Genetic diversity and population structure of Shorea macrophylla using genome‐wide single‐nucleotide polymorphisms and microsatellite markers in Indonesia for conservation

India is blessed with an abundance of diverse rice landraces in its traditional cultivated areas. Two marker systems (simple sequence repeats (SSR) and single nucleotide polymorphism (SNP)) were used to study a set of 298 rice landrace accessions collected from six different regions of India (Andaman and Nicobar Islands, Chhattisgarh, Jharkhand, Uttar Pradesh, Uttarakhand, and West Bengal). Thirty hyper-variable simple sequence repeats (HvSSRs) and 32,782 single nucleotide polymorphisms (SNPs) were used in inferring genetic structure and geographical isolation. Rice landraces from Uttar Pradesh were the most diverse, with a gene diversity value of 0.42 and 0.49 with SSR and SNP markers, respectively. Neighbor-joining trees classified the rice landraces into two major groups with SSR and SNP markers, and complete geographical isolation was observed with SSR markers. Fast STRUCTURE analysis revealed four populations for SSR markers and three populations for SNP markers. The population structure with SSR markers showed that few individuals from Uttarakhand and Andaman and Nicobar Islands were grouped in small clusters. Population structure analysis with SNP markers showed not very distinct region-wise clustering among the rice landraces. Discriminant analysis of principal components (DAPC) and minimum spanning network (MSN) using SSR markers showed region-wise grouping of landraces with some intermixing, but DAPC and MSN with SNP markers showed very clear region-wise clustering. Genetic differentiation of rice landraces between the regions was significant with both SSR (Fst 0.094–0.487) and SNP markers (Fst 0.047–0.285). A Mantel test revealed a positive correlation between the genetic and geographic distance of rice landraces. The present study concludes that rice landraces investigated in this study were very diverse, and unlinked SSR markers show better geographical isolation than a large set of SNP markers.

Analysis of the genetic structure of Indonesian Oryza sativa and O. rufipogon using neighbour-joining trees based on single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers revealed that O. sativa in Indonesia is separated from O. rufipogon. Accessions of O. sativa in this study were differentiated into two major groups, indica and tropical japonica, excluding some varieties. SSR and SNP markers revealed the high value of differentiation (F ST) and genetic distance (D) between indica and tropical japonica and we discovered four loci by SNP markers and one locus by SSR markers that play a role in differentiation between indica and tropical japonica. Interestingly, genetic diversity (H) in O. rufipogon was lower than that in O. sativa, however H in O. rufipogon was the highest and H in tropical japonica was the lowest when O. sativa was divided into two groups. Inbreeding coefficient (Fst) showed evidences that gene flow (Nm) between species and within species might be one of the mechanisms related to the diversification and differentiation of Indonesian rice germplasm by asymmetric pattern between species and within O. sativa as revealed by SSR and SNP markers. In addition, we found evidences on stabilizing selection in Indonesian rice germplasm and they might be the reasons why Indonesian rice germplasm did not differentiate due to source location of landrace. However, we found a weak relation between SSR and SNP markers probably due to highly polymorphic in SSR and the different properties of both markers.

Genetic Diversity of Tropical Hybrid Rice Germplasm Measured by Molecular Markers

Finger millet is an important cereal crop in eastern Africa and southern India with excellent grain storage quality and unique ability to thrive in extreme environmental conditions. Since negligible attention has been paid to improving this crop to date, the current study used Next Generation Sequencing (NGS) technologies to develop both Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP) markers. Genomic DNA from cultivated finger millet genotypes KNE755 and KNE796 was sequenced using both Roche 454 and Illumina technologies. Non-organelle sequencing reads were assembled into 207 Mbp representing approximately 13% of the finger millet genome. We identified 10,327 SSRs and 23,285 non-homeologous SNPs and tested 101 of each for polymorphism across a diverse set of wild and cultivated finger millet germplasm. For the 49 polymorphic SSRs, the mean polymorphism information content (PIC) was 0.42, ranging from 0.16 to 0.77. We also validated 92 SNP markers, 80 of which were polymorphic with a mean PIC of 0.29 across 30 wild and 59 cultivated accessions. Seventy-six of the 80 SNPs were polymorphic across 30 wild germplasm with a mean PIC of 0.30 while only 22 of the SNP markers showed polymorphism among the 59 cultivated accessions with an average PIC value of 0.15. Genetic diversity analysis using the polymorphic SNP markers revealed two major clusters; one of wild and another of cultivated accessions. Detailed STRUCTURE analysis confirmed this grouping pattern and further revealed 2 sub-populations within wild E. coracana subsp. africana. Both STRUCTURE and genetic diversity analysis assisted with the correct identification of the new germplasm collections. These polymorphic SSR and SNP markers are a significant addition to the existing 82 published SSRs, especially with regard to the previously reported low polymorphism levels in finger millet. Our results also reveal an unexploited finger millet genetic resource that can be included in the regional breeding programs in order to efficiently optimize productivity.

Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis.

Information about the genetic diversity and population structure in elite breeding material is of fundamental importance for the improvement of crops. The objectives of our study were to (a) examine the population structure and the genetic diversity in elite maize germplasm based on simple sequence repeat (SSR) markers, (b) compare these results with those obtained from single nucleotide polymorphism (SNP) markers, and (c) compare the coancestry coefficient calculated from pedigree records with genetic distance estimates calculated from SSR and SNP markers. Our study was based on 1,537 elite maize inbred lines genotyped with 359 SSR and 8,244 SNP markers. The average number of alleles per locus, of group specific alleles, and the gene diversity (D) were higher for SSRs than for SNPs. Modified Roger’s distance (MRD) estimates and membership probabilities of the STRUCTURE matrices were higher for SSR than for SNP markers but the germplasm organization in four heterotic pools was consistent with STRUCTURE results based on SSRs and SNPs. MRD estimates calculated for the two marker systems were highly correlated (0.87). Our results suggested that the same conclusions regarding the structure and the diversity of heterotic pools could be drawn from both markers types. Furthermore, although our results suggested that the ratio of the number of SSRs and SNPs required to obtain MRD or D estimates with similar precision is not constant across the various precision levels, we propose that between 7 and 11 times more SNPs than SSRs should be used for analyzing population structure and genetic diversity.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-009-1256-2) contains supplementary material, which is available to authorized users.

Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were evaluated in an effort to reliably DNA fingerprint sweet cherry (Prunus avium L.) cultivars and advanced selections from the breeding program at the Summerland Research and Development Center (Summerland, BC, Canada). SSR markers were found that differentiated the 35 cultivars and selections tested. However, groups of cultivars closely related to the parental cultivars, Lapins and Sweetheart, were differentiated by only a few SSR markers each. These last few markers were discovered by specifically screening within these small groups of cultivars and the resulting markers had lower discriminating power (Dj) statistics within the full set of 35 cultivars and selections. To further characterize the differences in one of these closely related groups, SNP markers were identified in the cultivar Sweetheart and an analysis was made of how these markers segregated into three of its open-pollinated progeny. Large blocks of the ‘Sweetheart’ genome (34%) did not contain informative SNP markers, which was consistent with its ancestry where the cultivar Van is both a parent and grandparent. The three progeny cultivars differed from ‘Sweetheart’ at 14%, 31%, and 29% of the 3011 SNP positions tested. These were located in blocks of linked haplotypes covering from 2.5 to 20 million bps each and were distinct for the three cultivars. The cultivar Staccato®, which required the most effort for SSR marker discrimination, also had the lowest number of SNP position differences from ‘Sweetheart’ (14%). These informative SNP markers were located in only five small regions of the sweet cherry genome, which also contained the discriminating SSR markers and provides an explanation for the difficulty of locating SSR markers for this cultivar. In addition to clearly differentiating these cultivars, this SNP analysis shows the level of variation expected within this closely related group.

The ratio of amylose to amylopectin in maize kernel starch is important for the appearance, structure, and quality of food products and processing. This study aimed to identify quantitative trait loci (QTLs) controlling amylose content in maize through association mapping with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. The average value of amylose content for an 80-recombinant-inbred-line (RIL) population was 8.8 ± 0.7%, ranging from 2.1 to 15.9%. We used two different analyses-Q + K and PCA + K mixed linear models (MLMs)-and found 38 (35 SNP and 3 SSR) and 32 (29 SNP and 3 SSR) marker-trait associations (MTAs) associated with amylose content. A total of 34 (31 SNP and 3 SSR) and 28 (25 SNP and 3 SSR) MTAs were confirmed in the Q + K and PCA + K MLMs, respectively. This study detected some candidate genes for amylose content, such as GRMZM2G118690-encoding BBR/BPC transcription factor, which is used for the control of seed development and is associated with the amylose content of rice. GRMZM5G830776-encoding SNARE-interacting protein (KEULE) and the uncharacterized marker PUT-163a-18172151-1376 were significant with higher R2 value in two difference methods. GRMZM2G092296 were also significantly associated with amylose content in this study. This study focused on amylose content using a RIL population derived from dent and waxy inbred lines using molecular markers. Future studies would be of benefit for investigating the physical linkage between starch synthesis genes using SNP and SSR markers, which would help to build a more detailed genetic map and provide new insights into gene regulation of agriculturally important traits.

Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers are amongst the most common markers of choice for studies of diversity and relationships in horticultural species. We have used 11 SSR and 35 SNP markers derived from transcriptome sequencing projects to fingerprint 48 accessions of a collection of brinjal (Solanum melongena), gboma (S. macrocarpon) and scarlet (S. aethiopicum) eggplant complexes, which also include their respective wild relatives S. incanum, S. dasyphyllum and S. anguivi. All SSR and SNP markers were polymorphic and 34 and 36 different genetic fingerprints were obtained with SSRs and SNPs, respectively. When combining both markers all accessions but two had different genetic profiles. Although on average SSRs were more informative than SNPs, with a higher number of alleles, genotypes and polymorphic information content (PIC), and expected heterozygosity (H e ) values, SNPs have proved highly informative in our materials. Low observed heterozygosity (H o ) and high fixation index (f) values confirm the high degree of homozygosity of eggplants. Genetic identities within groups of each complex were higher than with groups of other complexes, although differences in the ranks of genetic identity values among groups were observed between SSR and SNP markers. For low and intermediate values of pair-wise SNP genetic distances, a moderate correlation between SSR and SNP genetic distances was observed (r2 = 0.592), but for high SNP genetic distances the correlation was low (r2 = 0.080). The differences among markers resulted in different phenogram topologies, with a different eggplant complex being basal (gboma eggplant for SSRs and brinjal eggplant for SNPs) to the two others. Overall the results reveal that both types of markers are complementary for eggplant fingerprinting and that interpretation of relationships among groups may be greatly affected by the type of marker used.

Comparative Analysis of Genetic Diversity and Structure in Rice Using ILP and SSR Markers

Single nucleotide polymorphism (SNP) markers are increasingly being used in crop breeding programs, slowly replacing simple sequence repeats (SSR) and other markers. SNPs provide many benefits over SSRs, including ease of analysis and unambiguous results across various platforms. We have identified and mapped SNP markers in the tropical tree crop Theobroma cacao, and here we compare SNPs to SSRs for the purpose of determining off-types in clonal collections. Clones are used as parents in breeding programs and the presence of mislabeled clones (off-types) can lead to the propagation of undesired traits and limit genetic gain from selection. Screening was performed on 186 trees representing 19 Theobroma cacao clones from the Institute of Agricultural Research for Development (IRAD) breeding program in Cameroon. Our objectives were to determine the correct clone genotypes and off-types using both SSR and SNP markers. SSR markers that amplify 11 highly polymorphic loci from six linkage groups and 13 SNP markers that amplify eight loci from seven linkage groups were used to genotype the 186 trees and the results from the two different marker types were compared. The SNP assay identified 98% of the off-types found via SSR screening. SNP markers spread across multiple linkage groups may serve as a more cost-effective and reliable method for off-type identification, especially in cacao-producing countries where the equipment necessary for SSR analysis may not be available.

Genetic diversity in Cucurbita pepo landraces revealed by RAPD and SSR markers

Rice is arguably the most important food crop of the world and due to its small genome size compared to other major cereals, rice was selected as model crop species for decoding of its full genome. The international rice genome sequencing project (IRGSP), a consortium of laboratories from ten different countries, has generated a very high quality map based sequence of the 12 chromosomes of japonica rice cultivar ‘Nipponbare’ and made it available in the public domain. A whole genome draft sequence of indica type rice variety ‘93-11’ has also been reported by the Beijing Genomics Institute. Annotation and comparative analysis of these and other partial genomic sequences has provided a wealth of information to the rice geneticists and breeders. Simple Sequence Repeat (SSR) markers are now easily available for any region of the rice genome. SSR markers have also been derived from the expressed sequence tags (ESTs) and unigene sequences, which correspond to the expressed component of the genome and thus have greater potential in comparative genome analysis. Furthermore, millions of single nucleotide polymorphism (SNP) and insertion-deletion (InDel) markers have already been identified in rice. Saturation of the genome with such sequence based SSR and SNP markers is accelerating fine mapping and map-based cloning of genes, and thus, development of gene-based allele-specific markers. Rice improvement programs are expected to benefit greatly from the use of these markers in near future.

Tomato landraces are less sensitive to environmental stresses and grown mainly under rain fed conditions. They are still grown in small farms due to quality and special demand of consumers. These landraces are valuable sources of genetic traits, and plant breeders can use breeding programs for crop improvement. One of the primary needs of the crop improvement is the estimation of genetic diversity. Development of microsatellite simple sequence repeat (SSR) markers from map-referenced bacterial artificial chromosomes (BAC) clones is a very effective means of targeting markers to marker scarce positions in the genome. This study was aimed at developing a set of functional SSR markers via in silico analysis of publicly available tomato DNA sequences. As a result, 17 SSR markers were developed and tested on one tomato commercial cultivar and eight local landraces. 12 loci (27 alleles) were scored and showed 100% polymorphic patterns. The calculated polymorphism information content (PIC) values for the SSR markers developed ranged from 0.62 to 0.97 (mean 0.89). The SSR motifs CT(26) AT(27) and TTC(6) TTA(4) had the highest PIC value (0.97), while CAA(5)A(8) had the lowest PIC value (0.62). According to tomato expressed sequence tag (EST) analysis, some of these developed SSR markers, such as mono and di-nucleotide are related to some genes. The T(16) motif is related to hydroxyproline-rich glycoprotein, which is a family protein from Arabidopsis thaliana . On the other hand, the SSR with tri-nucleotide repeat motif AAC(4)A(11) was related to a putative homologous protein to A7Q2S4 from Vitis vinifera . Keywords: Tomato landraces, in silico simple sequence repeat (SSR) markers, DNA markers, genetic diversity

ABSTRACTSucrose is a desirable sugar in soybean seed that affects the quality of soyfoods and feed; therefore, soybean cultivars with high sucrose would be valuable for soyfood and soybean meal markets. The objective of this study was to identify quantitative trait loci (QTL) associated with seed sucrose content using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers that can be used for indirect selection in breeding. A low sucrose line, MFS‐553, was crossed with a high sucrose plant introduction, PI 243545, to develop an F2–derived QTL mapping population. A total of 626 SSR primers covering 20 soybean chromosomes were used to screen the parents and 209 SSR markers were polymorphic. The polymorphic SSR markers were used to genotype 220 F2:3 lines. Subsequently, a total of 94 F3:4 lines derived from the initial F2:3 population were genotyped with 5361 SNP markers spanning 20 chromosomes, of which 2016 were polymorphic. Seed from the F2:3, F3:5, and F3:6 lines were analyzed for sucrose using high performance liquid chromatography (HPLC). Following the linkage map construction, composite interval mapping (CIM) and multiple interval mapping (MIM) were performed to locate sucrose QTL. Three novel QTLs for seed sucrose were mapped to chromosomes 5, 9, and 16, accounting for 46, 10 and 8%, respectively, of the phenotypic variation for sucrose content. SSR and SNP markers linked to these QTLs can be used for marker assisted selection (MAS) in breeding soybean lines with the desired sugar profile.