Genetic Analysis on Plant Height in Rice in Different Growing Seasons

[Objective] The aim was to carry out the genetic analysis on plant height of rice（Oryza sativa L.）cultivated in different seasons.[Method] Three rice parents with great difference in plant height including CB1（83.1 cm）,CB4（105.5 cm）and CB7（115.6 cm）were chosen to construct two parental combinations：CB1×CB4 and CB7×CB4,and the corresponding filial generations P1,F1,P2,B1,B2 and F2 were obtained.The 6 populations were planted in middle and late seasons respectively to measure their height traits.The Akaike＇s information criterion（AIC）of the mixed major gene and polygene model was used to indentify the existence of major genes affecting quantitative traits in B1,B2,F2 populations.When the major genes existed,the genetic effects of the major genes and polygenes and their genetic variance were estimated through segregation analysis.[Result] One additive major gene plus additive-dominance polygenes was the most fitted genetic model for the trait in all B1,B2,F2 populations in two planting seasons.The heritability values of the major genes varied from 38.63% to 78.53% and those of polygenes varied from 1.72% to 36.04%,and the total heritability values were 45.52-92.93%.The additive effect d value of the two genetic populations under two planting seasons was-4.56,-9.16,-7.19,and-9.38,respectively,as suggested that additive effect of the major genes would decrease the express of the plant height trait.[Conclusion] The heritability of plant height trait was affected by planting seasons and the combinations clearly as a whole.

Genetic Analysis of Embryo Production Frequency in Wheat × Maize Cross

A DH population derived from C49S-87/01Y1-1069 was used to study the inheritance of wheat haploid embryo production frequency（EPF） in wheat × maize cross with the mixed major gene and polygene inheritance model of quantitative traits. The results showed that the EPF of wheat × maize cross was controlled by two dominant epistatic genes and polygene with gene effects of 1.95 for the first major gene, 6.69 for the second one and 2.80 for the polygene. The inheritability of major genes was as high as 72.09%, suggesting that the differences in EPF among wheat materials were mainly influenced by genotype. However, non-genetic factors were still important, especially for wheat materials with low EPF.

Genetic Analysis of Stripe Disease Resistance in Rice Restorer Line C224 Using Major Gene plus Polygene Mixed Effect Model

The inheritance of stripe disease resistance in a rice restorer line C224 was analyzed using the mixed effect model of major gene plus polygene for quantitative traits.In addition,the resistance was investigated in seven crosses of C224 with maintainer lines.The results showed that the stripe resistance of C224 was controlled by two major genes with additive-dominance-epistasis effects plus polygenes with additive-dominance effects （E-1 model）.These two genes had additive effects of-12.47% and-24.75%,respectively,showing negative dominance effects.There were significant epistasis and interaction effects between the two major genes.The heritability of the two major genes was 92.12%,while that of polygenes was 2.74%,indicating that the stripe resistance had dominant major gene effect.Of the seven crosses,five displayed high or medium resistance to the stripe disease.

A 3-D in vitro tumor model for investigation of bacteria-mediated gene delivery

Introduction Cancer is an attractive target of gene therapy and currently represents the disease in most clinical trials[1]. Strategies for cancer gene therapy include: (1) stimulation of immune responses to tumor cells,(2) delivery of specific enzymes

Artificial Intelligence Prediction of One-Part Geopolymer Compressive Strength for Sustainable Concrete

Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological concrete.In terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part geopolymer.However,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely reported.Therefore,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part geopolymer.The database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing temperature.The performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed GEP.Sensitivity and parametric analysis were also performed to identify the significant contributor to strength.According to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 days.The water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks

Genome-wide association studies(GWASs)have identified over 140 colorectal cancer(CRC)-associated loci;however,target genes at the majority of loci and underlying molecular mechanisms are poorly understood.Here,we utilized a Bayesian approach,integrative risk gene selector(iRIGS),to prioritize risk genes at CRC GWAS loci by integrating multi-omics data.As a result,a total of 105 high-confidence risk genes(HRGs)were identified,which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC.Among the 105 HRGs,CEBPB,located at the 20q13.13 locus,acted as a transcription factor playing critical roles in cancer.Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK,PI3K-Akt,and Ras signaling.Next,by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls,we elucidated that rs1810503,a putative functional variant regulating CEBPB,was associated with CRC risk(OR=0.90,95%CI=0.86–0.93,P=1.07×10^(−7)).The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls.Mechanistically,the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via longrange promoter-enhancer interactions,mediated by the transcription factor,REST,and thus decreased CRC risk.In summary,our study provides a genetic resource and a generalizable strategy for CRC etiology investigation,and highlights the biological implications of CEBPB in CRC tumorigenesis,shedding new light on the etiology of CRC.

CRISPR/Cas9-mediated targeted gene correction in amyotrophic lateral sclerosis patient iPSCs

Amyotrophic lateral sclerosis （ALS） is a complex neu- rodegenerative disease with cellular and molecular mechanisms yet to be fully described. Mutations in a number of genes including SOD1 and FUS are associated with familial ALS. Here we report the generation of induced pluripotent stem cells （iPSCs） from fibroblasts of familial ALS patients bearing SOD1＋1A27~c and FUS＋/GISe6A mutations, respectively. We further gener- ated gene corrected ALS iPSCs using CRISPR/Cas9 system. Genome-wide RNA sequencing （RNA-seq） analysis of motor neurons derived from SOD1＋~A272c and corrected iPSCs revealed 899 aberrant transcripts. Our work may shed light on discovery of early biomarkers and pathways dysregulated in ALS, as well as provide a basis for novel therapeutic strategies to treat ALS.

The effects of Kangxianling on renal fibrosis as assessed with a customized gene chip

OBJECTIVE:To determine the mechanisms by which Kangxianling(KXL) treats renal interstitial fibrosis using a customized gene chip.METHODS:Twelve out of 18 specific pathogen-free sprague dawley(SPF SD) rats underwent a unilateral ureteral occlusion.These rats were then randomly assigned into either the model unilateral ureteral obstruction(UUO) or Kangxianling(KXL) group.The other six rats were assigned to the sham-operated group.The UUO and sham-operated groups were given normal saline via intragastric administration,whereas the KXL group was given KXL via intragastric administration.All rats were sacrificed for renal tissue collection(i.e.left nephridial tissue),and the detection of genetic changes with the customized chip.RESULTS:Compared to the sham-operated group,transforming growth factor-β1(TGF-β1),Smad2,and Smad3 genes were significantly up-regulated in the UUO group,with >1.5-fold rise(P<0.01).The Smad7 gene was significantly reduced in the UUO versus sham-operated group,with a down-regulation of >1.5-fold(P<0.01).In the KXL group,TGF-β1,Smad2,and Smad3 genes were significantly reduced compared to the UUO group,with a down-regulation of >1.5-fold(P<0.01),whereas the Smad7 gene was significantly increased compared to the UUO group,with an up-regulation of >1.5-fold(P<0.01).CONCLUSION:It was found that KXL can significantly reduce the gene levels of TGF-β1,Smad2,and Smad3.Immunohistochemistry findings also revealed significantly lower TGF-β1/Smads-mediated gene transcription activity.These findings suggest that KXL may negatively regulate the TGF-β1/Smads signal pathway to inhibit the occurrence of renal fibrosis.

Segregation Analysis on Genetic System of Quantitative Traits in Plants

Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene and pure polygene inheritance model was a specific case of the general model.Based on the proposed theory,the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants.At present,this procedure can be used to evaluate the genetic effect of individual major genes(up to two to three major genes),the collective genetic effect of polygene,and their heritability value.This paper introduces how to establish the procedure,its main achievements,and its applications.An example is given to illustrate the steps,methods,and effectiveness of the procedure.

Efficient generation of the mouse model with a defined point mutation through haploid cell-mediated gene editing

Generation of mouse models carrying a defined point mutation,especially disease-related point mutations,is of considerable interest for research in biology and medicine.The standard method based on embryonic stem cell（ESC）-mediated homologous recombination（HR）is time-and labor-consuming.

XAANTAL2 （AGL14） Is an Important Component of the Complex Gene Regulatory Network that Underlies Arabidopsis Shoot Apical Meristem Transitions

In Arabidopsis thaliana, multiple genes involved in shoot apical meristem （SAM） transitions have been char- acterized, but the mechanisms required for the dynamic attainment of vegetative, inflorescence, and floral meristem （VM, IM, FM） cell fates during SAM transitions are not well understood. Here we show that a MADS-box gene, XAANTAL2 （XAL2/AGL14）, is necessary and sufficient to induce flowering, and its regula- tion is important in FM maintenance and determinacy, xal2 mutants are late flowering, particularly under short-day （SD） condition, while XAL2 overexpressing plants are early flowering, but their flowers have vege- tative traits. Interestingly, inflorescences of the latter plants have higher expression levels of LFY, AP1, and TFL1 than wild-type plants. In addition we found that XAL2 is able to bind the TFL1 regulatory regions. On the other hand, the basipetal carpels of the 35S：：XAL2 lines lose determinacy and maintain high levels of WUS expression under SD condition. To provide a mechanistic explanation for the complex roles of XAL2 in SAM transitions and the apparently paradoxical phenotypes of XAL2 and other MADS-box （SOCl, AGL24） over- expressors, we conducted dynamic gene regulatory network （GRN） and epigenetic landscape modeling. We uncovered a GRN module that underlies VM, IM, and FM gene configurations and transition patterns in wild- type plants as well as loss and gain of function lines characterized here and previously. Our approach thus provides a novel mechanistic framework for understanding the complex basis of SAM development.

IC4R-2.0:Rice Genome Reannotation Using Massive RNA-seq Data

Genome reannotation aims for complete and accurate characterization of gene models and thus is of critical significance for in-depth exploration of gene function.Although the availability of massive RNA-seq data provides great opportunities for gene model refinement,few efforts have been made to adopt these precious data in rice genome reannotation.Here we reannotate the rice(Oryza sativa L.ssp.japonica)genome based on integration of large-scale RNA-seq data and release a new annotation system IC4 R-2.0.In general,IC4 R-2.0 significantly improves the completeness of gene structure,identifies a number of novel genes,and integrates a variety of functional annotations.Furthermore,long non-coding RNAs(lncRNAs)and circular RNAs(circRNAs)are systematically characterized in the rice genome.Performance evaluation shows that compared to previous annotation systems,IC4 R-2.0 achieves higher integrity and quality,primarily attributable to massive RNA-seq data applied in genome annotation.Consequently,we incorporate the improved annotations into the Information Commons for Rice(IC4 R),a database integrating multiple omics data of rice,and accordingly update IC4 R by providing more user-friendly web interfaces and implementing a series of practical online tools.Together,the updated IC4 R,which is equipped with the improved annotations,bears great promise for comparative and functional genomic studies in rice and other monocotyledonous species.The IC4 R-2.0 annotation system and related resources are freely accessible at http://ic4 r.org/.

Identification of Tumor Evolution Patterns by Means of Inductive Logic Programming

In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained some hints about further approach to the hypotheses. on a real-world dataset, we try to give knowledge-driven validations of such