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The constitutive expression of the chrysanthemum gene CmERF110 in Arabidopsis thaliana affects lateral branching

 Background: Producers of cut flower chrysanthemum are obliged to manually remove lateral buds, a procedure which consumes one third of the total production cost. The formation of lateral buds in ‘SEI NO ISSEI’ is suppressed when the plants are exposed to high temperatures, but the molecular basis of this phenomenon is not well understood. Here, the transcriptome of buds formed by decapitated chrysanthemum plants grown under a high temperature regime was characterized with a view to revealing which genes known to be involved in a pathway determining shoot branching were induced/repressed by the treatment. Results: The transcriptomic data was acquired using RNA-Seq technology, based on the Illumina HiSeq™ 2000 platform. Four libraries were generated from pooled lateral buds of decapitated ‘SEI NO ISSEI’. To predict the potential functions of unigenes in the ‘SEI NO ISSEI’ buds, after assembly, we performed seven functional database annotations. 132,396 unigenes were assembled, of which 79,116 unigenes were annotated in the seven functional databases. The percentage of unigenes annotated in the NR, NT, Swiss-Prot, KEGG, COG, Interpro, and GO databases were 54.59%, 42.96%, 39.05%, 41.84%, 20.72%, 37.25%, and 13.01%, respectively. Multiple differentially expressed transcription factors and auxin-related genes were identified in buds of decapitated ‘SEI NO ISSEI’ under 28°C/23°C or 38°C/33°C. Constitutively expressing CmERF110 in wild type Arabidopsis thaliana produced a bushy plant. A quantitative analysis of gene expression changes in the CmERF110 transgenic A. thaliana plants showed that the presence of the transgene altered the abundance of transcript produced by TIR1, ARF2, ARF16, IAA3 and IAA9 (encoding auxin signaling proteins) and PIN1, AUX1, LAX1, LAX2 and ABCB1 (auxin transport). Conclusions: This study reported a highly complete transcriptome from the buds of decapitated ‘SEI NO ISSEI’. Differential abundant transcripts during high temperature treatments were identified and validated by qPCR, many of these differentially abundant transcripts as key players in bud outgrowth. These include known members of the AP2/ERF, MYB, WRKY, bHLH families and auxin-related genes. CmERF110 regulated shoot branching when its encoding gene was heterologously expressed in A. Thaliana. The regulation acted through the auxin-related genes.

Background
The ability of the plant shoot to form branches has a major effect on the plant's architecture, a trait of major importance in the context of crop domestication and improvement [1,2]. Axillary meristems are composed of a group of cells which have retained their meristematic potential [3]. Following their initiation, these structures develop into axillary buds, which either remain dormant or develop into a new branches, depending a number of both internal and/or external cues [4]. Three forms of bud dormancy have been recognized: paradormancy occurs when growth ceases because of physiological factors external to the bud; endodormacy when growth is regulated by internal physiological factors; and ecodormancy when external environmental factors are most important [5]. The major environmental cues regulating the induction and release of bud dormancy are temperature and light, although the extent of the influence and the importance of crosstalk between temperature-and light-regulated signaling pathways appear to be somewhat species-dependent [6]. The relevant physiological factors include phytochrome, sugar and phytohormones, which are basically associated with direct phenotypic changes when plants perceive environmental signals [7]. The phytohormones 5 associated with bud growth and development include abscisic acid, ethylene, gibberellic acid, cytokinin, strigolactone and auxin.
Chrysanthemum is a valuable ornamental species [22]. Producers of cut flowers are required to manually remove lateral buds, a costly and energy-consuming procedure. In the cultivar 'SEI NO ISSEI', the formation of lateral buds has been shown here to be suppressed when the plants are exposed to a high temperature regime. In order to reveal the molecular basis of this suppression, the transcriptome of this cultivar was characterized, which resulted in the recognition that the gene encoding a specific ethylene response factor was up-regulated in response to a high temperature exposure. By expressing this gene heterologously in Arabidopsis thaliana, it was possible to determine that its product regulates shoot branching, 6 acting through the auxin-related genes. The conclusion was that it may be possible, through the manipulation of this gene within chrysanthemum, to achieve a branchless chrysanthemum plant, which would be of substantial value to breeders of chrysanthemums directed at the market for cut flowers.

Results
The effect of high temperature on bud outgrowth in 'SEI NO ISSEI' Decapitated 'SEI NO ISSEI' plants exposed to the 28°C/23°C treatment presented an acrotonic pattern of bud out-growth along their stems, whereas those exposed to 38°C/33°C produced very few buds (Fig. 1a). After a four day exposure to two temperature regimes (28°C/23°C or 38°C/33°C), there was no difference in the bud burst rate. However, when decapitated chrysanthemum was exposured to 28°C/23°C or 38°C/33°C on the seventh day, the bud burst rate was significantly different in the fifth and sixth nodes (the first node n-1 refers to the first bud of decapitated chrysanthemum from top to bottom). Buds formed by plants exposed for ten days to 28°C/23°C exhibited a significantly higher bud burst rate than those of plants exposed to 38°C/33°C (Fig. 1b). In the former plants, bud growth was acrotonic, as also shown by the pattern of leaf development, whereas bud growth under the higher temperature regime was inhibited and no acrotonic gradient was observed.
The length of a bud of different position was two to twelve fold greater in plants exposed for ten days to the lower temperature regime than in those exposed to the higher temperature regime (Fig. 1c).

Transcriptome sequencing and read assembly
In order to study the differentially expressed genes of buds of decapitated 'SEI NO

Unigene functional annotation
To predict the potential functions of unigenes in the 'SEI NO ISSEI' buds, after  (Table 3). Among them, the NR database had the largest number of unigenes, so we counted the species distribution according to the NR annotation results. The most common species was Vitis vinifera, which accounted for 16.71% of species distribution, followed by Solanum tuberosum (8.54%), Theobroma cacao (6.95%) and Erythranthe guttata (6.00%). The proportion of other species was 61.81% ( Figure S1).

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To clarify the potential functions of unigenes in the buds of 'SEI NO ISSEI', we calculated its functional classification based on the COG annotation results. The COG annotation divided unigenes into 25 categories, the most of which was "general functional prediction only" (7601, 16.89%), followed by "replication, recombination and repair" (4309, 9.57%) and "transcription" (4187, 9.30%).
To further understand the potential functions, GO term enrichment analysis was performed. A total of 85,084 unigenes were divided into 53 functional groups, which mainly included biological process (23), cellular component (16) and molecular function (14). In biological process, the main functional groups were "metabolic process" (8904) and "cellular process" (8337). In cellular component, the main functional groups were "cell" (6393) and "cell part" (6393). Among the molecular function, "catalytic activity" (9984) and "binding" (8266) were most ( Figure S3). The results suggested that these main categories might play an important role in buds.
In addition, we calculated its functional classification based on the results of the KEGG database. A total of 58,140 unigenes were clustered, including cellular processes, environmental information processing, genetic information processing, human diseases, metabolism and organismal systems. The three main pathways were the "global and overview maps" in metabolism (12,893,22.18%), the "translation" in genetic information processing (5,562, 9.57%), and the "carbohydrate metabolism" (5,163, 8.88%) ( Figure S4).

Differentially transcribed of auxin-related genes in buds
Auxin plays a key role in bud growth and development, we analyzed auxin-related differential genes from RNA-seq data. There were 32 differential transcriptions associated with auxin, 21 genes in the signalling pathway and 11 genes in the transport pathway ( Fig. 3 and Table S3). Among 21 transcripts associated with auxin signalling process, the abundance of TIR1, ARF2, ARF4, ARF5, ARF8, ARF16, ARF18, ARF19, IAA3 and IAA9 transcript were low in buds outgrowth (n-24h and n-96h) compared to other time points (h-24h and h-96h), while PIN1, PIN2, AUX1, LAX1, LAX2 and ABCB1 (associated with auxin transport process) were significantly upregulated in buds outgrowth compared to inhibited buds.

Verification of RNA-seq data by qRT-PCR
In the library of bud outgrowth, fourteen differentially expressed genes were selected for qRT-PCR to test the reliability of RNA-seq data. The qRT-PCR assays largely validated the RNA-Seq based identification of differential transcription ( Fig.   4 and 5). We selected four transcription factors, including Unigene28455_All (ERF110), Unigene9775_All (MYB4), CL2694.Contig5_All (WRYY40) and CL3647.Contig6_All (bHLH36) and ten auxin-related genes (TIR1, ARF2, ARF16, IAA3 and IAA9), which were all related to shoot branching and potential candidate genes for regulating chrysanthemum branching.

The phenotype of A. thaliana plants heterologously expressing CmERF110
When  Fig. 6a and 6b). Axillary buds were rarely formed in the first three rosette leaf axils of WT plants, whereas nearly all rosette leaves carried buds or branches in the axils of WT/ERF110 (active buds), brc1 (inactive buds) and brc1/ERF110 (active buds) plants. A greater number of high order branches was produced by WT/ERF110, brc1 and brc1/ERF110 plants than by WT plants (Fig. 6g-j). WT/ERF110, brc1 and brc1/ERF110 plants formed a similar number of primary cauline leaf branches (CI) as did WT ones (Fig. 6k). WT/ERF110 and brc1/ERF110 plants produced significantly more secondary cauline leaf branches (CII) than did, respectively, WT and brc1 plants (Fig. 6l). The brc1/ERF110 plants formed more rosette branches (RI and RII) than did WT plants. The RI and RII phenotype of brc1 plants was weaker than that of WT/ERF110 ( Fig. 6m and 6n). The conclusion was that the product of BRC1 influenced the plants' RI and RII performance, while the constitutive expression of CmERF110 mainly affected CII as well as RI and RII.

The constitutive expression of CmERF110 in A. thaliana reprogrammed the transcription of auxin-related genes
The effect of constitutively expressing CmERF110 on the transcription of the auxinrelated genes was tested in 21 day old A. thaliana seedlings. The abundance of PIN1, AUX1, LAX1, LAX2 and ABCB1 transcript was from 1.30 to 3.14 fold higher in the transgenic plants than in WT plants, while TIR1, ARF2 , ARF16 , IAA3 and IAA9 were down-regulated by between 1.23 and 1.33 fold (Fig. 7). The suggestions that in the transgenic plants, the CmERF110 product participated in the shoot branching, acting through the auxin-related genes.

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The capacity to form branches is an important determinant of crop productivity.
Shoot branching includes the formation of axillary buds in the axil of leaves and subsequent outgrowth of the buds [29]. The presence of an apical shoot meristem inhibits lateral bud outgrowth, and removal of this meristem initiates lateral bud outgrowth [30]. The outgrowth of lateral buds in the chrysanthemum cultivar 'SEI NO ISSEI' was found to be significantly compromised when the plants were exposed to a high temperature regime. In Rosa, temperature has also been shown to influence the budburst gradient along the stem [31] [43], which laid the foundation for us to study the burst of chrysanthemum buds under the contrast temperature (CL142.Contig2_All) and ABCB1 ( CL2492.Contig2_All) were all down-regulated ( Fig. 3 and Table S3). Physiological experiments conducted many years ago established auxin as a key regulator of axillary shoot branching [8]. TIR1 is an F-box protein, which acts as an auxin receptor [17]. It has been shown in tomato that a deficiency of ARF2a transcript results in the promotion of axillary shoot formation [32] and 13 ARF16 has been established as auxin-inducible [33] [45]. Several proteins are known to regulate auxin transport: these include the auxin efflux carrier PIN and the auxin influx facilitators AUX1 and LAX [34][35][36] [49][50][51]. ABCB1 is expressed in shoot and root apices [37], where it functions primarily to introduce auxin synthesized in the meristem into long-distance polar auxin transport streams [38][39][40] [53][54][55]. Our experimental results were consistent with the previous studies, indicating that under high temperature treatments the inhibition of bud outgrowth in chrysanthemum may be regulated by auxin-related genes.
A large number of transcription factors act in plants to regulate their growth and development [41]. Here, the ERF family became the particular focus of the transcriptomic analysis, because these factors are prominent in the response to abiotic stress [42,43], as well as being involved in numerous signal transduction pathways [44]. The sequence of five of the unigenes classed as being differentially transcribed as a result of the high temperature treatment identified them as likely members of the ERF family: both were more abundantly transcribed under h-96h than under n-96h ( Fig. 2 and Table S2), consistent with their products exerting control over bud outgrowth under high temperature conditions. The poplar gene EBB1 is known to encode an AP2/ERF transcription factor; plants over-expressing it exhibit early budbreak and those under-expressing it suffer from delayed budbreak [45]. The chrysanthemum ERF transcription factor CmERF053 has been shown to regulate shoot branching [46], while the product of the Larix kaempferi AP2/ERF gene LkAP2L2 exerts a pleiotropic effect on both branching and seed development [47]. The A. thaliana gene EBE encodes an AP2/ERF transcription factor, which has a notable effect on shoot architecture [48]. Finally, the peach transcription factor PpERF3b promotes precocious side-branching [49]. These previous studies suggested that ERFs played essential roles in the control of plant bud development, so a more in-depth investigation regarding this important group of temperaturerelated genes is required. CmERF110 was up-regulated by the high temperature regime inhibiting bud outgrowth in 'SEI NO ISSEI', however, its constitutive expression in A. thaliana induced a bush-like phenotype. Based on the above results, we supposed that the function of CmERF110 in both A. thaliana and chrysanthemum, may regulate different downstream genes or form protein complex with different protein interactions to regulate the shoot branching through affecting the auxin-related genes, but the mechanism needs further experimental verification.
Such as, auxin has been shown to enhance root-growth inhibition under aluminum (Al) stress in Arabidopsis . However, in maize (Zea mays), auxin may play a negative role in the Al-induced inhibition of root growth [50]. Previously, TSRF1, an ethylene response factor (ERF) protein from tomato, binds to GCC box in the promoters of pathogenesis-related genes positively regulates pathogen resistance in tomato and tobacco [51,52], but negatively regulates osmotic response in tobacco [52].
However, overexpression of TSRF1 enhances the osmotic and drought tolerance of rice by modulating the increase in stress responsive gene expression [53]. Our study also showed that the function of CmERF110 in chrysanthemum and Arabidopsis was opposite, and the previous studies further demonstrated that our findings were reliable.
In A. thaliana, the BRC1 product suppresses bud formation, since in the loss-offunction brc1 mutant, axillary meristem formation is promoted, the buds develop more rapidly and the plant branches more profusely [54,55]. When a transgene comprising CmERF110 driven by the CaMV 35S promoter was introduced into the brc1 mutant, the resulting plants produced more branches than when the same transgene was introduced into a WT background, although the latter transgenic formed more branches than did either brc1 or WT plants (Fig. 6). brc1 mutants has a significantly higher number of rosette branches (RI and RII) than WT plants, and brc1 plants has a similar number of primary and secondary cauline leaf branches (CI and CII) as the wild type [54]. Consistent with previous studies, the loss of BRC1 influenced the number of rosette branches formed, while the CmERF110 transgene affected both the number of secondary cauline leaf branches and rosette branches.
A qRT-PCR analysis identified a number of genes which were transcriptionally reprogrammed as a result of constitutively expressing CmERF110 in A. thaliana. The abundance of PIN1, AUX1, LAX1, LAX2 and ABCB1 transcript was higher in the transgenic plants than in the WT ones, so the transgenic lines exhibited a multibranched phenotype (Fig. 6). The high expression level of auxin transport protein in lateral buds is positively correlated with shoot branching. For example, the expression of RhPIN1 is upregulated during the process that sucrose promotes lateral buds [56]. In Arabidopsis, the expression level of PIN1 is significantly upregulated [57]. In decapitated peas, the growth of lateral buds are promoted and rapidly upregulate the expression of PsAUX1 and PsPIN1 [58]. In addition, the auxin signalling genes are also involved in the development of shoot branching.
Increasing the R/FR in Arabidopsis can promote branching and inhibit the expression of IAA3 [59]. The lateral bud outgrowth of leafy spurge is accompanied by downregulation of ARF2 expression [60]. In tomato, ARF2a acts downstream of IAA3 and IAA9 during the development of axillary shoots [32], SlARF2a inhibits lateral bud growth, and the down-regulated strains of IAA3 and IAA9 show an increased branching phenotype [61,62]. Similar expression patterns of IAA3, IAA9 and ARF2a suggest that they may function closely in axillary buds [32]. In our study, a further 16 effect of constitutively expressing CmERF110 in A. thaliana was to lower the abundance of TIR1 transcript, and reduced that of IAA3 and IAA9, with a knock-on effect on the transcription of ARF2 and ARF16 (Fig. 7). These transcriptional changes were consistent with the previous studies, thereby driving branch induction to completion.

Conclusions
In summary, this study reported a highly complete transcriptome from the buds of decapitated 'SEI NO ISSEI'. Differentially expressed genes during high temperature treatments were identified and validated by qPCR, many of these differentially abundant transcripts as key players in bud outgrowth, including the AP2/ERF, MYB, WRKY, bHLH families and auxin-related genes. To our knowledge, the present study has identified that CmERF110 regulated shoot branching when its encoding gene was heterologously expressed in A. Thaliana. The regulation acted through the auxin-related genens. The gene therefore represents a potential candidate for manipulating the shoot branching behavior of chrysanthemum. What remains to be established is how CmERF110 regulates bud outgrowth, how it interacts with other gene products influencing bud growth, and whether shoot branching in chrysanthemum can be manipulated by over-expressing CmERF110.

cDNA library construction and RNA-Seq analysis
RNA was extracted using a Total RNA Isolation System (Takara Bio Inc., Otsu, Japan) following the manufacturer's protocol [24]. After extract total RNA and treated with DNase I, mRNA was isolated using oligo (dT) and fragmented in mixed fragmentation buffer. Using the mRNA fragments as templates, the first strand of cDNA was synthesized, then the second strand was synthesized by using DNA polymerase I, RNase H, dNTPs and buffer. Purified double strands cDNA was resolved with EB buffer for end reparation and single nucleotide A (adenine) was added to each 3' end. After that, the A-tailed fragments were connected with adapters. The suitable fragments were selected for the PCR amplification. The constructed library was tested with the Agilent 2100 Bioanalyzer and ABI StepOnePlus Real-Time PCR System, then the quality-tested samples were sequenced using the Illumina HiSeq 2000 platform (Illumina, San Diego, CA, USA) [22]. Raw reads were edited by removing low-quality, adaptor-polluted and high content of unknown base(N) reads [25], after which we got clean reads. Trinity software [26] was then used to assemble the transcriptome and the resulting unigenes were assigned a putative function based on homologs present in the NR (NCBI nonredundant protein), NT (NCBI non-redundant nucleotide), Swiss-Prot, KEGG (Kyoto Encyclopedia of Genes and Genomes) and COG (Cluster of Orthologous Groups) databases. Conflicting assignments were resolved by applying priority in the order NR, Swiss-Prot, KEGG and COG. Differentially expression genes (DEGs) were identified by imposing the criteria P value <0.05, false discovery rate (FDR) ≤0.0001 and |log 2 ratio| ≥1.0. All sequencing data have been deposited in the NCBI sequence read archive (www.ncbi.nlm.nih.gov/sra).

Quantitative real-time PCR (qRT-PCR) assay
Total RNA was extracted from the buds of chrysanthemum plants subjected to each of the various temperature treatments and from 21 day old A. thaliana plants carrying the transgene p35S::CmERF110. Each treatment was represented by three biological replicates. A 1 μg aliquot of each RNA was subjected to an RNase-free DNase I treatment, then converted to ss cDNA (after) using PrimeScript ® Reverse Transcriptase (Takara). The subsequent 20 μL qRT-PCRs (three technical replicates per biological replicate) each contained 10 μL SYBR Green PCR master mix (Takara), 10 ng cDNA and 0.2 μM of each primer; the reactions were given an initial denaturation (95°C/2 min) followed by 40      The transcriptional response after 24 h of high temperature treatment of a selection of four t 34 Figure 5 The transcriptional response after 96 h of high temperature treatment of a selection of four t 35 Figure 6 The phenotypic consequence of constitutively expressing CmERF110 in A. thaliana in the wild Figure 7 The abundance of transcript generated from auxin-related genes involved in the regulation o


extfieldsofstudy: Chemistry Physics

provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2019.jsonl.gz.gz

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Identification of lactic acid bacteria as antimicrobial from milk Toraja Belang buffalo

Lactic acid bacteria can produce antimicrobial compound. The bacteria can be found in milk. The objective of this research is to study antibacterial activity and identification of lactic acid bacteria from milk of Toraja Belang Buffalo South Sulawesi. The lactic acid bacteria were isolated by pour plate method using MRSA containing 1 % CaCO3. Antimicrobial activity of the isolates against Salmonella typhi, Staphylococcus aureus and EPEC were assayed using agar well diffusion method. The result showed that among 14 isolates of LAB, the most potent antibacterial activity of Cell Free Supernatant against to EPEC is K1B, Staphylococcus aureusis K4A2 and Salmonella typhi is K5B2. Based on the 16S rDNA sequence, K1B, K4A2 and K5B2 isolates were identified as Enterococcus faecalis ATCC19433T with similarity 99.758 %, 100% and 99.759% respectively.

Introduction
The use of antibiotics for the long term can lead to resistance and damages commensal microflora in the human intestine. This can affect increasing the occurrence of allergies and autoimmune diseases than influence effectiveness and cost of treatment [1]. Use of antibiotics for the long term can lead to resistance and damages commensal microflora in the human intestine. This can affect increasing the occurrence of allergies and autoimmune diseases than influence effectiveness and cost of treatment [2].
Lactic acid bacteria are non-pathogenic and can be found in a variety of habitats, such as fermented foods and milk [3]. The LAB of milk as an antimicrobial has been widely practiced, among them [4] who found Lactobacillus fermentum, Pediococcusspp, Leuconostoc mesentronoides subs. mesentronoides, and Lactococcus from fermented milk. Enterococcus faecium and Lactobacillus lactis from Camel milk in Egypt [5]. Pediococcus shahsavar, Enterococcus alborz, Pediococcus sigal and Enterococccus faecalis from cow milk in Iran [6]. Lactobacillus plantarum, Lactobacillus brevis, Lactobacillus pentosus, Lactobacillus lactis from buffalo milk in North Sumatra [7].
One of animal capable producing milk and never been reported diversity and potential those antimicrobial its from Belang Buffalo Toraja (Bubalus bubalis Linn). Belang Buffalo is an endemic animals Tana Toraja, Makassar South Sulawesi. The population of Toraja Belang Buffalo has decreased, so it needs to be conserved. One of the conservation way is study the diversity and potential of lactic acid bacteria from the milk of Belang Buffalo. Therefore, this research needs to be done. The objective of the research is to isolate and identify lactic acid bacteria from the milk of Toraja Belang Buffalo which has potential as antimicrobial.

Materials and Methods
Pathogen bacteria are EPEC ATCC 25922, Staphylococcus aureus 134-P, and Salmonella typhi ATCC 58105535 obtained from Microbiology Laboratory, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia.

Isolation of lactic acid bacteria from fresh milk of Toraja Belang buffalo
Fresh milk samples were obtained from Belang Buffalo, South Sulawesi Province, Indonesia. Lactic acid bacteria were isolated by pour plate technique using MRSA containing 1% CaCO 3 [8]. Fresh milk 25 mL was diluted with 225 mL NaCl, 0.86 % and it made dilution series up to 10 -6 dilutions. The suspension of each dilution 0.1 mL inoculated into MRSA medium in Petri dish according pour plate method. Bacterial cultures from fresh milk were incubated at 37° C for 48 hours. Each isolate was purified and it carried out Gram stained and catalase test. The selected isolates were stored at -20° C containing 20% glycerol.

Assay of pathogenicity
Pathogenicity assay was carried out based on hemolytic activity of LAB. Hemolysis assay was carried out using Columbia agar plate containing 5% sheep blood. The Culture of each bacterial isolate on the MRSA medium at 24 hour incubation was taken 1 loop and inoculated on the blood agar surface. Cultures were incubated at 37° C for 24 hours, then observed β-hemolysis (clear zone), α-hemolytic (green zone) and γ-hemolytic (without clear zone).

Antimicrobial activity assay of lab cell free supernatant against pathogenic bacteria
Antimicrobial activity of LABwere tested against pathogenic bacteria well diffusion method [9,10]. Each isolate of LAB from culture stock was taken one loop and inoculated into 10 mL MRS broth and incubated at 37 °C for 24 h. Bacterial culture was centrifuged at 10.000 rpm, 4 °C for 10 min. The supernatant was filtered using 0.22 μm millipore membrane.
Pathogenic bacteria consist of Salmonella typhi ATCC58105535, Staphylococcus aureus 134-P, and EPECATCC 25922 were grown in Nutrient Broth at 37 °C till logarithmic phase with 10 6 cell/mL density. The bacteria cultures 100 μL of each pathogenic bacteria was spread on the surface of NA medium and then incubated at 4 o C for one hour. The well was made on the NA medium with 5 mm diameter and filled with 50 μL of LAB. The culture was incubated 37° C for 24 hours. The antimicrobial activity was determined by measuring of the clear zone around the wells with three replications. The data of antimicrobial activity was analysedone-way analysis of variance (ANOVA) with α = 5% using SPSS 16.0 software program.

Identification of lactic acid bacteria as antimicrobial
The LAB isolate was identified based on phenotype character and similarity of 16S rDNA sequences. Phenotypes of bacterial isolates were characterized based on Bergey's Manual of Systematic Bacteriology. The DNA of LAB was extracted with modified of i-genomic Soil DNA Extraction Mini Kit. The 16S rDNA sequence of LAB was amplified [9,11]. Sequence of 16S rDNA was amplified using 27f primer (5'-AGAGTTTGATCCTGGCTC AG-3') and 1492r (5'CTACGGCTACCTTGTTACGA-3'). The PCR mix reaction consist of 25 μL PCR master mix, 2.0 μL each primer, 19.0 μL ddH2O, and 2.0 μL DNA template. The sequence of 16S rDNA was amplified using a 35-cycle PCR program consist of the initial denaturation at 94 C for 5 min; denaturation at 94 C for1 min; annealing 54 C for 30 seconds, extension at 72 C for 1 min, and final

Isolation of lactic acid bacteria from fresh milk of Toraja Belang buffalo
Lactic acid bacteria can be found in nutrient-rich habitats such as milk. Milk contains many nutrients, which are good for LAB growth, such as proteins, fats, carbohydrates (lactose), vitamins and minerals. Lactose is utilised by the bacteria for its metabolism, producing lactic acid so milk becomes acidic.
Lactic acid bacteria from fresh milk of Toraja Belang Buffalo was obtained 14 isolates that grown in MRSA medium at 37 C. The isolated are K1A, K1B, K2B1, K2B2, K2C1, K2C2, K3A, K4A1, K4A2, K5A1, K5A2, K5B1 and K5B2. The whole of isolates were positive gram, negative catalase. The whole isolates were gamma haemolytic or non haemolytic, which means the isolates were nonpathogenic. Lactic acid bacteria as antimicrobial should be non-pathogenic. Hemolytic means that the isolates are virulence and causing high infection [10,12].

Antimicrobial activity of lab cell free supernatant against pathogenic bacteria
The fourteen isolates of LAB were tested their activity against to pathogens ie EPEC, Salmonella typhi and Staphylococus aureus. The results of antimicrobial activity that LAB, have different ability inhibiting pathogenbacteria (Figure 2). Isolate K5B2 has inhibition zone 9.23 mm greater than K5A2 was 4.53 mm against Salmonella typhi ATCC58105535 (p <0.05). The LAB supernatant of K1A, K1B, K2B1, and K2B2 were able to inhibit the growth of EPECATCC25922 with inhibition zone 11.4, 13.2, 10.13, and 10.87 mm respectively (p> 0.05). The supernatant inhibition activity of LAB against Staphylococcus aureus 134-P were varies (p <0.05) among isolate of K1B, K2B1, K2C1, K2C2, K4A1, K4A2, K5A1, and K5B2. The highest antimicrobial activity capable of inhibiting EPEC is K1B, Staphylococcus aureus is K4A2 and Salmonella typhi is K5B2. The ability of lactic acid bacteria producing antimicrobial compounds such as organic acids (lactic acid and acetic acid) and or bacteriocin that can suppress the growth of pathogens [14]. Antibacterial activity from lactic acid bacteria is caused by the production of organic acids (acetic acid and lactic acid) so as to decrease the pH of the medium or due to competition of nutrients. In addition, antibacterial activity is also due to bacteriocin. The differences ability of isolates to inhibit pathogen may be due to differences in the component or the amount of antimicrobial produced by the LAB isolates [13].
The mechanism of inhibition of bacterial growth by organic acids is due to its hydrophobic nature, thus facilitating the diffusion of protons into cells through cell membranes. This causes the intracellular pH to be higher than the extracellular pH. In the cell, the organic acid will dissociate and decrease the intracellular pH by means of proton release. This proton release results in disruption of metabolic functions (such as substrate translocation and oxidative phosphorylation), so that bacterial cell growth becomes inhibited [15].

Identification of lactic acid bacteria as antimicrobial
The K1B, K4A2 and K5B2 isolates from fresh milk of Toraja Belang buffalo as antimicrobil were identified based on 16S rDNA sequence. The phylogenetic tree (Figure 3) showed that these isolates are closely related to the Enterococcus faecalis ATCC 19433. Based on the 16S rDNA sequence, K1B, K4A2 and K5B2 isolates were identified as Enterococcus faecalis ATCC19433 T with similarity 99.758 %, 100% and 99.759%, respectively ( Figure 3).
Enterococcus as antimicrobial was found from camel milk in Egypt [5] and cow milk from Iran [6]. Although some studies suggest that Enterococcus faecalis can cause urinary tract infections, it is common in immune compromised cases or as opportunistic cases [15].  Figure 3. Philogeny tree of K2B1 isolate and reference strain based on 16S rDNA sequence with Neighbor-Joining, Tamura-Nei algorithm with bootstrap 1000.

Conclusion
The isolate K1B, K4A2 and K5B2 can inhibit the pathogen growth and were identified as Enterococcus faecalis ATCC19433 T .


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Variation for Heat Tolerance During Seed Germination in Diverse Carrot [Daucus carota (L.)] Germplasm

Carrot production is constrained by high levels of heat stress during the germination stage in many global regions. Few studies have been published evaluating the effect of heat stress on carrot seed germination or screening for genetic heat stress tolerance. The objectives of this study were to evaluate the response of diverse carrot germplasm to heat stress, identify heat-tolerant germplasm that may be used by plant breeders, and define the appropriate temperature for assessing heat tolerance in germinating carrot seed. To identify an appropriate screening temperature, three commercial hybrids and an open pollinated variety were evaluated at five temperatures (24, 32.5, 35, 37.5, and 40 °C). In preliminary studies, 35 °C was identified as the optimal temperature for screening heat tolerance of carrot seed. Cultivated and wild carrot plant introductions (PIs) (n = 270) from the U.S. Department of Agriculture (USDA) National Plant Germplasm System (NPGS) representing 41 countries, inbred lines from the USDA Agricultural Research Service (n = 15), and widely grown commercial hybrids (n = 8) were evaluated for heat tolerance under heat stress and nonstress conditions (35 °C and 24 °C, respectively) by calculating absolute decrease in percent germination (AD), inhibition index (II), relative heat tolerance (RHT), and heat tolerance index (HTI). All measurements of heat tolerance identified significant differences among accessions; AD ranged from −13.0% to 86.7%, II ranged from 35.7% to 100.0%, RHT ranged from 0 to 1.36, and HTI ranged from 0.0 to 1.45. The broad-sense heritability (H2) calculations ranged from 0.64 to 0.86 for different traits, indicating a moderately strong genetic contribution to the phenotypic variation. Several wild carrot accessions and inbred lines displayed low levels of heat tolerance, whereas cultivated accessions PI 643114 (United States), PI 652400 and PI 652403 (Turkey), PI 652208 (China), and PI 652403 (Russia) were most heat tolerant. This is the first evaluation of heritability for heat stress tolerance during carrot seed germination, the first measure of HTI, and the first correlation calculation between heat and salt tolerance during germination in carrot.

The ambient temperature of our planet has significantly increased over the past century (0.13°C per decade in last 50 years) as part of current global climate change attributed to anthropogenic activities and natural factors (Rohde et al., 2013). Modern climate models have predicted that mean global temperature will rise by 1.1°C by the end of this century and intense heat waves will also occur more frequently (IPCC, 2013). Heat stress, caused by elevated temperature, is a major threat for cereals, fruits, and vegetable production, especially in warm regions of the world (Farooq et al., 2011;Hasanuzzaman et al., 2013). Vegetables are a rich source of essential dietary micronutrients (Graham et al., 1999) but the effects of heat stress on the productivity of most vegetables have yet not been well-characterized (Fahad et al., 2017;Mahmood et al., 2017). It may be anticipated that cool-season vegetables, like carrot, are especially sensitive to heat stress.
Carrot (Daucus carota L., 2n = 2x = 18) is a biennial, cool-season, Apiaceous root vegetable that is a rich dietary source of provitamin A carotenoids (a-and b-carotene), which is vital for human development and health (Tanumihardjo, 2012). The optimal germination temperature of carrot is 20 to 30°C (Corbineau et al., 1994) and, like most crops, abiotic stress reduces carrot yield (Bano et al., 2014, Kahouli et al., 2014. Heat, drought, and/or salinity-induced stress contributes to the much lower carrot yields in countries like Pakistan and most of South Asia relative to North America or Europe (FAO, 2017).
Previous studies have reported that temperatures higher than 27°C can cause significant reduction in root mass, which accounts for the yield of a carrot (Rosenfeld, 2004). High temperature causes heat stress and is considered to be one of the major abiotic factors that limits carrot production because of its adverse effects on seed germination, seedling emergence, and plant growth (Landjeva et al., 2008). Heat tolerance is a complex trait that varies with the severity of stress and plant growth stage. Therefore, there is a need to identify heattolerant carrot germplasm with stable growth and yield under high temperature at various stages of growth. Seedling establishment, vegetative growth, and the reproductive phase of the life cycle in carrot are all critical developmental stages, but without the ability to germinate under heat stress, tolerance at later stages of growth is irrelevant. Heat stress tolerance in seeds is typically a multicomplex and polygenic trait (Senthil-Kumar et al., 2007) that varies from species to species and environmental conditions (intensity and exposure period of stress). It has been demonstrated in previous studies that the seed germination of various crops, including wheat (Balla et al., 2012), maize (Iloh et al., 2014;Riley, 1981), rice (Shah et al., 2011), chick pea (Sleimi et al., 2013), and spinach (Hum-Musser et al., 1999), is adversely affected as temperature increases.
Several previous studies demonstrated the negative effects of low temperature on carrot seed germination and stand establishment Pereira et al., 2007;Vieira et al., 2005), but relatively little has been reported about the effects of high temperatures. Vieira et al. (2005) demonstrated that high temperature inhibits carrot seed germination. High temperature affects some physiological and biochemical processes like oxygen requirement during seed imbibitions (Nascimento et al., 2008). There is no known mechanism for thermotolerance in carrot and insufficient information is available to characterize the influence of high temperature on carrot seed germination and biomass production. The most expansive carrot germplasm evaluation, to date, for heat tolerance at the germination stage, was done by Nascimento et al. (2008), who evaluated 34 commercial cultivars and 63 diverse germplasm accessions. They evaluated heat stress traits including ethylene production, time to first germination, and RHT under 35°C. The current lack of information limits our understanding of heat tolerance mechanisms in carrot. To expand the information needed to better understand those mechanisms, the objectives of this study were to identify the optimal temperature conditions for evaluating heat tolerance in carrot; to evaluate a large carrot germplasm collection for heat tolerance traits, including HTI, II, and AD at the germination stage; to evaluate the relationship between domestication status and root color on heat tolerance; and to calculate broad-sense heritability for carrot.

Materials and Methods
Germplasm. A total of 293 carrot genetic stocks consisting of 207 cultivated and 63 wild accessions from the USDA NPGS collection of PIs, 15 inbred lines from the USDA carrot breeding program, and eight commercial fresh market hybrids widely grown in the United States were included in this analysis. To better identify heat stress effects on germination, carrot accessions with more than 50% germination under nonstress conditions were included, as in recent evaluations of salinity tolerance (Bolton and Simon, 2019). The 293 carrot accessions originated from 41 countries and were classified into 14 regions based on their origin (Eastern Africa, Northern Africa, Southern Africa, North America, South America, Central Asia, Eastern Asia, Southern Asia, Western Asia, Eastern Europe, Northern Europe, Southern Europe, Western Europe, and Oceania) and they represent much of the global genetic diversity for carrot (Iorizzo et al., 2013). A subset of these accessions is also being evaluated in field trials in Bangladesh and Pakistan for heat tolerance at various stages of growth (A. Ali and M.A. Rahim, personal communication).
Determination of optimal heat tolerance evaluation temperature. A pilot experiment was conducted to determine the optimal temperature for evaluating heat tolerance in carrot. For this experiment, three widely grown commercial hybrids (coded as A, B, and C) and the cultivar Brasilia were selected to test seed germination under five temperatures (24.0, 32.5, 35.0, 37.5, and 40.0°C). 'Brasilia' was included because it is widely grown in the warmer climate of Brazil and is known to be relatively heat tolerant, whereas the three hybrids represent cultivars bred for more temperate production areas. The temperature at which statistically most significant differences were recorded between accessions, that being the lowest P value, was chosen as the optimal temperature to evaluate heat tolerance at the seed germination stage.
Germination assay. This experiment was conducted using a randomized complete block design with six replications and two treatments, that is, control (24°) and heat stress (35°). Twenty seeds from each carrot accession were placed on P5 filter paper in 60 · 15 mm petri dishes (Fisher Scientific, Waltham, MA). Petri dishes were added with 7 mL of distilled water and were placed in complete darkness at 24 ± 1°C for control in plastic bins and at 35 ± 1°C in an incubator (Fisher Scientific) for heat stress.
Evaluation under 35°C. Seed germination data were collected for a total of 10 d with measurements taken 2, 4, 6, 8, and 10 days after sowing. A seed was scored as germinated when the radicle had emerged and had a length of more than 1 mm. At each measurement time, any germinated seed was removed from the petri dish. Standard criteria for determining performance of carrot accessions under heat stress included final percent germination under nonstress conditions (PG Control ), final percent germination under heat stress (PG Heat ), AD, II, RHT, and HTI, as were used to evaluate salinity tolerance in carrot (Bolton and Simon, 2019). These measurements were calculated with the following equations: AD = PG Control -PG Heat ; II = 100 * (PG Control -PG Heat )/(PG Control ); RHT = PG Heat / PG Control ; HTI = (PG Heat *PG Control )/(PG Average ) 2 , whereas PG Average is the average percent germination of all carrot accessions evaluated under no heat stress.
Data analysis. Statistical mixed linear models (Eq. [1]) were used for analysis of variance (ANOVA) for six measurements related to seed germination on the basis of carrot accessions, origin of carrot accessions, and heat treatments.
where Y ij = the value of the measurements for the j th carrot accession in the i th replication where i = 1, ., 6, and j = 1, ., 289; m = total mean (constant), R i = effect of the i th replication (random effect) on the response measurement, A j = effect of the j th accession (fixed effect) on the response measurement, and Ɛ ij = effect of the experimental error associated with ij th observation. All analyses were performed in R. 3.4.4 (R Core Team, 2018). The lmer function in the lme4 package was used for ANOVA test (Bates et al., 2018). The mean separation analysis on the basis of region of origin of carrot accession was performed using least significant difference test function found in the agricolae package with alpha = 0.05 (De Mendiburu, 2014). Pearson rank correlations between measurements were calculated using the cor function found in the stats package (R Core Team, 2018).
The among-accession and within-accession variances were used for calculating broadsense heritability (H 2 ) as derived from Falconer and Mackay (1996) where s 2 G = genotypic (accessions) variance, s 2 P = phenotypic variance, s 2 E = variance due to experimental error, s 2 R = variance due to replication, and r = the number of replications for each treatment. Variance components were derived using formulas: s 2 G = (MSA -MSE) / r, s 2 E = MSE, s 2 R = (MSR -MSE) / n, with MSA = mean square accession, MSE = mean square error, MSR = mean square replication, r = number of replications, and n = number of accessions.

Results and Discussion
Optimal temperature for evaluation of heat tolerance at germination stage. Percent seed germination for the four cultivars evaluated in a preliminary study under nonstress conditions ranged from 44.0% to 84.0%, with a mean of 63.8%. Increasing temperature to 32.5°C reduced the mean percent germination to 57.2% and lowered the range from 45.0% to 80.0%. At 35°C, the mean percent germination was further reduced to 33.3% and lowered the range from 4.0% to 60.0%. At 37.5°C, only 'Brasilia' germinated, whereas at 40°C no germination occurred (Fig. 1). ANOVA for percent seed germination of the four carrot cultivars displayed a highly significant treatment effect (F = 154.63, P < 0.0001) and moderately significant accession effect (F = 4.78, P = 0.0044) on percent seed germination (Table 1). A significant difference between accessions was observed in the control temperature (24°C), whereas the most significant difference between accessions was recorded at 35°C (F = 13.18, P = 0.0002), indicating that 35°C is an optimal temperature to screen carrot germplasm for heat tolerance at the germination stage. At 37.5°C, only 'Brasilia' germinated, and at a low rate, whereas at 40°C there was no seed germination ( Table 2).
The results from this experiment indicate that a temperature of 35°C is an optimal temperature to test for heat tolerance, which was the same temperature used by Nascimento et al. (2008).
Germination assay. The average percent germination for the 293 carrot accessions under nonstress conditions ranged from 50.0% to 100.00%, with a mean of 81.6% and a standard deviation of 12.6%. When seeds were tested under 35°C, the average percent germination was reduced to 59.0% with a minimum value of 0.0%, a maximum of 97.5%, and a standard deviation of 19.5% (Fig. 2). These results indicate that heat stress significantly reduced percent seed germination in most carrot accessions. For all traits related to heat stress, there was a significant replication effect (P value < 0.0001) that may be attributed to variation within the incubator as reflected by the larger replication effect at 35°C than at 24°C (Table 3). Significant variation was recorded for the average percent germination among carrot accessions under control conditions (F = 8.35, P < 0.0001) (  Table 1). Percent germination also varied significantly under heat stress among carrot accessions (F = 4.88, P < 0.0001). PI 643114 (United States, 97.5%) had the highest percent germination value, whereas accessions PI 652208 (China), PI 652248 (Russia), PI 652400 (Turkey), and PI 652403 (Turkey) all had the second highest value (94.2%), indicating a high level of heat tolerance. Inbred B493B had the lowest percent germination value under heat stress (0.0%), followed by PI 652354 (Turkey, 4.2%), B7254B (7.5%), and PI 279764 (Syria, 10.8%), indicating that they were especially heat sensitive.
Several of the accessions with high percent germination under heat stress were cultivated PIs from diverse geographic regions. PI 643114 (United States), PI 652400 and PI 652403 (Turkey), PI 652208 (China), and PI 652403 (Russia) all had low AD and II values (-0.3% to 1.7%), high RHT values (0.95 to 1.0) and high HTI values (1.33 to 1.45). The most heat-sensitive carrot accessions were inbred lines and wild PIs. Inbred lines B493B and B7254B, and wild PIs from Syria (PI 279764) and Turkey (PI 652354) all had a percent germination less than 5.0% under heat stress, AD values from 50.8% to 86.7%, II values from 85.6% to 100.0%, and RHT and HTI values from 0.0 to 0.14. Surprisingly, the most tolerant accessions were not primarily from warmer regions of the world but were from very diverse geographic origins; and many tolerant accessions were cultivated varieties, suggesting that some degree of selection has occurred for heat tolerance in cultivated carrot in different parts of the world. Another interesting result was the low tolerance from several wild accessions native to regions with high levels of heat stress (Syria and Turkey), suggesting that adaptation to heat stress did not play a major role in carrot evolution and distribution based on these wild populations. In other species, sources of abiotic stress tolerance are often identified in crop wild relatives (Hajjar and Hodgkin, 2007). It appears that carrot differs from other species in this regard, as the least tolerant accessions are usually wild accessions whereas the most tolerant accessions are cultivated accessions. It should be noted that several wild carrot accessions were heat tolerant and several cultivated PIs were sensitive, contrary to general trends. That inbreds B493B and B7254B were highly sensitive was not surprising, as inbreeding depression may potentially make them more susceptible to the heat stress.
Interestingly, PI 652403 (Turkey) identified as heat tolerant in this study was also identified as one of the most salt tolerant accessions in a previous study, making this a potentially useful source of both salt and heat tolerance at the germination stage for carrot breeders (Bolton and Simon, 2019). Also, B493B had 0.0% germination under both salt stress in previous studies and heat stress in this study, indicating that this inbred line is very sensitive to two major forms of abiotic stress and can serve as a sensitive check in future studies.
AD in germination is a parameter used to measure heat stress (PG Control -PG Heat ). AD is a useful trait to identify accessions with very low tolerance to heat stress because it measures the actual reduction in germination. In this experiment, mean AD for all accessions evaluated was 22.6% and ranged from -13.0% to 86.7% ( Fig. 3A) with statistically significant variation observed among carrot accessions (F = 3.02, P < 0.0001) ( Table 3). PI 652154 (Netherlands, -13.0%) and PI 478370 (China, -12.3%) had the lowest AD values, indicating heat tolerance. A total of 15 accessions had negative AD values, indicating that heat stress increased percent germination compared with the nonstress conditions. Accessions displaying a negative AD value often had a low percent germination under control temperatures and low percent germination values under heat stress close to the overall group average (60%). These low AD value accessions might not be useful sources of heat tolerance for breeders, but do provide interesting material to investigate the genetic control of increased germination under heat stress. PI 652354 (Turkey, 86.7%) and PI 515992 (Hungary, 84.2%) had the highest AD values, indicating that heat stress greatly reduced germination and thus they were very heat sensitive.   Table 3) and had a range from 35.7% to 100.0% (Fig. 3B). PI 652154 (Netherlands, -35.7%) and PI 478370 (China, -22.3%) had the lowest II, agreeing with AD and indicating that heat stress increased germination for these accessions. B493B had a maximum II value of 100.0% followed by PI 652354 (Turkey, 95.6%), indicating that they are highly heatsensitive accessions.
RHT (RHT = PG Heat / PG Control ) is a useful criterion for evaluating heat stress, as it gives a way to account for the percent germination under the control. RHT was also significantly different among carrot accessions (F = 8.34, P < 0.0001) (Table 3) with a population mean of 0.74 and a range from 0 to 1.36 (Fig. 3C). PI 652154 (Netherlands, 1.36) and PI 478370 (China, 1.22) had the highest RHT values, whereas B493B, 7254B, PI 279764 (Libya), PI 515992 (Hungary), and PI 652354 (Turkey) all had low values (0.0 to 0.14). Similar to AD, accessions with high RHT values displayed low percent germination values under control conditions and thus provide a more useful resource for understanding the genetics of performing better under heat stress rather than useful breeding material.
Heat tolerance index [HTI = (PG Heat *PG Control )/(PG Average ) 2 ] is an important trait to consider, as it takes into account both the percent germination under heat stress and under control conditions while comparing each accession to the population average, thus giving a ranking among all accessions evaluated. An accession with a high HTI will have higher percent germination under both conditions, making it a useful accession to be selected for use in a commercial growing setting. HTI was significantly different among carrot accessions evaluation (F = 7.28, P < 0.0001) (Table 3) with a population mean of 0.74 and a range from 0.0 to 1.45 (Fig. 3D). PI 643114 (United States, 1.45) and PI 652208 (China, 1.4) had the highest HTI, suggesting that they were highly heat tolerant and had high percent germination under nonstress conditions, whereas inbred lines B493B and B7254B, along with PI 652354 (Turkey), had the lowest HTI values (0.0-0.06).
The accessions used in this study demonstrate a wide range of phenotypic variation for each of the heat stress parameters measured. Exposure to 35°C significantly reduced germination for most of the carrot diversity panel, agreeing with an earlier study (Nascimento et al., 2008). This evaluation reports a similar range of variation for heat tolerance as Nascimento et al. (2008), and evaluated nearly three times additional carrot accessions, including a broad range of cultivated open pollinated varieties. There were differences between these two evaluations for the four overlapping accessions ('Brasilia', PI 261782, PI 285613, and PI 537093) that may be attributed to differences in the seed lot and/or the number of replications that were used. These results suggest the value of evaluating a large number of diverse carrot accessions for heat stress, as has been suggested for salt stress in carrot (Bolton and Simon, 2019).
Heat tolerance according to geographic origin. Significant differences were observed for seed germination under control conditions and for all heat germination parameters among the 14 different geographic origins of carrot accessions (P values < 0.0001) ( Table 4). When comparing cultivated, wild, inbred, and hybrid accessions, accessions from Eastern and Central Asia demonstrated an average higher heat tolerance at the germination stage. Accessions from Eastern Asia had a mean AD of 13.96% and a range from -12.3% to 36.8%, a mean II of 14.5, and a range from -22.3% to 39.1%, a mean RHT of 0.86 and a range from 0.61 to 1.22, and a mean HTI of 0.82, and a range from 0.26 to 1.40. Accessions from Central Asia had similar values and ranges to those from Eastern Asia with a mean AD of 13.7% and a range from -5.0% to 30.5%, a mean II of 15.4% and a range from -17.8% to 44.1%, a mean RHT of 0.85 and a range from 0.56 to 1.17, and a mean HTI of 0.83 and a range from 0.29 to 1.38. Accessions from Eastern Africa and Southern Europe only included one and six accessions, respectively, but were among the most heat sensitive, having RHT and HTI values of 0.52 or lower along with AD and II values (41.4% to 50.6%) ( Table 5). Although accessions from Central and Eastern Asia were on average more heat tolerant, it is important to note the wide range of phenotypic variation within a single region and thus the need to evaluate multiple accessions from within a region when possible.
Heat tolerance according to domestication status and root color. No significant difference was observed for mean percent germination under nonstress conditions in comparing cultivated PIs (82.0%), wild PIs (80.2%), and inbred lines (78.4%) ( Table 6). Under heat stress, cultivated PIs demonstrated a significantly higher tolerance than the wild PIs and inbred lines, with a mean percent germination under heat of 64.3% and a range from 12.5% to 97.5%, a mean AD of 17.7%, mean II of 20.0%, mean RHT of 0.80, and mean HTI of 0.81. An important observation to note is that most wild PIs originated from Western Asia (Table 7) and the inbred lines are exclusively from the USDA breeding program, potentially accounting for the trends we observed. No significant difference in heat tolerance was observed between the wild PIs and inbred lines for all traits, and most accessions from  (Table 6). It is important to note that the number of samples for each color category were not equal and were not equally distributed across geographic origins, thus the trends reported here should be confirmed with larger sample sizes.
Broad-sense heritability. A high broadsense heritability (H 2 ) was observed for germination under nonstress conditions (H 2 = 0.88), for germination under heat stress (H 2 = 0.79), and for HTI (H 2 = 0.86), indicating a significant genetic basis for these traits. Heritability values for AD (H 2 = 0.66), II (H 2 = 0.66), and RHT (H 2 = 0.64) all were moderately high, suggesting a genetic basis for these traits. Interestingly, the heritability values for heat stress germination were lower than that observed in the same set of accessions for salt stress germination (Bolton and Simon, 2019). These differences in heritability suggest that either there is a smaller genetic component for heat tolerance germination in carrot, a larger environmental component that accounts for the phenotypic variation, or that it is a more genetically complex trait than salt tolerance germination with multiple genes responsible for the phenotype. These genetic factors warrant further investigation with the goal of identifying significant quantitative trait loci associated with heat tolerance at the germination stage.  Correlation among heat tolerance parameters, seed weight, and salt tolerance. Pearson correlation coefficients calculated for each of the heat tolerance parameters along with hundred seed weight (HSW) of each accession (Table 7) indicated that germination under nonstress conditions was highly correlated to the HTI (r = 0.74), but the correlation with germination under heat stress conditions (r = 0.50) was lower. Germination without stress was not strongly correlated to the other parameters evaluated (r = -0.20 to 0.16). These results indicate that percent germination under nonstress conditions does not predict heat tolerance germination in carrot. HSW had no correlation with percent germination under heat stress (r = 0.00) and a very weak negative correlation with germination under nonstress conditions (r = -0.20). These results were similar to those observed for salt tolerance germination where nonstress germination was also correlated with salt tolerance index (STI) (r = 0.54) and with stress salt stress (r = 0.40). Germination under salt stress was slightly  (Bolton and Simon, 2019). These data suggest that heat tolerance parameters and salt tolerance parameters follow similar trends, with heat tolerance having slightly stronger correlations among those parameters. Pearson correlation between HTI and the STI values calculated in Bolton and Simon (2019) display a strong correlation (0.69) between the two traits, suggesting that many of the accessions tolerant to one stress are also tolerant to the other. These results are not surprising, as heat stress and salt stress have similar effects on seed physiology and often cause similar stress responses. Although not evaluated in this study, it will be interesting to compare heat tolerance of these accessions in the field to heat tolerance at the seed germination stage and to determine if there is any correlation between the two studies.

Conclusions
This study identified a wide range of phenotypic variation for heat tolerance at the germination stage in a diverse collection of carrot germplasm. Five cultivated carrot accessions representing four countries (PI 643114, United States; PI 652208, China; PI 652248, Russia; and PIs 652400 and 654203, Turkey) were identified as the most heat-tolerant accessions, whereas inbred lines B493B and B7254B, along with wild accessions PI 279764 (Libya) and PI 652354 (Turkey) were identified as heat-sensitive accessions. The wide geographic range from which all the tolerant accessions originated was particularly surprising, as it suggests that heat tolerance has been under selection in multiple regions of the world where carrot is cultivated. This study adds to the current body of research for heat tolerance in carrot seed germination by identifying an optimal temperature for screening and measuring a high heritability of tolerance in a large collection of germplasm from diverse global regions. HTI was confirmed to be a particularly important measure of tolerance. This evaluation, coupled with recent evaluations of salt tolerance in the same diverse germplasm, provides valuable information for future studies of abiotic stress in carrot.  Table 1. Carrot accession, root color, country of origin, domestication status (DS), mean percent germination without heat stress (Nonstress) ± SE, mean percent germination with 35°C heat stress (Stress) ± SE, mean absolute decrease (AD), mean inhibition index (II), relative heat tolerance (RHT), mean heat tolerance index (HTI), hundred seed weight (HSW), and rank based on HTI. (Continued) Carrot accession, root color, country of origin, domestication status (DS), mean percent germination without heat stress (Nonstress) ± SE, mean percent germination with 35°C heat stress (Stress) ± SE, mean absolute decrease (AD), mean inhibition index (II), relative heat tolerance (RHT), mean heat tolerance index (HTI), hundred seed weight (HSW), and rank based on HTI.


extfieldsofstudy: Biology Medicine

s2fieldsofstudy:
Agricultural And Food Sciences
Biology

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Relationships between Hha1 Calpastatin Gene Polymorphism, Growth Performance, and Meat Characteristics of Awassi Sheep

Simple Summary The Awassi sheep is a very important breed, and using molecular selection to enhance meat production is important. Following genotyping of Awassi sheep housed at two different research stations in Jordan, three genotypes were identified for the calpastatin Hha1 gene. Following a fattening trial, the polymorphic calpastatin gene affected final (marketing) body weight and longissimus muscle width. Hha1 restriction sites found in Calpastatin gene can be used for molecular marker-assisted selection in Awassi for meat purposes. Abstract Advances in molecular genetics have allowed the identification of genes that can enhance livestock production. The aim of this study was to investigate possible relationships between the calpastatin (CAST) Hha1 gene polymorphisms and growth performance, carcass characteristics, and meat quality in Awassi sheep. A total of 87 blood samples were collected from two-week-old Awassi ram lambs. The amplification of the CAST Hha1 gene yielded a fragment of 622 bp. Three CAST genotypes were found in Awassi sheep: MM for two fragments (385 bp and 281 bp), MN for three fragments (622 bp, 385 bp, and 281 bp), and NN for only one fragment (622 bp). The M and N allele frequencies of the CAST Hha1 genotypes were 0.765 and 0.235, respectively, while the genotypic frequencies of MM, MN, and NN were 0.586, 0.356, and 0.057, respectively. Based on CAST Hha1 gene polymorphisms, three groups of lambs (MM: n = 8; MN: n = 6; and NN: n = 3 genotypes) were subjected to a fattening period of 70 days to investigate growth performance and meat characteristics. Only the final body weight and longissimus muscle width were significantly different between the three genotypes, while no significant differences were detected in any other carcass characteristics and meat quality parameters. In this study, new variants were observed in CAST using the Hha1 restriction site, potentially assisting in Awassi sheep breeding and selection programs to improve final body weight and longissimus muscle width.

Introduction
Awassi sheep is a multi-purpose, fat-tailed sheep breed [1], predominantly found in Jordan and the Middle East [1]. This breed is well-adapted to harsh environmental conditions [2], and is used for both meat and milk production [1]. High variation has been observed in the growth performance of Awassi sheep [1,2]. However, in recent years, substantial advances have been made through the application of molecular genetics in the identification of different chromosomal regions and loci that affect traits of interest in livestock production [3]. This has provided opportunities to launch genetic improvement programs in livestock by the direct selection of genes or genomic regions that affect economically-profitable traits through marker-assisted selection and gene introgression [4]. Growth traits and carcass characteristics are controlled by multiple genes. Calpastatin (CAST), for example, plays a significant role in growth traits and carcass characteristics [5]. CAST works by inhibiting protease enzymes that degrade muscle protein, and influences meat production, tenderness, and quality [6]. The effects of CAST gene polymorphism on growth performance, carcass characteristics, and meat quality have not been fully investigated in Awassi sheep. Therefore, this study was conducted to investigate possible relationships between the CAST Hha1 gene polymorphisms and growth performance, carcass characteristics, and meat quality in Awassi sheep.

Materials and Methods
All procedures used in this study were approved by the Animal Care and Use Committee (ACUC) at Jordan University of Science and Technology, Jordan, approval Number 14/5/5/145.

Genotyping and PCR Analysis
A total of 87 blood samples were collected from two-week-old Awassi ram lambs housed at two experimental sheep breeding stations: the National Agricultural Research Center (NARC), Al Khanasry Research Station (42 ram lambs), and the Jordan University of Science and Technology Center (JUST) for Research and Production (45 ram lambs), both located in the northern part of Jordan. Blood samples were stored at 20 • C until DNA extraction was performed using the E.Z.N.A Blood DNA kit (Omega Bio-tek, United States), and the quality of isolated DNA was tested using 1.5% agarose gel electrophoresis.
Polymerase Chain Reaction-Restricted Fragment Length Polymorphism (PCR-RFLP) genotyping was used as previously described [7,8] to find new possible polymorphisms in the region between exons 61 bp 1C, 88 bp 1D, and 473 bp of the CAST gene previously studied [8]. A 622 bp amplicon was amplified using forward 5 -TGGGGCCCAATGACGCCATCGATG-3 and reverse 5 -GGTGG AGCAGCACTTCTGATCACC-3 primers on the Life Pro Thermal Cycler (Hangzhou Bioer Technology Co., Hangzhou, China). The optimum annealing temperature for PCR was determined empirically using gradient PCR, using reaction mix and conditions as described previously [7,8]. Briefly, initial denaturation was conducted at 95 • C for 3 min, followed by 35 cycles of annealing at 63 • C for 50 s, polymerization at 72 • C for 60 s, and a final extension at 72 • C for 10 min. Then 10 µL of the PCR product was digested with Hha1 restriction enzyme at 37 • C for 12 h, and resolved on 2% agarose gel, as described [7]. One PCR product from each different genotype of the CAST gene was purified and sequenced in both directions to confirm the detected genotypes, using 3730 × l DNA Analyzer and Big Dye Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific, United States).

Fattening Trial and Meat Evaluation
Depending on the detected CAST gene genotypes, three groups of lambs (MM: n = 8; MN: n = 6; and NN: n = 3) were subjected to a fattening period of 70 days to investigate growth performance and meat characteristics. During the fattening period, lambs were housed individually in shaded pens (1.5 m × 1.75 m). All lambs were introduced slowly to the fattening diet, which contained 16% crude protein and 2.78 Mcal metabolizable energy/kg [9], composed of 15% soybean, 61.4% barley, 21% wheat straw, 1.5% salt, 0.1% limestone, and 0.1% minerals and vitamins. The diet as a total mixed ration (TMR) and fresh drinking water were offered ad libitum. Fresh feed and leftovers were weighed daily for the calculation of feed intake and feed efficiency. Live body weight was recorded biweekly.
At the end of the fattening period, all lambs were slaughtered for the evaluation of carcass traits and meat quality, as previously described [10][11][12]. Briefly, carcasses were divided into four parts, namely shoulder, rack, loin, and leg cuts, in addition to the fat tail and the rib-eye area, fat depth, tissue depth, rib fat depth, eye muscle width, eye muscle depth, eye muscle area, and leg fat depth, measured as previously described [10,12]. The right leg was dissected to determine muscle, bone, subcutaneous Animals 2019, 9, 667 3 of 8 fat, and intermuscular fat components. Longissimus muscles were excised from the right side of loin cuts, cleaned from all subcutaneous fat, vacuum-packaged, and frozen at −20 • C for meat quality measurements, as described [13]. Meat quality parameters were Warner-Bratzler shear force values for cooked meat samples, water holding capacity, cooking loss, and color coordinates (whiteness, redness, yellowness) [10,12,13].

Statistical Analysis
Data were analyzed using the general linear model (GLM) of SAS (version 8.1, SAS Inc., Cary, NC, USA). The genotype was inserted as the only fixed effect in the model. The initial body weight was inserted as a covariate for the following traits: final body weight, fasting live weight, hot carcass weight, cold carcass weight, dressing percentage, and average daily gain. Dry matter intake, feed conversion ratio, carcass cut, dissected leg, non-carcass components, and meat quality parameters were also analyzed using the GLM procedure of SAS. Least square means of the GLM procedure of SAS was used to further identify significant differences among the means. Significant differences were considered at p ≤ 0.05.

Genotyping of Awassi Ram Lambs for the CAST Gene
The Hha1 calpastatin gene 622 bp PCR fragment, as previously measured [8] by the ladder on a 2% agarose gel, was sequenced following purification ( Figure 1). Three genotypes were found in Awassi sheep as shown in Figure 2A: MM or TT genotypes of two fragments (385 bp and 281 bp), MN or CT genotype of three fragments (622 bp, 385 bp, 281 bp), and NN or CC genotype of only one fragment (622 bp), by Hha1 restriction enzyme analysis. The M or T and N or C allele frequencies of the CAST Hha1 genotypes were 0.765 and 0.235, respectively, while the genotypic frequencies of NN, MN, and MM were 0.057, 0.356 and 0.586, respectively. To our knowledge, there are no reports that have investigated the different restriction sites found in the ovine CAST gene using the Hha1 variant, as shown on animal 66 ( Figure 2B), which showed a rare variant where a 600 bp fragment was observed.

Evaluation of Awassi Fattening Response to Various Genotypes of the CAST Gene
Following a 70 day fattening period for the Awassi ram lambs, significant differences were observed between CAST genotypes for final body weight ( Table 1). The MM genotype had the highest body weight, followed by MN and NN. Fasting body weight, average daily gain, dry matter intake, and feed conversion ratio were non-significantly affected by the Hha1 genotypes. However, overall weight gain (data not shown) was greater in MM, which was significantly different from either MN or NN genotypes. These results are contradictory to previous findings, where a strong association between the calpastatin gene and body weight was reported in male sheep in Indonesia, with the MN showing higher (p < 0.017) body weights than NN genotype ram lambs [14]. Jawasreh et al. [8] found that live weight and average daily gain were higher in Awassi ram lambs that carry the MN genotype when compared to the MM genotype. The size of skeletal muscles is largely dependent on the balance between the rate of degradation and the rate of synthesis, as well as the inhibitory effect of the calpastatin for the calpains [15]. This may result in a decreased degradation rate of protein and an increased rate of protein synthesis in skeletal muscles. The identified polymorphisms for the calpastatin gene, using Hha1, show rare occurrence, and might contribute less than other polymorphic forms using MspI [8].
one fragment (622 bp), by Hha1 restriction enzyme analysis. The M or T and N or C allele frequencies of the CAST Hha1 genotypes were 0.765 and 0.235, respectively, while the genotypic frequencies of NN, MN, and MM were 0.057, 0.356 and 0.586, respectively. To our knowledge, there are no reports that have investigated the different restriction sites found in the ovine CAST gene using the Hha1 variant, as shown on animal 66 ( Figure 2B), which showed a rare variant where a 600 bp fragment was observed.

Evaluation of Awassi Fattening Response to Various Genotypes of the CAST Gene
Following a 70 day fattening period for the Awassi ram lambs, significant differences were observed between CAST genotypes for final body weight ( Table 1). The MM genotype had the highest body weight, followed by MN and NN. Fasting body weight, average daily gain, dry matter intake, and feed conversion ratio were non-significantly affected by the Hha1 genotypes. However, overall weight gain (data not shown) was greater in MM, which was significantly different from either MN or NN genotypes. These results are contradictory to previous findings, where a strong The three CAST genotypes did not (p > 0.05) influence hot carcass weight, cold carcass weight, dressing percentage, non-carcass components (heart, liver, spleen, kidney, kidney fat, mesenteric fat, testis, fat tail, lung, and trachea), and carcass cuts weights (shoulders, leg, loin) ( Table 1). Dissected leg Animals 2019, 9, 667 5 of 8 cuts were also comparable (p > 0.05) in their intermuscular fat, subcutaneous fat, total fat, total lean, and total bone. No significant differences were found in longissimus muscle weights among the three genotypes (Table 1). With Awassi sheep, the high population variability, alongside the rarity of the CAST mutations, might actually contribute to the discrepancy between ours and others results with regard to the contribution of the CAST gene in muscling. Table 1. Least-square means (± standard error (SE)) for growth performance and carcass components, according to the different genotypes of the CAST/Hha1 gene in Awassi ram lambs. The longissimus muscle widths differed slightly (p = 0.0518) between the genotypes with the highest width, found in the MN genotype followed by MM ( Table 2). The longissimus muscle width in the MM and MN genotypes were both significantly different from the NN genotype (p = 0.05). The longissimus muscle area, tissue depth, fat depth, rib fat depth, fat thickness, muscle area, width, and depth were comparable (p > 0.05) among the different CAST genotypes ( Table 2). The rarity of the genotypes analyzed in this study partly contributed to the low number of animals analyzed, and thus a larger scale study might show higher levels of significance for the effect of the calpastatin genotypes on the final body weights and longissimus muscle width in Awassi lambs. Jawasreh et al. [8] found that Awassi sheep that carried the MM genotype had a higher total bone weight than MN genotypes, while lambs that carry the MN genotype had a higher (p ≤ 0.05) meat-to-bone ratio than the MM genotype. In Kivircik sheep, Yilmaz et al. [16] reported significant differences among calpastatin genotypes in back fat thickness and skin and backfat thickness values of the loin eye muscle. In addition, Yilmaz et al. [16] also found that Kivircik lambs with MN and MM genotype had lower carcass fat than those of the NN genotype. In a study carried out on Afshari lambs, no correlation between calpastatin genotypes and carcass traits was reported [17]. Greguła-Kania [18] found that the longest muscle (M. longissimus lumborum) and fat thickness were not affected by CAST genotypes in lambs at 80 and 120 days of age. Also, there was no association between different CAST gene variants and carcass weight or dressing percentage of thin-tail sheep [19]. The lack of changes in the fat depth and thickness in Awassi sheep could be due to the way Awassi sheep mobilize their fat reserves to their tails rather than to their intra-or intermuscular spaces. Altogether, these results show the breed distinction in their response the various CAST gene mutations, and thus the need to investigate the CAST gene with other restriction enzymes to identify further mutations and explore their significance. Meat quality characteristics in each CAST genotype in Awassi ram lambs are shown in Table 3. All meat quality parameters were similar (p > 0.05) among the MM, MN and NN CAST genotypes. These results are in agreement with Dagong et al. [19], who reported a non-significant difference among calpastatin genotypes in meat tenderness, pH, water holding capacity, and cooking loss of thin-tail sheep. Inconsistent with our findings, many studies revealed a significant effect of the variation in the calpastatin gene on meat quality in Awassi sheep [8]. The size of skeletal muscle fibers, the muscle protein synthesis rate, and the muscle protein degradation rate are among the characteristics that are the most affected by calpastatin gene polymorphism in pigs [20]. With the calpain system playing an important role in muscle fiber growth [20,21], and with the calpain system activity decreasing with the increase in CAST gene activity [20], the calpain activity may play an imperative role that is necessary for cell proliferation, myoblast fusion, fibers growth, and fiber numbers [22]. The calpain system influence can also be observed in fiber numbers, by modulating myoblast fusion and changing the myoblast proliferation rate [23]. Table 3. Least-square means (± SE) for meat quality characteristics, according to different genotypes of the CAST Hha1 gene in Awassi ram lambs.