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. 2023 Aug 2;30(9):103747. doi: 10.1016/j.sjbs.2023.103747

Hungarian indigenous Tsigai, a promising breed for excellent heat tolerance and immunity

Putri Kusuma Astuti a,b, Zoltán Bagi a, Lilla Bodrogi c, Tímea Pintér c, Gabriella Skoda c, Roland Fajardo a,d, Szilvia Kusza a,⁎
PMCID: PMC10432802  PMID: 37601567

Abstract

The adverse effects of climate change on sheep farming have become more noticeable in recent decades. Extensive efforts have been made to untangle the complex relationship between heat tolerance, animal health, and productivity, also to identify a resilient and economically suitable breed for selection that can be resilient to future climate change conditions. Using quantitative real-time polymerase chain reaction (qRT-PCR), we observed the seasonal variations in the expression of several important genes related to heat stress and immunity (HSP70, IL10, TLR2, TLR4, and TLR8) in three of the most widely kept sheep breeds in Hungary: The indigenous Tsigai, Hungarian Merino, and White Dorper. We found that the seasonal stressor affected the relative gene expression of all genes in this study. Notably, The Hungarian indigenous Tsigai was the most robust breed adapted to the Hungarian continental (hot summer, cold winter) environment, with excellent thermotolerance and immunity. Furthermore, despite suffering from heat stress in the summer, Hungarian Merino maintained their robust immune system well throughout the year.

Keywords: Gene expression, Ovis aries, Heat stress, TLRs, HSP70, IL10

1. Introduction

Sheep (Ovis aries) have been thought to be one of the most robust livestock that has inhabited a wide range of geographical areas since their domestication due to their exceptional adaptability to various types of diets and tolerance to adverse climatic conditions (Kijas et al., 2009, Sawyer and Jitik Narayan, 2019). However, in these constantly changing climate conditions, sheep are facing additional stressors (Aboul Naga et al., 2021, Mehaba et al., 2021). These challenges have, significant economic consequences as well. Farmers, of the one of the major sheep exporters, New Zealand, for example, have been facing impacts of climate change for more than a decade, which unfavourably determine the profitability of their production (Moris et al., 2009). Heat stress seriously endangers reproduction of certain sheep breeds, and thus appears as a notably risk for efficient sheep management (Van Wettere et al., 2021).

Many aspects of cellular behaviour must change in response to environmental stressors, one of them is the changes in gene expression, which are a fundamental component of stress reactions (de Nadal et al., 2011), as are changes in metabolism, cell cycle progression, protein homeostasis, cytoskeletal architecture, vesicular trafficking, and enzymatic activity modification, which requires more energy expenditure and may compensate animals' growth potential and productive capacity (Richter et al., 2010). Excessive heat exposure triggers multiple cellular responses and induces transcription and translation of several genes and modifications in protein synthesis, such as increased expression of heat shock proteins (HSPs), which function as intracellular chaperones in heat-stressed animals, preventing protein and cell damage (Hooper et al., 2018).

The expression of HSPs is a possible sign of animal response to intense environmental stress. On the basis of their molecular size and similarity in amino acid sequence, HSPs are divided into multiple families (Morage, 2006). Genetic and biochemical research indicates that the 70-kDa heat shock protein (HSP70) family assists in the folding of proteins during translation in the cytoplasm of both prokaryotic and eukaryotic cells and is primarily found in cytosol and nucleus. There are constitutively expressed and inducible versions of HSP70 that are activated by stress stimuli (Hansen, 2004). Its expression is a possible indicator of an animal's capacity to adjust to intense environmental stress; a strong association exists between the development of HSPs and the induction of thermotolerance through the inhibition of stress kinase activity (Dangi et al., 2014).

Despite the disruption in HSP cellular mechanism, the alteration in immune-related gene regulation to either compromise or enhance immune cell activity is also induced during heat shock (Rashmol et al., 2019). Interleukin-10 (IL10) is a major inflammatory regulator released by macrophages, regulatory T cells, dendritic cells and certain epithelial cells (Mallikarjunappa et al., 2020). In sheep, IL10 has been linked to susceptibility to various diseases, such as Peste des petits ruminants virus (PPRV) (Wani et al., 2018), bluetongue virus (BTV) (Sánchez-Vizcaíno et al., 2015), and Haemonchus contortus infection (Glass, 2012). Another one is the Toll-like receptors (TLRs), an extensively studied immune-related gene expressed on numerous cell types, including mucosal surface cells and tissue immune cells (Cruz-Tamayo et al., 2021). TLRs are a collection of evolutionarily conserved pattern-recognition receptors (PRRs) that can detect a variety of pathogen-associated molecular patterns (PAMPs) from a wide range of microorganisms and activate innate immune responses (Janeway and Medzhitov, 2002) and are found to be essential for host resistance to gastrointestinal parasitic infection (Benavides et al., 2016) and classical Scrapie in sheep (García-Martínez et al., 2022).

With the threat of unavoidable climate change and its harmful effects, effort are constantly made to thoroughly comprehend how environmental conditions generated some coping mechanisms in the animal's body. Many studeis has reported the seasonal effect on heat-stress related gene expression in livestock (Singh et al., 2014, Archana et al., 2018, Kumar et al., 2018). Given the scarcity of research on studies of seasonal gene expression in sheep, this study aims to describe the seasonal changes of relative expression level of the following heat stress and heat stress-related genes; HSP70, IL10, TLR2, TLR4, and TLR8 in three sheep breeds reared in Hungary today (Hungarian indigenous Tsigai – indigenous breed in Central-Eastern-Southern Europe; Merino – worldwide spread sheep breed, its dispersal started in the 18th century in Hungary; White Dorper – tropics origin, was introduced in Hungary 10 years ago), with the goal of observing the adaptability of the three breeds to Hungarian temperate climatic conditions, also to contribute with valuable knowledge on biological response to seasonal stressors in sheep.

2. Materials and methods

2.1. Sample collection and location

Total blood sample was initially collected from 24 animals (12 ewes and 12 rams) from three different breeds; Hungarian Merino, Hungarian indigenous Tsigai, and White Dorper, four rams and four ewes per breed. All three breeds represent the major breeds reared in Hungary. Hungarian indigenous Tsigai is a natural breed, belonging to the Tsigai group, indigenous to the Eastern and Central Europe. The Hungarian Merino is the result of Merino breeding in Hungary beginning in the late 17th century and continuing into the 18th century, when it began to be crossed with local breeds. White Dorper is a relatively new breed in Hungary imported from South Africa. All animals included in the study were relatively the same age (2 to 3 years old), body weight (ewes: 45 to 55 kg; rams: 65 to 75), and in excellent health condition with no physical and anatomical abnormalities. The animals were kept in the Kismacs Experimental Station of Animal Husbandry of the University of Debrecen, located at 127 m above sea level (47.58° N and 21.58° E). The average annual maximum and minimum ambient temperature ranges from −7.5 to 28.0 °C with annual precipitation of 550 to 600 mm. The sampling was done in four different seasons in 2019–2020; spring (April), summer (August), autumn (November), and winter (January). All animals received the same management during the experiment period. The breeds were kept and fed together throughout the year, segregated by sex in sheep shed technology, which included an enclosure. The exception was the autumn breeding season, when they were kept in harems. All animals are feed ad libitum a diet which consisted of hay + fodder 0.4 kg/sheep/day, with free access to clean water. Fodder contained 50% corn, 50% oats. During lambing, ewes receive an extra 1 kg of alfalfa hay. 4 weeks before insemination and during insemination, they were additionally given alfalfa silage 1 kg/sheep/day. Selenium lick blocks were available to the animals for 365 days.

Due to the lengthy research period, several animals had to be culled (dead or removed from the farm) from the target individuals during implementation. In spring, all 24 samples were collected, in summer 21 animals (1 Hungarian Indigenous Tsigai ewe, 1 Hungarian Indigenous Tsigai ram, and 1 Merino ram died), in autumn 17 animals (2 Merino ewes died and 2 White Dorper were removed from the farm), and in winter 15 animals (1 Merino ram died and 1 Merino ram was removed from the farm). At the end of the research period, 15 animals had completed four-season sampling; Hungarian Merino (2 ewes and 1 ram), Hungarian indigenous Tsigai (3 ewes and 3 rams), and White Dorper (2 ewes and 4 rams). In every peak season of the year, about 5 ml blood sample was obtained from the jugular vein of the same animals in Tempus™ Blood RNA Tube (Applied Biosystem) and preserved at −70 °C until further analysis.

2.2. Climatological data

The climatic conditions during the sampling day were recorded at every hour. The THI was calculated for each sampling day using the following equation by (Mader et al., 2006). The severity of heat stress in livestock is typically rated using the THI, which ranges from 0 (no stress) to > 84 (extreme heat stress), categorized as follows; no stress (≤67), mild (68–74), moderate (75–78), severe (79–83) and extreme (≥84) (Lewis Baida et al., 2021).

THI=0.8×Tdb+RH100×Tdb-14.4+46.4

Tdb- Dry bulb temperature (°C), RH- Relative humidity (%).

2.3. Quantification of gene expression levels using qRT-PCR

The total RNA was isolated from 3 ml of total blood using Tempus Spin RNA Isolation Kit (Applied Biosystems, USA) following the manufacturer’s instructions and treated with DNase (Quiagen, catalog number: 79256).

RNA quality and quantity assessment were done using a NanoDrop ND-1000 Spectrophotometer, (Thermo Fisher Scientific, Waltham, MA, USA). 300 ng total RNA was reverse transcribed into cDNA with specific primers (Table 1) by the qPCRBIO cDNA Synthesis Kit (PCR Biosystems, London, United Kingdom). The amount of cDNA equivalent to 5 ng of starting total RNA was used as template for each real-time PCR reaction. Forward and reverse primers (Table 1) were created with Primer Express v3.0.1 software (Applied Biosystems, Foster City, CA, USA) and confirmed for target Identity with Primer Blast from the National Center for Biotechnology Information (NCBI) (Ye et al., 2012). Real-Time PCR System, Roche Light Cycler96 was used for qPCR with a 3-min denaturation, followed by 50 cycles of 95 °C for 15 s, 62 °C for 20 s and 72 for 15 s. High resolution melting analysis was performed for each run.

Table 1.

Detailed list of primers for qRT-PCR analysis of target genes.

Target gene GenBank accession Primer Size of amplified product (bp)
HSP70 NC_056073.1 F: GGAGTCGTACGCCTTCAACA
R: CACCTTCTTCTTGTCCGCCT		 85
IL10 NC_056065 F: TGATGCCACAGGCTGAGAAC
R: CAGAAAACGATGACAGCGCC		 110
TLR2 NM_001048231.1 F: ACTCCATCCCCTCTGGTCTC
R: CAGGTCTCTGTTGCCGACAT		 86
TLR4 NM_001135930.1 F: GGTGGAGCTCTATCGCCTTC
R: GGTGCGTTACCCCTGCTATT		 77
TLR8 NM_001135929.1 F: CAGTGAGTTGCCGTTGTTGG
R: GGTGCGTTACCCCTGCTATT		 77
GAPDH NC_040254.1 F: CTGGCCAAGGTCATCCAT
R: ACAGTCTTCTGGGTGGCAGT		 86
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Reactions were set up with PowerUpTM SYBR! Green Master Mix (Applied Biosystems, Foster City, CA, USA) following the manufacturers’ instructions. The amount of cDNA equivalent to 5 ng of starting total RNA was used as template for each real-time PCR reaction.

For relative gene expression studies, one housekeeping gene (glyceraldehyde 3-phosphate dehydrogenase (GAPDH)) was amplified alongside the target genes (IL10, TLR2, TLR4, TLR8, and HSP70). Quantitative PCR was done in triplicate for each sample.

2.4. Statistical analysis

Using the Pfaffl method (Pfaffl, 2001) which requires primer efficiency for both gene of interest (GOI) and housekeeping genes using a standard curve and its cycle threshold (Ct) values and accounts for differences in primer efficiencies during the fold change calculation. The relative quantification of the target gene was determined by comparing the expression levels of GAPDH as a reference gene and GOI of HSP70, IL10, TLR2, TLR4, and TLR8 with Spring season value as the calibrator. The standard deviation (SD) of the relative gene expression was determined by calculating the mean value of the breed population’s gene expression ratio per GOI, which then use to calculate the individual deviation within the breed. LinReg PCR version 2017.0 software (Ramakers et al., 2003) was used to calculate primer efficiency. Further, because the substantial variation in relative gene expression levels makes finding statistically significant differences between groups more difficult, Ct values with less fluctuation were employed to detect statistically significant differences between groups. Ct value data were analyzed by mixed Analysis of variance (ANOVA) with a general linear model (GLM) with repeated measurement in SPSS Version 25 (IBM Corp., Armonk, NY, USA), with breed, sex, season, breed*sex, breed*season, sex*season, and breed*sex*season as the mixed design factors. Mauchly’s test was used to decide the assumption of sphericity in the repeated measurement, and Levene’s test was based on the median for the equality of error variance within season measurement. Further, a post-hoc multiple comparison test was done using the Tukey test for breed and season as the factors. Visualization of the data was done using GraphPad Prism version 8.0.0 for macOS (GraphPad Software, San Diego, CA, USA). The results are shown as the mean ± SD. A difference with p < 0.05 was determined as statistically significant.

3. Results

3.1. Climatological conditions

The climatic data during the sampling day in each season of the year and the calculated temperature humidity index (THI) is presented in Table 2. The THI in all sampling days were within the thermoneutral zone, except for summer season which was 78.99.

Table 2.

The THI in each sampling season.

Season Date Time Temperature (°C) Relative humidity (%) THI
Spring 29/04/2020 12.00–13.30 19.31 62.66 64.94
Summer 13/08/2019 12.00–13.00 32.80 34.50 78.99
Autumn 19/11/2020 12.00–13.30 7.88 99.84 46.19
Winter 22/01/2020 12.00–13.30 −3.33 99.70 26.06
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3.2. Ct value

The gene expression of all GOI (Table 3) in this study were significantly different (p < 0.05) in each season, showing the dynamic gene expression according to seasonal variation. The interaction between the season, breed, and sex were identified in IL10 gene expression (p < 0.05), indicating the changes in gene expression in each season were not equivalent in each breed and sex group. According to the between-group test, it was found that there were significant differences in gene expression (p < 0.05) in each breed group across the season for IL10 and TLR4 genes.

Table 3.

Mean and standard deviation of CT value of IL10, TLR2, TLR4, TLR8, and HSP70 of Hungarian indigenous Tsigai, Hungarian Merino, and White Dorper in each season of the year.

Gene Season CT-Value (Mean ± Std. Deviation)
Hungarian indigenous Tsigai Hungarian Merino White Dorper Overall
HSP70 Summer 22.540 ± 0.473 22.500 ± 0.279 22.500 ± 0.628 22.516 ± 0.482a,b
Autumn 24.835 ± 1.032 24.413 ± 1.260 23.940 ± 0.758 24.393 ± 0.992c
Winter 22.582 ± 1.040 22.273 ± 0.055 21.515 ± 0.597 22.093 ± 0.875a
Spring 23.037 ± 0.934 23.203 ± 0.106 22.898 ± 0.691 23.015 ± 0.705b
Overall 23.248 ± 1.273a 23.097 ± 1.031a 23.7133 ± 1.086a 23.004 ± 1.162
IL10 Summer 32.953 ± 1.581 32.897 ± 1.055 32.122 ± 1.946 32.609 ± 1.605c
Autumn 31.215 ± 0.757 30.127 ± 0.624 30.345 ± 0.441 30.649 ± 0.752b
Winter 29.808 ± 1.496 28.503 ± 0.055 28.175 ± 0.444 28.894 ± 1.218a
Spring 29.755 ± 0.981 29.473 ± 0.352 29.110 ± 0.527 29.441 ± 0.742a
Overall 30.933 ± 1.772b 30.250 ± 1.791a,b 29.938 ± 1.802a 30.398 ± 1.815
TLR2 Summer 26.927 ± 1.259 26.400 ± 1.003 26.115 ± 1.283 26.497 ± 1.201b
Autumn 27.528 ± 1.370 25.370 ± 0.491 25.698 ± 0.549 26.365 ± 1.340b
Winter 24.195 ± 1.214 24.313 ± 1.270 23.837 ± 0.243 24.075 ± 0.906a
Spring 24.453 ± 0.778 23.843 ± 0.167 24.095 ± 0.807 24.188 ± 0.716a
Overall 25.759 ± 2.023b 24.982 ± 1.261a,b 24.936 ± 1.262a 25.281 ± 1.559
TLR4 Summer 24.617 ± 0.731 24.363 ± 0.548 23.002 ± 0.660 23.920 ± 1.000a
Autumn 26.613 ± 1.076 25.640 ± 1.521 25.720 ± 0.620 26.061 ± 1.049b
Winter 23.613 ± 0.275 23.787 ± 1.278 22.983 ± 0.451 23.396 ± 0.677a
Spring 24.105 ± 0.767 23.837 ± 0.317 23.095 ± 0.339 23.647 ± 0.703a
Overall 24.737 ± 1.367b 24.401 ± 1.183b 23.700 ± 1.292a 24.256 ± 1.365
TLR8 Summer 26.572 ± 1.185 25.910 ± 1.404 25.873 ± 1.529 26.160 ± 1.319c
Autumn 25.952 ± 0.905 24.820 ± 1.129 24.340 ± 0.919 25.081 ± 1.162b
Winter 23.610 ± 1.528 23.620 ± 1.652 23.048 ± 0.557 23.387 ± 1.190a
Spring 23.282 ± 0.707 22.953 ± 0.826 22.562 ± 0.237 22.928 ± 0.638a
Overall 24.854 ± 1.798b 24.326 ± 1.616a,b 23.956 ± 1.578a 24.389 ± 1.698
GAPDH Summer 26.590 ± 2.218 25.013 ± 2.806 25.983 ± 3.166 26.032 ± 2.616
Autumn 22.877 ± 1.181 21.450 ± 0.236 21.902 ± 0.387 22.201 ± 0.956
Winter 21.833 ± 1.724 21.787 ± 1.180 21.107 ± 1.462 21.533 ± 1.467
Spring 21.662 ± 0,707 21.710 ± 0.295 21.640 ± 0.664 21.663 ± 0.591
Overall 23.240 ± 2.501 22.490 ± 2.011 22.658 ± 2.589 22.857 ± 2.589
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SD: Standard deviation; a-c: different superscript showed significant difference (p < 0.05).

3.3. Relative gene expression

The relative expression was calculated using the Pfaffl method (Pfaffl, 2001) and is presented in Table 4 and visualized as Fig. 1 (A-E). The spring season was considered as a thermo-neutral season and used as a calibrator.

Table 4.

Relative gene expression calculation with Pfaffl method [26] of IL10, TLR2, TLR4, TLR8, and HSP70 of Hungarian indigenous Tsigai, Hungarian Merino, and White Dorper in each season of the year, relative to spring season as a calibrator.

Gene Season Relative gene expression (Mean ± SD)
Hungarian indigenous Tsigai Hungarian Merino White Dorper
HSP70 Summer 0.777 ± 0.313 7.494 ± 11.932 0.652 ± 0.219
Autumn 0.527 ± 0.192 0.378 ± 0.193 0.381 ± 0.083
Winter 0.810 ± 0.889 2.487 ± 2.092 0.524 ± 0.498
Spring 1.039 ± 0.326 1.024 ± 0.265 1.078 ± 0.441
IL10 Summer 6.299 ± 6.412 1.976 ± 1.642 17.395 ± 5.848
Autumn 0.578 ± 0.175 0.554 ± 0.156 1.202 ± 0.166
Winter 0.838 ± 0.516 2.553 ± 2.128 4.443 ± 5.364
Spring 1.124 ± 0.576 1.026 ± 0.294 5.949 ± 6.477
TLR2 Summer 12.053 ± 11.018 3.317 ± 2.720 14.263 ± 13.417
Autumn 0.369 ± 0.219 0.304 ± 0.054 0.419 ± 0.116
Winter 2.062 ± 2.126 1.838 ± 2.630 1.644 ± 1.695
Spring 1.028 ± 0.261 1.019 ± 0.231 1.107 ± 0.420
TLR4 Summer 0.379 ± 0.100 15.204 ± 19.950 14.263 ± 13.417
Autumn 0.428 ± 0.090 0.324 ± 0.291 0.419 ± 0.116
Winter 2.283 ± 1.817 3.414 ± 4.913 1.644 ± 1.695
Spring 1.021 ± 0.242 1.028 ± 0.306 1.107 ± 0.420
TLR8 Summer 5.747 ± 5.481 7.497 ± 6.507 6.910 ± 8.130
Autumn 0.257 ± 0.085 0.842 ± 0.353 0.228 ± 0.080
Winter 1.593 ± 1.818 6.617 ± 9.523 0.898 ± 1.296
Spring 1.061 ± 0.406 1.271 ± 1.018 1.100 ± 0.597
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SD: Standard deviation.

Fig. 1.

Fig. 1

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Bar graph of relative gene expression of (A) HSP70, (B) IL10, (C) TLR2, (D) TLR4, and (E) TLR8 in each season of the year with the spring season as the calibrator. The X-axis is the relative gene expression in different season of the year. The Y-axis is gene expression for each different breeds in the study. Different colours represent different breed; red for Hungarian indigenous Tsigai, blue for Hungarian Merino, and yellow for White Dorper.

For HSP70, relative gene expression with different peak was observed; spring for Hungarian indigenous Tsigai (1.039 ± 0.326) and White Dorper (1.078 ± 0.441), summer (7.494 ± 11.932) for Hungarian Merino. In all GOI in this study, the lowest expression relative to the spring season was found in the autumn.

An increasing gene expression trend was identified for IL10 in the summer season. The highest relative gene expression means of IL10 were found in the summer season for White Dorper (17.395 ± 5.848) and Hungarian indigenous Tsigai (6.299 ± 6.412), but for Hungarian Merino, the highest expression was identified in the winter season (2.553 ± 2.128).

For the two Toll-like receptor genes, TLR2 and TLR8, in spring and autumn, the gene expression tend to be low and a higher relative gene expression was observed in winter and summer. Both genes were observed to be overexpressed during the summer time in all breeds, with the mean relative gene expression value of 12.053 ± 11.018, 3.317 ± 2.720, and 14.263 ± 13.417 for TLR2 in Hungarian indigenous Tsigai, Hungarian Merino, and White Dorper, respectively. While for TLR8 were 5.747 ± 5.481, 7.497 ± 6.507, and 6.910 ± 8.130, respectively.

Besides that, for TLR4, the highest expression was observed in the summer for Hungarian Merino (15.204 ± 19.950) and White Dorper (14.263 ± 13.417), but not for Hungarian indigenous Tsigai, which was observed in the winter (2.283 ± 1.817). But still, a lower expression was observed during the thermoneutral seasons; spring and autumn.

4. Discussion

The health and well-being of animals are determinant factors in achieving maximum productivity. The seasonal stressor is one of the major components in achieving this optimum profit in livestock farming, as has been proven by many previous findings (Lara and Rostagno, 2013, Hughes et al., 2018). The seasonal variation shows temperature, humidity, rainfall, and daylight gradients across the year, which may affect the livestock's homeostasis directly through changes in physiological and biological processes, also behavior adjustment (Martelli et al., 2018, Berihulay et al., 2019). Understanding the livestock's seasonal adjustment is critical for successful and profitable livestock farming, especially in an era where climate change is the most pressing issue, exposing animals to temperatures beyond their comfort zones and compensating for their production ability.

The thermal comfort zone for sheep varies among breeds, which correlates to their morphological characteristic facilitating the body's heat exchange with the environment, for example the coat colors and characteristics or the physical characteristic of the hair/wool (Paim et al., 2014). This morphological diversity in livestock provides a potent system for genetic dissection of traits with complex inheritance, which also demonstrates their adaptation to their environment and is an indication of natural selection driving greater diversity (Boyko et al., 2010). In this study, the three most common sheep breeds in Hungary were observed; the Hungarian indigenous Tsigai; the commercial breed with a long history of crossbreeding, the Hungarian Merino, which both are cold tolerant breeds; and the South African commercial breed, White Dorper, which is a breed with a high tolerance to heat. All of the breeds in this study have a dominating white coat colour, with both the Hungarian indigenousTsigai and Hungarian Merino having long wool and White Dorper having short wool. The aim was to see if there is any difference in adaptability to the Hungarian environment between the three different breeds, although all of them have been acclimatized to it as these breeds have been widely kept in Hungary.

Generally, sheep have an upper critical between 25 and 31 °C, depending on factors such as breed, age, and physiological state. Heat stress occurs when the effective temperature of the environment is higher than this upper critical temperature (Hopkins et al., 1978). To assess livestock productivity responses to climate change, the simplest method is to use the THI, which is calculated by combining the average temperature (°C) and relative humidity (%) of a given location (Ratchamak et al., 2021). It is undeniable, however, that THI may not entirely portray the thermal environment in which animals live because it does not take into consideration such factors as wind velocity, solar radiation, the shade provided to animals, or the availability of water. According to the THI calculation of each sampling season, almost-severe heat stress was observed in the summer season (THI = 78.99), which generated some gene expression changes inside the sheep body, explained as follows.

Thermal acclimation and adaption in small ruminants are invariably correlated with increased HSP concentrations. The HSPs have been the core of molecular responses in livestock to heat stress, but its stress tolerance mechanism is complex and not fully understood. With high HSP concentrations, cells can respond to heat stress better, while low levels of HSP make them more vulnerable (Rout et al., 2018, Joy et al., 2020). As it was observed in this study, Hungarian Merino, the cold tolerant breed with a high susceptibility to heat stress, the relative gene expression of HSP70 was upregulated in the summertime, indicating heat-stress induced HSP70 expression. As explained by Aleena et al. (2018) and Hooper et al. (2018), a relatively higher HSP70 gene expression level suggests a greater need to protect the conformation of proteins on the cells from heat stress damage such as denaturation and aggregation. A previous study on goats showed HSP70 gene is essential in goat environmental stress tolerance and adaptation, and its expression increases during heat stress (Banerjee et al., 2014, Archana et al., 2018) since it is a mechanism to protect proteins from degradation and facilitates their refolding, thereby enhancing cell survival (Dangi et al., 2014).

The expression pattern of the HSP70 gene is species- and breed-specific for goats, as shown by research by Banerjee et al. (2014), possibly due to variances in thermal tolerance and adaptability to different climatic circumstances. They also confirmed that summertime expression of HSP70 gene is more remarkable in Indian cold-adapted goats (Gaddi and Chegu) than in heat-adapted goats (Sihori and Barbari). The spike of HSP70 expression due to heat stress in other livestock has also been reported, e.g., cattle (Bharati et al., 2017) and buffalo (Yadav et al., 2021). In comparison, the Hungarian indigenous Tsigai and White Dorper HSP70 expression in this study showed a small range of relative gene expression during the season of the year.

The Hungarian indigenous Tsigai, as expected, has good adaptability to the Hungarian environment (Gáspárdy et al., 2006) and Kusza et al., 2010, Kusza et al., 2011, Kusza et al., 2015 explained that the Hungarian indigenous Tsigai sheep is an ancient breed that has its origins traced to Asia Minor, located in modern-day Turkey. This breed was introduced to Hungary during the latter half of the 1700s. The breed has gained importance in Hungary owing to its resilience and capacity to adapt to harsh climatic and the breed has a historical significance, contributing to the country's agricultural heritage and economy. While, the White Dorper has a better thermotolerance due to the advantageous morphological characteristics such as short hair, thin skin, and a low number of hair follicles per unit area that help in combating heat stressors by facilitating heat dissipation (Gootwine, 2011) without necessitating them to make physiological regulation such as increasing heart rate and respiration rate to help to release the internal heat or reducing feed intake and body weight to decrease the endogenous heat production (Marai et al., 2007). Many findings have proven their extraordinary thermoregulation and resistance to heat stress (Almeida et al., 2013, Joy et al., 2020).

The colour and characteristics of an animal's coat can have a significant impact on its ability to acclimate to changing temperatures. Wool, not only have significant economic value, but also according to a review by Astuti et al. (2022) acts as a protective barrier that helps regulate body temperature by preventing heat loss in cold environments and blocking excessive heat gain in hot environments. Nevertheless, the thickness and type of wool can also impact an animal's ability to regulate its body temperature. For instance, wool sheep with thicker wool may have a lower thermoregulatory capacity due to the insulation effect of the wool, which inhibits body heat from escaping. In contrast, animals with thinner wool may have improved thermoregulation due to air stability within the fleece, which reduces heat loss via convection (McManus et al., 2020). The heritability of wool traits is moderate to low, as they are influenced by multiple genetic and environmental factors. The wool-growing process in the epidermis involves intricate coordination among numerous genes and cell types, such as Ubiquitin conjugating enzyme E2 E3 (UBE2E3) and Rhopilin Rho GTPase binding protein 2 (RHPN2), which play crucial roles in keratinocyte differentiation and cell proliferation (Zhao et al., 2021), Follistatin (FST) genes which regulates hair follicle morphogenesis and cycling (Ma et al., 2017), also Keratin (KRTs) and Keratin-associated protein (KRTAP) which also plays important role in epithelial cell’s stress response and apoptosis (Sulayman et al., 2018). The genetic and cellular mechanisms underlying the relationship between wool characteristics of sheep and their thermal adaptation remain obscure and complex. The incomplete understanding of the complexities of these biological processes contributes to a continuing lack of clarity on the subject.

Aside from its direct role in molecular protection against heat stress (intercellular function), the external HSP70 also plays a vital role in the immune system. One is by signalling immune cells against invading pathogens via increased neutrophils and macrophages (Dybdahl et al., 2005), in collaboration with host pattern recognition molecules like toll-like receptors (TLR) through the pathogen-associated molecular pattern (PAMP) to activate immune response (Hassan et al., 2019). The other is through the intervention of intracellular inflammatory signalling pathways, such as in the production of interleukin-10 (IL10), the foremost anti-inflammatory and immunosuppressive cytokine (Borges et al., 2012).

Heat stress causes an imbalance in the immune system by shifting the adaptive immune function from the normal cell-mediated to humoral immunity, which is a significant contributor to the poor health that results from it. Heat stress has been shown to reduce sheep's immunity, making them more susceptible to disease (Sophia et al., 2016, Shi et al., 2020). It is widely thought that heat-stress-induced glucocorticoids impair immunological homeostasis via altered cytokine production. However, the specific mechanism is unknown (Bagath et al., 2019). In this study, the expression of immune-related genes (IL10, TLR2, TLR4, and TLR8) was also studied to reveal the relationship between heat stress and immune deprivation in sheep.

The expression of IL10 was significantly different in each season and was not equivalent in each breed. In White Dorper, it was overexpressed in the summertime, as was the case in Hungarian indigenous Tsigai but with a lower peak. However, in Hungarian Merino, peak expression was seen only during the winter, and seasonal variation was minimal. The previous study on various cattle breeds; Karan Fries (Sheikh et al., 2016), Sahiwal cows (Grewal et al., 2021), and Jersey (Kim et al., 2020) showed a higher IL10 expression when facing heat stress, also in sheep, an increased plasma IL10 production was reported during the hyperthermia (Caroprese et al., 2014), which was explained as a mechanism to increase immune tolerance under heat stress condition. Meanwhile, Rashamol et al. (2019) showed no significantly different expression of IL10 in heat stress and non-heat stress Malabari goats, demonstrating strong resilience to heat stress, notably in the ability to maintain the innate immune response, which is consistent with the expression of IL10 in Hungarian Merino in this study. Further explained by Loukovitis et al. (2022) that Merino was initially brought to Hungary in the 17th century, giving them plenty of time to acclimatize to the country's semi-arid environment and pastures, although as a imported multipurpose breed, Hungarian Merino has undergone numerous improvements programs since then by crossing them with various Merino and Merino-derived breeds. In contrast, because of its historical value, the Hungarian indigenous Tsigai has been included in the national gene conservation program in order to preserve its original qualities, particularly the traits that allowed them to thrive in a specific Hungarian environment. Nonetheless, the Hungarian Merino population has been declining recently, possibly as a result of the introduction of imported international breeds, which have become more popular among farmers in Hungary.

Pathogen identification by the highly specialized innate immune system relies heavily on Toll-like receptors (TLRs). When under stress, the immune system can either be enhanced or suppressed. In the hot summer, TLR2, TLR4, and TLR8 expression was elevated in all breeds, except for TLR4 in the Hungarian indigenous Tsigai, which showed a minimum expression fluctuation during the year with the highest expression in winter. Similarly, the TLR2 expression in Merino also showed a minimum fluctuation. This finding is in accordance with the observation in Bengal goats (Paul et al., 2015), Malabari goats (Vandana et al., 2019), and Thapakar cattle (Bharati et al., 2017) in their case TLR genes were overexpressed in summertime.

TLRs are involved in the first line of defence against stress by detecting endogenous ligands such as HSPs. Researchers have already established that HSPs can stimulate the TLR2 and TLR4 pathways (Beg, 2022). HSPs improve antigen-presenting capacity via binding to TLR, and HSPs' exposure to these TLRs may lead to the activation of dendritic cells and macrophages and the generation of immune-enhancing cytokines critical to host infection survival (Gobert et al., 2004, Paul et al., 2015). Increased TLR2, TLR4, and TLR8 expression and signalling in immune cells can in turn enhance thermo-tolerance by increasing the innate immune response to PAMPs via a distinct immune response mechanism (Zhao et al., 2007).

The Hungarian indigenous Tsigai excelled in preserving its immune response while being subjected to hyperthermic conditions, as shown by the breed's lower expression of TLR4 compared to other breeds and the downregulation of TLR4 in the summer. According to research conducted by Gavojdian et al. (2015), the Hungarian indigenous Tsigai is less susceptible to lameness and pneumonia than the Dorper and White Dorper. Similar results were demonstrated in the spleen of Osmanabadi goats (Sophia et al., 2016), indicating the highly adaptive nature of this breed and their improved innate immune response against heat shock proteins when exposed to heat stress. It was also noted by Bharati et al., (2017) that TLR4 could be crucial for providing a long-term immunological response to reduce the harmful effects of heat stress (Inflammation and tissue injury) and confer thermo-tolerance under prolonged heat stress. It also identifies the Gram-negative bacteria-specific lipopolysaccharide (LPS) (Bulgari et al., 2017).

In this study, the Hungarian Merino was subjected to heat stress during the summer, as indicated by the relative expression of HSP70, but they maintained an effective immune response by maintaining high levels of IL10 and TLR2 gene expression throughout the year. It should come as no surprise that the indigenous Hungarian indigenous Tsigai has remarkable resilience to its natural environment and keep its resistance to seasonal stressors intact, while the immigrant White Dorper is only moderately suited to Hungarian climate. Through our research on genes for heat resistance and immunity, we confirmed that these three breeds are optimal for the Hungarian environment, given the risks posed by current and projected climate change. We recognize that our study is limited by the small and unequal sample size for each breed, which may reduce the study’s statistical power and realiability, but we are confident that the results are indicative. It is essential to recognize the intricate nature of the five genes analyzed in this study, as well as their complex interactions with numerous other genes. The complexity of their functions and interrelationships is not to be disregarded, necessitating a more in-depth investigation into the relationship between sheep productivity and genetic adaptability.

5. Conclusion

This study confirmed the relative expression of genes involved in heat stress and immunity; HSP70, IL10, TLR2, TLR4, and TLR8 are varied with the seasons in all three studied breeds of sheep, evidencing that seasonal stressor affects the thermo-balance and immunity of the sheep. The thermotolerance of the Hungarian Tsigai (indigenous breed) and White Dorper (tropical breed) is higher than that of the Hungarian Merino. However, the Hungarian indigenous Tsigai and, secondarily, the Hungarian Merino appear to have advantages over the White Dorper in terms of strength to maintain immunity under heat stress conditions.

CRediT authorship contribution statement

Putri Kusuma Astuti: Visualization, Writing – original draft. Zoltán Bagi: Writing – review & editing. Lilla Bodrogi: Methodology, Writing – review & editing. Tímea Pintér: Methodology, Writing – review & editing. Gabriella Skoda: Methodology, Writing – review & editing. Roland Fajardo: Writing – review & editing. Szilvia Kusza: Conceptualization, Methodology, Resources, Writing – review & editing, Supervision.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was funded by the bilateral S&T cooperation programme, within the project “Effect of heat stress in Pramenka types of sheep using DNA and RNA based methods” from the National Development, Research and Innovation Fund (2021-1.2.4-TÉT-2021-00047), also by the EFOP-3.6.2-16-2017-00001 project, entitled: “Complex rural economic development and sustainability research, development of the service network in the Carpathian Basin”. P.K.A. was supported by Tempus Public Foundation within the Stipendium Hungaricum Programme. Authors would thank Csaba Rácz for providing climatic data during the sampling period, János Oláh for helping in sampling and Husein Ohran, Péter Strausz, George Wanjala and András Jávor for their valuable comments in preparation of mansucript.

Ethic declarations

All methods were carried out in accordance to the European Union's Animal Experimentation Directive (2010/63/EU) and ARRIVE guidelines.

Footnotes

Peer review under responsibility of King Saud University.

Contributor Information

Putri Kusuma Astuti, Email: astuti@agr.unideb.hu.

Zoltán Bagi, Email: bagiz@agr.unideb.hu.

Lilla Bodrogi, Email: Bodrogi.Lilla@uni-mate.hu.

Tímea Pintér, Email: Pinter.Timea@uni-mate.hu.

Gabriella Skoda, Email: Skoda.Gabriella@uni-mate.hu.

Roland Fajardo, Email: rolandfajardo@bai.gov.ph.

Szilvia Kusza, Email: kusza@agr.unideb.hu.

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