Bangladesh is a reservoir of diverse rice germplasm and is home to many landraces with unique, important traits. Molecular characterization of these landraces is of value for their identification, preservation, and potential use in breeding programs. Thirty-eight rice landraces from different regions of Bangladesh including some high yielding BRRI varieties were analyzed by 34 polymorphic microsatellite markers yielding a total of 258 reproducible alleles. The analysis could locate 34 unique identifiers for 21 genotypes, making the latter potentially amenable to identity verification. An identity map for these genotypes was constructed with all the 12 chromosomes of the rice genome. Polymorphism information content (PIC) scores of the 34 SSR markers were 0.098 to 0.89 where on average 7.5 alleles were observed. A dendogram constructed using UPGMA clustered the varieties into two major groups and five subgroups. In some cases, the clustering matched with properties like aromaticity, stickiness, salt tolerance, and photoperiod insensitivity. The results will help breeders to work towards the proper utilization of these landraces for parental selection and linkage map construction for discovery of useful alleles.
Genetic diversity of crop plants is the key resource for maintaining agricultural productivity. This wealth of genetic diversity has been utilized and preserved during the natural process of domestication and cultivation of crop plants. But thousands of allelic variations of traits of economic significance remain unutilized, many of which are found in traditional cultivars or landraces. Developmental activities and increasing land-use are gradually destroying natural habitats resulting in the reduction of this diversity. The situation is further aggravated by introduction of modern varieties to replace these landraces, which has happened in the case of rice cultivars. Hence it is important to understand the evolution and ecology of rice landraces in order to catalogue and preserve them for future use.
Bangladesh is an agroeconomy based country lying astride the tropic of cancer between 20°25′ and 26°38′N latitudes and 88°01′ and 92°40′E longitudes which conserves a broad range of agroecological environmental diversity in climate, physiography, soil, and hydrology [
The agroecological condition in northeast region of Bangladesh is more diverse than the rest and provides suitable environment for growth of rice varieties with wide genetic variation. Traditional varieties still continue to be grown in large areas of the region due to their adaptation to the local prevailing conditions. Consumers do not hesitate to pay higher prices for the fine aromatic or glutinous rice found in these areas, each sought after due to unique cultural traditions. The Sundarban forest area spans one-third of the southern portion of 3 districts in Bangladesh and is known to be highly saline. Salinity levels gradually decline from west to east [
Genetic uniqueness is brought about by two factors, inheritance and new mutations or deletions. Since all genetic differences between individuals are present in the primary sequence of their genomic DNA, the most straightforward method of locating uniqueness is by identifying a variant sequence in an individual for the genome under study [
Since polymorphic microsatellite markers show different banding pattern among varieties, those which show distinctive banding pattern can be used as a unique identifier for that specific variety. The divergent germplasm collection at IRRI and BRRI has the problem of duplication of name since many traditional varieties are cultivated in multiple regions of the country and are known by different names due to variation in local languages. This underlines the importance of unique identifiers for determining the singularity of these landraces.
In the present study, 38 different varieties of rice from different regions of the country were used for fingerprinting. The study included some recently released stress tolerant rice varieties. The objective of the study was to predict unique identifiers that can be used to determine the identity of any specific variety for further studies. An identity map using the GGT software has also been produced. Assessment of this genetic variation and grouping through similarity and dissimilarity will be valuable for proper selection of parents in breeding and mapping for introgression of novel traits from rice landraces in order to develop improved varieties. Thus the information generated from the study will be used in identifying efficient strategies for the sustainable management of the genetic resources of rice crops in Bangladesh.
A total of 38 cultivars with different characteristics like aromaticity (Kataribhog, Chinigura), stickiness (Beruin varieties), and salt tolerance (Pokkali, Horkuch, and Boilam) as well as farmer popular landraces of some regions along with BRRI derived modern varieties BRRI dhan41, BRRI dan53, BRRI dhan55, and BRRI dhan56 were subjected to DNA fingerprinting. The varieties were collected from different regions of Bangladesh (Table
List of rice varieties collected from different regions.
Variety | Accession | Location | NPGRC* id | Properties |
---|---|---|---|---|
Capsule | IRIS 121-7435 | Satkhira, SW | Salt tolerant | |
Rajashail 1062 | IRIS 121-7407 | |||
Rajashail Unknown | ||||
Rajashail Breeding | ||||
Mohini | Khulna | Biotic stress tolerant | ||
Chinikanai | IRIS 307-55477 | Satkhira | 97A00031 | Fine aromatic |
Nonashail 599 | Noakhali | |||
Horkuch | IRIS 109-1513 | Khulna | Salt tolerant | |
Ranisalute | Khulna | Salt tolerant | ||
Patnay | Khulna | 95A00208 | Salt tolerant | |
Boilam 3538 | IRIS 6-82602 | Noakhali | Salt tolerant | |
Binnatoa | IRIS 40-171906 | Noakhali | Salt tolerant | |
Bashful Balam | IRIS 109-1516 | |||
Kali boro 1281 | IRIS 6-94498 | Faridpur | ||
Khaia boro 4539 | IRIS 1-57186 | Habiganj | ||
Gheegoj 243 | IRIS 1-60817 | Noakhali | ||
Shakkar khar 1605 | Fine aromatic | |||
Soloi 1713 | IRIS 1-58930 | Faridpur | 04A02113 | |
Latial 7 | Moulovibajar | 97A00003 | Also known as Lathishail | |
Kataribhog 5 | IRIS 1-58168 | Dinajpur | Aromatic | |
Chinigura 17 | Moulovibajar | Aromatic | ||
Raujan 1 | Moulovibajar | |||
Push beruin | Moulovibajar | |||
Kathaliberuin | Moulovibajar | Semiglutinous | ||
Horidhan | Jhenaidah | High yield | ||
Lal bajal | Feni | |||
Chikan dhan | Fine aromatic | |||
Binni dhan | IRIS 307-50894 | |||
Paijon | IRIS 307-52869 | Dinajpur | ||
Kachra | IRIS 6-73379 | Khulna | Salt tolerant | |
Morichbati | IRIS 1-28568 | |||
Jaldepa | ||||
Lal dupa | IRIS 307-51001 | |||
BRRI dhan41 | BRRI | Mod. salt tolerant (tolerance source SR26B) | ||
BRRI dhan53 | BRRI | Mod. salt tolerant | ||
BRRI dhan55 | BRRI | Mod. salt cold tolerant (tolerance source | ||
BRRI dhan56 | BRRI | Mod. drought tolerant (tolerance source is unknown, probably WAY RAREM as this variety is recommended for acid soils and high active Al and Fe) | ||
Pokkali | IRIS 121-25932 | Sri Lanka | Salt tolerant |
Collection sites for rice samples.
Genomic DNA was isolated from (0.5–1.0 g) pooled leaf tissue using the modified CTAB method [
Polymerase chain reaction (PCR) was performed using 50 ng template DNA, 0.1 mM dNTPs, 0.33
For the microsatellite DNA fingerprinting of the cultivars, polymorphism was scored according to their molecular weight on polyacrylamide gels by the “molecular weight analysis” Alpha Ease FC imaging system (
GGT2 [
Cluster analysis was based on similarity matrices using the unweighted pair group method with arithmetic mean (UPGMA) [
Using 34 rice microsatellite (RM) markers, a total of 258 reproducible polymorphic bands or alleles were identified from 38 rice landraces. On average, 2–13 polymorphic alleles were found (ranging from 75 to 450 bp) across the various rice genotypes. The allelic pattern of landraces using SSR primers representing the 12 rice chromosomes is shown in Figure
Polymorphism information content of different SSR markers.
Marker | Major allele frequency | Allele number | Chromosome | Gene diversity | PIC |
---|---|---|---|---|---|
RM10115 | 0.39 | 3 | 1 | 0.6440 | 0.57 |
RM3412 | 0.24 | 12 | 1 | 0.8670 | 0.85 |
RM7075 | 0.36 | 10 | 1 | 0.8054 | 0.78 |
RM1349 | 0.21 | 9 | 1 | 0.8629 | 0.85 |
RM472 | 0.34 | 8 | 1 | 0.7576 | 0.72 |
RM12476 | 0.34 | 5 | 2 | 0.7576 | 0.72 |
RM13628 | 0.29 | 8 | 2 | 0.8130 | 0.79 |
RM5404 | 0.53 | 6 | 2 | 0.6593 | 0.62 |
RM3867 | 0.34 | 11 | 3 | 0.8186 | 0.80 |
RM261 | 0.21 | 13 | 4 | 0.8823 | 0.87 |
RM5749 | 0.39 | 5 | 4 | 0.7105 | 0.66 |
RM17391 | 0.29 | 7 | 4 | 0.7881 | 0.76 |
RM127 | 0.39 | 5 | 4 | 0.7008 | 0.65 |
RM169 | 0.50 | 3 | 4 | 0.6219 | 0.55 |
RM440 | 0.16 | 13 | 5 | 0.9017 | 0.89 |
RM31 | 0.24 | 8 | 5 | 0.8296 | 0.81 |
RM19516 | 0.26 | 7 | 6 | 0.8158 | 0.79 |
RM20417 | 0.47 | 6 | 6 | 0.6814 | 0.63 |
RM103 | 0.61 | 5 | 6 | 0.5900 | 0.56 |
RM436 | 0.26 | 7 | 7 | 0.8213 | 0.80 |
RM180 | 0.21 | 13 | 7 | 0.8906 | 0.88 |
RM560 | 0.79 | 3 | 7 | 0.3546 | 0.33 |
RM407 | 0.55 | 3 | 8 | 0.5360 | 0.44 |
RM210 | 0.18 | 11 | 8 | 0.8781 | 0.87 |
RM23409 | 0.79 | 2 | 8 | 0.3324 | 0.28 |
RM23966 | 0.24 | 9 | 9 | 0.8504 | 0.83 |
RM24834 | 0.66 | 5 | 9 | 0.5291 | 0.50 |
RM25181 | 0.16 | 10 | 10 | 0.8767 | 0.86 |
RM5806 | 0.18 | 9 | 10 | 0.8601 | 0.84 |
RM3137 | 0.18 | 10 | 11 | 0.8809 | 0.87 |
RM26652 | 0.21 | 9 | 11 | 0.8740 | 0.86 |
RM101 | 0.95 | 3 | 12 | 0.1011 | 0.10 |
RM27933 | 0.18 | 12 | 12 | 0.8795 | 0.87 |
RM28746 | 0.33 | 8 | 12 | 0.7846 | 0.75 |
Representative gel showing the polymorphic bands between the varieties. (genotyped with RM7075).
Polymorphism information content (PIC) was estimated for each of the 34 markers by Powermarker Software using the equation by Botstein and coworkers [
Analysis of 34 polymorphic SSR markers generated a total of 34 unique bands on PAGE for 21 cultivars. Alleles were represented by different color codes in the GGT Software. Any unique color in the location of a specific marker represents the unique allele or banding of that SSR marker. The unique identifiers observed in the current study are well distributed among all chromosomes of rice except chromosome 6 and 11. No unique identifiers could be located in these 2 chromosomes in the current study. Most of the unique identifiers found in this study have high PIC score except RM 101 which had the very low PIC score of 0.099. It is however unique for the varieties Boilam 3538, BRRI dhan53, and Nonashail 599. The unique identifiers represented by GGT are given in Figure
List of 34 unique identifiers found from the study.
Variety | Marker | Chr | PIC | MW |
---|---|---|---|---|
Capsule | RM27933 | 12 | 0.87 | 172 |
Rajashail 1062 | RM17391 | 4 | 0.76 | 182 |
Chinikanai | RM261 | 4 | 0.87 | 110 |
Horkuch | RM180 | 7 | 0.88 | 143 |
RM23966 | 9 | 0.83 | 226 | |
Ranisalute | RM27933 | 12 | 0.87 | 160 |
Boilam 3538 | RM101 | 12 | 0.099 | 319 |
RM27933 | 12 | 0.87 | 140 | |
Bashful Balam | RM472 | 1 | 0.72 | 272 |
Kali boro 1281 | RM3867 | 3 | 0.8 | 216 |
Shakkar khar 1605 | RM472 | 1 | 0.72 | 270 |
RM28746 | 12 | 0.74 | 142 | |
Soloi 1713 | RM7075 | 1 | 0.77 | 169 |
RM472 | 1 | 0.72 | 284 | |
Latial 7 | RM23966 | 9 | 0.83 | 234 |
Kataribhog 5 | RM210 | 8 | 0.87 | 158 |
RM24834 | 9 | 0.49 | 314 | |
Chinigura 17 | RM3412 | 1 | 0.85 | 124 |
Raujan 1 | RM3412 | 1 | 0.85 | 107 |
Push beruin | RM3412 | 1 | 0.85 | 117 |
Horidhan | RM13628 | 2 | 0.79 | 215 |
RM261 | 4 | 0.87 | 119 | |
RM440 | 5 | 0.89 | 191 | |
RM210 | 8 | 0.87 | 157 | |
Chikan dhan | RM25181 | 10 | 0.86 | 137 |
Binni dhan | RM13628 | 2 | 0.79 | 268 |
RM180 | 7 | 0.88 | 115 | |
BRRI dhan53 | RM261 | 4 | 0.87 | 130 |
RM25181 | 10 | 0.86 | 158 | |
RM101 | 12 | 0.099 | 279 | |
BRRI dhan56 | RM31 | 5 | 0.81 | 126 |
Pokkali | RM3412 | 1 | 0.85 | 95 |
RM7075 | 1 | 0.77 | 162 | |
RM28746 | 12 | 0.74 | 126 |
Identity map for all varieties created using GGT software [
From the dendrogram (Figure
Dendogram constructed based on the polymorphism of the 38 varieties using the 34 markers used in the study.
The markers used in this study had di-, tri-, or tetranucleotide motifs. 55.88% markers were dinucleotide, 38.26% were trinucleotide, and only 5.88% were tetranucleotide. Among the 10 highly polymorphic markers, 60% had dinucleotide motif, 30% had trinucleotide motif, and only 1% had tetranucleotide motif which shows the high polymorphism value of dinucleotide motif-containing markers among the Bangladeshi rice landraces.
The rice germplasm in Bangladesh is vast and divided mainly into three different major groups, that is, indica, aus, and aromatic [
Genetic variations among accessions in this study were assessed using microsatellite markers. Rice microsatellite (RM) or simple sequence repeat (SSR) markers are robust and codominant (i.e., they can detect heterozygous loci), exhibit high allelic variation, and are widely distributed throughout the Oryza genome [
The molecular identity of local and BRRI varieties and their association with each other will provide important information for the better management of the rice varieties for breeding and preservation. In the current study, on average 2–13 polymorphic alleles were found (ranging from 80 to 350 bp) across the various rice genotypes. Dinucleotide repeat motifs displayed higher level of variation among the rice genotypes than the other motifs which confirmed the abundant nature of dinucleotide repeat polymorphism as reported earlier [
The UPGMA (unweighted pair group method with arithmetic mean) method was applied in the construction of the dendrogram that is a simple agglomerative or bottom-up data clustering method used for the creation of phylogenetic trees. UPGMA algorithm examines the structure present in a pairwise distance matrix for constructing a rooted tree or dendrogram. The fingerprinting result with 34 RM markers grouped the landraces into 2 major groups and 5 subgroups after cluster analysis. The varieties could be differentiated according to their aromaticity, stickiness properties, high yielding characteristics, photoperiodicity, and modern or traditional characteristics. Interestingly, the salt tolerant genotypes were present in 3 different groups. This suggests involvement of different sets of genes responsible for their tolerance and intercrossing could lead to a combination of different mechanisms. This hypothesis will however need to be tested further. Some varieties were grouped together even though there were no known similar properties amongst them. More markers or a different set may provide a different picture of relatedness. Major varieties in Group I constituted well known aromatic varieties like Kataribhog, Chinigura, and so forth; however, some of the varieties like Horkuch and Ranisalute are well known for their salinity tolerance but not aroma. In a recent study by Platten and coworkers [
Most of the markers were found to be of high PIC score which indicates the ability of the markers to detect polymorphism between closely related varieties in high resolution. The level of polymorphism determined by the PIC value (mean = 0.69) is consistent with the range of PIC values observed in the earlier published reports. In one of these reports the PIC values ranged from 0.24 to 0.92 with an average value of 0.61 [
Unique identifier can be used as a distinctive passport for local germplasm. This can be very useful in identification of variants as well as their progenies which is important for protecting the intellectual property right (IPR) for Bangladeshi accessions. A total of 34 unique identifiers for 21 varieties were observed from the analysis of 34 markers and an identity map presented (Table
In short, the study could successfully locate 34 unique identifiers for 21 varieties from the analysis of 34 polymorphic SSR markers. As these markers can verify the respective varieties uniquely, they can be used in crop identity protection in breeding programs to improve rice varieties. The polymorphic markers used in the study were evaluated by PIC score which is a measure of polymorphism of the markers. This score is valuable for choosing highly polymorphic markers for linkage analysis and variety selection for breeding program of rice germplasm. A dendogram was constructed based on the frequency based distances of the 38 cultivars under study, which could cluster the cultivars in the two major subpopulation structures of
The authors declare that there is no conflict of interests regarding the publication of this paper.
Nusrat Yesmin and Sabrina M. Elias contributed equally to this work.
Funds for this project were kindly provided by BAS-USDA, that is, from the Bangladesh Academy of Sciences (BAS) with funds from the Bangladesh Chapter of USDA.