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Identification of WUSCHEL-related homeobox (WOX) gene family members and determination of their expression profiles during somatic embryogenesis in Phoebe bournei

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  • WUSCHEL-related homeobox (WOX) transcription factor (TF)-encoding genes play crucial roles during embryo development. The function of WOX genes in embryonic development has been thoroughly studied in Arabidopsis thaliana, but little is known about their function in woody species, especially Phoebe bournei, an endemic and endangered species in China. In the present study, a total of 15 WOX genes were identified in P. bournei, and phylogenetic analysis resulted in their assignment to three typical clades: an ancient clade, an intermediate clade, and a modern/WUS clade. The gene structure and sequence characteristics and the physicochemical properties of WOX proteins were also analyzed. Promoter prediction indicated that WOX genes are likely involved in plant growth and development and hormone responses. Subsequently, we evaluated the expression patterns of WOX genes in response to auxin (IAA), abscisic acid (ABA), and methyl jasmonate (MeJA) treatments. According to tissue-specific expression patterns, we screened nine WOX genes that were present in embryonic calli and that might participate in the somatic embryogenesis (SE) of P. bournei. Furthermore, the expression profiles of these nine WOX genes during three phases of embryogenic calli development and three phases of somatic embryo development, namely, spheroid embryogenesis, immature cotyledon-producing embryogenesis and mature cotyledon-producing embryogenesis, were monitored. Overall, we systematically analyzed the expression patterns of WOX genes in P. bournei during SE, the information of which provides a basis for further elucidating the molecular mechanism through which WOX TFs function in P. bournei embryo development.
  • Fenugreek (Trigonella foenum-graecum L.) is a dicotyledonous, annual aoutogamouse self-polinating and diploid (2n = 16) legume belonging to the Fabaceae family[1]. Trigonella foenum-graecum L. is probably indigenous to the eastern Mediterranean region, western Asia, and India, but its natural distribution is hard to ascertain, as it has been widely cultivated since antiquity, the first written record dating back as far as 400 BC. Its cultivation spread to China, Ethiopia, Europe and the southern part of the former Soviet Union and throughout the Arab world[2,3].

    Ethiopia is an original homeland of a fenugreek subspecies known as the Mediterranean ecotype, which has a distribution extending from Eritrea to Somalia[4]. In Ethiopia, fenugreek growing regions are located at 1,800−2,300 m.a.s.l. and are characterized by a subtropical climate, including wet and dry seasons[5]. Ethiopia is one of the countries in the world where fenugreek is most widely cultivated[3,6]. The production and distribution of fenugreek is similar to those of other cool season food legumes such as faba bean, field pea, lentil, chickpea, and grass pea[7]. During the 2014 cropping season, fenugreek covered 20,524.39 hectares in the country with an average yield of 1.224 t/ha. Fenugreek ranks 9th among highland pulses in terms of production in Ethiopia.

    Fenugreek is a multi-purpose crop which is utilized as food, feed, spices and medicinal plant, and the oil is used in perfumery in France[8]. Fenugreek is one of oldest medicinal plants; its leaves, seeds and sometimes even the whole plant have been used as medicine[9]. Extracts from fenugreek seed powders are used for treating disease and a variety of ailments, including wounds, skin irritations, head lice, and high blood sugar[2]. Fenugreek seed extract can be used as an anti-diabetic to lower blood sugar and cholesterol levels[10]. Extracts from fenugreek seeds can be used to make teas to reduce fever and menstrual pains, or as ointments to treat skin infections and irritation[11]. Ground seeds are often used to give a maple flavor to sweets and candy. Taken internally, fenugreek is used to treat bronchitis, coughs, respiratory problems and sinus conditions[12]. Fenugreek, as most of the species of the genus Trigonella, is strongly anti-fungal and can be used as an insect repellent[11].

    Both ripened and unripened seeds, as well as green leaves, have been used as a food in south and central Asian countries[13]. The protein content of Fenugreek is high (43.8 g/100 g) and most of the time it is used to supplement low-protein foods such as cereal crops[14]. The leaf of fenugreek contains 86.1% moisture, 4.4% protein, 0.9% fats, 1.5% minerals, 1.1% fiber and 6.0% carbohydrates. Its mineral and vitamin contents are calcium, phosphorus, iron, carotene, riboflavin, niacin and vitamin C[15]. The seed contains 13.7% moisture, 26.2% protein, 5.8% fat, 3.0% mineral, 7.2% fiber and 44.1% carbohydrate[16].

    It enriches soil through symbiosis with micro-organisms, which fix atmospheric nitrogen[17]. It is rich in protein (25.5%), fats (5%−10%), available carbohydrate (45%−60%), mucilaginous matter (20%) and saponins (4.8%)[18]. Fenugreek stands as a major legume crop for generating cash, it may also create a good opportunity for the country to increase its currency reserves and generate income for poor farmers, and it could play an important role in enhancing the food and nutrition security of the country[19]. However, this important crop is neglected and underutilized that will inadvertently entail the risk of losing some important germ-plasm that has been maintained by farmers over hundreds or thousands of years. Limited information is available about the variability of fenugreek accessions and production systems in Ethiopia[20].

    Land-races or farmer varieties are important sources of genetic diversity and potential materials that could be used to enhance genetic variability and therefore serve as the basis for a formal plant breeding program[21]. Land-races are traditional varieties with distinct identities that have been locally adapted and cultivated by farmers over centuries, without assistance from formal crop improvement programs; such varieties are a major source of genes for the development of new varieties[22]. Land-races often exhibit a high capacity to tolerate biotic and a biotic stresses, resulting in high yield stability (consistence productivity from year-to-year) under low input agricultural systems[23].

    In Ethiopia, farmers are producing the crop from seed stocks of land-races that are adapted to specific agroecological conditions and only six improved varieties have been released for cultivation, all from Sinana, Sirinka and Debreziet Agricultural Research Centres[24]. This indicates that the national agricultural research has little information on genetic variability of fenugreek in agroecological and morpho agronomic traits as compared to other highland pulse crops. It is necessary to assess the genetic variability of the fenugreek accessions across diverse agroecological conditions that could help to improve fenugreek. Therefore, the study under taken on genetic variability of fenugreek accessions from different agroecological and morpho-agronomic traits has a paramount importance for improvement of the crop and to design appropriate breeding methods.

    The study was conducted at Raare Haramaya University's experimental site in Ethiopia during the 2016 cropping season, at a latitude of 9°26′ N, a longitude of 42°3′ E, and an altitude of 1,980 m.a.s.l. Haramaya University is roughly 520 kilometres east of Addis Ababa. The location is in a bimodal rainfall sub-humid mid-altitude agro-climatic zone. The long rainy season lasts from July to September, while the short rainy season lasts from October to December. In 2016, 377.7 mm of precipitation fell and temperatures ranged from 11.3 to 23.7 °C. The soil at the test site is fuvisols with a sandy clay loam texture. In the experiment, 155 accessions from Ethiopian Biodiversity institute national gene bank and four standard checks, as well as one local accession were used. Table 1 provides a summary of the accessions.

    Table 1.  Accessions collected from different geographic regions of Ethiopia.
    No.Geographic regionAZNoAAL (m.a.s.l.)
    1Northern EthiopiaDifferent zones of Tigray82,410
    2Northeastern EthiopiaNorth and South Wollo161,910−2,880
    3Northwestern EthiopiaSouth and North Gondar, East and West Gojam, Metekel962,330−2,700
    4Central EthiopiaArsi and North Shewa222,000−2,700
    5Western EthiopiaEast and West Wellega21,950
    6Southeastern EthiopiaBale and Borena41,730−2,560
    7Southwestern EthiopiaGamogofa2Not known
    8Eastern EthiopiaEast and West Hararghe51,700
    9Released varieties4
    10Local check cultivar1
    AL = Altitude range, NoA = Number of accessions, AZ= Administrative zone. Source: Ethiopian Biodiversity Institute (EBI).
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    Table 2.  Genetic variation of accessions was estimated using formula described in the following table.
    To calculate Formula Reference
    GDCG ni=1(XijXik) Sneath and Sokal (1973)
    GA GA (K )(σp)(h2 ),
    GA(%) (GA) X100
    Fehr (1987)
    PCA To find characters account more for total variation SAS software version 9.1 (SAS, 2000) and Statistica basic–7
    PCA = Principal component analysis, GA = Genetic advance as part of the mean, GDCG = Genetic divergence and clustering of genotypes, variations, (k = selection differential (at 5% selection intensity, k = 2.063).
     | Show Table
    DownLoad: CSV

    Due to the 160 accessions used, the experiment used an augmented block design. Replications were not possible due to the small number of seeds, but checks were replicated in each block. The experiment has five blocks which contain 36 entries, including four standard checks (the 'Chala', 'Hunda'ol', 'Eibbsa', 'FGP# = 1', and local checks). While each accession was assigned only once during the experiment, the checks were distributed randomly within each block and replicated once in each block. A plot was divided into two rows, each measuring 2 m in length, with each row 0.25 m, making each plot 2 m × 2 m × 0.25 m, or 1 m2. There were 40 plants total in each plot (2 m × 2 rows × 10 cm) due to the 10 cm space between plants.

    Data collection was conducted using plants that were cultivated in both rows. All other agronomic procedures were followed as per the recommendation for fenugreek. Five plants were chosen at random from each plot, and data collected include their days to flowering, days to maturity, seed yield (kg/ha), thousand seed weight (g), the number of primary branches, plant height at flowering (cm), the number of pods per plant, the number of secondary branches, average pod length (cm), the number of seeds per pod, and seed yield per plant (g/plant). All data sets were subjected to analysis of variance (ANOVA) using the Statistical Package for Augmented Design (SPAD) softwareware[25].

    The analysis of variance (ANOVA) results are shown in (Table 3). The ANOVA results revealed highly significant (p < 0.01) differences among entries for days to 50% flowering, days to 90% maturity, number of pods per plant, number of seeds per pod, number of primary branches, number of secondary branches, thousand seed weight, plant height at flowering, and seed yield kg per hectare, as well as significant (p < 0.05) differences for average pod length and seed yield per plant.

    Table 3.  Mean squares from analysis of variance for 11 traits of 160 fenugreek accessions.
    Trait Block (4) Treatment (159) Among checks (4) Among tests (154) Tests vs checks (1) Error (16) CV (%)
    DF 2.74ns 9.59** 9.38** 17.14** 11.1** 1.39 2.30
    DM 48.90ns 78.17** 102.08** 68.38** 1489.92** 25.48 4.19
    PHF (cm) 73.97** 58.46** 56.66** 47.44** 1763.13** 10.63 10.63
    NPPP 282.34** 62.86** 7.41ns 60.57** 637.20** 3.65 13.80
    NSPP 1.45ns 4.75** 2.93ns 4.76** 10.06** 1.14 8.17
    NPB 0.04ns 1.47** 0.27** 1.05** 71.17** 0.05 9.56
    NSB 0.78** 0.61** 0.10ns 0.62** 1.41** 0.11 19.67
    APL (cm) 0.37ns 1.10* 1.50ns 1.08* 1.99ns 0.53 7.61
    SYPP (g) 0.57ns 0.99* 0.77ns 1.00* 0.42ns 0.45 17.75
    Yhkg 21,746.3ns 130778.6** 130256** 131178** 71357.6* 15973 12.46
    TSW (g) 11.21ns 24.09** 16.68ns 24.20** 37.45* 6.56 13.65
    ns = non-significant, * and ** = significant and highly significant at p < 0.05 and p < 0.01, respectively. Numbers in parenthesis represented degree of freedom. DF = Days to 50% flowering, DM = Days to 90% maturity, PHF (cm) = Plant height at flowering, NPPP = Number of pods per plant, NSPP = Number of seeds per pod, NPB = Number of primary branches, NSB = Number of secondary branches, APL (cm) = Average pod length, SYPP (g) = Seed yield per plant in gram, Yhkg = Yield in kg per hectare, TSW (g) = Thousand seed weight in gram and CV (%) = Coefficient of variation in percentage.
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    The four released varieties and one local land-race used as standard checks revealed highly significant differences (p < 0.01) in the number of primary branches, days to 50% flowering, days to 90% maturity, seed yield kg per hectare, and plant height at flowering, while the standard checks revealed non-significant differences in the other traits. The ANOVA also revealed highly significant (p < 0.01) differences in days to 50% flowering, days to 90% maturity, plant height at flowering, number of pods per plant, number of seeds per pod, number of primary branches, and number of secondary branches between check varieties and entries/tests, as well as a significant (p < 0.05) difference in thousand seed weight and seed yield kg per hectare. The mean squares for seed yield per plant and average pod length for check varieties vs test entries were non-significant.

    The presence of adequate variations was demonstrated by the presence of significant differences among test genotypes for all traits. The observed results indicated that the selected genotypes had a higher chance of improving the traits of interest. Other researchers found significant differences in days to flowering, days to maturity, plant height at 90% maturity, number of primary branches, number of secondary branches, number of pods per plant, number of seed per plant, thousand seed weight, and seed yield among fenugreek accessions[24,26]. Scholar reported existence of significant differences for number of primary branches, number of secondary branches, plant height, and number of seeds per pod[27]. Study conducted among 50 fenugreek genotypes significant variation observed in grain yield, number of pods per plant, seed yield per plant, and eight other traits[28]. Other investigators reported among 40 fenugreek accessions and found significant differences in plant height, primary branches, days of flowering, pods per plant, days to maturity, seed yield per plant, and thousand seed weight[29].

    In all traits, there was a wide range of mean performance differences among 160 fenugreek accessions. Days to 50% flowering ranged from 41.14 to 57.04 d, with an overall mean of 51.34 days, while days to 90% maturity ranged from 97.67 to 138.21 d, with an overall mean of 119.32 d (Table 4). Among the four released varieties, 'FGP#1 = 1' was the earliest to attain 50% flowering (48.6 d) and days to 90% maturity (123.3 d) with a low seed yield 888.33 kg/ha while variety 'Ebbisa' was the late to reach 50% flowering (53 d) and days to 90% maturity 133.68 d with a high yield 1,272.12 kg/ha. Accessions flowered and matured 3.125% and 61.875% earlier than the earliest released varieties, respectively.

    Table 4.  Mean performance for days to flowering and maturity in respect to 12 collection zones, 58 woredas of eight geographic regions.
    No. Zone Geo. Reg. Altitude
    (m.a.s.l.)
    No.
    woredas
    No.
    accessions
    Days to 50% flowering Days to 90% maturity
    Min Max Mean SD CV
    (%)
    Min Max Mean SD CV
    (%)
    1ArsiCE2,000−2,55061142.2457.0450.884.298.40103.97135.85117.159.888.40
    2ShewaCE2,110−2,70071149.0454.6452.671.703.20111.85133.21122.095.964.80
    3WellegaWE1,9502250.2452.0451.141.272.40118.97123.09121.032.912.40
    4BaleSEE1,850−2,5602344.2453.2447.345.1010.70106.97120.07112.067.026.20
    5HarargheEE1,7004552.2457.0455.001.723.10109.67125.39121.486.635.40
    6BorenaSEE1,7301154.24119.67
    7GojamNWE2,380−2,510114741.9656.0451.183.196.2098.17138.21118.059.588.10
    8WelloNEE1,910−2,88071641.1456.2449.344.318.70100.71132.21118.899.447.90
    9GondarNWE2,330−2,700104842.0456.2451.172.384.6097.67133.15119.038.537.10
    10TigrayNE24106846.0456.6452.063.446.60105.85131.21120.579.117.50
    11MetekelNWENA1152.96126.15
    12GamogofaSWENA2253.0453.0453.040.000.00122.95127.35125.153.112.40
    13Released448.6053.2050.702.134.20123.30133.68128.204.753.70
    14Local150.40124.06
    OverallMinimum41.1497.67
    Maximum57.04138.21
    Mean51.34119.32
    SD3.068.52
    CV (%)2.304.19
    Geo. Reg. = Geographic Region, Min = Minimum value, Max = Maximum value, SD = Standard deviation, CV (%) = Coefficient of Variation in percent, NA = Altitude not recorded, CE = Central Ethiopia, WE = Western Ethiopia, EE = Eastern Ethiopia, SEE = South-east Ethiopia, NEE = North-east Ethiopia, NWE, = Northwest Ethiopia, NE = Northern Ethiopia, SE = Southern Ethiopia.
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    Bale 47.34, 112.06 and Wello 49.34, 118.89 accessions were early for flowering and maturity, whereas Gamogofa, Arsi, Shewa, Wellega, Hararghe, Borena, Gojam, Gondar, Tigray, and Metekele accessions were late (Table 4). Early maturity accessions were obtained from moist woyna dega (mid altitude), wet dega (high land), and dry woyna dega (mid altitude) agroecologies. The variation in days to flowering and days to maturity observed among accessions provides a great opportunity for breeders to develop varieties for various agroecologies in Ethiopia. Early maturing accessions may be better suited to agroecologies with low rainfall and short duration, whereas late types may be better suited to highland areas with consistent rainfall. The current study results are consistent with those reported previously[7,24] , who found significant differences in days to flowering and days to maturity among 36 and 144 fenugreek accessions, respectively. Another study reported on 36 geographically diverse Ethiopian fenugreek accessions and found 42.5 to 52.5 d to flowering with a mean of 47.1 d and 123.5 to 162 d to maturity with a mean of 141.8 d[30].

    Tables 5 & 6 show the mean performance of 12 groups of accessions in relation to the administrative zones where they were collected. The accessions displayed a wide range of variation in plant height at flowering, ranging from 10.86 to 52.14 cm, with a mean height of 30.67 cm. Hunda.ol, the tallest check variety, had a mean plant height of 43.74 cm, and 12.9% of the accessions were taller. The number of primary and secondary branches of accessions ranged from 0.85 to 4.49 and 0.3 to 3.88, respectively, with an overall mean of 2.37 and 1.70. Hundao.la had the highest mean number of primary and secondary branches among the check varieties 4.24 and 2.05, respectively. All accessions had lower mean performance, numbers of primary branches, and plant height than the check variety with the highest mean value (Table 5). Hararghe, Bale, Metekel, and Arsi accessions had a higher mean number of secondary branches than the check variety with the highest mean value. Accessions from Tigray, Gamogofa, Gondar, Borena, Wello, Shewa, Wellega, and Gojam zones, on the other hand, had a lower mean number of secondary branches than the check variety with the highest mean value (Table 6).

    Table 5.  Mean performance of accessions for growth traits in respect to 12 collection zones, 58 woredas of eight geographic regions.
    No. Zone Geo. Reg. Altitude
    (m.a.s.l.)
    No.
    woredas
    No.
    accessions
    Plant height at flowering (cm) No. of primary branches
    Min Max Mean SD CV (%) Min Max Mean SD CV (%)
    1ArsiCE2,000−2,55071117.6645.4626.958.0829.900.854.292.431.2149.00
    2ShewaCE2,110−2,70081118.4632.9426.554.3516.401.054.252.481.0241.00
    3WellegaWE1,9502225.8728.4627.171.836.801.073.252.161.5471.00
    4BaleSEE1,850−2,5602326.0634.4630.134.2114.001.353.602.801.2645.00
    5HarargheEE1,7004517.2739.1625.528.4533.100.854.182.951.3545.00
    6BorenaSEE1,7301121.862.35
    7GojamNWE2,380−2,510134717.4648.3429.717.5925.400.953.951.870.8145.00
    8WelloNEE1,910−2,88071610.8646.1626.367.5728.700.853.352.030.9546.00
    9GondarNWE2,330−2,700114815.8752.1431.867.8324.600.864.492.041.1355.00
    10TigrayNE2,4106822.3640.8427.706.1022.000.953.311.891.0052.00
    11MetekelNWENA1130.853.21
    12GamogofaSWENA2247.1430.6438.8915.6730.001.013.412.211.7076.00
    13Released434.9243.7438.983.659.303.684.243.990.246.00
    14Local136.403.74
    OverallMinimum10.860.85
    Maximum52.144.49
    Mean30.672.37
    SD7.681.09
    CV (%)10.639.56
    Geo. Reg. = Geographic Region, Min = Minimum value, Max = Maximum value, SD = Standard Deviation, CV (%) = Coefficient of variation in percent, NA = Altitude not recorded, CE = Central Ethiopia, WE = Western Ethiopia, EE = Eastern Ethiopia, SEE = Southeast Ethiopia, NEE = Northeast Ethiopia, NWE = Northwest Ethiopia, NE = Northern Ethiopia, SE = Southern Ethiopia.
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    Table 6.  Mean performance of accessions from 12 collection zones of eight geographic regions for number of secondary branches.
    No. Zone Geo. Reg. Altitude
    (m.a.s.l.)
    No.
    woredas
    No.
    accessions
    No. of secondary branches
    Min Max Mean SD CV (%)
    1ArsiCE2,000−2,5507111.083.182.100.7937.00
    2ShewaCE2,110−2,7008110.303.881.931.2162.00
    3WellegaWE1,950221.082.781.931.2062.00
    4BaleSEE1,850−2,560231.283.882.781.3548.00
    5HarargheEE1,700451.283.882.721.1943.00
    6BorenaSEE1,730111.68
    7GojamNWE2,380−2,51013470.303.481.400.8157.00
    8WelloNEE1,910−2,8807160.302.981.620.6741.00
    9GondarNWE2,330−2,70010480.303.851.580.8654.00
    10TigrayNE2,410680.302.951.200.8369.00
    11MetekelNWENA112.15
    12GamogofaSWENA221.152.481.810.9451.00
    13Released41.822.101.960.140.70
    14Local11.78
    OverallMinimum0.30
    Maximum3.88
    Mean1.70
    SD0.91
    CV (%)19.67
    Geo.Reg. = Geographic Region, Min = Minimum value, Max = Maximum value, SD = Standard Deviation, CV (%) = Coefficient of variation in percent, NA = Altitude not recorded, CE = Central Ethiopia, WE = Western Ethiopia, EE = Eastern Ethiopia, SEE = Southeast Ethiopia, NEE = Northeast Ethiopia, NWE = Northwest Ethiopia, NE = Northern Ethiopia, SE = Southern Ethiopia.
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    Researchers reported the presence of variation among fenugreek genotypes for growth traits, which agreed with the current study findings. In line with this finding reported existence of significant differences in plant height, number of primary and secondary branches among 36 fenugreek accessions, respectively[30] . Research conducted on 15 and 40 fenugreek accessions collected from various geographic regions indicates significant differences in plant height and number of primary branches[31,29] respectively.

    The average pod length (cm) ranged from 4.32 to 12.3 cm, with a mean of 9.58 cm, and the number of pods per plant ranged from 0.19 to 39.23 pods, with a mean of 13.85 pods. The accessions obtained from the Arsi, Hararghe, Gojam, Wello, Gamogofa, and Shewa zones had mean pod lengths greater than the check varieties, but none of the groups of accessions had mean values greater than the check varieties for number of pods per plant (Table 7). Accessions had seed yields per plant ranging from 4.21 to 19.1 g with a mean of 13.07 g and seed yields per pod ranging from 0.72 to 5.91 g with a mean of 3.80 g, respectively. The accessions obtained from Wello, Metekel, Arsi, Shewa, and Bale zones had higher mean seed yield per plant than the check varieties, while only Borena accessions had higher mean values for number of seed per pod than the check varieties (Table 8). The weights of 1,000 seeds ranged from 10.05 to 36.97 g, with a mean weight of 18.75 g. The mean thousand seed weight of accessions obtained from Gamogofa, Tigray, Gondar, Wello, Hararghe, Bale, Borena, and Shewa was higher than that of released check varieties (Table 9). The observed differences in yield components among accessions suggested a higher chance of obtaining accessions with higher mean values than commercial varieties to be developed as improved varieties.

    Table 7.  Mean performance of accessions for yield components in respect to 12 collection zones, 58 woredas of eight geographic regions.
    No. Zone Geo. Reg. Altitude
    (m.a.s.l.)
    No.
    woredas
    No.
    accessions
    Average pod length (cm) No. of pods per plant
    Min Max Mean SD CV (%) Min Max Mean SD CV (%)
    1ArsiCE2,000−2,5507119.2510.8610.040.547.004.3536.6317.2411.2865.00
    2ShewaCE2,110−2,7008117.8210.609.410.718.002.6538.7313.5312.2890.00
    3WellegaWE1,950228.209.548.870.9511.005.5523.3514.4512.5987.00
    4BaleSEE1,850−2,560238.359.459.080.647.0013.0521.0516.054.3627.00
    5HarargheEE1,700458.8510.859.630.788.005.1524.2511.027.8371.00
    6BorenaSEE1,730119.756.25
    7GojamNWE2,380−2,51013478.1112.259.840.859.001.0938.7313.252.3417.00
    8WelloNEE1,910−2,8807168.5712.3210.000.9710.001.9526.8311.018.6678.00
    9GondarNWE2,330−2,70010484.3211.929.311.2213.000.9539.2313.2010.1376.00
    10TigrayNE2,410687.5310.829.331.0111.000.1926.8314.139.9370.00
    11MetekelNWENA117.836.19
    12GamogofaSWENA2210.0013.6211.812.5622.006.1924.0915.1412.6683.00
    13Released48.8010.109.350.636.7016.7219.7818.401.367.40
    14Local19.1919.08
    OverallMinimum4.320.19
    Maximum12.339.23
    Mean9.5813.85
    SD1.049.60
    CV (%)7.6113.80
    Geo. Reg. = Geographic Region, Min = Minimum value, Max = Maximum value, SD = Standard Deviation, CV (%) = Coefficient of variation in percent, NA = Altitude not recorded, CE = Central Ethiopia, WE = Western Ethiopia, EE = Eastern Ethiopia, SEE = Southeast Ethiopia, NEE = Northeast Ethiopia, NWE = Northwest Ethiopia, NE = Northern Ethiopia, SE = Southern Ethiopia.
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    Table 8.  Mean performance of accessions from 12 collection zones of eight geographic regions for yield component and yield.
    No. Zone Geo. Reg. Altitude
    (m.a.s.l.)
    No.
    woredas
    No.
    accessions
    No. of seed per pod Seed yield per plant (g)
    Min Max Mean SD CV (%) Min Max Mean SD CV (%)
    1ArsiCE2,000−2,5507119.1914.5012.981.5113.001.204.863.941.1228.00
    2ShewaCE2,110−2,70081111.2914.8213.650.987.001.954.823.900.9023.00
    3WellegaWE1,950227.4914.0010.754.6043.003.463.923.690.338.90
    4BaleSEE1,850−2,560236.4913.4910.023.5035.003.274.484.250.6415.00
    5HarargheEE1,700457.8314.8011.882.5922.003.094.473.520.5917.00
    6BorenaSEE1,7301114.591.09
    7GojamNWE2,380−2,51013474.2016.7513.252.3443.001.245.333.760.9625.00
    8WelloNEE1,910−2,8807165.2116.2012.962.3818.000.725.304.071.0626.00
    9GondarNWE2,330−2,70010485.6017.4013.282.1116.001.065.913.821.1028.00
    10TigrayNE2,410685.5915.7011.993.0525.001.984.343.540.8824.00
    11MetekelNWENA1111.353.97
    12GamogofaSWENA2212.4312.5612.490.091.000.894.252.572.3892.00
    13Released412.9814.8413.800.815.903.294.273.850.4110.60
    14Local113.124.23
    OverallMinimum4.200.72
    Maximum19.105.91
    Mean13.073.80
    SD2.231.02
    CV (%)8.1717.75
    Geo. Reg. = Geographic Region, Min = Minimum value, Max = Maximum value, SD = Standard Deviation, CV (%) = Coefficient of variation in percent, NA = Altitude not recorded, CE = Central Ethiopia, WE = Western Ethiopia, EE = Eastern Ethiopia, SEE = South-east Ethiopia, NEE = North-east Ethiopia, NWE = Northwest Ethiopia, NE = Northern Ethiopia, SE = Southern Ethiopia.
     | Show Table
    DownLoad: CSV
    Table 9.  Mean performance of accessions for yield in respect to 12 collection zones, 58 woredas of eight geographic regions.
    No. Zone Geo. Reg. Altitude
    (m.a.s.l.)
    No.
    woredas
    No.
    accessions
    Thousand seed weight (g) Yield (kg/ha )
    Min Max Mean SE CV (%) Min Max Mean SE CV (%)
    1ArsiCE2,000−2,5507116.6923.0916.344.1826.00428.121,404.221,105.40381.6834.00
    2ShewaCE2,110−2,70081115.4535.5921.565.7527.00633.571,318.85914.64249.4627.00
    3WellegaWE1,9502216.4919.3717.932.0411.00747.991,338.181,043.07417.3240.00
    4BaleSEE1,850−2,5602311.7933.6920.1211.8559.001,213.531,971.221,499.49411.5927.00
    5HarargheEE1,7004510.6933.8918.579.4951.00534.321,422.98949.41361.7138.00
    6BorenaSEE1,7301114.19250.18
    7GojamNWE2,380−2,510134710.0536.9618.194.9828.00278.772,275.331,026.24356.6334.00
    8WelloNEE1,910−2,88071610.5123.4718.394.1022.00327.521,285.65871.08367.1640.00
    9GondarNWE2,330−2,700104810.5134.2719.754.6524.00401.592,101.631,007.89396.4839.00
    10TigrayNE2,4106811.2524.3518.894.5624.00720.251,411.271,060.22252.9123.00
    11MetekelNWENA1117.811,152.38
    12GamogofaSWENA2219.5121.9120.711.708.001,048.021,444.481,246.26280.3322.00
    13Released417.2419.6018.321.095.94888.331,272.121,078.58182.4416.90
    14Local114.821,004.87
    OverallMinimum10.05250.09
    Maximum36.972,275.33
    Mean18.751,035.53
    SD5.00394.88
    CV (%)13.6512.87
    Geo. Reg. = Geographic Region, Min = Minimum value, Max = Maximum value, SD = Standard Deviation, Yield kg/ha = yield kg per hectare in, CV (%) = Coefficient of variation in percent, NA = Altitude not recorded, CE = Central Ethiopia, WE = Western Ethiopia, EE = Eastern Ethiopia, SEE = Southeast Ethiopia, NEE = Northeast Ethiopia, NWE = Northwest Ethiopia, NE = Northern Ethiopia, SE = Southern Ethiopia.
     | Show Table
    DownLoad: CSV

    The current study results are also consistent with those reported by Feysal[24], who found significant differences in number of pods per plant, number of seeds per pod, and thousand seed weight among 36 fenugreek accessions. A wide range of differences in the number of pods per plant, thousand seed weight, and seed yield per plant among 144 fenugreek accessions was reported[7]. There are significant differences in number of pods per plant and seed yield per pod among 36 fenugreek accessions collected from different parts of Ethiopia[30] and significant differences in number of pods per plant among 16 accessions.

    The minimum and maximum yields of fenugreek accessions were 250.09 and 2,275.33 kg/ha, respectively, with a mean yield of 1,035.33 kg/ha (Table 9). A total of 40 accessions outperformed the high yielding check variety, Ebbisa (1,272.12 kg/ha) by 25%. The mean yield of accessions obtained from the Bale, Arsi, Metekele, and Gamogofa zones was higher than the mean yield of check varieties, whereas accessions obtained from Tigray, Wello, Gondar, Gojam, Wellega, Borena, Shewa, and Hararghe zones had a lower mean yield than the mean yield of check varieties (Table 9).

    Accessions obtained from moist wet dega (high land), moist woyna dega (mid altitude), dry woyna dega (mid altitude), and dry kola (low land) had higher mean yield per plant and per hectare, whereas accessions obtained from wet woyna dega (mid altitude) had lower yields. The observed mean yield variations among accessions, as well as the significant number of accessions that outperformed released varieties for yield, suggested that the success of yield improvement is high through selection of high performing accessions and further evaluation. Scholars reported among 16 and 36 genotypes of fenugreek accessions for yield 1,259 to 2,222 kg/ha and 763.55 to 2,076.44 kg/ha[24,32] respectively.

    Euclidean distances (ED) were calculated for pairs of accessions as an estimate of genetic distances among 160 fenugreek accessions. Table 10 compares the mean ED of each accession to the other 159 accessions. The ED between 12,720 accession pairs ranged from between Fgcoll2007369 and Fgcoll207375 to 10.6 between Fgcoll207375 and Fgcoll53093. The overall mean ED was 4.54, with a standard deviation of 1.00 and a coefficient of variation of 22.19, respectively (Table 10).

    Table 10.  Mean Euclidian distances of accessions estimated from 11 agromorphological traits.
    No. Genotype Min Max Mean SD CV (%)
    1 FgColl53006 2.71 7.23 4.58 0.9 19.01
    2 FgColl53072 3.43 7.46 5.39 0.9 16.07
    3 FgColl53075 2.41 6.46 4.38 0.9 19.74
    4 FgColl216898 2.14 8.18 4.65 0.9 19.59
    5 FgColl53079 1.52 7.57 3.72 1.1 28.8
    6 FgColl230067 2.72 7.55 5.08 0.9 18.03
    7 FgColl232194 1.63 7.78 4.63 1.1 24.29
    8 FgColl232195 1.63 7.6 4.27 1.1 25.31
    9 FgColl236992 1.67 7.05 4.08 1 23.83
    10 FgColl216900 2.58 8.05 4.96 1 19.31
    11 FgColl216899 2.88 7.68 5.26 1 19.8
    12 FgColl53023 2.28 7.3 4.95 1.1 21.77
    13 FgColl53086 1.87 7.1 4.13 1 24.87
    14 FgColl239073 2.03 7.34 4.03 1 25.32
    15 FgColl212549 2.58 7.89 5.14 1 20.18
    16 FgColl212552 1.24 6.71 4.39 1 23.02
    17 FgColl53106 2.09 7.51 4.29 1.1 25.27
    18 FgColl229246 1.5 7.52 3.84 1.2 30.78
    19 FgColl229244 1.93 8.05 4.67 1 20.51
    20 FgColl237982 2.15 7.7 4.57 1 22.38
    21 FgColl53088 1.86 7.49 4.12 1.1 25.55
    22 FgColl53002 1.68 6.54 3.61 1 26.93
    23 FgColl53085 2.94 7.89 4.84 0.9 18.48
    24 FgColl212877 2.8 7.97 5.51 1 18.53
    25 FgColl215406 3.83 8.64 6.12 0.9 14.87
    26 FgColl53090 2.48 7.51 4.82 0.9 18.19
    27 FgColl215820 1.68 7.34 3.63 1.1 31.44
    28 FgColl208680 3.71 9.44 6.22 1 15.44
    29 FgColl207378 2.66 7.75 5.27 1 19.52
    30 FgColl230540 1.85 7.49 3.93 1 24.86
    31 FgColl230882 2.2 7.39 4.57 1 21.97
    32 FgColl216830 2.19 7.93 4.53 1.1 24.28
    33 FgColl219343 2.21 8.01 5.03 1.1 21.92
    34 FgColl215334 1.59 6.51 4.46 0.8 18.17
    35 FgColl53027 1.62 7.53 4.42 1 22.43
    36 FgColl53026 2.68 7.43 5.26 0.9 17.58
    37 FgColl53035 1.71 6.91 3.88 0.9 23.36
    38 FgColl53029 2.09 7.02 4.63 1 21.27
    39 FgColl53028 2.46 8.54 4.77 1.2 24.21
    40 FgColl53042 2.19 7.89 4.27 1.2 27.12
    41 FgColl53043 1.13 7.47 3.82 1.11 29.19
    42 FgColl53041 1.68 6.56 3.89 0.99 25.31
    43 FgColl212775 1.24 6.65 4.1 1.03 25.03
    44 FgColl53097 3.44 8.5 5.58 0.95 17.07
    45 FgColl53098 1.66 7 3.77 1.05 27.9
    46 FgColl53099 1.67 7.43 3.94 1.01 25.65
    47 FgColl53081 1.21 7.12 3.83 1.11 29.14
    48 FgColl53076 2.57 8.46 4.82 0.99 20.62
    49 FgColl53078 2.3 7.98 4.59 1.03 22.36
    50 FgColl2007369 0.07 7.55 5.35 1.04 19.41
    51 FgColl53021 2.45 8.44 4.53 1.02 22.46
    52 FgColl239062 2.17 9.67 5.93 1.02 17.22
    53 FgColl239063 1.1 8.1 3.93 1.16 29.59
    54 FgColl239064 2.35 7.78 4.98 1.02 20.41
    55 FgColl212776 1.66 7.69 4.17 1.05 25.17
    56 FgColl212777 1.88 6.73 3.87 0.9 23.35
    57 FgColl53107 3.39 8.86 5.65 1.03 18.23
    58 FgColl215335 1.13 7.5 4.12 1.1 26.59
    59 FgColl53047 1.35 7.04 4 1.05 26.31
    60 FgColl53048 1.75 7.45 4.18 1.05 25.03
    61 FgColl53049 2.1 8.34 4.51 1.12 24.79
    62 FgColl236621 3.37 8.44 5.84 0.91 15.52
    63 FgColl236622 1.8 8.27 4.22 1.18 27.92
    64 FgColl53054 2.7 7.72 5.11 0.95 18.57
    65 FgColl53055 1.62 8.16 4.68 1.09 23.33
    66 FgColl53056 2.3 7.64 4.84 1.04 21.56
    67 FgColl53071 1.5 7.07 3.8 1.13 29.7
    68 FgColl53063 2.29 7.48 4.86 1.05 21.5
    69 FgColl53037 1.89 7.84 4.05 1.04 25.67
    70 FgColl53039 1.81 7.91 4.2 1.1 26.12
    71 FgColl53040 2.32 7.92 4.16 0.9 21.63
    72 FgColl53057 2.31 7.48 4.63 0.94 20.31
    73 FgColl53058 1.44 7.66 3.91 1.05 26.74
    74 FgColl53059 2.09 8.18 3.97 1.06 26.64
    75 FgColl53044 2.39 7.45 3.87 0.83 21.35
    76 FgColl23045 1.59 6.27 4.2 0.82 19.54
    77 FgColl53046 2.36 7.93 4.95 0.92 18.56
    78 FgColl215261 2.27 7.76 4.33 1.09 25.05
    79 FgColl213116 1.96 6.99 4.24 0.96 22.69
    80 FgColl213115 2.25 7.24 4.96 0.94 18.93
    81 FgColl213114 1.72 7.17 3.72 1 27.3
    82 FgColl212657 1.78 7.38 4.47 1 22.22
    83 FgColl215731 1.77 8.16 4.18 1.1 25.78
    84 FgColl213111 1.71 6.64 4.06 0.9 21.75
    85 FgColl213112 1.73 7.26 3.95 1.1 27.1
    86 FgColl53013 1.99 6.98 3.78 0.9 24.84
    87 FgColl53014 2.65 8.92 5.85 1 17.56
    88 FgColl53102 4.4 10.3 6.52 0.9 14.48
    89 FgColl53103 2.23 7.84 4.49 1.1 24.17
    90 FgColl53104 2.23 7.65 4.24 1.1 25.96
    91 FgColl53105 1.83 7.86 4.12 1.2 28.09
    92 FgColl226090 0.55 7.6 4.03 1.2 29.61
    93 FgColl53012 3.31 8.32 5.7 0.9 16.43
    94 FgColl208463 2.34 8.04 4.71 0.9 19.12
    95 FgColl207379 3.43 8.25 5.26 1 19.13
    96 FgColl207370 2.57 8.01 4.51 0.9 20.74
    97 FgColl207380 1.6 7.22 3.88 1.1 27.75
    98 FgColl207395 2.37 8.73 5.01 1.1 21.2
    99 FgColl207393 1.88 7.15 3.86 0.9 23.97
    100 FgColl207394 1.98 8.3 5.18 10 18.56
    101 FgColl207384 2.02 6.97 4.17 1 24.45
    102 FgColl207385 1.44 6.61 3.86 1.1 27.26
    103 FgColl207386 2.71 8.36 4.79 0.9 19.64
    104 FgColl207369 0.07 7.55 5.35 1 19.39
    105 FgColl207371 2.3 7.87 4.4 1 23.32
    106 FgColl207381 2.17 7.69 4.54 1.1 24.5
    107 FgColl207382 1.87 7.11 4.19 1 24.22
    108 FgColl207383 1.68 7.44 3.87 1.1 28.83
    109 FgColl207375 4.7 10.6 7.26 1 13.41
    110 FgColl207376 2.48 7.19 4.38 1 23.61
    111 FgColl207377 1.1 8.7 4.4 1.2 27.15
    112 FgColl212779 2.39 9.24 4.82 1.2 23.94
    113 FgColl208035 2.32 7.26 4.5 1 21.91
    114 FgColl207396 1.77 7.43 4.02 1 25.75
    115 FgColl207366 1.82 7.6 3.78 1 25.93
    116 FgColl207367 1.99 7.27 4.59 1.1 23.07
    117 FgColl228558 3.26 9.44 5.49 1 18.78
    118 FgColl227227 2.5 8.85 5.33 1.1 19.92
    119 FgColl205176 1.95 6.48 4 0.8 20.07
    120 FgColl53108 4.08 9.67 6.15 1 16.73
    121 FgColl53109 2.38 7.39 4.92 1.01 20.56
    122 FgColl207354 1.47 6.36 3.71 0.9 24.16
    123 FgColl207355 2.52 8.33 4.91 1.05 21.46
    124 FgColl207356 0.55 7.56 4.19 1.2 28.74
    125 FgColl207387 2.08 6.49 3.86 0.79 20.54
    126 FgColl207388 2.74 7.29 4.76 0.93 19.47
    127 FgColl207389 2.09 7.17 4.15 0.95 22.98
    128 FgColl207390 2.17 6.85 4.36 0.86 19.83
    129 FgColl07391 1.67 7.63 4.07 1.11 27.17
    130 FgColl207392 2.94 8.6 5.13 0.95 18.41
    131 FgColl207372 1.44 7.59 3.75 1.02 27.29
    132 FgColl207373 1.99 6.98 3.85 0.88 22.89
    133 FgColl207374 3.13 7.51 5.21 0.91 17.54
    134 FgColl207361 1.67 7.35 3.98 1.08 27.17
    135 FgColl207357 1.99 7.02 4.17 0.96 23.02
    136 FgColl207358 2.87 7.92 5.36 1.06 19.7
    137 FgColl207362 2.38 7.3 4.66 0.95 20.4
    138 FgColl207364 1.44 6.97 3.79 1.09 28.77
    139 FgColl207365 2.84 7.94 5.26 0.92 17.52
    140 FgColl53008 2.47 8.96 4.57 1.04 22.67
    141 FgColl53009 1.95 6.68 3.66 0.92 25.22
    142 FgColl239065 2.58 7.65 4.88 1.08 22.06
    143 FgColl229846 2.38 9.32 4.94 1.1 22.24
    144 FgColl219509 1.35 7.02 4.07 1.08 26.57
    145 FgColl53092 1.93 7.18 4.07 0.91 22.27
    146 FgColl53093 3.6 10.6 5.79 1.02 17.57
    147 FgColl53094 2.57 8.06 4.95 0.82 16.66
    148 FgColl238247 1.71 7 4.02 0.96 23.96
    149 FgColl220026 2.11 7.44 4.92 0.98 19.91
    150 FgColl220027 1.74 7.58 4.33 1.08 24.99
    151 FgColl235133 1.93 7.18 3.91 0.92 23.53
    152 FgColl207368 1.98 8.56 5.25 1.06 20.15
    153 FgColl9562 2.26 6.7 4.29 0.87 20.27
    154 FgColl215585 1.21 7.47 3.8 1.11 29.09
    155 FgColl207599 2.45 8.81 5.13 1.15 22.45
    156 Chala 0.98 6.72 4.08 0.92 22.65
    157 Ebbisa 1.37 7.36 4.39 0.97 22.01
    158 Hunda,ola 1.37 7.14 4.54 0.95 20.82
    159 FGP# = 1 0.98 6.07 3.77 0.88 23.3
    160 Local 1.1 5.97 3.85 0.9 23.29
    Overall 0.07 10.6 4.54 1 22.19
    Min = Minimum, Max = Maximum, SD = Standard deviation, CV (%) = Coefficient of Variation in percent.
     | Show Table
    DownLoad: CSV

    Unweighted Pair-Group Method with Arithmetic Means (UPGMA) methods based on the Euclidean distance (ED) matrix were used to cluster accessions. The dendograms constructed at cut point 3.54 (ED of accessions minus standard deviation) resulted in the grouping of 160 fenugreek accession into two different clusters, indicating a high level of genetic diversity among the accessions (Fig. 1). The clustering of accession in the current study is useful to breeders. A representative accession from a specific cluster may be chosen for genetic base enhancement. Individual or group differences in phenotypic diversity are caused by differences in genetic composition and the environment in which they are grown[33]. Cluster analysis is used to individuals belonging based on the characteristics they share. Individuals are mathematically grouped together in the same cluster because their descriptions are similar. If the classification is successful, individuals within a cluster will be closer when plotted geometrically, while individuals from different clusters will be farther apart[34]. Genotypes within a cluster are considered to be relatively similar, whereas genotypes between clusters are more dissimilar, and estimates the extent of diversity among accessions[35].

    Figure 1.  Dendrogram from UPGMA of 160 fenugreek accession for 11 traits.

    In the current study, the wide range of genetic distances 0.07 to 10.6 among pairs of accession was observed and accession were grouped into two distinct clusters indicated the presence of genetic diversity among 160 fenugreek accessions. In cluster analysis, one of the important aspects is constructing the optimal number of clusters or number of acceptable clusters which involves deciding where to 'cut' a dendrogram to find the true or natural groups. In this study, the cut point was less than the overall mean Euclidean distances by the standard deviation of accession distances. Therefore, the two major groups could be considered as true groups based on the clustering method used. A group consisted of more accession and an acceptable cluster is when the within-cluster genetic distance is less than the overall mean genetic distance and between cluster distances greater than within cluster distance of the two clusters involved[36].

    Research conducted among 30 fenugreek genotypes indicated that genotypes are grouped into nine clusters, whereas 167 fenugreek genotypes clustered into four major groups based on morphological traits such as plant height, days to flowering, branches per plant, pods per plant, pod length, seeds per pod, test weight, seed yield per plant[31,37]. The 144 fenugreek accessions were grouped into nine clusters based on Mahalanobis' D2 statistic. Researchers evaluated and reported 36 fenugreek accessions for 17 agro-morphological traits and grouped the accessions into eight distinct clusters[24].

    Table 10 shows the mean ED calculated for each accession by averaging a specific accession to the other 159 accession. The average distance (ED) was calculated to determine which accession (s) were closest or farthest away from others. As a result, 149 had mean ED values ranging from 3.61 to 5.51, with the overall mean ED minus and plus standard deviation values of 3.54 and 5.54 indicating that the accession had average genetic distances. In contrast, nine accessions had mean ED ranging from 5.58 to 6.22, which was between 5.54 (overall mean ED + SD) and 6.54 (overall mean ED + 2SD), and the other two had mean ED > 6.54. This indicated that these accessions had significantly higher mean ED than the overall mean ED and that they were distant from other accessions. Accession with values between mean SD may be considered to have average distances to others, while those with values (mean-SD) and (mean-2SD) may be considered to have lower mean distances to others than the average distance of accessions.

    These findings indicate that these additions may be considered desirable for inclusion in the crossing program[38]. FgColl207375 was the most distant from other fenugreek accessions, followed by FgColl53102, with mean EDs of 7.26 and 6.52, respectively. FgColl53002 (3.61) and FgColl215820 (3.63), on the other hand, were the closest to other fenugreek accessions. Greater distances were found to be more important for improving desirable traits than closer proximity. According to Rahim[39], who demonstrated that hybrids of genotypes with the greatest distance resulted in the highest yield, crosses between these accessions can be used in breeding programs to achieve maximum heterosis.

    The 11 traits distant accessions were distinguished by high mean values for FgColl207375, FgColl53102, FgColl53108, FgColl208680, and FgColl215406 and low mean values for FgColl53002, FgColl215820, FgColl53009, and FgColl207354. That suggested that this accession could be used in crossing programs and/or further evaluated to obtain hybrids or improved varieties with higher mean values for Chala, Ebbisa, Hundao'la, and FGP# = 1 than the fenugreek population studied. that the high level of diversity and genetic distance in fennel land-races is beneficial for breeding[40]. According to Ghaderi et al.[41], increasing parental distance implies a large number of contrasting alleles at the desired loci, followed by recombination of these loci in the F2 and F3 generation. As recombination is expected from crosses involving parents from the distance clusters, the greater the opportunities for effective selection for yield factors will be following a cross of distantly related parents.

    Some of the clusters may contain accession with high mean values for some traits, but the clusters also contained accession with lower mean values for yield and other desirable traits, making them difficult to consider in future breeding programs. Therefore, the consideration of accession for fenugreek breeding programs from these clusters needs to be evaluation and selection of individual accession for higher mean values for some desirable traits and without having lower mean values for other desirable traits. Low mean performance of clusters implies difficulty to select traits for direct selection and further improvement.

    The results of genetic distances and cluster analyses revealed that geographical location was one of the isolation factors that contributed to accessions variability, either by enhancing free exchange of genotypes among nearby geographic regions or by hindering exchange due to geographic distance. The current study findings are consistent with those of Balai et al.[42] in fenugreek, who found significant diversity among genotypes from different geographical origins and a good opportunity for improvement through hybridization and selection by crossing from different clusters. In contrast scholars that conduct research reported that no genetic differentiation among fenugreek genotypes due to geographic origins[43,44].

    The principal component analysis revealed that five principal components with Eigenvalues of 17.9, 15.2, 12.3, 11.1, and 9.4 accounted for 65.9% of the total variation (Fig. 2a). The first two principal components, PC1 and PC2 contributed the most to total variability, with proportion values of 17.9 and 15.2 respectively as shown in Fig. 2b. Characters with the highest absolute value are closer to zero, according to Chahal & Gosal[45]. As a result, the differentiation of genotypes into different clusters in the current study was due to the cumulative effect of a number of traits rather than a small contribution from each trait.

    Figure 2.  Eigenvalues and vectors of the correlation matrix for 11 traits accession. (a) Trait's contribution. (b) Relationship of parameters.

    Thus, traits with relatively higher values in the first principal component (PC1), such as the number of seeds per pod and number of pods per plant contributed more to total variability and, ultimately, differentiated the accession clusters. The second principal component included the number of secondary branches, number of primary branches and seed yield kg per hectare as indicated in Fig. 2b.

    According to the principal component analysis, the first three PCA explained 33.1% of the total variation among the accession. Positive contributors to the PCA included number of seeds per pod and number of pods per plant. When compared to other components, the first principal component contributes the most variability in the data as shown in Fig. 2b & c. The results showed that the PCA can be used to understand potential traits for breeding material selection and evaluation. Research reported in fenugreek accessions shows that, the first PCA contributes more variability than the other components of PCA[37]. Days to flowering, days to maturity, and thousand seed weight were also linked to second PCA in chickpea, according to Malik[46]. Findings reported in other investigation shows that the first PCA was associated with number of pods per plant, seed yield per plant, plant height at flowering and number of secondary branches while second PCA with days to flowering and days to maturity in chickpea[47].

    Evidence on the extent and pattern of genetic variability in a crop population is required to design crop improvement breeding strategies. For all traits, analysis of variance revealed significant differences between test accessions. This suggested that there were significant variations among accessions that could be used in breeding programs to develop varieties. The findings also support further genetic analysis of all of the studied characters. As a result, for number traits, higher values of genotypic (GCV) and phenotypic (PCV) coefficients of variation were estimated. This indicates that these traits were highly heritable, and that improvement of these traits could be accomplished through the selection of high performing genotypes. The large genetic distances between accessions were evident when measured in terms of Euclidean distances.

    Based on the Euclidean distance (ED) matrix and dendogram constructed using the Unweighted Pair-Group Method with Arithmetic Means, the 160 fenugreek land-races were divided into two different clusters (UPGMA). The accession from south western Ethiopia had the greatest genetic distance to all groups of accessions and check varieties, ranging from 3.01 to 3.88, with the highest mean ED of 3.44. This demonstrated that geographical location was one isolation factor that contributed to diversity in accessions and can enhance or hinder the possibility of free exchange of breeding materials nearby. In general, the results of diversity analyses indicated that fenugreek accessions were diverse, implying a higher chance of crop improvement through crossing of distant genotypes through selection of accessions for high mean performance of traits of interest.

    The principal component analysis revealed that five principal components (PC1 through PC5, with eigenvalues of 17.9, 15.2, 12.3, 11.1, and 9.4, respectively) accounted for 65.9% of the total variation. As a result, the differentiation of the accessions into different clusters in the current study was due to the cumulative effect of a number of traits rather than the contribution of a few major traits. The current study suggested that the accessions stored at the Ethiopian Biodiversity Institute had significant genetic variability. Thus, there is an excellent opportunity to contribute to farmers' food security and livelihoods by improving fenugreek through selection and hybridization, which involves crossing distant accessions from different clusters with various combinations of advantageous traits.

    The authors confirm contribution to the paper as follows: conceptualization and writing of manuscript, data collection, structural arrangement of manuscript: Roba R; proof reading and technical advice, advice on the design of the manuscript: Mohammed W. Both authors reviewed the results and approved the final version of the manuscript.

    The data are not included due to third party rights but analysed data during the study are available from the corresponding author on reasonable request.

    This research was supported by the McKnight Foundation's Legume Diversity Project, Ethiopia, by providing financial support for the research.

  • The authors declare that they have no conflict of interest.

  • Supplemental Table S1 PbWOX primers used for semi-qPCR and qPCR.
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  • Cite this article

    Zhang M, Chen X, Lou X, Zhang Y, Han X, et al. 2023. Identification of WUSCHEL-related homeobox (WOX) gene family members and determination of their expression profiles during somatic embryogenesis in Phoebe bournei. Forestry Research 3:5 doi: 10.48130/FR-2023-0005
    Zhang M, Chen X, Lou X, Zhang Y, Han X, et al. 2023. Identification of WUSCHEL-related homeobox (WOX) gene family members and determination of their expression profiles during somatic embryogenesis in Phoebe bournei. Forestry Research 3:5 doi: 10.48130/FR-2023-0005

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ARTICLE   Open Access    

Identification of WUSCHEL-related homeobox (WOX) gene family members and determination of their expression profiles during somatic embryogenesis in Phoebe bournei

Forestry Research  3 Article number: 5  (2023)  |  Cite this article

Abstract: WUSCHEL-related homeobox (WOX) transcription factor (TF)-encoding genes play crucial roles during embryo development. The function of WOX genes in embryonic development has been thoroughly studied in Arabidopsis thaliana, but little is known about their function in woody species, especially Phoebe bournei, an endemic and endangered species in China. In the present study, a total of 15 WOX genes were identified in P. bournei, and phylogenetic analysis resulted in their assignment to three typical clades: an ancient clade, an intermediate clade, and a modern/WUS clade. The gene structure and sequence characteristics and the physicochemical properties of WOX proteins were also analyzed. Promoter prediction indicated that WOX genes are likely involved in plant growth and development and hormone responses. Subsequently, we evaluated the expression patterns of WOX genes in response to auxin (IAA), abscisic acid (ABA), and methyl jasmonate (MeJA) treatments. According to tissue-specific expression patterns, we screened nine WOX genes that were present in embryonic calli and that might participate in the somatic embryogenesis (SE) of P. bournei. Furthermore, the expression profiles of these nine WOX genes during three phases of embryogenic calli development and three phases of somatic embryo development, namely, spheroid embryogenesis, immature cotyledon-producing embryogenesis and mature cotyledon-producing embryogenesis, were monitored. Overall, we systematically analyzed the expression patterns of WOX genes in P. bournei during SE, the information of which provides a basis for further elucidating the molecular mechanism through which WOX TFs function in P. bournei embryo development.

    • Phoebe bournei, a rare and endangered protected tree species that is unique to China, which produces excellent material and fragrance, can be used for the production of furniture and as an ornamental tree[1] . However, few natural resources of this species are available, and this species undergoes a long juvenile phase. Currently, seed propagation is the main reproduction technique, and unstable yields driven by fruiting characteristics has a large impact on seedling production[2].

      Somatic embryogenesis (SE) is one of the most important techniques for tree breeding programs, but the mechanism underlying SE is poorly understood[3]. In angiosperms, a mature somatic embryo is induced from embryonic calli and subsequently develops into spherical, heart-shaped, torpedo, and cotyledon-producing embryos[4]. Moreover, regulation of the different stages of SE requires specific cell fate changes, and many transcription factors (TFs) are involved in this process. For example, WUSCHEL (WUS), WUSCHEL-related homeobox (WOX), BABY BOOM (BBM), AGAMOUS-like (AGL), LEAFY COTYLEDON (LEC), Receptor-Like Kinase (SERK), and Vmyb Avian Myeloblastosis Viral Oncogene Homolog (MYB) genes function as indispensable regulators transforming nonembryogenic calli cells into embryogenic calli cells or driving changes between the different developmental stages of SE[510]. As such, SE requires precise transcriptional regulation. SE regeneration techniques have been determined for P. bournei[11], and high-quality genomic data of this species have been released by our group[12]. However, the transcriptional regulatory mechanism behind the transitions among the different stages of SE in P. bournei remains elusive.

      An increasing number of studies have shown that WOXs are extensively involved in plant organ regeneration, growth and development, stress responses, and other transcriptional regulatory processes, especially those that occur during SE[1317]. In Arabidopsis, AtWUS was shown to be expressed at the proembryonic (16-cell) stage and is involved in subsequent maturation during SE[18]. AtWOX2, AtWOX8, and AtWOX9 participate in polarity establishment during early embryonic development, and AtWOX2 is expressed in apical cells, while AtWOX8 and AtWOX9 are expressed specifically in basal cells, which are indispensable for the correct establishment of the apical–basal axis[19,20]. Moreover, PaWOX2 was also shown to be highly expressed in embryogenic cells in Picea abies[21], and the overexpression of PpWOX2 was shown to affect related traits of somatic embryos in Pinus pinaster[17]. In Vitis vinifera, VvWOX2 and VvWOX9 are expressed at high levels during SE and can be used as marker genes for SE[22]. Furthermore, MtWOX9-1 was shown to increase the embryogenic capacity of recalcitrant plant species, e.g., Medicago truncatula[23]. These studies have shown that WOXs are crucial during the process of embryonic development or somatic embryo regeneration. Moreover, in woody plant species, global transcriptomic data and expression analysis have resulted in the identification of WOXs expressed during SE in Dimocarpus longan, hybrid sweetgum, and Elaeis guineensis, suggesting that WOXs are functionally conserved in woody plants species[7,9,24]. Based on this, understanding the dynamic relationship between WOXs and SE in P. bournei is helpful for optimizing the somatic embryo regeneration system and creating a large number of clones rapidly.

      Previous studies have shown that overexpression or ectopic expression of embryogenesis-related TFs can induce the SE process. Another way is to apply exogenous phytohormones[25]. Adding exogenous phytohormones to media can affect the morphology and quality of SE in many species[26]. The interactions between phytohormones and TFs has been under increasing scrutiny. Several studies have shown that some TFs, such as LEC2, BBM, and WUS, are regulated by auxin synthesis, transport, and responses during SE[10,27,28]. Correct establishment of the auxin gradient and PIN1-mediated auxin transport were shown to affect the expression level of WUS, which in turn affected the status of the embryonic calli[27]. LEC2 and BBM transcriptionally regulate the endogenous auxin (IAA) biosynthesis-related genes YUCs/TAAs and increase the DR5 auxin response, further maintaining somatic embryo growth[10,28,29]. Furthermore, LEC2 was shown to bind directly to the early embryonic marker genes WOX2 and WOX3, triggering SE[5,25]. Abscisic acid (ABA) is another important hormone involved in SE, especially during embryo maturation. Application of exogenous ABA to the media was shown to induce embryo maturation and prevent early germination in Carica papaya, Pseudotsuga menziesii, and Phoenix dactylifera[3032]. Methyl jasmonate (MeJA) plays a function similar to that of ABA in promoting mature SE. MeJA functions synergistically with ABA, but the effects of MeJA cannot replace the effects of ABA[33]. In Liriodendron hybrids, MeJA was shown to increase both SE and the maturation rate and decreased the deformation rate[34]. However, studies on the relationships between MeJA and WOXs are lacking. Taken together, these results suggested that TFs and hormones jointly regulate plant SE. In P. bournei, how WOXs respond to hormones during SE has not been thoroughly characterized. So we preliminarily explored the expression patterns of WOX under auxin, ABA, and MeJA treatments.

      In the present study, 15 WOX genes were identified across the P. bournei genome, and their gene structures and protein sequences were characterized. Then, the expression patterns of WOXs among six tissues and at different stages of SE were determined. To elucidate how these WOXs respond to hormones, their expression levels in response to auxin, ABA, and MeJA were analyzed. Our results revealed WOX members in P. bournei and several possible associations between WOXs and plant hormones. The results of this study will provide further insight into the function of WOXs involved in regulating SE in woody plant.

    • The half-sibling family of P. bournei designated 'WY1' was cultivated in the greenhouse. The epicotyls, stem tips, roots, stems, and leaves of three-month-old seedlings and embryogenic calli induced from immature embryos were frozen in liquid N2 and used for semiquantitative analysis of PbWOX genes. Growth of embryonic calli was induced in cotyledon-stage embryos of the 'WY1' mother tree and subcultured at 24 °C in the dark, as described in our previous study[11]. Somatic embryos of P. bournei at six developmental stages, including three stages of calli, the globular embryo stage, and immature and mature cotyledon-producing embryo stages, were collected under a stereomicroscope (OLYMPUS, Beijing, China) and then frozen in liquid N2 for RNA extraction. With respect to calli growth in liquid media for hormone treatment, 0.1 g of calli was transferred to liquid media supplemented with 100 μM IAA, ABA, and MeJA for 3, 6, 12, 24, and 48 h. Calli in untreated liquid media were used as controls. Sampling was performed at the same time, and three replicates were included.

    • The PbWOXs were identified by two methods. Firstly, using the hidden Markov model, we downloaded the sequence of the conserved homeobox domain of the WOX (PFAM00046) from an online website (http://pfam.xfam.org), and the hmm search module in HMMER (version 3.1) software was used to search the protein sequences of the P. bournei genome[12]. The threshold was set to < E20. Secondly, we downloaded 15 AtWOXs proteins sequence from the TAIR database (www.arabidopsis.org), then used them as query sequences to perform the BLASTp search (E-value < 1e-5) with P. bournei protein sequences. By combining the two methods, candidate sequences without a homeobox domain were omitted. The 15 obtained PbWOX protein sequences were subjected to MUSCLE alignment of MEGA (version 7.0) together with the sequences of 15 AtWOXs, 13 OsWOXs, 18 PtWOXs, eight AtriWOXs, seven SmWOXs, three PpaWOXs, one OstuaWOX, and one OstluWOX protein downloaded from the online Plant Transcription Factor Database (PlantTFDB) website (http://planttfdb.cbi.pku.edu.cn). The neighbor-joining (NJ) method with 1000 bootstrap repetitions was subsequently used to construct a phylogenetic tree, and the other parameters were set to their default.

    • Exons and introns of individual PbWOXs were visualized via the online software Gene Structure Display Server (GSDS) (version 2.0) (http://gsds.gao-lab.org), and Multiple Em for Motif Elicitation (MEME) (version 5.11) (http://meme-suite.org/) was used to predict the motifs of the PbWOX family proteins. The ProtParam (https://web.expasy.org/protparam/) online website was subsequently used to predict the physicochemical properties of PbWOX family members, such as their number of amino acids, molecular weight, and isoelectric point. ClustalX (version 1.81) was used for multiple sequence alignment to confirm the presence of WUS-box domain and the homeobox domain. The genome sequence and gene annotation information file was added to the TBtools GFF3 Sequence Extractor submenu, the upstream bases was set to 2000, the upstream CDS 2.0 kb of all genes in P. bournei were obtained. Then 2.0 kb upstream promoter sequences of 15 PbWOX genes were obtained from the TBtools quick fasta extractor submenu[12,35]. Finally, we uploaded the obtained file to an online site PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) to analyze cis-acting elements.

    • Total RNA was extracted using a RNAprep Pure Plant Kit (TIANGEN, Beijing, China). Then, the RNA was quantified by a Nanodrop ND-1000 spectrophotometer and checked according to the A260/280 nm and A260/A230 nm values. Subsequently, cDNA was synthesized using a PrimeScriptTM RT Reagent Kit with gDNA Eraser (Perfect Real Time) (Takara, Dalian, China), and each RNA sample was 2000 ng. The obtained cDNA was subsequently diluted five times for quantitative RT‒PCR.

      Specific primers of the 15 PbWOX genes were designed using the Primer 3 online website (http://bioinfo.ut.ee/primer3-0.4.0/), and the sequences of these primers are listed in Supplemental Table S1. The expression levels of the PbWOX genes were detected via quantitative RT–PCR and a CFX 96-well Real-Time PCR System (Bio-Rad, USA). The qPCR mixture volume was 10 μL, which comprised 5 μL of 2× ChamQTM SYBR qPCR Master Mix, 0.4 μL of cDNA, 0.2 μL of forward primer, 0.2 μL of reverse primer, and 4.2 μL of ddH2O. The PCR was carried out as follows: predegeneration at 95 °C for 1 min, 45 cycles of denaturation at 95 °C for 10 s followed by annealing at 57 °C for 10 s, and extension at 72 °C for 20 s. PbEF1α was used as an internal control, and the relative gene expression levels were calculated according to the 2−ΔΔCᴛ method[36].

    • All the treatments were performed at least three times. The data were subjected to ANOVA and Duncan's multiple range test at the 5% significance level via SPSS (version 26.0) software.

    • After performing hidden Markov model (HMM) searches and removing redundant and/or sequences without the homeobox domain, we identified 15 PbWOX members. Phylogenetic analysis of 15 AtWOXs, 18 PtWOXs, 13 OsWOXs, eight AtriWOXs, seven SmWOXs, three PpaWOXs and WOX protein sequences from two green algal species resulted in the assignment of the 15 PbWOX genes to an ancient branch, an intermediate branch and a modern/WUS branch (Table 1). Specifically, the ancient branch consisted of three PbWOXs (PbWOX13a, PbWOX13b, and PbWOX13c); the intermediate branch consisted of four PbWOXs, namely, PbWOX9, PbWOX11/12a, PbWOX11/12b, and PbWOX11/12c, which were classified into two subclasses; and the remaining eight members, namely PbWUS, PbWOX1a, PbWOX1b, PbWOX2a, PbWOX2b, PbWOX3, PbWOX4 and PbWOX5/7, were assigned to the modern/WUS branch (Fig. 1a).

      Figure 1. 

      Phylogenetic relationships of PbWOX proteins. (a) NJ tree constructed of the amino acid sequence of WOXs from Phoebe bournei (Pb), Arabidopsis thaliana (At), Populus trichocarpa (Pt), Oryza sativa (Os), Amborella trichopoda (Atri), Selaginella moellendorffii (Sm), Physcomitrella patens (Ppa), Ostreococcus tauri (Ostau) and Ostreococcus lucimarinus (Ostlu). (b) Synteny analysis of WOX genes between P. bournei and A. thaliana. Gray lines indicate all synteny blocks in the genome, and the red lines indicate duplicated WOX gene pairs.

      Table 1.  Subclass information of WOXs among P. bournei and other representative species.

      Taxonomic groupSpeciesAncient cladeIntermediate cladeModern/ WUS
      clade
      Total
      DicotsA. thaliana34815
      P. trichocarpa671118
      MonocotsO. sativa16613
      MagnolialesP. bournei34815
      AmborellalesA. trichopoda1258
      PteridophytaS. moellendorffii617
      BryophytaP. patens33
      ChlorophytaO. tauri11
      O. lucimarinus11

      However, the number of PbWOX genes was the same as that of Arabidopsis (Fig. 1a). Nonetheless, PbWOXs probably expanded differently than did those of Arabidopsis. For example, three homologs of AtWOX11/12 and AtWOX13, two homologs of AtWOX1 and AtWOX2, one homolog each of AtWUS, AtWOX3, AtWOX4, AtWOX5/7, and AtWOX9, and no homologs of AtWOX6 and AtWOX10 were found in P. bournei (Fig. 1b).

    • A sequence analysis of the PbWOXs showed that PbWOX1b comprised the largest number of amino acid residues (528) and had the largest molecular weight (59.19 kD). Conversely, PbWOX5/7 comprised 169 amino acid residues and had the smallest molecular weight (19.37 kD). All PbWOX genes contain introns, the number of which ranged from two to eight (Fig. 2a). Then, to better understand each member of the PbWOXs, we predicted the physicochemical properties by the use of an online website. The theoretical isoelectric point of PbWOX was found to be between 5.48 (PbWOX11/12c) and 9.93 (PbWOX13c) (Table 2).

      Figure 2. 

      Information on the PbWOX genes and proteins. (a) Phylogenetic tree and gene structure. (b) Architecture of conserved protein motifs. (c) Multiple sequence alignment.

      Table 2.  Summary of the PbWOX gene family members.

      Gene IDGene nameOrthologous in ArabidopsisTheoretical pIMolecular weightNumber of amino acids
      OF24054-RAPbWUSAtWUS8.5831622.96276
      OF03970-RAPbWOX1aAtWOX19.3737209.6328
      OF11837-RAPbWOX1bAtWOX18.8959188.97528
      OF19048-RAPbWOX2aAtWOX27.0924524.5218
      OF05256-RAPbWOX2bAtWOX26.8324496.61219
      OF16243-RAPbWOX3AtWOX39.0522752.66194
      OF04424-RAPbWOX4AtWOX48.2524797.85220
      OF05362-RAPbWOX5/7AtWOX5, AtWOX79.5119371.68169
      OF24594-RAPbWOX9AtWOX97.1945272.57413
      OF22069-RAPbWOX11/12aAtWOX11, AtWOX125.6830055.89268
      OF11766-RAPbWOX11/12bAtWOX11, AtWOX125.9530330.35277
      OF28194-RAPbWOX11/12cAtWOX11, AtWOX125.4827450.91252
      OF25757-RAPbWOX13aAtWOX135.9132705.61288
      OF14063-RAPbWOX13bAtWOX136.1032380.27286
      OF07768-RAPbWOX13cAtWOX139.9331294.66272

      Motif 1 and motif 2 were detected in all 15 PbWOXs, motif 3 was specific to the members of the intermediate clade, motif 4 (T-L-X-L-F-P-X-X, where X indicates any amino acid) was present in all members of the modern/WUS clade except PbWOX5/7, and motif 5 was specific to PbWOX13a and PbWOX13b (Fig. 2b). There are residues composing homeobox domain motifs that contain three helixes spaced by one loop and one turn (Fig. 2c). Eight members in the modern/WUS clade shared a WUS-box domain (Fig. 2c).

    • The cis-acting elements in the promoter region of PbWOXs were divided into four main categories: light-related, hormone-related, stress-related and development-related. (Fig. 3). Specifically, the light response elements constituted the largest proportion, of which the number of G-box elements was the largest. Several other elements involved circadian rhythm were also detected. The hormone-responsive elements included 45 ABA-responsive elements (ABREs), 30 MeJA-responsive elements (CGTCA motif–containing elements), 24 gibberellin (GA)-responsive elements (P-boxes, GARE motif–containing elements, TATC-boxes), 10 salicylic acid-responsive elements (TCA-elements), and nine auxin-responsive elements (TGA-elements, AuxREs, AuxRR-core elements). Abiotic stress response elements were predicted with 38 regulatory anaerobic inductor elements (ARE), 20 drought-responsive elements that could bind MYBs (MBSs), 15 low-temperature–responsive elements (LTRs), eight defense- and stress-responsive elements and five anoxic-specific induction-responsive elements. Moreover, in development-related cis-acting elements, 14 CAT boxes, 12 O2-sites, and six RY elements were predicted, respectively. In the PbWOX promoters, the most common cis-acting elements were G-boxes (light-related), ABREs (ABA-related), CGTCA motif-containing elements (MeJA-related) and AREs (drought-related). This result implied that PbWOX participated in plant growth process and stress response.

      Figure 3. 

      Predicted cis-acting elements in PbWOX promoters. (a) Frequency of cis-acting elements in the 2.0 kb upstream regions of PbWOXs. The corresponding colored bar chart indicates the occurrence of different cis-acting elements. (b) Number of cis-acting elements in each WOX gene.

    • To further understand the potential roles of PbWOXs during different developmental stages and at different physiological status, semi-qPCR was used to study the expression patterns of 15 PbWOXs in six tissues. The expression levels of PbWOXs varied significantly among the tissues (Fig. 4). Specifically, five genes, namely, PbWOX2a, PbWOX5/7, PbWOX9, PbWOX13a, and PbWOX13b, were expressed in almost all the tissues, while PbWUS, PbWOX1a, PbWOX2b and PbWOX3 were highly expressed in the epicotyls, with low or no expression in the other tissues. In addition, PbWOX11/12a, PbWOX11/12b and PbWOX11/12c were highly expressed specifically in both the roots and embryogenic calli, while expression of PbWOX1b and PbWOX4 was nearly absent in the calli. In total, nine PbWOXs were expressed in embryogenic calli, and thus, these genes may be involved in the SE of P. bournei; PbWOX2a exhibited the highest expression level.

      Figure 4. 

      Semiquantitative analysis of PbWOXs in different tissues. (a) Tissue samples, 1 - epicotyl, 2 - stem tip, 3 - root, 4 - stem, 5 - leaf, 6 - calli. (b) Semiquantitative PCR electropherogram.

    • Previous studies have shown that WOXs play important roles during SE. The expression levels of nine PbWOXs were analyzed in calli at three different developmental stages (Fig. 5ac) and in embryos at three different developmental stages (Fig. 5dg). Embryonic calli were induced by immature zygotic embryos (Fig. 5a); then, the embryonic calli developed to the second stage (Fig. 5b) after two or three rounds of propagation, and the calli developed to the third stage (Fig. 5c) after two rounds of propagation. Globular embryos (Fig. 5d), immature cotyledon-producing embryos (Fig. 5e) and mature cotyledon-producing embryos (Fig. 5f) were also selected. The qPCR results showed that the expression levels of PbWOX2a and PbWOX9 increased during embryogenic calli development but decreased as the embryos matured. PbWUS was specifically and highly expressed in the immature cotyledon-producing embryos. The expression level of PbWOX5/7 increased during calli development but decreased after calli differentiation. Three homologous genes, PbWOX11/12 and PbWOX13a, were highly expressed in cotyledon-producing embryos, and their expression peaked upon maturity (Fig. 5g).

      Figure 5. 

      Expression patterns of PbWOXs during SE of P. bournei. (a) Calli-1. (b) Calli-2. (c) Calli-3. (d) Globular embryo. (e) Immature cotyledon-producing embryo. (f) Mature cotyledon-producing embryo. (g) Analysis of gene expression via qPCR. The data are the means ± SDs of three biological replicates. The values followed by the same letter are not different according to Duncan’s multiple-range test. PbEF1α was used as an endogenous control.

    • With respect to the cis-acting elements of PbWOXs, we investigated the expression patterns of PbWOXs in response to auxin, ABA, and MeJA (Fig. 6). Under IAA treatment, PbWUS expression was induced and increased continuously as the treatment duration increased; PbWOX5/7 was strongly induced after 3 h of treatment, after which the expression level decreased. The expression levels of PbWOX2a and PbWOX9 significantly decreased, and the expression levels of PbWOX11/12b, PbWOX11/12c, PbWOX13a, and PbWOX13b also slightly decreased.

      Figure 6. 

      Relative expression levels of PbWOXs under hormone treatment. The data are the means ± SDs of three biological replicates. The values followed by the same letter are not different according to Duncan's multiple-range test. PbEF1α was used as an endogenous control.

      PbWUS was also induced in response to ABA treatment, while PbWOX2a, PbWOX9, and PbWOX13b were inhibited. The expression levels of PbWOX5/7 and PbWOX13a decreased, reached their lowest level after 12 h of ABA treatment, and then gradually increased. PbWOX11/12b and PbWOX11/12c showed similar expression patterns; their expression increased after 3 h but then decreased. PbWUS expression was induced in response to MeJA treatment, peaked at 12 h, and then gradually decreased. PbWOX5/7, PbWOX9 and PbWOX13b expression was inhibited significantly. PbWOX11/12b and PbWOX11/12c expression increased after 3 h but then decreased.

    • WOXs are specific to plants and largely involved in key developmental processes, especially those associated with somatic cell regeneration. With the publication of many plant genome sequences, WOX genes have been identified in several plant species. In the present study, we identified 15 PbWOXs, same as the number in Arabidopsis[37], and different orthologous revealed that chromosomal duplication events may occur in P. bournei. Furthermore, the length of introns showed regular characteristics across different clades. For instance, genes in the intermediate clade contained shorter intron sequences than did those of ancient clade, and five genes in the modern/WUS clade had the shortest intron. Taken together, these results suggested that the intron fragments underwent refinement during the evolution of the PbWOX genes. A similar phenomenon was observed in Camellia sinensis[38], which was exemplified by most WOX introns in members of the modern/WUS clade are much shorter than those in the ancient clade. In addition, compared with that in algae, ferns and other more ancestral plant species with one or two members, the WOX family gene in woody plant species has expanded in number and evolved in terms of sequence.

      Tissue-specific expression of a gene implies that the gene plays an indispensable role in certain tissues. We found that, like those in Arabidopsis, the WUS genes in P. bournei were mainly expressed in the epicotyls and shoot apical meristems (SAMs), but this is unlike the patterns of other popular genes, which are expressed in the SAMs, roots, stems, and leaves[39]. These results suggested that PbWUS might play a crucial role in maintaining the differentiation of the SAM. In Arabidopsis, AtWOX4 participates in TDIF-TDR-WOX4 signaling to maintain vascular meristem organization during secondary growth[40], which is similar to what occurs in poplar[41,42]. Here, PbWOX4 was also highly expressed in the stems; thus, this gene may have a function in P. bournei like that of its homologs in Arabidopsis and poplar. In addition, PbWOX4 was also expressed in the roots, leaves, and other plant tissues except embryogenic calli, suggesting that this gene is not involved in plant regeneration or development in vitro. Like AtWOX11, PtoWOX11/12a, and PtoWOX11/12b, three members, namely, PbWOX11/12a, PbWOX11/12b, and PbWOX11/12c, were expressed in the roots and embryogenic calli. Previous studies have shown that WOX11 is involved in adventitious root formation, which has an essential function in root regeneration during de novo plant regeneration[4346]. Therefore, it was speculated that these three PbWOX11 members might participate in calli propagation and/or root regeneration in P. bournei.

    • SE is one of the important mechanisms of plant asexual reproduction and is subject to complex transcriptional regulation, which in turn enables precise cell fate transitions and the formation of a complete plant. This hierarchical transcriptional regulatory network structure for SE has been revealed in Arabidopsis; in this process, WOX2 and WOX3 are the key TFs that induce SE[5]. According to the tissue expression patterns among tissues, we identified nine WOX genes that were expressed in embryogenic calli—the early stage of SE.

      WUS plays a crucial role in embryogenesis by promoting the fate of cells to transform and develop into embryos, and WUS can also drive the activity of embryonic stem cells. An earlier study showed that WUS is expressed in the four inner apical cells of 16-cell embryos and promotes the formation of the SAM during embryo development, and overexpression of WUS promotes the formation of high-frequency SE. Like in other species, such as Coffea canephora[47], Medicago truncatula[48], and Gossypium hirsutum[15], WUS overexpression resulted in an increased SE induction ratio. In our study, the expression level of WUS significantly increased in the late stage of embryogenic calli and increased significantly again at the immature cotyledon-producing embryo stage. These results indicated that PbWUS promotes the proliferation of embryogenic calli, affects the establishment of cell axial polarity, such as the formation of apical bud meristems during embryonic development in plants, and especially promotes the transition to cotyledon-producing embryos.

      In addition to WUS, WOX2 and WOX9 are the most reported WOX genes involved in plant SE. In the present study, PbWOX2a and PbWOX9 exhibited similar expression patterns, which were exemplified by higher expression levels observed at the embryogenic cell stage and during early somatic embryo formation. In Arabidopsis, it has been proposed that AtWOX2 and AtWOX9 play crucial roles in apical–basal axis formation during embryo development[19]. AtWOX2 is expressed in the apical cell, whereas AtWOX9 is expressed in the basal cell. These genes expressed at specific sites drive the fate of cells in the embryo. In grapevine, both VvWOX2 and VvWOX9 are labeled marker genes of early embryogenic phases[22]. In addition, WOX2 and WOX9 were found to play crucial roles in the early stage of SE in the gymnosperm Picea abies[21,49]. Therefore, PbWOX2a and PbWOX9 might be marker genes for early embryonic development of P. bournei.

      WOX11 has been reported to be an important upstream gene involved in the generation of root system architecture and to promote adventitious root formation during de novo root organogenesis from leaf explants[44,50], but this gene has not been found to be related to root regeneration in plant SE. We noted that PbWOX11/12a, PbWOX11/12b, and PbWOX11/12c were all detected in the embryogenic calli, specifically in immature and mature cotyledon-producing embryos. A similar phenomenon has been observed in grapevine, exemplified by VvWOX11 being highly expressed in torpedo-stage and cotyledon-producing embryos[22]. These findings further support that WOX11/12 might play an important role in the later stage of somatic embryo development and is probably related to root development, but whether WOX11/12 is involved in root primordium formation remains to be confirmed.

      In P. bournei, two WOX13 genes orthologous to AtWOX13 were detected in calli and somatic embryos, but their expression patterns differed. The expression level of PbWOX13a gradually increased with embryo development, while that of PbWOX13b showed no significant change. To our knowledge, WOX13 is expressed ubiquitously and participates in calli formation and organ reconnection in Arabidopsis[51]. However, the molecular regulatory roles of WOX13 during somatic embryo regeneration remain unclear, and expression profiles have been reported in only Vitis vinifera, in which three VvWOX13 genes exhibited low expression levels in somatic embryos, and the expression profile was unaffected by environmental changes[22]. Our data showed that two PbWOX13s also exhibited ubiquitous expression patterns. Nevertheless, PbWOX13b expression seemingly changed nonsignificantly during embryonic calli induction and mature cotyledon-producing embryos, while the expression level of PbWOX13a slightly increased in the later stage of somatic embryo development. Taken together, these results suggested that PbWOX13a might play a regulatory role at the later stage of somatic embryo development.

    • SE is a highly efficient method for plant regeneration[52]. Overexpression of WUS, WOX2, WOX9, BBM, and SERK is an efficient way to induce SE, and application of plant growth regulators such as auxin, MeJA, ABA, and GA is another useful method[6,47,5355]. These hormones undergo crosstalk with various TFs and play a primary role in SE[20]. However, information on interactions between phytohormones and WOX genes in P. bournei is lacking. In our study, referring to the information of cis-acting elements in the promoters of PbWOXs, we evaluated that the expression profiles of PbWOXs in embryogenic calli after treatment with IAA, MeJA, and ABA.

      Auxin was first discovered to affect embryonic initiation in carrot and has been widely used to induce SE not only in angiosperms but also in gymnosperms[56]. Moreover, studies have indicated that auxin distribution is positively correlated with the accumulation of WUS, WOX2, and WOX9 transcripts[27,57,58]. In P. bournei, the expression of WUS and WOX5/7 was induced by auxin. However, the expression of WOX2 and WOX9 was inhibited, opposite to what has been reported in Picea abies[49]. In view of this phenomenon, we analyzed the possible causes of species differences or differences in auxin concentration. Whether WOX2/WOX9 and auxin play a synergistic or antagonistic role in somatic embryo initiation remains to be determined.

      ABA involvement in embryo development and maturation has been demonstrated in the SE of several species. In late embryonic development, LEA proteins accumulate in large quantities and act as components of ABA-inducible systems. On the other hand, exogenous ABA in culture media has been shown to promote the maturation and regeneration of somatic embryos[55]. Previous studies have shown that embryo cells cultured in media supplemented with 100 μM ABA produced more embryos in sugi[59]. Six SlWOXs were significantly upregulated after 3 h of 100 μM ABA treatment in tomato[60]. Our data showed that PbWOX11/12a, PbWOX11/12b and PbWOX11/12c were also briefly induced after 3 h of ABA treatment. At the same time, these three genes were highly expressed in the cotyledon-producing embryo stage of SE. It was further speculated that the expression of PbWOX11/12s is likely to be activated by ABA signaling, thereby promoting somatic embryo maturation.

      MeJA is another hormone that increases somatic embryo induction and maturation rate. The effect of MeJA is similar to that of ABA to some extent, but it cannot replace ABA[33]. Previously, 50 μM and 100 μM MeJA were used to treat embryonic calli of longan[61], and exogenous applications of 10-400 μM MeJA produced more mature somatic embryos to different extents[62] Here, we used qPCR to measure the expression changes of PbWOXs after 100 μM MeJA treatment and hoped to determine the relationship between PbWOXs and MeJA. Our data showed that the expression levels of PbWUS and PbWOX11/12a were induced rapidly after MeJA treatment. In addition, the expression levels of PbWOX2a and PbWOX9 were inhibited by MeJA after 3 h. Therefore, applying MeJA to calli for a suitably short time might promote the somatic embryo differentiation process in P. bournei.

    • The WOX family is unique to plants, and WOX members play important regulatory roles in plant development, such as embryonic patterning. In the present study, we identified 15 PbWOX members in P. bournei, and their expression patterns among different tissues and SE process were determined, and the relationships between PbWOXs and hormones were also analyzed. These results are helpful to further study the regulatory roles of PbWOXs during SE, thus provides the important gene resources for regulating the SE process in P. bournei and other forestry trees.

      • We acknowledge Wenting Xu from Zhejiang A&F University for providing basic experimental materials. We thank for professor Longjun Cheng (Zhejiang A&F University) for his guidance. This work was supported by the Zhejiang Science and Technology Major Program on Agricultural New Variety Breeding (2021C02070-10), the National Natural Science Foundation of China (32171828 and 32101545).

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2023 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (6)  Table (2) References (62)
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    Zhang M, Chen X, Lou X, Zhang Y, Han X, et al. 2023. Identification of WUSCHEL-related homeobox (WOX) gene family members and determination of their expression profiles during somatic embryogenesis in Phoebe bournei. Forestry Research 3:5 doi: 10.48130/FR-2023-0005
    Zhang M, Chen X, Lou X, Zhang Y, Han X, et al. 2023. Identification of WUSCHEL-related homeobox (WOX) gene family members and determination of their expression profiles during somatic embryogenesis in Phoebe bournei. Forestry Research 3:5 doi: 10.48130/FR-2023-0005

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