Promising drought tolerant rice cultures viz., CPMB ACM 04 004, CPMB ACM 04 006 and PM 01 011, PM 03 002 and RM 04 001 were developed through marker aided selection (MAS) and farmers participatory plant breeding approach in the Department of Plant Molecular Biology and Biotechnology, CPMB with the help of Department of Plant Breeding and Genetics, AC&RI, Madurai, ARS, Paramakudi and CSRC, Ramnad. Among these drought tolerant rice lines, PM 01 011 performed better over years and across locations. It recorded an average grain yield of 3891 kg/ha, which is 14.40 per cent increased yield over the ruling check variety PMK (R) 3 (3401 kg/ha) and is accepted for release as location specific variety for Ramnad and Sivagangai districts during the year 2008. This culture is being proposed for release during 2009.
Evolving high yielding rice genotypes with durable resistance to bacterial blight (BB) is pertinent considering the extensive damage caused by the disease in most of the rice growing regions. Two high yielding BB susceptible indica rice cultivars, ADT43 and ASD16 popular among farmers and consumers across South India have been introgressed with three BB resistance genes xa5, xa13 and Xa21 from isoline IRBB60 using functional markers
A short duration (115-120 days) rice culture, AD (Bio) 09518 (ADT 43 x IRBB60-5-1) with the yield potential of 5767 kg/ha and high resistance to bacterial blight has been developed through marker-assisted pedigree breeding. It has medium slender grains with high head rice recovery (80.6%). The culture, AD (Bio) 09518 has a amylose content of 25.48 per cent.
On cooking, the rice quality is equivalent to CO 51. The culture has soft gel and good volume expansion. This culture was tested under adaptive research trial (ART-Rice 14/2015-16, 2016-17, Special transplanted Early (May-June sowing) for the two consecutive years. In the first year ART 14 (2015-16), the results from 55 locations across 15 districts revealed that AD (Bio) 09518 recorded an average grain yield of 5999 kg/ha. In the second year ART 14 (2016-17), AD (Bio) 09518 had given an average yield of 5439 kg/ ha in 113 days from 26 locations and manifested on par yield with CO 51 (5484 kg/ha) and ADT 43 (5426 kg/ha).
Under artificial screening in green house condition both at TNAU, Coimbatore and Indian Institute of Rice Research, Hyderabad, it showed high resistance to bacterial blight. Out of the 12 pathogenic races tested, the culture is resistant to almost all (11) races of the BB pathogen. The culture also showed moderate resistance to leaf folder.
AD (Bio) 13060 (ADT 47/IRBB60) is developd through marker asssited selection for BB resistance (xa5, Xa13, Xa21). It is a short duration culture (115 days) and evaluated for four years to study the yield performacne and resistance against BB isolates. It gave a mean yield of 6073 Kg/ha, 21% increase over ADT43 and 13% increase over ADT47. This culture is highly resistant to BB pathogen and now under multilcoation testing.
A fine grain rice culture, AD (Bio) 13066 (ADT 43 x IRBB60) with the yield potential of 6000 kg/ha and high resistance to bacterial blight was developed through marker-assisted pedigree breeding It is mid early duration (125 days) culture with medium slender grain. It is now under multi location evaluation.
The aim is to pyramid genes for Gall Midge (Gm1, Gm4), Blast (Pi54 , Pi9) and bacterial blight (xa13, Xa21, Xa33, Xa38) resistance in rice varieties CO43 and ASD16 . The recipient lines were susceptible to the above stresses. The donor lines viz., B95-1 X Tetep (Xa21 and Pi54), B95-1 X Kavya (Xa21 X Gm1), B95-1 X Abhaya (Xa13 and Gm4) and VRP1 (Pi9) were utilized for introgression studies. Molecular markers tightly linked to the resistance genes were utilized in the present study. So far pyramiding six genes (Gm1+Gm4+xa13+Xa21+Pi9+Pi54) has been completed. Pyramiding with additional two genes(Xa33, Xa38) are in progress.
A database comprising of the rice varieties released from a public institution, Tamil Nadu Agricultural University (TNAU),Coimbatore, India. Backed by MS-SQL, and ASP-Net at the front end, this database provide information on both quantitative and qualitative descriptors of the rice varities inclusive of their parental details. Enabled by an user friendly search utility, the database can be effectively searched by the varietal descriptors, and the entire contents are navigable as well. The database comes handy to the plant breeders involved in the varietal improvement programs to decide on the choice of parental lines. TNAURice is available for public access at (http://www.btistnau.org/germdefault.aspx).
Millets are small seeded annual grasses and grow well, under the marginal conditions of soil fertility and moisture, which provide staple food for millions of people. Breeding research in millets, habitually engages different species, cultivars, and varieties. This makes an immense challenge to maintain the different varieties and their identification characters. On account of this fact, the MilletDB clearly brings out the variations of different morphological traits of the TNAU released varieties. These database covers information on various qualitative and quantitative traits on maize, sorghum, cumbu, panivaragu, samai, tenai, kuthiraivali, ragi and varagu. MilletDB is an Internet-accessible database, which is designed by using the front-end language PHP and back-end as MySQL and is equipped with extensive search options. It is a user-friendly database and made publicly available, to improve the research and development of millet crops by making the wealth of available millet varieties.
The oilseed database brings out the variations in different morphological traits of the TNAU released varieties. The databases cover information on various qualitative and quantitative traits on oilseeds ( Groundnut, sesame and sunflower )varieties. Oilseed database is an Internet-accessible database, which is designed by using the front-end language PHP and back-end as MySQL and is equipped with extensive search options. These are user-friendly databases and are publicly available http://www.btistnau.in).
Millets are small seeded annual grasses and grow well, under the marginal conditions of soil fertility and moisture, which provide staple food for millions of people. Breeding research in millets, habitually engages different species, cultivars, and varieties. This makes an immense challenge to maintain the different varieties and their identification characters. On account of this fact, the MilletDB clearly brings out the variations of different morphological traits of the TNAU released varieties. These database covers information on various qualitative and quantitative traits on maize, sorghum, cumbu, panivaragu, samai, tenai, kuthiraivali, ragi and varagu. MilletDB is an Internet-accessible database, which is designed by using the front-end language PHP and back-end as MySQL and is equipped with extensive search options. It is a user-friendly database and made publicly available, to improve the research and development of millet crops by making the wealth of available millet varieties.
Non-coding RNAs (ncRNAs) are functional RNA molecules that are transcribed from DNA but are not translated into proteins. In general ncRNAs function to regulate gene expression at the transcriptional and post-transcriptional level. There are about 2700 noncoding RNA families that are classified for rice in RFAM database. Major ones being, 5s rRNA, transfer RNA, plant signaling etc. Sequence based query tool have been developed which implements a blast like algorithms to search and display the database sequences having identical or similar sequences with other details such their RNA family ID, accession number description, sequence range etc. This tool includes information about 5 major families and developed using PHP.
The databases on SSR markers in rice, wheat and adzuki bean are being developed. Markers data was mined from published literatures and online databases. A total of 196 SSR motifs and their primer sequences, which was used for constructing linkage map of adzuki bean, were retrieved from NIAS Genebank. Followed by, we have developed an initial in‐house database (named VigSSR) with the retrieved SSR markers of the adzuki bean. The database is developed with three different search options viz., detailed search, quick search and reference search. The users could retrieve the information on (i) types of motifs (ii) forward and reverse primers (iii) annealing temperature and (iv) expected product size. VigSSR was developed using MySQL as backend tool. PHP and CSS were used for developing user interface. Developing database on polymorphic SSR markers in rice and wheat is in progress.
Cotton is a major field crop in many countries, constituting a valuable cash crop for many small holders in developing countries. It is an important industrial crop in both developed and developing countries. Cotton is known to suffer from number of diseases caused by fungal, bacterial and viral origins. There is now more relative importance for different diseases may be air borne foliar diseases like grey mildew, alternaria leaf spot, myrothecium leaf spot, bacterial blight, rust, cotton leaf curl virus..
Recent breakthrough in structural and bioinformatics strategies have enabled greater integrated understanding of complex plant-pathogen interactions. The study on modelling and docking of pathogenic protein and host proteins with and anti-microbial peptides /new lead molecules have shown to possess antimicrobial activity. As results, the promising lead molecules may serve as one of the potential fungicide for cotton fungal disease.
In order to keep pace with increasing human population growth, rice yields will need to double by 2050. A major obstacle in achieving optimal yields is the occurrence of rice diseases caused by numerous fungal, bacterial, and viral pathogens. For example, Rice blast, sheath blight, and bacterial blight are the three most devastating diseases in Oryza sativa. Rice blast epidemics often result in between 10% and 30% yield loss, which on a lower estimate, would be enough rice to feed 60 million people for 1 year. Bioinformatics studies on the devastating plant diseases helps to understand the mechanism of action in effect of cost and time.
Computational strategies will be developed to understand the specificity and selectivity of proteins and their interactions in the major crop diseases. Efforts will be laid to design inhibitors to resist plants from various pathogens. Further, comparative genomic studies will be performed to assign protein function and structure for putative proteins which may have role in plant diseases.
| S.No | Project Title | Principal Investigator | Period |
|---|---|---|---|
| 1 | Development of database and software tools for identifying polymorphic SSR markers in plant genomes | Dr. M. Jayakanthan | 2015 – 2018 |
| 2 | Deciphering Long Noncoding RNAs and Database development in Rice | Dr. N. Saranya | 2015 - 2018 |
| 3 | Functional annotation of hypothetical proteins present in Xanthomonas oryzae pv. oryzae for prioritizing the targets against Bacterial blight | Dr. M. Jayakanthan | 2018 – 2020 |
| S.No | Project Title | Principal Investigator | Period | Amount |
|---|---|---|---|---|
| 1 | Whole genome sequencing of contrasting genotypes of blackgram to identify novel genes/alleles and pathways contributing to disease resistance against MYMIV | PI:Dr.M.Jayakanthan Co-PI:Dr. M. Sudha |
2018 – 2019 | 1.5 lakhs |
| 2 | Genome-wide identification of rice long non-coding RNAs responsive to Xanthomonas oryzae infection | Dr.N.Saranya Co-PI:Dr.A.Ramanathan | 2018 - 2019 | 1.5 lakhs |
| 3 | DNA finger printing and barcoding of varieties hybrids and pre-release cultures for varieties/hybrids identification and notification | PI:Dr.N.Kumaravadivel | 2018 – 2019 | 11 lakhs |
| S.No | Project Title | Principal Investigator | Period | Amount |
|---|---|---|---|---|
| 1 | Development of shoot fly resistance sorghum varieties suitable for Tamil Nadu through marker assisted selection. | PI:Dr. N. Kumaravadivel | 2015 – 2020 | 66.79 lakhs |
| 2 | Enrichment of nutritional quality in maize through molecular breeding | PI:Dr. N. Senthil | 2015 - 2020 | 88.69 lakhs |