научная статья по теме MARKER ASSISTED EVALUATION OF MORPHOLOGICAL AND GENETIC ATTRIBUTES OF SUB-POPULATIONS OF NILI-RAVI BUFFALO: A VULNERABLE DAIRY TYPE RIVERINE BREED OF INDIA Биология

Текст научной статьи на тему «MARKER ASSISTED EVALUATION OF MORPHOLOGICAL AND GENETIC ATTRIBUTES OF SUB-POPULATIONS OF NILI-RAVI BUFFALO: A VULNERABLE DAIRY TYPE RIVERINE BREED OF INDIA»

ГЕНЕТИКА ЖИВОТНЫХ

УДК 575.1:599.735.5

MARKER ASSISTED EVALUATION OF MORPHOLOGICAL AND GENETIC ATTRIBUTES OF SUB-POPULATIONS OF NILI-RAVI BUFFALO: A VULNERABLE DAIRY TYPE RIVERINE BREED OF INDIA

© 2015 P. Kathiravan1, 3, P. K. Dubey1, 4, S. Goyal1, 5, B. P. Mishra1, 6, G. Singh2, S. M. Deb2, D. K. Sadana1, B. K. Joshi1, and R. S. Kataria1

National Bureau of Animal Genetic Resources, GTRoad By-Pass, Karnal-132001 Haryana, India

e-mail: katariaranji@yahoo.co.in 2Central Institute for Research on Buffaloes, Sub-campus Nabha, Punjab, India 3Animal Production and Health Section, International Atomic Energy Agency, Vienna, Austria 4Immune regulation, WPI-IFREC, Osaka University, Osaka, Japan 5RIKEN Centre for Life sciences, Yokohama, Japan 6Division of Animal Biotechnology, Indian Veterinary Research Institute, Izatnagar-243122, Bareilly, U.P., India

Received September 2, 2014

In the present study, we report the distribution of true to type and atypical Nili-Ravi buffalo, a vulnerable dairy type riverine breed of North India and its underlying genetic structure. Out of total investigated buffaloes 73.5% had bilateral wall eyes while 5.4% had unilateral wall eyes and 21.1% had no wall eyes. 41.15% of Nili-Ravi buffaloes maintained in the breeding farm were having typical true to the type characteristics (both eyes walled, white markings in forehead, muzzle/chin, all the four legs and tail) while only 28.5% of Nili-Ravi buffaloes were true to the type under field conditions. Genotypic data were generated in four groups of Nili-Ravi buffalo (FMTNR - Typical Nili-Ravi from farm; FMANR - Atypical Nili-Ravi from farm; FDTNR -Typical Nili-Ravi from field; FDANR — Atypical Nili-Ravi from field) at 16 microsatellite loci. Comparative genetic analysis of various groups of Nili-Ravi buffaloes with Murrah revealed significant between group differences with an estimated global FST of 0.063. Pair-wise FST values ranged from 0.003 (between FDTNR and FDANR) to 0.112 (between FMTNR and FDTNR). Phylogenetic analysis and multi-dimensional scaling revealed clustering of FDTNR and FDANR together while FMTNR and FMANR clustered separately with Murrah in between farm and field Nili-Ravi buffaloes. Based on the results, the paper also proposes three pronged strategy for conservation and sustainable genetic improvement of Nili-Ravi buffalo in India.

DOI: 10.7868/S001667581507005X

Livestock populations have been evolved over centuries due to sustained natural and artificial selection with adaptation to local agricultural production systems and agro-ecological environments. The domestic animal genetic resource represents a unique resource to respond to the present and future needs of livestock production. According to "The state of the World's Animal Genetic Resources for Food and Agriculture" [1], a total of 7616 breeds have been recorded in Global Databank, ofwhich 6536 are local breeds and 1080 are transboundary breeds. Unfortunately, this enormous livestock diversity is shrinking at a rapid pace. About 9% of livestock breeds are extinct and about 20% are at risk of extinction [2]. This figure may still be higher as the risk status of about 36% of breeds is not known. Among the domesticated populations, it is estimated that 1 to 2 breeds are lost every week and the impact of these losses on global or local diversity remains undocumented. In India, the domestic animal diversity is represented by 30 defined breeds of cattle, 10 breeds of buffaloes, 42 sheep, 20 goat, 7 camel, 6 horse, 18 poultry and a few types of pigs, yak, mith-

un, quails, geese and others. Among these different species, the domestic water buffalo is an economically important species not only in India but in many Asian and Mediterranean countries [3]. Asian buffalo (Bubalus bubalis) includes two sub-species known as the river and swamp types, which differ by karyology, morphology and the purpose for which they are reared [4]. Buffalo rearing in India is primarily oriented towards milk production but also include draught animal power especially for transport and haulage in hilly areas and for wet field operations in paddy cultivated regions. Indian riverine buffaloes are represented by ten well recognized breeds viz. Murrah, Nili-Ravi, Jaf-farabadi, Mehsana, Surti, Bhadawari, Nagpuri, Pan-dharpuri, Marathwada, and Toda. The genetic diversity ranges from high yielding dairy type (Murrah, Nili-Ravi, Mehsana, etc.) to extensively managed semiwild type (Toda) animals.

Nili-Ravi is one of the best dairy type river buffalo breeds in the Indian sub-continent alongside Murrah, Mehsana and Jaffarabadi. The original breed tract of Nili-Ravi buffalo was the erstwhile undivided central

Punjab and presently the buffaloes are distributed in both sides of Punjab in India and Pakistan. Nili-Ravi is found in Ferozepur, Amritsar, and Gurdaspur districts of Indian side of Punjab. Nili-Ravi is one of the very few trans-boundary buffalo breeds and has been exported to many countries like China, Philippines [5], Brazil, Trinidad, Bulgaria, etc. [6]. Nili-Ravi is better adapted to the local agro-climatic condition of Punjab, resistance to the tropical diseases and thrives well under poor management conditions. This breed gives better performance in the irrigated area where they have an easy access to water and plenty of green fodder. A recent survey estimated population size of Nili-Ravi type of buffalo in its breed tract to be around 0.2 million [7] which has declined further after that. The morphological characteristics of Nili-Ravi buffaloes have undergone changes over the years and true to the type Nili-Ravi buffaloes have declined drastically. Different types of Nili-Ravi buffaloes with varying morphological and phenotypic characteristics (deviation from typical wall eye and five white markings) are available in farmers' fields. In order to genetically improve and conserve Nili-Ravi buffalo, a nucleus breeding farm was established at Regional station of Central Institute of Research on Buffalo at Nabha, Punjab, India. The nucleus farm assists conservation of Nili-Ravi buffaloes along with its breed improvement by dissemination of quality semen from selected Nili-Ravi bulls through progeny testing program. The present study aims (i) to quantify the distribution of true to type Ni-li-Ravi and atypical Nili-Ravi buffaloes in farm and field conditions (ii) to evaluate genetic characteristics by estimating microsatellite allele distribution and genetic differentiation of different groups of Nili-Ravi buffalo and (iii) to devise a strategy for increasing typical Nili-Ravi buffaloes and to conserve them under farm and field conditions.

MATERIALS AND METHODS

Morphological features of typical and atypical Nili-Ravi

Information on morphological characteristics especially wall eyes (one or both eyes), white markings on forehead, muzzle, chin, forelimbs, hind limbs and tail were recorded on 615 Nili-Ravi buffaloes maintained under farm (Central Institute for Research on Buffaloes, Regional Station, Nabha) and farmers' field conditions. This included 344 adult buffaloes and 148 young calves from farm and 123 adult buffaloes from field. Those buffaloes with both eyes walled, white markings on all the four limbs, forehead, muzzle/chin and tail were considered as typical Nili-Ravi and buffaloes which lacked one or more of these features were considered as atypical Nili-Ravi. All the features listed were tested for significance of variation between farm and field animals by chi square test.

Blood samples and microsatellite genotyping

Blood samples were collected from 80 unrelated Nili-Ravi buffaloes, 40 each from farm and farmers' fields respectively. Samples were collected in such a way so as to include at least 20 buffaloes with typical and atypical morphological characteristics in each group. Genomic DNA was extracted by standard phenol-chloroform method [8]. A total of 16 heterologus bovine microsatellite markers viz. BM1818, ILSTS19, ILSTS25, CSSM33, ILSTS36, HEL13, ILSTS28, ILSTS58, ILSTS61, CSSM57, ILSTS52, ILSTS30, ILSTS33, ILSTS60, CSSM45, and ILSTS26 were utilized to genotype the sampled individuals. The forward primer for each locus was labeled with one of the four fluorescent dyes FAM, HEX, NED, and PET (Applied Biosystems, USA). Polymerase chain reaction and genotyping of samples were performed following the procedure as described earlier [9]. The al-lele size data for each sample was extracted using GENEMAPPER software.

Statistical analysis

Microsatellite genotype data of 80 Nili-Ravi buffaloes in four groups and genotypic data on 14 markers of Murrah buffalo were utilized for comparative statistical analysis. Briefly, basic diversity indices like observed number of alleles, allele frequency, FIS, observed and expected heterozygosity were calculated using MICROSATELLITE ANALYZER (MSA) version 3.15 [10]. Pair-wise Nei's genetic distance, global and pair-wise FST were calculated using MSA. Pair-wise Nei's distance was utilized to construct dendrogram and radial tree following Neighbor Joining algorithm using PHYLIP version 3.5. To understand the genetic relationship of different groups of Nili-Ravi buffalo within a geometric space, multidimensional scaling (MDS) analysis was performed using SPSS version 13.0. Genotype assignment following Bayesian and frequency based approaches were performed as implemented in GeneClass 2 software [11]. Genetic structure was further investigated using Bayesian clustering approach as implemented in STRUCTURE program [12]. Individual animals were assigned to different inferred clusters based on their multilocus genotypes. Admixture model was used with a burn in period of 50000 iterations and 100000 Markov Chain Monte Carlo (MCMC) repetitions to calculate the probable number of genetic clusters. The standardized second order rate of change in Ln P(D) i.e. delta K was calculated in order to identify the best 'K' as reported previously [13].

RESU

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