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SCARNA3 in one contig and CEP170, PLD5 in another contig (Dikmen et al., 2013). Therefore, SNPs could be proved to be useful in genetic selection and for ...
Chapter-16

Genomic Technologies: A Way Forward for Learning Climate Resilience through Cellular Responses to Heat Stress Varij Nayan, Suneel Kumar Onteru and Dheer Singh Molecular Endocrinology Laboratory, Division of Animal Biochemistry, National Dairy Research Institute, Karnal-132001 (Haryana) INDIA In today’s world, we are certainly living in an era of strange paradox, where economic development and impact of climate change to the planet earth have been burning issues for all the stakeholders, that is, the whole humanity. The Intergovernmental Panel on Climate Change (IPCC) projected that global average surface temperature may increase in between 1.8° C and 4.0° C by 2100. With increases of 1.5° C to 2.5° C, approximately 20 to 30 per cent of plant and animal species are expected to be at risk of extinction (FAO, 2007) with severe consequences for food security in developing countries. India, in this scenario, is faced with dual challenge of sustaining its rapid economic growth while dealing with the global climate change threat. What is the best way forward then? Both the proponents and opponents have to decide what the right balance between each one’s priorities is? According to the FAO, the animal agriculture sector that includes production of feed crops, fertilizer manufacturing, meat, eggs, and milk, is responsible for 18% of all greenhouse gases (GHGs) emissions, measured in CO2 equivalent (Steinfeld et al., 2006). On the other hand, it is also likely that there are severe negative impacts of climate change on livestock (Upadhyay et al., 2008). The climate change can heighten the vulnerability of livestock systems and reinforce the existing factors that affect the livestock production systems. For farmers, losing livestock assets could prompt them to fall into chronic poverty and an adverse effect on their livelihoods. Animal agriculture is thus, both a victim of and a contributor to climate change. Both of these scenarios provide renewed and emerging challenges to animal scientists. They have to work both on GHGs mitigation strategies as well as to strengthen the adaptive capacity and production of climate resilient livestock.

Climate resilient livestock and heat stress Animal scientists have the impending challenge of enhancing the resilience of Indian livestock to climatic variability and climate change through development and application of improved production and risk management technologies. Abiotic stress is generally used to describe non-living factors such as intense solar radiation in Climate Resilient Livestock & Production System

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summer, extreme temperature, humidity, drought, flood, high winds, and other natural disasters, which adversely affect living organisms. As plants are affected by abiotic stress, animals too are vulnerable to them. Heat stress (HS) is the most stressful of all abiotic stressors in animals and is caused due to overexposure or overexertion in extreme environmental temperature. Temperature is a critical abiotic factor affecting organisms on ecological, organismal, cellular and molecular levels (Hochachka and Somero, 2002). Thermal stress is a unique and complex phenomenon that brings about numerous challenges beyond the animals baseline homeostatic mechanism causing alterations of the normal physiological mechanisms thus elicits a stressful response. At the cellular level, acute environmental change initiates the “heat shock” or cellular stress response. Changes in gene expression associated with a reaction to an environmental stressor involves acute responses at the cellular level (in most if not all cells) as well as changes in gene expression across a variety of organs and tissues associated with the acclimation response.

Heat stress and its effects on animal production There is a huge negative impact of heat stress on dairy industry every year. Heat stress (HS) shows negative impacts on all aspects of dairy cattle and buffalo reproduction (Rensis and Scaramuzzi, 2003; Hansen, 2007; Marai and Habeeb, 2010), milk production (West, 2003) and immune function (Elvinger et al., 1992). Length of oestrous cycle and degree of expression of oestrus in buffaloes are affected by various factors, such as season, climate, photoperiod, temperature and nutrition (Beg and Toty, 1999). Heat stress can have large effects on most aspects of reproductive function in mammals. These include disruptions in spermatogenesis and oocyte development, oocyte maturation, early embryonic development, foetal and placental growth and lactation. These deleterious effects of heat stress are the result of either the hyperthermia associated with heat stress or the physiological adjustments made by the heat-stressed animal to regulate body temperature. Many effects of elevated temperature on gametes and the early embryo involve increased production of reactive oxygen species. Heat stress was found to suppress aromatase activity in granulosa cells and decrease the estradiol concentrations in the follicular fluid and plasma of dairy cows (Badinga et al., 1993). Heat stress inhibits the FSH-R signalling pathway in the granulosa cells of growing follicles, causing decreased estrogen levels, which are known to produce increased follicular atresia. India is losing 2% of the total milk production, amounting to a whopping over Rs 2,661 crore due to rise in heat stress among cattle and buffaloes because of the global warming”. Heat stress downs the milk secretion by up regulating the activity of milk born negative feedback regulatory system (Silanikove et al., 2000).

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Genomic technologies for unravelling heat and abiotic stress towards climate resilient animals Heat and abiotic stress tolerance in animals is essential for improving productivity and prevents loss. Homeostasis, a set-value for metabolism under optimal conditions, is resultant of external stress factors viz. climatic, biotic, and nutrient imbalances. During the past decade, genomics technologies have emerged and may be useful in addressing, in an integrated fashion, the multigenicity of the animal abiotic stress response through deciphering of genome sequences; cell-, organ-, tissue- and stressspecific transcript collections; transcript, protein and metabolite profiles and their dynamic changes; protein interactions etc. Genomic technologies that can be used for studying abiotic stresses such as heat stress in dairy animals is illustrated in the figure elsewhere in the text and can include the followings:

Gene discovery An important genomic approach to identify abiotic stress-related genes is based on ESTs generated from different cDNA libraries representing abiotic or heat-stress treated tissues collected at various stages of development or other physiological and pathological conditions. NCBI dbEST release 130101 summarizes about the ESTs for each organism and can be accessed at http://www.ncbi.nlm.nih.gov/genbank/dbest/ dbest_summary/. For buffaloes, 1,857 ESTs are evident compared to 1,559,495 for cattle (as on 1st January, 2013). Therefore, specific sequencing programs based on cDNA libraries from heat –stress affected animal tissues and organs at many developmental stages are required to enrich dairy animals especially buffaloes EST datasets with stressresponsive genes.

Transcript profiling Genomic technological approaches such as MPSS, SAGE, quantitative real time PCR (qPCR) and array-based transcript profiling technologies allow us to perform an assessment of high-throughput expression of thousands of genes in control and stressor-treated tissues at various stages. Insights into gene expression patterns and functions coupled with stress tolerance can be explored by EST-based cDNA arrays. Gene expression profiling using cDNA macroarrays or microarrays can also be novel approaches to identify higher number of transcripts and pathways related to stress tolerance mechanisms. Studying co-regulation/ regulon identity for condition-specific coregulation of overlapping sets of genes is also required to gain further insights. It has to be noted that genes reacting to a particular stress differ between organisms, species, breeds and even genotypes. It happens because certain organisms, breeds or genotypes Climate Resilient Livestock & Production System

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have efficient stress signal perception and transcriptional changes that can lead to successful adaptive response and adaptations and eventually further tolerance.

Genome-wide transcriptome and methylome studies Identification of key molecules, regulators based on gene expression patterns related to multi-stress interactions can be achieved by genome-wide transcriptome analysis. This may prove an efficient tool for identifying biomarker for a particular abiotic stress. It has the ability to identify hundreds of genes encoding transcription factors that are induced or repressed by plethora of environmental stressors. Therefore, molecular cross-talk of gene regulatory networks among abiotic and heat stress treatments could be revealed.

Genome wide association studies (GWAS) To reduce the magnitude of heat stress, we can opt to select animals that are genetically resistant to heat stress. In many species of livestock, thermo-tolerant strains or breeds have been developed (Hansen, 2011). In this context, GWAS can be used to identify genetic markers that can be used to select animal breeds and species having heat tolerance or resistant to deleterious effects of heat stress.  For instance, GWAS can be used to identify to identify quantitative trait loci (QTL) and single nucleotide polymorphisms (SNPs) associated with regulation of rectal temperature. Quantitative trait loci (QTL) can be identified for lowly-heritability traits and they used to improve reliability of genetic estimates despite the gain in reliability being less than the more heritable traits (Cole, 2011). In addition, GWAS can be useful for understanding the underlying biology of a trait by identifying candidate genes in physical proximity to QTL  (Cole et al., 2011; Berry et al., 2012). One such study has been performed in Holstein cows and identified these genes as part of the QTL – SNORA19, RFWD2 and SCARNA3 in one contig and CEP170, PLD5 in another contig (Dikmen et al., 2013). Therefore, SNPs could be proved to be useful in genetic selection and for identification of genes involved in physiological responses to heat stress.

Hapmap studies Haplotype refers to a combination of adjacent genetic markers that tend to be inherited together. Association analyses of haplotypes for heat stress can provide better reliability for an associated QTL region. Such haplotypes have been stored in hapmap projects of several species including farm animals e.g. in the international bovine hapmap (IBHM) project study. A haplotype in HSP70A1A has been identified to be associated with increased risk during heat stress in Chinese Holstein cattle (Xiong et al., 2013). 180

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Next generation sequencing (NGS) approaches Newer genomics approaches like next-generation sequencing (NGS) hold great promise for accelerating search for genes related to heat tolerance-related traits. With the advent of NGS technology, the sequence-based transcriptome analysis is in many ways considered superior to microarrays since the sequencing-based method is applicable in real time, digital and highly accurate. The application of NGS technologies to gene expression analysis has catalysed the development of techniques like Digital Gene Expression TAG (DGE-TAG), DeepSAGE and RNA-Seq. RNA-Seq is a newer approach to transcriptome profiling that uses deep-sequencing technologies. RNA-seq

Figure: Genomic technologies for unravelling heat and abiotic stress towards climate resilient animals

based on NGS technologies has several advantages for investigating transcriptome fine structure including detection of allele-specific expression and splice junctions (Malone and Oliver, 2011) and may allow direct high-throughput sequencing of RNA from the heat-stress challenged tissues in different conditions. It can help to identify candidate genes associated with climate resilience. NGS has been used to study variants in cattle to identify genes that contribute to heat tolerance, osmotic shock tolerance and other disease resistance.

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Perspectives on our experiences on heat stress in dairy animals To understand the cellular responses upon heat-stress and to improve our insights into global gene expression in heat stressed dairy animals, a study was conducted in our laboratory to analyse the global gene expression profiling of peripheral blood leukocytes of indigenous cattle (Tharparkar). The genes that were found to be differentially expressed were further validated in cattle (Tharparkar and Sahiwal) and buffaloes (Murrah). The results showed that heat stress affect expression of a significant numbers of genes in peripheral blood nuclear cells of diverse biological functions. Further analyses are required to understand their functional role in livestock during heat stress.

Conclusion Comparative analysis of the response to abiotic (e.g. heat) stresses among diverse tolerant organisms, breeds and species can lead to the identification of evolutionarily conserved and unique stress defence mechanisms. Role of computational methods and integrated omics technology including protein dynamics and metabolome landscape in a systems approach will be instrumental in future. Challenges to be met for integrated knowledge of animal abiotic stress responses and tolerance in changing climate scenario will include identification of sensors and signalling pathways, understanding the molecular basis of interplay among stresses and developmental processes/stages, examining long-term responses under a plethora of abiotic stress conditions in nature and simulating the farm conditions. The road ahead to animal agriculture’s adaptation to climate change should therefore integrate technological advances for climate resilient animals, policy, and finance options toward lowering emission and promoting inclusive growth.

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Cole, J.B., Wiggans, G.R., Ma, L., Sonstegard, T.S., Lawlor, T.J., Crooker, B.A., Tassell, C.P.V., Yang, J., Wang, S., Matukumalli, L.K.  and  Da, Y. 2011. Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows. BMC Genomics, 12: 408-465.  Dikmen, S.,  Cole, J.B.,  Null, D.J. and Hansen, P.J. 2013. Genome-wide association mapping for identification of quantitative trait loci for rectal temperature during heat stress in Holstein cattle. PLoS One,  8(7): e69202. Elvinger, F., Natzke, R.P. and Hansen, P.J. 1992. Interactions of heat stress and bovine somatotropin affecting physiology and immunology of lactating cows. J. Dairy Sci., 75: 449-462. FAO, 2007. Adaptation to Climate Change in Agriculture, Forestry, and Fisheries: perspective, framework and priorities. FAO, Rome. Hansen, P.J. 2007. Exploitation of genetic and physiological determinants of embryonic resistance to elevated temperature to improve embryonic survival in dairy cattle during heat stress. Theriogenology, 68S: 242-249. Hansen, P.J. 2011. Heat stress and climate change. In: Moo-Young M, (ed.), Comprehensive Biotechnology, Second Edition, vol. 4: 477-485. Amsterdam: Elsevier. Hochachka, P.W. and Somero, G.N. 2002. Biochemical Adaptation: Mechanism and Process in Physiological Evolution. Oxford University Press New York. Malone, J.H. and Oliver, B. 2011. Microarrays, deep sequencing and the true measure of the transcriptome. BMC Biol., 9: 34. Marai, I.F.M. and Habeeb, A.A.M. 2010. Buffaloes’ reproductive and productive traits as affected by heat stress. Tropical and Subtropical Agroecosystems, 12: 193-217. Rensis, F.D. and Scaramuzzi, R.J. 2003. Heat stress and seasonal effects on reproduction in the dairy cow- A Review. Theriogenolog, 60: 1139-1151. Silanikove. 2000. Effects of heat stress on the welfare of extensively managed domestic ruminants. Livestock Production Science, 67: 1-18. Steinfeld, H., Gerber, P., Wassenaar, T., Castel, V., Rosales, M. and de Haan, C. 2006. Livestock’s long shadow: environmental issues and options (Rome: Food and Agriculture Organization of the United Nations, pp. xxi, 86, 88, 99-101.

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