Molecular Diversity and Association Analysis of Drought and Salt Tolerance in Gossypium hirsutum L. Germplasm

Association mapping is a useful tool for the detection of genes selected during plant domestication based on their linkage disequilibrium（LD）. This study was carried out to estimate genetic diversity, population structure and the extent of LD to develop an association framework in order to identify genetic variations associated with drought and salt tolerance traits. 106 microsatellite marker primer pairs were used in 323 Gossypium hirsutum germplasms which were grown in the drought shed and salt pond for evaluation. Polymorphism（PIC=0.53） was found, and three groups were detected（K=3） with the second likelihood ΔK using STRUCTURE software. LD decay rates were estimated to be 13-15 cM at r2 0.20. Significant associations between polymorphic markers and drought and salt tolerance traits were observed using the general linear model（GLM） and mixed linear model（MLM）（P 0.01）. The results also demonstrated that association mapping within the population structure as well as stratification existing in cotton germplasm resources could complement and enhance quantitative trait loci（QTLs） information for marker-assisted selection.

Disagreement between symptom-reflux association analysis parameters in pediatric gastroesophageal reflux disease investigation

AIM: To assess the agreement within 3 commonly used symptom-reflux association analysis (SAA) parameters investigating gastroesophageal reflux disease (GERD) in infants. METHODS: Twenty three infants with suspected GERD were included in this study. Symptom index (SI), Symptom sensitivity index (SSI) and symptom association probability (SAP) related to cough and irritability were calculated after 24 h combined pH/multiple intraluminal impedance (MII) monitoring. Through defined cutoff values, SI, SSI and SAP values are differentiated in normal and abnormal, whereas abnormal values point towards gastroesophageal reflux (GER) as the origin of symptoms. We analyzed the correlation and the concordance of the diagnostic classification of these 3 SAA parameters.RESULTS: Evaluating the GER-irritability association, SI, SSI and SAP showed non-identical classification of normal and abnormal cases in 39.2% of the infants. When irritability was taken as a symptom, there was only a poor inter-parameter association between SI and SSI, and between SI and SAP (Kendall’s tau b = 0.37, P < 0.05; Kendall’s tau b = 0.36, P < 0.05, respectively). Evaluating the GER-cough association, SI, SSI and SAP showed non-identical classification of normal and abnormal cases in 52.2% of the patients. When cough was taken as a symptom, only SI and SSI showed a poor inter-parameter association (Kendall’s tau b = 0.33, P < 0.05). CONCLUSION: In infants investigated for suspected GERD with pH/MII-monitoring, SI, SSI and SAP showed a poor inter-parameter association and important dis-agreements in diagnostic classification. These limitations must be taken into consideration when interpreting the results of SAA in infants.

The association analysis polymorphism of CDKAL1 and diabetic retinopathy in Chinese Han population

AIM： To identify the contribution of CDKAL1 to the development of diabetic retinopathy（DR） in Chinese population.·METHODS： A case-control study was performed to investigate the genetic association between DR and polymorphic variants of CDKAL1 in Chinese Han population with type 2 diabetes mellitus（T2DM）. A welldefined population with T2 DM, consisting of 475 controls and 105 DR patients, was recruited. All subjects were genotyped for the genetic variant（rs10946398） of CDKAL1. Genotyping was performed by i PLEX technology. The association between rs10946398 and T2 DM was assessed by univariate and multivariate logistic regression（MLR） analysis.· RESULTS： There were significant differences in C allele frequencies of rs10946398（CDKAL1） between control and DR groups（45.06% versus 55.00%, P 〈0.05）.The rs10946398 of CDKAL1 was found to be associated with the increased risk of DR among patients with diabetes.·CONCLUSION： Our findings suggest that rs10946398 of CDKAL1 is independently associated with DR in a Chinese Han population.

Single-nucleotide polymorphisms,mapping and association analysis of 1-FFT-A1 gene in wheat

Fructans are major nonstructural carbohydrates in wheat （Triticum aestivum L.）. Fructan 1-fructosyltransferase （1-FFT） is the key enzyme in fructan biosynthesis. In the present study, 96 sequence variants were detected in the 1-FFT-A 1 gene among 26 wheat accessions including UR208, and 15 of them result in amino acid substitutions, forming four haplotypes. Two markers M39 and M2164 were developed based on the InDe121-39 and SNP-2164 polymorphisms to distinguish the three haplotypes in the 1-FFT-AI. 1-FFT-A1 was located on chromosome 4A using marker M2164 and was flanked by markers Xcwm27 and 6-SFT-A 1. By association analysis using a natural wheat population consisted of 154 accessions, the results showed that the two markers were significantly associated with water-soluble carbohydrate （WSC） content in the lower internode stem and total stem at the early and middle grain filling stages, 1 000-grain weight （TGW） at different grain filling stages and peduncle length （PLE）. Comparison of the effects of three haplotypes on agronomic traits indicated that TGW, PLE and total number of spikelets per spike （TNSS）were significantly influenced by haplotypes. Haplll showed a significant positive effect on TGW, PLE and TNSS.

Association analysis of grain traits with SSR markers between Aegilops tauschii and hexaploid wheat(Triticum aestivum L.)

Seven important grain traits, including grain length（GL）, grain width（GW）, grain perimeter（GP）, grain area（GA）, grain length/width ratio（GLW）, roundness（GR）, and thousand-grain weight（TGW）, were analyzed using a set of 139 simple sequence repeat（SSR） markers in 130 hexaploid wheat varieties and 193 Aegilops tauschii accessions worldwide. In total, 1 612 alleles in Ae. tauschii and 1 360 alleles in hexaploid wheat（Triticum aestivum L.） were detected throughout the D genome. 197 marker-trait associations in Ae. tauschii were identified with 58 different SSR loci in 3 environments, and the average phenotypic variation value（R2） ranged from 0.68 to 15.12%. In contrast, 208 marker-trait associations were identified in wheat with 66 different SSR markers in 4 environments and the average phenotypic R2 ranged from 0.90 to 19.92%. Further analysis indicated that there are 6 common SSR loci present in both Ae. tauschii and hexaploid wheat, which are significantly associated with the 5 investigated grain traits（i.e., GA, GP, GR, GL, and TGW） and in total, 16 alleles derived from the 6 aforementioned SSR loci were shared by Ae. tauschii and hexaploid wheat. These preliminary data suggest the existence of common alleles may explain the evolutionary process and the selection between Ae. tauschii and hexaploid wheat. Furthermore, the genetic differentiation of grain shape and thousand-grain weight were observed in the evolutionary developmental process from Ae. tauschii to hexaploid wheat.

A Developed Algorithm of Apriori Based on Association Analysis

A method for mining frequent itemsets by evaluating their probability of supports based on association analysis is presented. This paper obtains the probability of every 1\|itemset by scanning the database, then evaluates the probability of every 2\|itemset, every 3\|itemset, every k \|itemset from the frequent 1\|itemsets and gains all the candidate frequent itemsets. This paper also scans the database for verifying the support of the candidate frequent itemsets. Last, the frequent itemsets are mined. The method reduces a lot of time of scanning database and shortens the computation time of the algorithm.

An approach to incorporate linkage disequilibrium structure into genomic association analysis

In this study, we propose to use the principal component analysis （PCA） and regression model to incorporate linkage disequilibrium （LD） in genomic association data analysis. To accommodate LD in genomic data and reduce multiple testing, we suggest performing PCA and extracting the PCA score to capture the variation of genomic data, after which regression analysis is used to assess the association of the disease with the principal component score. An empirical analysis result shows that both genotype-based correlation matrix and haplotype-based LD matrix can produce similar results for PCA. Principal component score seems to be more powerful in detecting genetic association because the principal component score is quantitatively measured and may be able to capture the effect of multiple loci.

Polymorphism and association analysis of a drought-resistant gene TaLTP-s in wheat

Lipid transfer protein （LTP） is a kind of small molecular protein, which is named for its ability to transfer lipid between cell membranes. It has been proved that the protein is involved in the responding to abiotic stresses. In this study, TaLTP-s, a genomic sequence of TaLTP was isolated from A genome of wheat （Triticum aestivum L）. Sequencing analysis exhibited that there was no diversity in the coding region of TaLTP-s, but seven single nucleotide polymorphisms （SNPs） and 1 bp insertion/deletion （InOel） were detected in the promoter regions of different wheat accessions. Nucleotide diversity （T1） in the region was 0.00033, and linkage disequilibrium （LD） extended over almost the entire TaLTP-s region in wheat. The dCAPS markers based on sequence variations in the promoter regions （SNP-207 and SNP-1696） were developed, and three haplotypes were identified based on those markers. Association analysis between the haplotypes and agronomic traits of natural population consisted of 262 accessions showed that three haplotypes of TaLTP-s were significantly associated with plant height （PH）. Among the three haplotypes, Haplll is considered as the superior haplotype for increasing plant height in the drought stress environments. The G variance at the position of 207 bp could be a superior allele that significantly increased number of spikes per plant （NSP）. The functional marker of TaLTP-s provide a tool for marker-assisted selection regarding to plant height and number of spikelet per plant in wheat.

Association Analysis of the Growth of Black Poplar (Populus Nigra L.) Under Contrasting Nitrogen Levels

The European black poplar(Populus nigra L.)has been used as a germplasm resource for the breeding of new poplar varieties around the world.The identification and screening of its high nitrogen use efficiency genotypes could enable the breeding of new resource-efficient poplar varieties.The accessions were screened using MALDI-TOF MS genotyping technology for ammonium transporter(AMT)and nitrate transporters(NRT)genes against phenotypic data for seedling height and ground diameter traits,in both low and high nitrogen environments.Allele re-sequencing of seven genes related to root development was carried out using the minisequencing method.By cluster analysis,101 accessions of black poplar were divided into 4 populations,and it was concluded that Central Europe is the origin of the evolution of low-nitrogen and high-efficiency populations of European black poplar.Association study between SNP typing and seedling height and ground diameter traits showed that there were significant correlations between four SNP loci and growth traits under the contrasting N levels.We found that SNP3 and SNP4 in the PttAMT1;3 gene were significantly associated with seedling height traits,and that SNP2 and SNP7 in the PttAMT1;2 and PttAMT1;5 genes,respectively,were significantly associated with ground diameter traits.Thus,considerable allelic diversity is present within the candidate genes studied and can be utilized to develop functional markers to select for poplars with improved growth under N stress conditions.

Association Analysis of SP-SNPs and Avirulence Genes in Puccinia striiformis f. sp. tritici, the Wheat Stripe Rust Pathogen

Puccinia striiformis f. sp. tritici (Pst) is one of the pathogenic fungi on wheat, caused stripe rust that is a great threat for wheat production all over the world. Intensive efforts have been made to study genetics of wheat resistance to this disease, but few on avirulence of the pathogen due mainly to the nature of obligate biotrophism and the lack of systems for studying its genetics and molecular manipulations. To overcome these limitations, a natural Pst population comprising 352 isolates representative of a diverse virulence spectrum was genotyped using 97 secreted protein-single nucleotide polymorphism (SP-SNP) markers to identify candidate avirulence genes using association analysis. Among avirulence genes corresponding to 19 resistance genes, significantly associated SP-SNP markers were detected for avirulence genes AvYr1, AvYr2, AvYr6, AvYr7, AvYr8, AvYr44, AvYrExp2, AvYrSP, and AvYrTye. These results indicate that association analysis can be used to identify markers for avirulence genes. This study has laid the foundation for developing more SP-SNPs for mapping avirulence genes using segregating populations that can be generated through sexual reproduction on alternate hosts of the pathogen.

Genome-wide Association Analysis of Fast Chlorophyll Fluorescence Parameters in Maize

Fast chlorophyll fluorescence parameters are widely used to characterize the photosynthetic efficiency of plants. In this study, a genome-wide association analysis was used to detect key single-nueleotide polymorphisms （SNPs） associated with fast chlorophyll fluorescence parameters using more than 560 000 SNPs in a maize panel consisting of 404 inbred lines. In four fidd environments, 41 SNPs were detected to be associated with five fast chlorophyll fluorescence parameters, including ABS/CS0, ET0/CS0, TR0/ABS, ET0/TR0 and Pies. Among these identified SNPs, 8, 6, 18, 4 and 5 were significantly associated with ET0/TR0, ABS/ CS0, TR0/ABS, ET0/CS, and Plcs, respectively. These SNPs will help to discover genes for chlorophyll fluorescence parameters, better understand the genetic basis of photosynthesis, and assist in developing marker-assisted selection breeding programs in maize.

Association Analysis of Quantitative Traits in F_1 Families Derived from Two Maize Landraces

[ Objective] The objective of this study was to evaluate the genetic diversity and characterization of special maize population consisting of 135 Fl fami- lies. [ Method ] In this study, association analysis was conducted in 135 F1 families derived from two maize landraces, and the efficiency of this method was evalua- ted through simulation. [ Result] Association analysis with different kinds of families showed that large population size and robust phenotypic data were required for association mapping. For all the phenotypic traits, the model controlling beth population structure and relative kinship （ Q ＋ K） performed better than the model controlling relative kinship （K）, and similarly to the model controlling population structure （Q）. Across 100 simulation runs in QULINE, the average power of QTL detection for the two models were 88.64% and 83.64% respectively, and the number of false QTL was reduced from 399 with GLM model to 199 with K mod- el. Our simulation results suggested that these F1 families can be used for association analysis, and the power of the QTL detection was related to the maximum al- lele frequency （MAF）and the phenotypic variation （PVE） explained by QTL. [ Conclusion] The results from this study suggest that association analysis using the F1 families is an effective approach to study maize landraces for discovering elite genes which we are interested in from these special populations.

Genome-wide Association Analysis of Maize Flowering Traits

Flowering regulation is important for maize to adapt to a variety of environments as well as associated with high yield.In this study,the genetic mechanism of three flowering traits of 310 maize inbred lines with rich genetic background was investigated in three years at three different environments such as days to tasseling(DTT),days to silking(DTS)and days to pollen shedding(DTP).Based on mean performance,the longest flowering time was observed in Zhanyi(2018),whereas the shortest in Shizong(2019).The coefficient of variance depicted the range from 3.62%to 9.06%for three flowering traits under all environments.Therefore,we have integrated these flowering traits corresponding to SNP molecular markers for genome-wide association study(GWAS).Results showed that 22 SNPs markers were significantly associated with DTT according to physical position and average linkage disequilibrium(LD)decay distance,and a total of 234 candidate genes were identified near these significantly associated SNP markers.Moreover,KEGG and GO analysis showed that these genes were enriched in the regulation of the physiological pathways for flowering.In more details,16 genes involved in development of floral organs are more worthy of our attention in future studies.

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 analysis and candidate gene identification of salt tolerancerelated traits in maize

Soil salinization poses a threat to maize production worldwide,but the genetic mechanism of salt tolerance in maize is not well understood.Therefore,identifying the genetic components underlying salt tolerance in maize is of great importance.In the current study,a teosinte-maize BC2F7 population was used to investigate the genetic basis of 21 salt tolerance-related traits.In total,125 QTLs were detected using a high-density genetic bin map,with one to five QTLs explaining 6.05–32.02%of the phenotypic variation for each trait.The total phenotypic variation explained(PVE)by all detected QTLs ranged from 6.84 to 63.88%for each trait.Of all 125 QTLs,only three were major QTLs distributed in two genomic regions on chromosome 6,which were involved in three salt tolerance-related traits.In addition,10 pairs of epistatic QTLs with additive effects were detected for eight traits,explaining 0.9 to 4.44%of the phenotypic variation.Furthermore,18 QTL hotspots affecting 3–7 traits were identified.In one hotspot(L5),a gene cluster consisting of four genes(ZmNSA1,SAG6,ZmCLCg,and ZmHKT1;2)was found,suggesting the involvement of multiple pleiotropic genes.Finally,two important candidate genes,Zm00001d002090 and Zm00001d002391,were found to be associated with salt tolerance-related traits by a combination of linkage and marker-trait association analyses.Zm00001d002090 encodes a calcium-dependent lipid-binding(CaLB domain)family protein,which may function as a Ca^(2+)sensor for transmitting the salt stress signal downstream,while Zm00001d002391 encodes a ubiquitin-specific protease belonging to the C19-related subfamily.Our findings provide valuable insights into the genetic basis of salt tolerance-related traits in maize and a theoretical foundation for breeders to develop enhanced salt-tolerant maize varieties.

Genetic Diversity and Association Analysis for Salinity Tolerance, Heading Date and Plant Height of Barley Germplasm Using Simple Sequence Repeat Markers

The objective of this study was to investigate the genetic diversity of barley accessions. Additionally, association trait analysis was conducted for grain yield under salinity, heading date and plant height. For this purpose, 48 barley genotypes were analyzed with 22 microsatellite simple sequence repeat （SSR） markers. Four of the 22 markers （Bmac316, scssr03907, HVM67 and Bmag770） were able to differentiate all barley genotypes. Cluster and principal coordinate analysis allowed a clear grouping between countries from the same region. The genotypes used in this study have been evaluated for agronomic performance in different environments. Conducting association analysis for grain yield under salinity conditions using TASSEL software revealed a close association of the marker Bmag749 （2H, bin 13） in two different environments with common significant alleles （175, 177）, whereas the HVHOTR1 marker （2H, bin 3） was only significant in Sakhar Egypt with alleles size being 158 and 161. Heading date also showed an association with scssr03907 through the common significant specific allele 111 and EBmac0415 markers in three different agro climatic locations, whereas HVCMA, scssr00103 and HVM67 were linked to heading date in the Egyptian environment only. The plant height association analysis revealed significant markers Bmag770 via the significant allele 152 and scssr09398.

Diversity characterization and association analysis of agronomic traits in a Chinese peanut (Arachis hypogaea L.) mini-core collection

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A peanut （Arachis hypogaea L.） mini-core collection in China comprising 298 accessions was genotyped using lo9 simple sequence repeat （SSR） markers, which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments, exhibiting abundant genetic and phenotypic diversity within the panel. A model-based structure analysis assigned all accessions to three groups. Most of the accessions had the relative kinship of less than o.05, indicating that there were no or weak relationships between accessions of the mini- core collection. For 15 agronomic traits in the peanut panel, generally the Q ＋ K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model. In total, 89 SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q＋K model-based association analysis. Of these, eight alleles were repeatedly detected in two or three environments, and 15 alleles were commonly detected to be associated with multiple agronomic traits. Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers. Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.

Detection and fine-mapping of SC7 resistance genes via linkage and association analysis in soybean

Soybean mosaic virus（SMV） disease is one of the most serious and broadly distributed soybean（Glycine max（L.） Merr.） diseases. Here, we combine the advantages of association and linkage analysis to identify and fine-map the soybean genes associated with resistance to SMV strain SC7.A set of 191 soybean accessions from different geographic origins and 184 recombinant inbred lines（RILs） derived from Kefeng No.1（resistant） Nannong 1138-2（susceptible） were used in this study. The SC7 resistance genes were previously mapped to a 2.65 Mb region on chromosome 2 and a 380 kb region on chromosome 13. Among 19 single nucleotide polymorphisms（SNPs） detected via association analysis in the study, the SNP BARC-021625-04157 was located in the2.65 Mb region, and the SNP BARC-041671-08065 was located near the 380 kb region; three genes harboring the SNPs were probably related to SC7 resistance. The resistance gene associated with BARC-021625-04157 was then finemapped to a region of approximately 158 kb on chromosome2 using 184 RILs. Among the 15 genes within this region, one NBS-LRR type gene, one HSP40 gene and one serine carboxypeptidase-type gene might be candidate SC7 resistance genes. These results will be useful for map-based cloning and marker-assisted selection in soybean breeding programs.

Differential expression of FOXO1 during development and myoblast differentiation of Qinchuan cattle and its association analysis with growth traits

Our previous work reported a relationship between FOXO1 mutations and growth of Qinchuan(QC) cattle. Here, we performed differential expression analysis of FOXO1 and its association analysis with growth traits in QC cattle. First, we measured the expression of the FOXO1 gene in nine tissues during three developmental stages. The results showed that FOXO1 was abundantly expressed in tissues of calves but was strongly repressed in adulthood, although there was significant transcription in skeletal muscle. FOXO1 expression showed gradual up-regulation during differentiation of primary bovine skeletal muscle cells.We also identified six SNPs of the bovine FOXO1 gene by sequencing DNA pools of samples from 488 individuals, and association analysis indicated that five SNPs were significantly associated with some growth traits in the QC population. We further analyzed four haplotype combinations of the six SNPs and found significant correlation with body length(P<0.01). In conclusion, FOXO1 participates in bovine myocyte differentiation and expression, and may be a strong candidate as a gene that affects growth traits that could be exploited in a QC cattle breeding program. More generally, our data provide a new theoretical basis for QC beef breeding and beef quality improvement.

fGWAS:An R package for genome-wide association analysis with longitudinal phenotypes

The past two decades have witnessed a revolution in identifying genetic risk factors underlying diseases and complex traits using genome-wide association studies （GWAS） （Risch and Merikangas, 1996; Hirschhom and Daly, 2005; Altshuler et al., 2008）. Together with advanced high-throughput technologies for genotyping and sequencing, GWAS have discovered thousands of susceptibility loci for various traits （Welter et al., 2014）.