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Development and validation of InDel markers for identification of QTL underlying flowering time in soybean

更新时间:2016-07-05

1.Introduction

Soybean[Glycine max(L.)Merrill]is a globally important crop that provides a steady source of high-quality vegetable protein and oil for food products and industrial materials.Accordingly,many useful agronomic trait loci associated with growth,product quality,tolerance to biotic and abiotic stresses,and other characteristics have been identified in the past few decades.Accurate and well-saturated genetic linkage maps have become a valuable tool for genetics and plant breeding,as have genome assembly,QTL analysis,gene tagging,and marker-assisted selection(MAS).Since the first genetic map of soybean was constructed with phenotypic traits[1],various types of molecular markers including restriction fragment length polymorphism(RFLP),random amplification of polymorphic DNA(RAPD),amplified fragment length polymorphism(AFLP),and simple sequence repeat(SSR)markers have been used to construct linkage maps[2–5].Although the current BARCSOYSSR_1.0 database has a total of 33,065 SSR primer sets and the average density of SSR loci in the whole genome is one SSR marker per 0.072 cM[6],many genomic intervals contain no SSR markers,and they are not sufficient for positional cloning and fine mapping in all possible parental crosses.

A functional gene can be identified via forward and reverse genetics strategies[7,8].Positional cloning is widely used as a forward genetics approach to isolate genes in different organisms[9],and its utility can be fully exploited in modern molecular plant breeding systems,such as corn and soybean,when markers linked to genes of interest are discovered[10].The principle of positional cloning is to systematically narrow down the genetic interval containing a causal mutation by sequentially excluding all other regions in the genome[11].All rely on the development of highly dense genetic markers that are polymorphic between the accessions used for generating the mapping population(s)to provide adequate mapping resolution.This dependence is a major limiting factor for the rate of mapping progress.

4)同样的,对待识别的图片我们也进行一样的操作。即定义一个列表samples[],用img_path用于存储待识别图片的所有路径。接下来执行步骤2),3)类似的操作,最后得到存有测试数据的文件samples_test.npy文件。进入步骤5);

With the decreasing cost of next-generation sequencing,there have been several proposals to exploit single-nucleotide polymorphisms(SNPs)and Insertion/Deletions(InDels)for genetic mapping with high-density markers.In contrast to SNPs,InDel polymorphisms,another form of natural genetic variation,have received relatively little attention.Mechanisms such as transposable elements,slippage in simple sequence replication,and unequal crossover events can result in the formation of InDels[12].They can be converted to a user-friendly marker type,show high variation and codominant inheritance,and are relatively abundant and uniformly distributed throughout the genome[13,14].InDel markers are PCR-based and readily genotyped by fragment length polymorphism with minimal laboratory equipment.Recently InDel markers have been widely applied for genotyping,genetic diversity analysis,QTL mapping,map-based cloning,and even marker-assisted selection in Arabidopsis,rice,wheat,turnip,sunflower,pepper,sesame,cotton,and citrus[14–27].However,InDel markers have seldom been identified and used in soybean.A recent study used 73,327 InDels in six soybean cultivars to build a soybean barcode system for comparing data from different sources[28].In another study,165 validated InDel markers were used to develop an InDel-based linkage map for a mapping population between Hedou 12 and Williams 82[29].By exploiting the reference genome sequence of soybean and the large amount of intensive resequencing data available in public databases[30–35],it is now possible to detect genome-wide InDel polymorphisms amongst different accessions using whole-genome resequencing to guide rapid and efficient development of InDel markers for high-resolution genetic analysis.

鼻塞、鼻部胀痛、烦躁不安、溢泪、鼻痒、打喷嚏、头面部疼痛及压迫感、睡眠困难、夜间睡眠质量9项症状出现的例数如表1所示,其余10项无明显差异。

In this study,we attempted to develop InDel markers using genomic resequencing data using a series of bioinformatic approaches.In total,these methods yielded 12,619 new markers that were variously polymorphic amongst 56 soybean accessions.An InDel-based genetic map of soybean was constructed with 300 polymorphic InDel markers.QTL analysis was performed to identify genomic regions associated with flowering time.One major QTL(qDTF4)was identified in 2015 and confirmed in 2016.The InDel markers,genetic map,and QTL identified in this study will lay a foundation for the genetic/QTL analysis and isolation of genes underlying variation in flowering time and provide useful information for MAS breeding in soybean.

2.Materials and methods

2.1.Plant materials and trait evaluation

Primer 3 software[44]was employed to identify primers for each InDel site with the following parameters:predicted products ranged from 100 to 300 bp;the length of primers was limited to 18–24 bp with an optimum size of 20 bp;the annealing temperature was restricted to 57–62 °C;the GC content was set to 35%,50%,and 65%as the minimum,optimum,and maximum,respectively.Only primers with one hit in the genome assembly were retained.

Days to flowering were recorded at the R1 stage(days from emergence to first open flower appearing on 50%of plants).For chamber experiments,seeds from each line were sown in pots.After germination,the seedlings were thinned until each pot contained five uniform plants.Populations were sown in the field with a single seed every 20 cM in 5-m rows spaced 60 cM apart and 25 seeds per line.All trials received standard cultural practices to control insects and weeds.

2.2.Mapping populations and sequence data sets

The BA population,derived from a cross between Mufu12-604×HB-2 and consisting of 156 F2 genotypes,was used to test the newly developed markers and construct a high-density InDel linkage map.The DW population(144 RILs),derived from a cross between Dongnong 50(early-flowering in LD photoperiod)and Williams 82(late-flowering in LD photoperiod),was used to evaluate the InDel markers for QTL mapping.

Fifty six accessions,including 29 from three recent research papers and 27 from this study,were used for InDel polymorphism validation(Table 1).Young leaves from 27 accessions were collected three weeks after planting in growth chambers and separately quick-frozen in liquid nitrogen.Total DNA was extracted by the improved cetyltrimethylammonium bromide(CTAB)method[36].A sequencing library was constructed with at least 6 μg of genomic DNA following the manufacturer's instructions(Illumina Inc.,San Diego,CA).Paired-end sequencing libraries with an insert size of approximately 500 bp were sequenced on an Illumina HiSeq 2000 sequencer.

Table 1–Soybean accessions used in the study.

Sample ID Species Origin Sequencing depth Reference Suinong 14 Cultivar Heilongjiang,China 4.44 Li et al.[42]Suinong 20 Cultivar Heilongjiang,China 4.39 Li et al.[42]Pixiansilicao Cultivar Jiangsu,China 4.81 Li et al.[42]Zheng92116 Cultivar Henan,China 2.67 Li et al.[42]Zhonghuang 13 Cultivar Hebei,China 2.95 Li et al.[42]ZYD04186 Wild Jiangsu,China 5.98 Li et al.[42]ZYD04734 Wild Guizhou,China 4.30 Li et al.[42]ZYD02738 Wild Hebei,China 4.35 Li et al.[42]Sowon Cultivar Republic of Korea 30.20 Chung et al.[34]Pureun Cultivar Republic of Korea 29.40 Chung et al.[34]Kwangkyo Cultivar Republic of Korea 22.70 Chung et al.[34]Ilpumgeomjeong Cultivar Republic of Korea 17.90 Chung et al.[34]Seoritae Landrace Cheongwon,Republic of Korea 19.70 Chung et al.[34]PI96983 Landrace Shariin,Republic of Korea 19.00 Chung et al.[34]Haman Landrace Haman,Republic of Korea 22.00 Chung et al.[34]Geomjeongol Landrace Milyang,Republic of Korea 17.00 Chung et al.[34]Hwangkeum Cultivar Republic of Korea 20.80 Chung et al.[34]Williams 82 K Cultivar Republic of Korea 19.80 Chung et al.[34]IT162825 Wild Yecheon,Republic of Korea 19.90 Chung et al.[34]IT178480 Wild Boeun,Republic of Korea 22.40 Chung et al.[34]IT182869 Wild Jinju,Republic of Korea 19.70 Chung et al.[34]IT182840 Wild Imsil,Republic of Korea 21.10 Chung et al.[34]IT182848 Wild Gokseong,Republic of Korea 19.10 Chung et al.[34]Williams 82 Cultivar United States 60.18 Kim et al.[33]Hwanggeum Cultivar Republic of Korea 45.78 Kim et al.[33]Daepoong Cultivar Republic of Korea 41.67 Kim et al.[33]Baekun Cultivar Republic of Korea 60.94 Kim et al.[33]Shingi Cultivar Republic of Korea 61.53 Kim et al.[33]Sinpaldal 2 Cultivar Republic of Korea 60.57 Kim et al.[33]Fengshou 2 Cultivar Heilongjiang,China 6.21 This study Fengshou 11 Cultivar Heilongjiang,China 5.58 This study Fengshou 12 Cultivar Heilongjiang,China 5.76 This study Fengshou 17 Cultivar Heilongjiang,China 7.24 This study Fengshou 21 Cultivar Heilongjiang,China 5.89 This study Hefeng 29 Cultivar Heilongjiang,China 5.94 This study Hefeng 33 Cultivar Heilongjiang,China 5.82 This study Hefeng 39 Cultivar Heilongjiang,China 6.09 This study Hefeng 40 Cultivar Heilongjiang,China 6.14 This study Hefeng 45 Cultivar Heilongjiang,China 10.57 This study Hefeng 50 Cultivar Heilongjiang,China 6.41 This study Heihe 18 Cultivar Heilongjiang,China 5.99 This study Dongnong 50 Cultivar Heilongjiang,China 10.75 This study Parana Cultivar Brazil 12.36 This study Paranagoiana Cultivar Brazil 11.27 This study Glycine H Cultivar Lima,Peru 10.54 This study Garimpo Cultivar Brazil 12.23 This study Bedford Cultivar Tennessee,United States 10.95 This study H3 Cultivar Brazil 11.16 This study BR121 Cultivar Brazil 11.45 This study Bragg Cultivar Florida,United States 9.85 This study Bossier Cultivar Louisiana,United States 10.56 This study Tokei 780 Cultivar Japan 12.65 This study Hidaka 4 Wild Japan 13.24 This study AGS292 Cultivar Taiwan,China 11.03 This study K3 Cultivar Thailand 10.67 This study Harosoy Cultivar Ontario,Canada 11.17 This study

2.3.InDel detection and marker development

In order to provide the user with valuable information on marker distribution,the markers were named using the format IDNNXXXX,where ID represents InDel,NN the chromosome number(01–20),and the Xs the ordered number of each marker on its chromosome.For example,InDel marker ID06006 is the sixth marker on chromosome Gm06.

由以上分析得到赋形后的反射面,将其建模并带入后处理软件Postprocessor中,4个口径下的波束C/I值分别如图10~13所示。

The F7:8 seeds for the mapping populations were grown in walk-in plant growth chambers at 22°C,65%relative humidity,and long-day(LD)photoperiod(16 h light/8 h dark)in October 2015 and in the field in Harbin(45°43′N,126°45′E)and Mudanjiang(44°36′N,129°35′E),China in May 2016.

2.4.Nomenclature

The process used to detect InDel sites involved three steps.(i)Alignment of paired-end (PE) short reads. BWA(Burrows-Wheeler Aligner)software[37]was used to align paired reads to the reference genome with default parameters and Picard(http://broadinstitute.github.io/picard/)to mark duplicate reads.(ii)Detection of InDels.Five software tools:Samtools[38],GATK Unique Genotyper[39],Varscan[40],Pindel[41],and Soapindel[42],were used to identify InDels 5–50 bp in length.(iii)Optimization of InDels.A support vector machine(SVM)filter was trained on simulated data using a library for support vector machines(LIBSVM)[43]and the InDels were filtered with the SVM filter.The InDels with high polymorphism(MAF>0.4)among 56 individuals were chosen as molecular markers.

2.5.Screening and genotyping of InDel markers

Total genomic DNA was extracted from young leaves or seed flour of individual samples using the improved CTAB method.PCR amplification was performed in a 10 μL reaction consisting of a final concentration of 1×Easy Taq PCR SuperMix for PAGE(TransBionovo Co.,Ltd.,Beijing,China),0.2 μmol L−1 forward/reverse primers,and approximately 30–50 ng of genomic DNA as a template.The amplification protocol comprised an initial denaturation for 2 min at 94°C,35 cycles of denaturation for 30 s at 94°C,annealing for 30 s at 56 °C,and extension for 30 s at 72 °C,followed by a final extension for 5 min at 72°C.PCR products were resolved by 12%SDS-polyacrylamide gel electrophoresis.The gels were stained with ethidium bromide,and the bands were visualized and photographed under ultraviolet light.

2.6.Construction of a linkage map and QTL analysis of flowering time

The F2 population,BA,was used to evaluate the utility of InDel makers for mapping.JoinMap 4.0[45]was used to build the genetic map with 347 markers that were polymorphic between the two parents.The groups and orders of segregated markers were determined on the basis of an LOD(logarithm of the odds ratio for linkage)score of≥7.0 and a minimum LOD score of 1.0,with the threshold of 0.4 in each LG.Markers were tested for deviation from expected Mendelian segregation using a chi-squared test and sorted on the basis of the test(P<0.05).Both inclusive composite interval mapping(ICIM)and multiple-QTL mapping(MQM)were initially applied to detect QTL(LOD>2.0)for flowering time,using QTL IciMapping 4.0[46]and MapQTL 5[47],respectively.

3.Results

3.1.InDel identification and marker development in 56 soybean accessions

To evaluate the performance of the InDel markers,1000 random markers were tested by PCR with Williams 82 as the template.A total of 930 markers(93%)generated single and clear bands as expected,and only 70 markers(7%)either yielded no amplification product or were difficult to score.We next examined the distribution of the 12,619 InDels relative to genes of soybean and found that 429(3.4%)were located within the exons of annotated genes,where gene function may be expected to be influenced.Of these,135(1.1%)were non-3-nucleotide InDels,which were predicted to cause frameshift mutations.This finding indicates that the developed InDel markers are useful for identifying the genetic composition of soybean and provide a valuable source of allelic diversity for genetic and molecular dissection of traits.

The InDel sites were filtered by size and those with a size of 5–50 bp were retained.In total,12,619 primer pairs were obtained with a dense distribution across each of the 20 soybean chromosomes(Table S1).The frequency of InDel markers varied across the chromosomes,falling within the range of approximately 275–1207 markers per chromosome(Table 2).Based on this distribution of InDel markers,it was possible to construct high-density genetic maps and select InDels within specific regions for fine mapping.

Many accurate strategies with corresponding cost and throughput have been developed to detect SNPs as new polymorphic markers for the success of a map-based cloning project.However,detecting InDels is a more challenging task and requires substantial bioinformatic analysis.Several factors affect the discovery of InDels.The phylogenetic relationship between the genotypes used for InDel discovery is important.In this study,based on the alignment of the sequencing reads to a reference genome,17,613 InDel sites were identified among 56 soybean accessions including nine wild soybeans,four landraces,and 43 cultivars from many countries(Table 1).

To confirm the QTL results,the F7:9 seeds were grown in the field in Harbin and Mudanjiang on May 2016.The major QTL,which was assumed to be identical to qDTF4,was repeatedly identified by both ICIM and MQM in two environments.This result showed that the effect of qDTF4 was little affected by the environment and was consistent with the characterization of high heritability of flowering time.In addition,another minor QTL(qDTF11)was mapped on chromosome 11,and explained 6.5%and 9.4%of the phenotypic variation,with LOD scores 2.58 and 3.31,by ICIM and MQM,respectively(Table 3).

3.2.Genetic map construction

The DW population(144 RILs)originated from a cross between the Chinese cultivar Dongnong 50 and the American cultivar Williams 82 and was used to evaluate the InDelmarkers for QTL mapping.The F7:8 seeds were grown in walk-in plant growth chambers in October 2015.A total of 4 QTL,including one major(qDTF4)and three minor QTL(qDTF20,qDTF13,and qDTF12),were detected on four chromosomes using either ICIM or MQM.These QTL explained from 6.0%to 11.3%of phenotypic variation(PEV),with LOD scores ranging from 2.09 to 2.93(Table 3).

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A total of 347 polymorphic markers were scored in the genotype analysis of 156 progeny in the BA F2 population,with each primer pair yielding polymorphic bands at a single locus.After exclusion of 47 unlinked markers,300 marker loci were grouped into 20 LGs,which matched the 20 consensus LGs.Finally,a genetic map(Fig.1),designated as the BA map,was constructed with 20 LGs covering a total genetic distance of 2347.30 cM with an average density of one marker for every 7.82 cM(Table 2).The number of mapped markers per LG ranged from 10(H and D2)to 23(A2)with an average of 15 markers.The largest and smallest genetic distances between adjacent markers were 52.3 cM and 0.1 cM,respectively.Because of low marker density(Fig.2)and infrequent recombination compared with distal regions,our map did not cover all centromeric blocks,resulting in coverage of only a portion of some chromosomes(N,C2,M,O,H,and F)or of two clusters of markers,one from each arm(K and B1)in the F2 mapping study.Six marker orders(N,A1,M,B2,and E)in our genetic map that were in conflict with the physical map could be due to sequence assembly errors,inversions,and segregation distortion.

Table 2–Statistics of the BA map based on InDel markers.

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3.3.QTL analysis of flowering time

The developed InDel markers should be useful for genetic map construction because there are on average about 630 markers on each chromosome.We used a F2 mapping population to illustrate their application to linkage analysis.The F2 population consisted of 156 progeny derived from the cross Mufu 12-604×HB-2,which were not included in the 56 soybean accessions.A random subset of 2841 primer pairs were chosen to identify polymorphism between the parental lines,and 347(12.21%)polymorphic markers were validated.This finding shows that these InDel markers have universal applicability of performance and application,and can be expanded to all soybean germplasm,although these InDel markers were designed to capture the variation within 56 soybean accessions.

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4.Discussion

Genetic diversity in soybean as in other crops has decreased during domestication and improvement[35].The phylogenetic relationship between the genotypes used for InDel discovery is important.In this study,we collected 56 soybean accessions from several regions around the world,including nine wild soybeans,four landraces,and 43 cultivars.The germplasm from wild soybeans and landraces would therefore be useful in broadening the genetic basis and the detection of InDels.This report presents an optimized algorithm with no special requirements for the number of accessions and InDel detection software tools.Additional software can be added to this InDel detection procedure to further improve the performance of the proposed algorithms.

试验药剂4%氟嘧啶草醚+2.5%五氟磺草胺可分散油悬浮剂100毫升/亩对野慈姑防效很好,提高剂量后防效如何,尚待进一步试验。

Fig.1–Genetic linkage map of soybean constructed with InDel markers.Genetic positions and marker names are indicated on the left and right side of each chromosome,respectively.

InDels identification has become routine with the abundance of next-generation sequence data.The InDel markers developed in this study could be widely used in genotyping with minimum lab equipment and PCR options.The potential utility of InDel markers in multiplex PCR could reduce the cost of genotyping by reducing the quantity of reagents and DNA in PCR reactions.Furthermore,this strategy is efficient when hundreds of markers are screened but DNA availability is limited.Our InDel markers closely match many of the criteria for multiplex PCR.The critical parameters of the primers in multiplex PCR should be 18–34 bp or more in length,GC content of 35%–60%,and annealing at 55–58 °C.In addition,the primer length should be up to 28–30 bp and the annealing temperature should be increased for reducing non-specific PCR products.However,owing to the finite polymerase and DNA resources,many specific loci strongly suppress non-specific amplification.Thus,54°C is the appropriate temperature for amplifying multiple loci at the same time[48].All primers reported here were designed with a length of 18–24 bp and GC content of 35%–65%and were amplified at 56 °C,indicating the potential utility of these markers for multiplex PCR.

三是从运行到完善突出一个“细”字,体现了江岸食药监精益求精。在两个点位运行过程中,我们不断完善细节,截至目前,APP开了4次碰头会,“你点我检”活动已开展3次,培训人员50人次,每一次对细节的打磨,都让我们的工作更向前一步。特别是“你点我检”活动,群众对这种线上线下互动的食品安全监管新模式表现出了极大的兴趣和肯定,更提出了许多宝贵的意见与建议,当我们将检测结果反馈给送检群众时,他们的一声感谢成了我们最大的鼓励与动力。这是从群众中来、到群众中去最好的诠释。

Mapping QTL requires a genetic map covered with a high density of polymorphic markers.However,although reduction in the cost of next-generation sequencing technologies will allow the sequencing of numerous soybean accessions,the specialized expertise and the skilled applications of bioinformatics analysis will become a rate-limiting step in uncovering the molecular basis of natural variation.To avoid map-based cloning,a tedious task beset with complications,several recent papers have reported workflows for next-generation sequencing-based strategies for mutation mapping.The approach we advocate here is using resequenced genomes to rapidly facilitate InDel marker design for application to conventional mapping.Interestingly,Dongnong 50 and Williams 82 carry the same genotype(e1-as/E3/E4)for known major maturity loci,but a large difference of 30 days in R1 between the two cultivars was observed under long-day conditions.Thus,some new genes may be involved in control of flowering time and be strongly associated with photoperiod response.The main-effect QTL(qDTF4)was located in the same region as the E8 locus[49,50]and contained candidate genes E1-like-a and E1-like-b,two E1 homologs,which function similarly to E1 in adjusting flowering time in soybean[51].The frequencies of InDel markers developed in this study varied over chromosomes,falling within the range of 275–1207 markers per chromosome,indicating that it was possible to construct high-density genetic maps and select InDels within specific regions for fine mapping.

Fig.2–Physical distribution of 12,619 InDel markers across 20 chromosomes of soybean.The x axis shows the chromosome length in Mbp and the y axis the frequency of InDel markers.

Table 3–QTL of flowering time identified by two mapping methods.

ICIM,inclusive composite interval mapping;MQM,multiple-QTL mapping;PEV,phenotypic variation.

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Supplementary data for this article can be found online at https://doi.org/10.1016/j.cj.2017.08.001.

This work was supported by National Natural Science Foundation of China(31430065,31571686,31371643,31071445),National Key Research and Development Program(2016YFD0100401),“Strategic Priority Research Program”of the Chinese Academy of Sciences(XDA08030108),the Open Foundation of the Key Laboratory of Soybean Molecular Design Breeding of Chinese Academy of Sciences,“One-hundred Talents”Startup Funds from Chinese Academy of Sciences,Scientific Research Foundation for Returned Chinese Scholars of Heilongjiang Province,China(LC201417),and the Science Foundation for Creative Research Talents of Harbin Science and Technology Bureau,China(2014RFQYJ046).

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Jialin Wang,Lingping Kong,Kanchao Yu,Fengge Zhang,Xinyi Shi,Yanping Wang,Haiyang Nan,Xiaohui Zhao,Sijia Lu,Dong Cao,Xiaoming Li,Chao Fang,Feifei Wang,Tong Su,Shichen Li,Xiaohui Yuan,Baohui Liu,Fanjiang Kong
《The Crop Journal》 2018年第2期
《The Crop Journal》2018年第2期文献

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