation,amplitude modulation,and polarization conversion.Conventional design processes often involve extensive parameter sweeping,a laborious and computationally intensive task heavily reliant on designer expertise and judgement.Here,we present an efficient genetic algorithm assisted meta-atom optimization method for high-performance metasurface optics,which is compatible to both single-and multiobjective device design tasks.We first employ the method for a single-objective design task and implement a high-efficiency Pancharatnam-Berry phase based metalens with an average focusing efficiency exceeding 80%in the visible spectrum.We then employ the method for a dual-objective metasurface design task and construct an efficient spin-multiplexed structural beam generator.The device is capable of generating zeroth-order and first-order Bessel beams respectively under right-handed and left-handed circular polarized illumination,with associated generation efficiencies surpassing 88%.Finally,we implement a wavelength and spin co-multiplexed four-channel metahologram capable of projecting two spin-multiplexed holographic images under each operational wavelength,with efficiencies over 50%.Our work offers a streamlined and easy-to-implement approach to meta-atom design and optimization,empowering designers to create diverse high-performance and multifunctional metasurface optics.

Selection criteria of MPOB-Angola germplasm collection for yield improvement of the oil palm

Oil palm germplasm collected from Angola,Africa in 1991 were subjected to genetic variability potential studies.The collection was planted in the form of open-pollinated families as trials at the Malaysian Palm Oil Board(MPOB)Kluang Research Station,Johor,Malaysia,in 1994.Dura palms from 52 families and tenera palms from 44 families of MPOB-Angola were evaluated for their bunch yield and bunch quality components.The objectives of this study were to determine the genetic variability among the families and performance of MPOB-Angola germplasm for yield improvement.The analysis of variance(ANOVA)revealed highly significant differences between the dura and tenera families for most of the traits,suggesting the presence of high genetic variability,which is essential for breeding programmes.Among the duras,family AGO 02.02 displayed the best yield performance,with a high fresh fruit bunch,oil yield and total economic product at 240.40,29.46 and 37.93 kg palm^(-1)year^(-1),respectively.As for the teneras,family AGO 03.04 recorded the highest FFB yield and oil yield at 249.25 and 45.22 kg palm^(-1)year^(-1),respectively.Besides that,several families with big fruit sizes or producing a mean fruit weight of 14-17 g were also identified.Both dura and tenera from AGO 01.01 recorded the highest oil to bunch(O/B)of 17.76%and 28.65%,respectively.These findings will facilitate the selection of palms from the MPOB-Angola germplasm for future breeding programmes.

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.

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 variability and trait association analysis in linseed(Linum usitatissimum L.)for yield and related traits

Diversity information mining about a crop for different attributes is an essential step for effective breeding programs.The present investigation evaluates the quantum of genetic variability and determines the relationship among the important agro-economic traits based on two years of phenotypic data of 210 accessions of linseed.The traits,capsule weight per plant,capsule per plant,husk weight per plant,and seed weight per plant exhibited comparatively higher genetic coefficient of variation(GCV)and phenotypic coefficient of variation(PCV).In contrast,oil content and seed per capsule exhibited a lower value.The high magnitude of broad sense heritability was observed for all traits except seeds per capsule and husk weight per plant.The trait,capsules per plant,plant height,and days to 50%flowering showed high genetic advance coupled with high heritability.Hierarchical cluster analysis grouped 210 accessions into six distinct clusters.Out of 210,144(68.57%)accessions were grouped into three clusters(I,II,and III),in which cluster-III was the largest,containing 64 accessions followed by cluster II and cluster-I.The highest inter-cluster distance was observed between clusters-I and V(127.85),while the lowest was between clusters-II and IV(27.09).The positive correlation of capsule weight per plant with the seed weight per plant and a negative correlation with the days to 50%flowering indicates that high yielding linseed varieties with early flowering/maturity could be developed through direct and indirect selection.Further,seed yield and oil content could be enhanced together as indicated by ghe positive association among these two important traits.In this study,high yielding accessions with moderate to high oil content such as GP36,GP31,GP14,GP54,GP26,GP24,GP34,GP21,GP37 and GP27 and early flowering(less than 70 days)accessions such as GP2,GP26,GP27,CG33,CG44,CG42,CG132,and CG31 identified as potential genetic materials that could be exploited for developing early maturing varieties with high yield.In addition,information’s on various genetic parameters will help breeders to devise suitable breeding methodology for linseed genetic improvement for targeted traits.

Genetic Variations and Nonalcoholic Fatty Liver Disease:Field Synopsis,Systematic Meta-Analysis,and Epidemiological Evidence

Objective To systematically summarize the published literature on the genetic variants associated with nonalcoholic fatty liver disease(NAFLD).Methods Literature from Web of Science,PubMed,and Embase between January 1980 and September 2022 was systematically searched.Meta-analyses of the genetic variants were conducted using at least five data sources.The epidemiologic credibility of the significant associations was graded using the Venice criteria.Results Based on literature screening,399 eligible studies were included,comprising 381 candidate gene association,16 genome-wide association,and 2 whole-exome sequencing studies.We identified 465 genetic variants in 173 genes in candidate gene association studies,and 25 genetic variants in 17 genes were included in the meta-analysis.The meta-analysis identified 11 variants in 10 genes that were significantly associated with NAFLD,with cumulative epidemiological evidence of an association graded as strong for two variants in two genes(HFE,TNF),moderate for four variants in three genes(TM6SF2,GCKR,and ADIPOQ),and weak for five variants in five genes(MBOAT7,PEMT,PNPLA3,LEPR,and MTHFR).Conclusion This study identified six variants in five genes that had moderate to strong evidence of an association with NAFLD,which may help understand the genetic architecture of NAFLD risk.

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.