Apoorva Arora

Indian Institute of Wheat and Barley Research

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Indu Sharma

University of Southern California

Ratan Tiwari

Indian Institute of Wheat and Barley Research

Neeraj Dilbaghi

Guru Jambheshwar University of Science and Technology

Ramesh Kumar Sharma

Indira Gandhi Centre for Atomic Research

Karnam Venkatesh

Indian Institute of Millets Research

M. S. Saharan

Indian Agricultural Research Institute

V. K. Singh

Sardar Vallabhbhai Patel University of Agriculture & Technology

Pradeep Kumar

National Bureau of Plant Genetic Resources

Indu Sharma

Savitribai Phule Pune University

Sushil Kumar

Medical College of Wisconsin

Cooperative Institutions

Indian Institute of Wheat and Barley Research

Indian Council of Agricultural Research

Punjab Agricultural University

Chaudhary Charan Singh Haryana Agricultural University

Central Research Institute for Dryland Agriculture

Krishi Vigyan Kendra, Ghatkhed Amravati

Govind Ballabh Pant University of Agriculture and Technology

Chaudhary Charan Singh University

Assam University

Maharishi Markandeshwar University, Mullana

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Genetic variability among sheep breeds by random amplified polymorphic DNA-PCR

Kumar Shivam Atul P. Kolte B. R. Yadav Sushil Kumar Apoorva Arora

Random amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR) was employed to assess the genetic variability and phylogenetic relationship among six breeds of sheep, viz., Malpura, Kheri, Chokla, Garole and two crossbreds Avikalin and Bharat Merino. Twenty-four individuals from each breed/crossbred were selected randomly. Initially, 40 primers were screened, of which 16 were found polymorphic and utilized for estimation of genetic variability and phylogenetic relationship among the breeds. The genetic distance was found highest between Malpura and Garole (D=0.1428), and the lowest (D=0.0612) between Avikalin and Chokla. However, the genetic identity was observed highest (I = 0.9406) between Avikalin and Chokla and the lowest (I = 0.8669) between Malpura and Garole. The Kheri sheep was found close with Chokla (D=0.0741), followed by Malpura sheep (D=0.0902) based on genetic distance. The phylogenetic tree also showed that Avikalin and Chokla are more close, whereas Malpura and Garole are distant to each other. The present study suggested that RAPD-PCR can be used successfully for analyzing genetic variation and phylogenetic relationship among breeds of sheep.

Genetic distance

Genetic relationship

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Population structure and genetic diversity among Indian wheat varieties using microsatellite (SSR) markers

Australian Journal of Crop Science (2014)

Apoorva Arora Sushila Kundu Neeraj Dilbaghi Indu Sharma Ratan Tiwari

Platform for improvement of crop plants is largely setup by the genetic variability studies. The current work was performed to assess the status of genetic diversity among 319 Indian wheat varieties so that they can be used effectively for future breeding practices. Out of 30 markers applied, 50 polymorphic fragments generated from16 polymorphic primers were selected for diversity studies. Jaccob's similarity model and Bayesian analysis were performed using software package DARwin 5.0 and STRUCTURE 2.3.3 respectively. Grouping obtained from both the analysis were found to be consistent and was helpful in analyzing the distribution of genetic variability across different centres of wheat research in India. The total genetic diversity for all groups (Ht) was 0.38888 and within groups (Hs) was 0.3130 indicating less genetic variability among sub-populations (Gst=0.19). Gene flow (Nm) was also found to be relatively high with a value of 2.0654. Genetic variability parameters computed using POPGENE 1.32 (81%) and AMOVA (78.5%) revealed that the genetic diversity was mainly contained within the populations. This study can complement the breeding programs for identification of parental combinations effectively to maintain maximum genetic variability in progenies.

Genetic Variability

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Marker assisted diversity analysis and creation of spring wheat genotypic panel for association mapping

INFLIBNET (2014)

Apoorva Arora

Association mapping

Association (psychology)

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Quantifying stripe rust reactions in wheat using a handheld NDVI remote sensor

Gates Open Res (2019)

Apoorva Arora Ramesh Kumar Sharma M. S. Saharan Karnam Venkatesh Neeraj Dilbaghi

Stripe rust

10.21955/gatesopenres.1115856.1

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Evaluating vegetation indices for precision phenotyping of quantitative stripe rust reaction in wheat

Apoorva Arora Karnam Venkatesh Ramesh Kumar Sharma M. S. Saharan Neeraj Dilbaghi

Wheat production and productivity is widely affected by stripe rust infection. Resistance to this disease governed by additive-gene effect is one of the recent strategies being adopted in wheat breeding programme. While the present phenotyping approaches for scoring, the plants reaction often vary from person to person. A novel, repeatable and reliable approach can enhance the efficiency of determining genetic variability in large number of genotypes. Taking into consideration the emerging non-invasive tools to assess the physiological status of plants. The present investigation was undertaken to explore utility of optical measurements to variation of the stripe rust reaction in wheat genotypes. One hundred and twenty Indian wheat genotypes representing released varieties, elite genotypes, genetic stocks, and local landraces were used for the study. The stripe rust epidemics in the field were initiated with Yr27-virulent P. Striiformis race 78S84. The Area under the Disease Progress Curve (AUDPC) values were calculated from four weekly visual estimates of disease severity which ranged from 0 to 2077. Normalized difference vegetation index (NDVI), Chlorophyll content index (CCI) and Plant Canopy temperature (CT) were recorded twice, 7 days apart, when disease severity approached maximum values on the susceptible controls. The results indicate that the temporal ground-based NDVI is most effective in studying quantitative rust reaction with a significant regression coefficient (r2=0.63) between AUDPC and NDVI data followed by chlorophyll content index (r2=0.37) and canopy temperature (r2=0.21).

Rust (programming language)

Stripe rust

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Memory for Speech under Difficult Listening Conditions

Apoorva Arora

Memory for speech relies on the processing of the speech signal as it is received. With aging, working memory and processing speed decline making comprehension of speech, and hence its memory, difficult. Older adults overcome this challenge by utilizing their preserved linguistic knowledge as long as the total by processing burden for speech is below a threshold of resource overload. An experiment is presented here in which the processing burden for comprehension of spoken sentences in increased by increasing the speech rate and adding syntactic complexity. The recall accuracy for these sentences is compared between young and older adults to examine the possible compensatory mechanisms employed by older adults in the face of such challenges in their everyday lives.

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Genotypic characterization of elite Indian wheat genotypes using molecular markers and their pedigree analysis

Australian Journal of Crop Science (2013)

Rekha Malik Ratan Tiwari Apoorva Arora Pradeep Kumar Sonia Sheoran

Forty eight elite wheat genotypes including popular cultivars of India were analysed using 56 SSR and 12 STS markers. These markers were robust markers chosen out of 400 SSRs and 100 STS markers, showing good polymorphism and representing each chromosome of wheat genome. Estimated values of coefficient of parentage (COP) for the pair-wise combinations of 48 genotypes ranged from 0.0 to 0.58 with an average of 0.047. The average number of alleles per locus was 2.42 and average polymorphism information content of 0.469. Cluster analysis clearly demonstrated the bread wheat AVTs and popular genotypes in one group while durums, dicoccums and triticale in a separate group. Our results provide information for the discriminative SSR/STS markers for varietal characterization and genetic variation available in at molecular level in Indian wheat and enhance genetic variability in bread wheat breeding program.

Triticale

Common wheat

Plant Breeding

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