Molecular genetic diversity and association mapping of morphine content and agronomic traits in Turkish opium poppy (<Emphasis Type="Italic">Papaver somniferum</Emphasis>) germplasm

As the sole plant source of many potent alkaloids, opium poppy (Papaver somniferum L.) is an important medicinal crop. Nevertheless, few studies have characterized opium poppy germplasm with crop-specific molecular markers. Because Turkey is a diversity center for opium poppy, Turkish germplasm is a valuable genetic resource for association mapping studies aimed at identifying QTLs controlling morphine content and agronomic traits. In this study, the morphological diversity and molecular diversity of 103 Turkish opium poppy landraces and 15 cultivars were analyzed. Potentially useful morphological variation was observed for morphine content, plant height, and capsule index. However, the landraces exhibited limited breeding potential for stigma number, and seed and straw yields. Both morphological and molecular analyses showed distinct clustering of cultivars and landraces. In addition, a total of 164 SSR and 367 AFLP polymorphic loci were applied to an opium poppy association mapping panel composed of 95 opium poppy landraces which were grown for two seasons. One SSR and three AFLP loci were found to be significantly associated with morphine content (P < 0.01 and LD value (r ²) = 0.10–0.32), and six SSR and 14 AFLP loci were significantly associated with five agronomic traits (plant height, stigma number, capsule index, and seed and straw yields) (P < 0.01 and LD value (r ²) = 0.08–0.35). This is the first report of association mapping in this crop. The identified markers provide initial information for marker-assisted selection of important traits in opium poppy breeding.     

Genetic diversity and population structure of a diverse set of rice germplasm for association mapping

Germplasm diversity is the mainstay for crop improvement and genetic dissection of complex traits. Understanding genetic diversity, population structure, and the level and distribution of linkage disequilibrium (LD) in target populations is of great importance and a prerequisite for association mapping. In this study, 100 genome-wide simple sequence repeat (SSR) markers were used to assess genetic diversity, population structure, and LD of 416 rice accessions including landraces, cultivars and breeding lines collected mostly in China. A model-based population structure analysis divided the rice materials into seven subpopulations. 63% of the SSR pairs in these accessions were in LD, which was mostly due to an overall population structure, since the number of locus pairs in LD was reduced sharply within each subpopulation, with the SSR pairs in LD ranging from 5.9 to 22.9%. Among those SSR pairs showing significant LD, the intrachromosomal LD had an average of 25–50 cM in different subpopulations. Analysis of the phenotypic diversity of 25 traits showed that the population structure accounted for an average of 22.4% of phenotypic variation. An example association mapping for starch quality traits using both the candidate gene mapping and genome-wide mapping strategies based on the estimated population structure was conducted. Candidate gene mapping confirmed that the Wx and starch synthase IIa (SSIIa) genes could be identified as strongly associated with apparent amylose content (AAC) and pasting temperature (PT), respectively. More importantly, we revealed that the Wx gene was also strongly associated with PT. In addition to the major genes, we found five and seven SSRs were associated with AAC and PT, respectively, some of which have not been detected in previous linkage mapping studies. The results suggested that the population may be useful for the genome-wide marker–trait association mapping. This new association population has the potential to identify quantitative trait loci (QTL) with small effects, which will aid in dissecting complex traits and in exploiting the rich diversity present in rice germplasm.     

Molecular genetic diversity and association mapping of nut and kernel traits in Slovenian hazelnut (<Emphasis Type="Italic">Corylus avellana</Emphasis>) germplasm

European hazelnut (Corylus avellana L.), cultivated in several areas of the world including Europe, Anatolia, and the USA, is an economically important nut crop due to its high mineral, oleic acid, amino acid, and phenolic compound content and pleasant flavor. This study examined molecular genetic diversity and population structure of 54 wild accessions and 48 cultivars from the Slovenian national hazelnut collection using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers. Eleven AFLP primer combinations and 49 SSR markers yielded 532 and 504 polymorphic fragments, respectively. As expected for a wind-pollinated, self-incompatible species, levels of genetic diversity were high with cultivars and wild accessions having mean dissimilarity values of 0.50 and 0.60, respectively. In general, cultivars and wild accessions clustered separately in dendrogram, principal coordinate, and population structure analyses with regional clustering of the wild material. The accessions were also characterized for ten nut and seven kernel traits and some wild accessions were shown to have breeding potential. Morphological principal component analysis showed distinct clustering of cultivars and wild accessions. An association mapping panel composed of 64 hazelnut cultivars and wild accessions had considerable variation for the nut and kernel quality traits. Morphological and molecular data were associated to identify markers controlling the traits. In all, 49 SSR markers were significantly associated with nut and kernel traits [P < 0.0001 and LD value (r ²) = 0.15–0.50]. This work is the first use of association mapping in hazelnut and has identified molecular markers associated with important quality parameters in this important nut crop.     

Identification of SSR markers associated with saccharification yield using pool-based genome-wide association mapping in sorghum

Saccharification describes the conversion of plant biomass by cellulase into glucose. Because plants have never been selected for high saccharification yield, cellulosic ethanol production faces a significant bottleneck. To improve saccharification yield, it is critical to identify the genes that affect this process. In this study, we used pool-based genome-wide association mapping to identify simple sequence repeat (SSR) markers associated with saccharification yield. Screening of 703 SSR markers against the low and high saccharification pools identified two markers on the sorghum chromosomes 2 (23-1062) and 4 (74-508c) associated with saccharification yield. The association was significant at 1% using either general or mixed linear models. Localization of these markers based on the whole genome sequence indicates that 23-1062 is 223 kb from a β-glucanase (Bg) gene and 74-508c is 81 kb from a steroid-binding protein (Sbp) gene. Bg is critical for cell wall assembly and degradation, but Sbp can suppress the expression of Bg as demonstrated in Arabidopsis (Yang et al. 2005). These markers are found physically close to genes encoding plant cell wall synthesis enzymes such as xyloglucan fucosyltransferase (149 kb from 74-508c) and UDP-D-glucose 4-epimerase (46 kb from 23-1062). Genetic transformation of selected candidate genes is in progress to examine their effect on saccharification yield in plants.     

Genetic diversity, linkage disequilibrium, and association mapping analyses of peach (Prunus persica) landraces in China

The genetic diversity, population structure, and linkage disequilibrium (LD) of peaches are greatly important in genome-wide association mapping. In the current study, 104 peach landrace accessions from six Chinese geographical regions were evaluated for fruit and phenological period. The accessions were genotyped with 53 genome-wide simple sequence repeat (SSR) markers. All SSR markers were highly polymorphic across the accessions, and a total of 340 alleles were detected, including 59 private alleles. Of the six regions studied, the northern part of China as well as the middle and lower reaches of the Changjiang River were found to be the most highly diverse genetically. Based on population structure analysis, the peaches were divided into five groups, which well agreed with the geographical distribution. Of the SSR pairs in these accessions, 18.07% (P?<?0.05) were in LD. The mean r ² value for all intrachromosomal loci pairs was 0.0149, and LD decayed at 6.01?cM. The general linear model was used to calculate the genome-wide marker-trait associations of 10 complex traits. The traits include flesh color around the stone, red pigment in the flesh, flesh texture, flesh adhesion, flesh firmness, fruit weight, chilling requirement, flowering time, ripening time, and fruit development period. These traits were estimated by analyzing the 104 landraces. Many of the associated markers were located in regions where quantitative trait loci (QTLs) were previously identified. Peach association mapping is an effective approach for identifying QTLs and may be an alternative to QTL mapping based on crosses between different lines.     

Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r²?≥?0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.     

Population structure and association mapping of yield contributing agronomic traits in foxtail millet

Key message

Association analyses accounting for population structure and relative kinship identified eight SSR markers ( p < 0.01) showing significant association ( R ²  = 18 %) with nine agronomic traits in foxtail millet.

Abstract

Association mapping is an efficient tool for identifying genes regulating complex traits. Although association mapping using genomic simple sequence repeat (SSR) markers has been successfully demonstrated in many agronomically important crops, very few reports are available on marker-trait association analysis in foxtail millet. In the present study, 184 foxtail millet accessions from diverse geographical locations were genotyped using 50 SSR markers representing the nine chromosomes of foxtail millet. The genetic diversity within these accessions was examined using a genetic distance-based and a general model-based clustering method. The model-based analysis using 50 SSR markers identified an underlying population structure comprising five sub-populations which corresponded well with distance-based groupings. The phenotyping of plants was carried out in the field for three consecutive years for 20 yield contributing agronomic traits. The linkage disequilibrium analysis considering population structure and relative kinship identified eight SSR markers (p < 0.01) on different chromosomes showing significant association (R ² = 18 %) with nine agronomic traits. Four of these markers were associated with multiple traits. The integration of genetic and physical map information of eight SSR markers with their functional annotation revealed strong association of two markers encoding for phospholipid acyltransferase and ubiquitin carboxyl-terminal hydrolase located on the same chromosome (5) with flag leaf width and grain yield, respectively. Our findings on association mapping is the first report on Indian foxtail millet germplasm and this could be effectively applied in foxtail millet breeding to further uncover marker-trait associations with a large number of markers.     

Extent and genome-wide distribution of linkage disequilibrium in commercial maize germplasm

Association mapping is based on linkage disequilibrium (LD) resulting from historical recombinations and helps understanding the genetic basis of complex traits. Many factors affect LD and, therefore, it must be determined empirically in the germplasm under investigation to examine the prospects of successful genome-wide association mapping. The objectives of our study were to (1) examine the extent of LD with simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers in 1,537 commercial maize inbred lines belonging to four heterotic pools, (2) compare the LD patterns determined by these two marker types, (3) evaluate the number of SNP markers needed to perform genome-wide association analyses, and (4) investigate temporal trends of LD. Mean values of the squared correlation coefficient ( $ \bar{R} $ ) were almost identical for unlinked, linked, and adjacent SSR marker pairs. In contrast, $ \bar{R} $ values were lowest for the unlinked SNP loci and highest for the SNPs within amplicons. LD decay varied across the different heterotic pools and the individual chromosomes. The SSR markers employed in the present study are not adequate for association analysis, because of insufficient marker density for the germplasm evaluated. Based on the decay of LD in the various heterotic pools, we would need between 4,000 and 65,000 SNP markers to detect with a reasonable power associations with rather large quantitative trait loci (QTL). A much higher marker density is required to identify QTL with smaller effects. However, not only the total number of markers but also their distribution among and along the chromosomes are primordial for undertaking powerful association analyses.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Genetic diversity and population structure analysis of accessions in the US historic sweet sorghum collection

Sweet sorghum has the potential to become a versatile feedstock for large-scale bioenergy production given its sugar from stem juice, cellulose/hemicellulose from stalks, and starch from grain. However, for researchers to maximize its feedstock potential a first step includes additional evaluations of the 2,180 accessions with varied origins in the US historic sweet sorghum collection. To assess genetic diversity of this collection for bioenergy breeding and population structure for association mapping, we selected 96 accessions and genotyped them with 95 simple sequence repeat markers. Subsequent genetic diversity and population structure analysis methods identified four subpopulations in this panel, which correlated well with the geographic locations where these accessions originated or were collected. Model comparisons for three quantitative traits revealed different levels of population structure effects on flowering time, plant height, and brix. Our results suggest that diverse germplasm accessions curated from different geographical regions should be considered for plant breeding programs to develop sweet sorghum cultivars or hybrids, and that this sweet sorghum panel can be further explored for association mapping.     

Detection of favorable alleles for yield and yield components by association mapping in upland cotton

Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(??lgP?>?1.30, P?<?0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.     

A Genomic Resource for the Development,Improvement, and Exploitation of Sorghum for Bioenergy

With high productivity and stress tolerance, numerous grass genera of the Andropogoneae have emerged as candidates for bioenergy production. To optimize these candidates, research examining the genetic architecture of yield, carbon partitioning, and composition is required to advance breeding objectives. Significant progress has been made developing genetic and genomic resources for Andropogoneae, and advances in comparative and computational genomics have enabled research examining the genetic basis of photosynthesis, carbon partitioning, composition, and sink strength. To provide a pivotal resource aimed at developing a comparative understanding of key bioenergy traits in the Andropogoneae, we have established and characterized an association panel of 390 racially, geographically, and phenotypically diverse Sorghum bicolor accessions with 232,303 genetic markers. Sorghum bicolor was selected because of its genomic simplicity, phenotypic diversity, significant genomic tools, and its agricultural productivity and resilience. We have demonstrated the value of sorghum as a functional model for candidate gene discovery for bioenergy Andropogoneae by performing genome-wide association analysis for two contrasting phenotypes representing key components of structural and non-structural carbohydrates. We identified potential genes, including a cellulase enzyme and a vacuolar transporter, associated with increased non-structural carbohydrates that could lead to bioenergy sorghum improvement. Although our analysis identified genes with potentially clear functions, other candidates did not have assigned functions, suggesting novel molecular mechanisms for carbon partitioning traits. These results, combined with our characterization of phenotypic and genetic diversity and the public accessibility of each accession and genomic data, demonstrate the value of this resource and provide a foundation for future improvement of sorghum and related grasses for bioenergy production.     

Genetic dissection of sorghum grain quality traits using diverse and segregating populations

Key message

Coordinated association and linkage mapping identified 25 grain quality QTLs in multiple environments, and fine mapping of the Wx locus supports the use of high-density genetic markers in linkage mapping.

Abstract

There is a wide range of end-use products made from cereal grains, and these products often demand different grain characteristics. Fortunately, cereal crop species including sorghum [Sorghum bicolor (L.) Moench] contain high phenotypic variation for traits influencing grain quality. Identifying genetic variants underlying this phenotypic variation allows plant breeders to develop genotypes with grain attributes optimized for their intended usage. Multiple sorghum mapping populations were rigorously phenotyped across two environments (SC Coastal Plain and Central TX) in 2 years for five major grain quality traits: amylose, starch, crude protein, crude fat, and gross energy. Coordinated association and linkage mapping revealed several robust QTLs that make prime targets to improve grain quality for food, feed, and fuel products. Although the amylose QTL interval spanned many megabases, the marker with greatest significance was located just 12 kb from waxy (Wx), the primary gene regulating amylose production in cereal grains. This suggests higher resolution mapping in recombinant inbred line (RIL) populations can be obtained when genotyped at a high marker density. The major QTL for crude fat content, identified in both a RIL population and grain sorghum diversity panel, encompassed the DGAT1 locus, a critical gene involved in maize lipid biosynthesis. Another QTL on chromosome 1 was consistently mapped in both RIL populations for multiple grain quality traits including starch, crude protein, and gross energy. Collectively, these genetic regions offer excellent opportunities to manipulate grain composition and set up future studies for gene validation.

     

Genome-wide patterns of genetic variation in sweet and grain sorghum (Sorghum bicolor)

Background

Sorghum (Sorghum bicolor) is globally produced as a source of food, feed, fiber and fuel. Grain and sweet sorghums differ in a number of important traits, including stem sugar and juice accumulation, plant height as well as grain and biomass production. The first whole genome sequence of a grain sorghum is available, but additional genome sequences are required to study genome-wide and intraspecific variation for dissecting the genetic basis of these important traits and for tailor-designed breeding of this important C₄ crop.

Results

We resequenced two sweet and one grain sorghum inbred lines, and identified a set of nearly 1,500 genes differentiating sweet and grain sorghum. These genes fall into ten major metabolic pathways involved in sugar and starch metabolisms, lignin and coumarin biosynthesis, nucleic acid metabolism, stress responses and DNA damage repair. In addition, we uncovered 1,057,018 SNPs, 99,948 indels of 1 to 10 bp in length and 16,487 presence/absence variations as well as 17,111 copy number variations. The majority of the large-effect SNPs, indels and presence/absence variations resided in the genes containing leucine rich repeats, PPR repeats and disease resistance R genes possessing diverse biological functions or under diversifying selection, but were absent in genes that are essential for life.

Conclusions

This is a first report of the identification of genome-wide patterns of genetic variation in sorghum. High-density SNP and indel markers reported here will be a valuable resource for future gene-phenotype studies and the molecular breeding of this important crop and related species.     

Association mapping of six yield-related traits in rapeseed (Brassica napus L.)

Yield is one of the most important traits for rapeseed (Brassica napus L.) breeding, but its genetic basis remains largely ambiguous. Association mapping has provided a robust approach to understand the genetic basis of complex agronomic traits in crops. In this study, a panel of 192 inbred lines of B. napus from all over the world was genotyped using 451 single-locus microsatellite markers and 740 amplified fragment length polymorphism markers. Six yield-related traits of these inbred lines were investigated in three consecutive years with three replications, and genome-wide association studies were conducted for these six traits. Using the model controlling both population structure and relative kinship (Q + K), a total of 43 associations (P < 0.001) were detected using the means of the six yield-related traits across 3 years, with two to fourteen markers associated with individual traits. Among these, 18 markers were repeatedly detected in at least 2 years, and 12 markers were located within or close to QTLs identified in previous studies. Six markers commonly associated with correlated traits. Conditional association analysis indicated that five of the associations between markers and correlated traits are caused by one QTL with pleiotropic effects, and the remaining association is caused by linked but independent QTLs. The combination of favorable alleles of multiple associated markers significantly enhances trait performance, illustrating a great potential of utilization of the associations in rapeseed breeding programs.     

Development of genomic simple sequence repeat markers for linseed using next-generation sequencing technology

Linseed (Linum usitatissimum L.) is regarded as a cash crop of tomorrow because of the presence of nutraceutically important ??-linolenic acid (ALA) and lignan. However, only limited breeding progress has been made in this crop, mainly due to the lack of sufficient genetic and genomic resources. Among these, simple sequence repeats (SSR) are useful DNA markers for diversity analysis, genetic mapping and tagging traits because of their co-dominant and highly polymorphic nature. In order to develop SSR markers for linseed, we used three microsatellite isolation methods, viz., PCR Isolation of Microsatellite Arrays (PIMA), 5??-anchored PCR method, and Fast Isolation by AFLP of Sequences COntaining repeats (FIASCO). The amplified products from these methods were pooled and sequenced using the 454 GS-FLX platform. A total of 36,332 reads were obtained, which assembled into 2,183 contigs and 2,509 singlets. The contigs and the singlets contained 1,842 microsatellite motifs, with dinucleotide motifs as the most abundant repeat type (54%) followed by trinucleotide motifs (44%). Based on this, 290 SSR markers were designed, 52 of which were evaluated using a panel of 27 diverse linseed genotypes. Among the three enrichment methods, the 5??-anchored PCR method was most efficient for isolation of microsatellites, while FIASCO was most efficient for developing SSR markers. We show the utility of next-generation sequencing technology for efficiently discovering a large number of microsatellite markers in non-model plants.     

Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection

Association mapping based on the linkage disequilibrium provides a promising tool to identify genes responsible for quantitative variations underlying complex traits. Presented here is a maize association mapping panel consisting of 155 inbred lines with mainly temperate germplasm, which was phenotyped for 34 traits and genotyped using 82 SSRs and 1,536 SNPs. Abundant phenotypic and genetic diversities were observed within the panel based on the phenotypic and genotypic analysis. A model-based analysis using 82 SSRs assigned all inbred lines to two groups with eight subgroups. The relative kinship matrix was calculated using 884 SNPs with minor allele frequency ≥20% indicating that no or weak relationships were identified for most individual pairs. Three traits (total tocopherol content in maize kernel, plant height and kernel length) and 1,414 SNPs with missing data <20% were used to evaluate the performance of four models for association mapping analysis. For all traits, the model controlling relative kinship (K) performed better than the model controlling population structure (Q), and similarly to the model controlling both population structure and relative kinship (Q + K) in this panel. Our results suggest this maize panel can be used for association mapping analysis targeting multiple agronomic and quality traits with optimal association model.     

An SSR genetic map of Sorghum bicolor (L.) Moench and its comparison to a published genetic map.

Sorghum bicolor (L.) Moench is an important grain and forage crop grown worldwide. We developed a simple sequence repeat (SSR) linkage map for sorghum using 352 publicly available SSR primer pairs and a population of 277 F2 individuals derived from a cross between the Westland A line and PI 550610. A total of 132 SSR loci appeared polymorphic in the mapping population, and 118 SSRs were mapped to 16 linkage groups. These mapped SSR loci were distributed throughout 10 chromosomes of sorghum, and spanned a distance of 997.5 cM. More important, 38 new SSR loci were added to the sorghum genetic map in this study. The mapping result also showed that chromosomes SBI-01, SBI-02, SBI-05, and SBI-06 each had 1 linkage group; the other 6 chromosomes were composed of 2 linkage groups each. Except for 5 closely linked marker flips and 1 locus (Sb6_34), the marker order of this map was collinear to a published sorghum map, and the genetic distances of common marker intervals were similar, with a difference ratio 相似文献