Breeding Science
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Research Papers
Allelic variation of low molecular weight glutenin subunits composition and the revealed genetic diversity in durum wheat (Triticum turgidum L. ssp. durum (Desf))
Xin HuYanchun PengXifeng RenJunhua PengEviatar NevoWujun MaDongfa Sun
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Supplementary material

2018 Volume 68 Issue 5 Pages 524-535

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Abstract

Low molecular weight glutenin subunits (LMW-GS) play an important role in determining the bread-making characteristics of dough in the end-use quality of wheat. In this study, A total of 149 worldwide-originated durum wheat were used to analyze the composition of LMW-GS using MALDI-TOF-MS. Based on the allelic variation of glutenin subunits, the genetic diversity was evaluated for the 149 durum wheat. Five types of alleles were identified at the Glu-A3 locus with Glu-A3e, Glu-A3a/c, Glu-A3f, Glu-A3d and Glu-A3b accounting for 43.0%, 16.1%, 12.8%, 10.1% and 7.4 % of the accessions, respectively. Five types of alleles were identified at the Glu-B3 locus: Glu-B3d (60.4%), Glu-B3b (6.0%), Glu-B3c (6.0%), Glu-B3h (2.7%) and Glu-B3f (0.7%). Two novel alleles encoding abnormal subunits 40500 Da and 41260 Da were identified at the Glu-A3 and Glu-B3 loci, respectively. Further studies are needed to match these novel alleles to previously discovered novel alleles. Moreover, the genetic diversity analysis indicated that great genetic variation existed in durum wheat among encoding loci of glutenin subunits, released periods of varieties and different geographical origins. The results provide more important information of potential germplasm for the improvement of durum wheat and common wheat.

Introduction

Glutenin proteins, the compositions of wheat flour, play a key role in determining wheat rheological characteristics including dough strength and extensibility and bread-making performance (Bekes et al. 2001, Butow et al. 2003, Ma et al. 2005). Glutenin fractions consist of aggregated proteins linked by interchain disulfide bonds, and the polymeric glutenin proteins have various sizes ranging in molecular weight from less than 300,000 Da to more than 1,000,000 Da (Liu et al. 2010, Wieser et al. 2006, Wieser 2007). Glutenin subunits could be divided into high molecular weight glutenin subunits (HMW-GS) and low molecular weight glutenin subunits (LMW-GS) (D’Ovidio and Masci 2004, Jackson et al. 1983, Payne and Corfield 1979). It has been recognized that the molecular weight (MW) distribution of glutenins mainly determines the properties and baking performance of dough (Weegels et al. 1996).

LMW-GS contain a large amount of polypeptides. For the difficult to distinguish LMW-GS from gliadins, the composition, structure of LMW-GS and the relationship between LMW-GS and grain processing quality have not yet been studied to the same level as the HMW-GS (Appelbee et al. 2009, D’Ovidio and Masci 2004). LMW-GS, significant components of wheat storage proteins, are important in determining dough properties (including gluten strength and dough extensibility) (Cornish et al. 2001, Gianibelli et al. 2001). Therefore, identifying the allelic variation of LMW-GS and analyzing the relationships between LMW-GS and grain processing quality have been an attractive research area on quality improvement for the last 20 years, and the successful utilization of specific LMW-GS alleles is foundational and essential for quality breeding programs (Békés et al. 2006, Gupta et al. 1994, He et al. 2005).

LMW-GS were initially identified from the extracts of wheat flour by gel filtration and starch gel electrophoresis (Elton and Ewart 1966). Most LMW-GS are encoded by the Glu-A3, Glu-B3 and Glu-D3 loci on the short arms of chromosomes 1A, 1B and 1D, respectively (where, Glu-A3 and Glu-B3 in tetraploid wheat), and tightly linked to the complex Gli-1 loci, which encode γ- and ω-gliadins (Anderson et al. 2009, Payne et al. 1984, Pogna et al. 1990, Singh and Shepherd 1988). A few LMW-GS were encoded by the Glu-A3 locus on chromosome 1A, however, there is wide variation for LMW-GS encoded by Glu-B3 locus on chromosome 1B in common wheat (Gupta and Shepherd 1990, Liu et al. 2010, Yan et al. 2003). Although the Glu-D3 locus has less variation with five alleles initially reported by Gupta and Shepherd (1990), discrepancy exists among different studies about the alleles (Appelbee et al. 2009, Ikeda et al. 2006, Jackson et al. 1996), suggesting that further studies are necessary to clarify the genetic variation at this locus.

One-dimensional SDS-PAGE, 2-DE (two-dimensional gel electrophoresis (IEF × SDS-PAGE)) and HPLC (High performance liquid chromatography) methods have been generally used to identify and select specific HMW-GS and LMW-GS with superior quality in many breeding programs (Dworschak et al. 1998, Yahata et al. 2005). Matrix-assisted laser desorption/ionization time-of flight (MALDI-TOF-MS) is an effective and very important approach in rapidly and easily identifying glutenin subunits for its high accuracy and sensitivity in analyzing samples, which has been particularly useful in wheat quality breeding programs (Dworschak et al. 1998, Elfatih et al. 2013, Liu et al. 2009, 2010, Peng et al. 2016, Zheng et al. 2011). MALDI-TOF-MS has widely been used to identify the HMW-GS compositions of common landraces of bread wheat collected from the Yangtze-River region of China (Zheng et al. 2011), to detect the compositions of HMW-GS in durum wheat from different countries (Elfatih et al. 2013), to establish an analytical standard for identifying LMW-GS using a set of 19 near-isogenic lines (NIL) of cultivar Aroona (Wang et al. 2015).

Durum wheat (Triticum durum Desf.) is a tetraploid species containing A and B genomes (2n = 4x = 28, AABB) (Peng et al. 2011), and is the main material of semolina for the processing of pasta, bagel and other local end-products of Mediterranean (Fabriani et al. 1988, Nachit et al. 1992). The quality of durum wheat end-products depends mainly on glutenin composition. Different composition of HMW-GS and LMW-GS and their combinations may result in differences in gluten elasticity and strength (Elfatih et al. 2013). Generally, the LMW-GS are associated with resistance and extensibility of dough (Cornish et al. 2001, Metakovsky et al. 1990), and some allelic forms of LMW-GS present even greater effects than HMW-GS on these characteristics (Gupta et al. 1994, Payne et al. 1987). LMW-GS are also important for the end-use quality of dough in durum wheat, especially subunits encoded by loci on chromosome 1B (D’Ovidio and Masci 2004, Josephides et al. 1987). LMW-2, a specific allele encoding typical LMW-GS, is associated with the best pasta making characteristics (Payne et al. 1984), and also seems to be significant in determining bread-making properties (D’Ovidio and Masci 2004, Peña et al. 1994). Generally, as the genetic basis of modern wheat cultivars is narrow, special durum wheat cultivars, containing unusually useful genes are rich resources for wheat quality improvement (Li et al. 2006). The aims of the present study were to: (a) identify the LMW-GS compositions of worldwide-originated durum wheat using MALDI-TOF-MS, and reveal the difference of the LMW-GS compositions in different accessions, and (b) evaluate the genetic diversity in world-wide origin durum wheat based on the allelic variation of LMW-GS and HMW-GS, and genetic diversity in different released periods of varieties and geographical origins, respectively.

Materials and Methods

Plant materials

A total of 149 accessions of worldwide-originated durum wheat (Triticum turgidum L. ssp. durum (Desf.), 2n = 4x = 28, AABB) were used in this study, including 25 from East Asia (EA), 24 from West Asia (WA), 33 from Europe (EU), 16 from Africa (AF), 32 from North America (NA), 12 from South America (SA), and 7 from Australia (AU) (Table 1). The accessions used in the present study were also included in the study of Elfatih et al. (2013), and were all obtained from USDA (United States Department of Agriculture).

Table 1 The LMW-GS compositions for 149 accessions analyzed by MALDI-TOF-MS
Code Accession identifiera Accession name Regions Place of origin Year of collection Type Glu-A3 Glu-B3
H45 PI 233213 Sevindz EA Azerbaijan 1956 Cultivar 40503 Da d
H61 PI 345707 Sevindz EA Azerbaijan 1969 Cultivar 40494 Da d
H1 CItr 11495 Wash. No. 2628 EA Heilongjiang, China 1932 Cultivar b d
H14 CItr 5077 FHB4495 EA China 1916 Landrace e b
H142 PI 70658 Tulatai Maitai EA Heilongjiang, China 1926 Landrace d h
H143 PI 70662 Lumanian EA Heilongjiang, China 1926 Landrace d 41300 Da
H146 PI 74830 ICARDA-IG-82496 EA Jiangsu, China 1927 Landrace a/c d
H147 PI 79900 N-85 EA Heilongjiang, China 1929 Landrace d 41325 Da
H15 CItr 5083 FHB4501 EA China 1916 Landrace a/c f
H16 CItr 5094 FHB4512 EA Beijing, China 1916 Landrace d 41259 Da
H19 CItr 8327 Suifu EA Sichuan, China 1924 Landrace e d
H23 PI 124292 ICARDA-IG-82575 EA Jiangsu, China 1937 Landrace f d
H54 PI 283853 China 34 EA China 1962 Cultivar e d
H90 PI 435100 Bian Sui EA China 1979 Cultivar e d
H92 PI 447421 ST-33 EA Xinjiang, China 1980 Cultivar f d
H84 PI 41015 Jalalia EA Madhya Pradesh, India 1915 Landrace b d
H85 PI 41342 Hansia Broach EA Gujarat, India 1915 Landrace b d
H133 PI 61351 Medea EA Hokkaido, Japan 1924 Landrace d 41291 Da
H134 PI 61352 Roumania EA Hokkaido, Japan 1924 Landrace d 41289 Da
H130 PI 61112 CItr 7395 EA Kazakhstan 1924 Landrace a/c 41248 Da
H131 PI 61123 CItr 7406 EA Kazakhstan 1924 Landrace 40511 Da 41284 Da
H32 PI 176228 ICARDA-IG-84631 EA Nepal 1949 Landrace b d
H41 PI 210910 T 1 EA Punjab, Pakistan 1953 Cultivar a/c d
H42 PI 210911 T 2 EA Punjab, Pakistan 1953 Cultivar a/c d
H83 PI 388132 FAO 33.268 EA Punjab, Pakistan 1974 Landrace a/c d
H123 PI 591959 DW 1 WA Cyprus 1994 Cultivar e d
H43 PI 210952 Damliko WA Cyprus 1953 Landrace f d
H47 PI 237632 Tripolitico WA Cyprus Cultivar e d
H25 PI 140184 ICARDA-IG-82637 WA Khuzestan, Iran 1941 Landrace e c
H44 PI 222675 ICARDA-IG-85523 WA East Azerbaijan, Iran 1954 Landrace a/c d
H48 PI 243790 ICARDA-IG-85615 WA Tehran, Iran 1957 Landrace e d
H56 PI 289821 ICARDA-IG-97583 WA Fars, Iran 1963 Landrace e c
H144 PI 70736 ICARDA-IG-82459 WA Iraq 1926 Landrace e b
H28 PI 165846 Amarah WA Iraq 1948 Cultivar f b
H37 PI 208903 Rash Kool WA Iraq 1953 Landrace e d
H38 PI 208907 Lara WA Iraq 1953 Landrace e d
H39 PI 208908 Mendola WA Iraq 1953 Landrace a/c d
H40 PI 208910 Sin El-Jamil WA Iraq 1953 Landrace e 41259 Da
H51 PI 253801 K918 WA Ninawa, Iraq 1958 Landrace e d
H49 PI 249816 N-163 WA Israel 1958 Cultivar e d
H50 PI 249820 Neveh Yaar 51 WA Israel 1958 Cultivar e 41269 Da
H57 PI 292035 WA Israel 1963 Cultivar e c
H81 PI 384043 Merarit WA Israel 1973 Cultivar 40643 Da c
H82 PI 388035 Line 76 WA Israel 1974 Cultivar e b
H105 PI 520415 Syrian Durum 27 WA Syria 1987 Cultivar e d
H24 PI 134596 Fere-Alexandrinum WA Syria 1939 Landrace e d
H33 PI 182697 Nashabie WA Dimashq, Syria 1949 Landrace a/c d
H36 PI 193391 Aleppo WA Halab, Syria 1951 Landrace b 41267 Da
H26 PI 152567 Aden WA Yemen 1945 Cultivar a/c h
H109 PI 546462 Gergana EU Khaskovo, Bulgaria 1990 Cultivar 40580 Da d
H60 PI 344743 Apulicum 233 EU Bulgaria 1969 Cultivar e 41254 Da
H72 PI 352450 EU France 1969 Cultivar d 41283 Da
H12 CItr 2468 EU Germany 1904 Landrace 40472 Da d
H58 PI 306664 Heines Hartveizen EU Lower Saxony, Germany 1965 Cultivar f d
H64 PI 352389 Caravicos EU Greece 1969 Cultivar f d
H124 PI 593005 V. 433 EU Latium, Italy 1996 Cultivar f d
H68 PI 352408 T-1560 EU Italy 1969 Cultivar e d
H69 PI 352415 Aziziah 17/45 EU Latium, Italy 1969 Cultivar b d
H115 PI 56233 CItr 7041 EU Lisboa, Portugal 1923 Cultivar f d
H74 PI 376498 DF 14/71 EU Romania 1972 Cultivar a/c d
H75 PI 376500 DF 31/71 EU Romania 1972 Cultivar a/c d
H76 PI 376501 DF 42/71 EU Romania 1972 Cultivar a/c 41292 Da
H77 PI 376509 DF 4/72 EU Romania 1972 Cultivar 40617 Da d
H78 PI 376511 DF 6/72 EU Romania 1972 Cultivar a/c b
H79 PI 376512 DF 7/72 EU Romania 1972 Cultivar a/c d
H13 CItr 3267 Chistunka EU Altay, Russian Federation 1911 Landrace d 41227 Da
H132 PI 61189 CItr 7472 EU Krasnoyarsk, Russian Federation 1924 Landrace e d
H70 PI 352436 T-2114 EU Former Soviet Union 1969 Cultivar d h
H71 PI 352437 T-2115 EU Former Soviet Union 1969 Cultivar 40503 Da b
H67 PI 352404 Torcal EU Spain 1969 Cultivar 40499 Da d
H35 PI 192711 Ostpreuss EU Gotland, Sweden 1950 Cultivar e d
H63 PI 352377 T-357 EU Switzerland 1969 Cultivar a/c d
H111 PI 560702 TU85-008-10-2 EU Siirt, Turkey 1986 Landrace e d
H112 PI 560717 TU85-054-01-2 EU Bitlis, Turkey 1986 Landrace e 41267 Da
H113 PI 560718 TU85-054-02 EU Bitlis, Turkey 1986 Landrace e d
H114 PI 560889 TU86-24-02-2 EU Siirt, Turkey 1989 Landrace f c
H21 PI 109588 T-538 EU Ankara, Turkey 1935 Cultivar 40491 Da 41252 Da
H62 PI 346985 Hacimestan EU Turkey 1970 Cultivar e d
H52 PI 278223 Gartons Early Cone EU England, United Kingdom 1962 Cultivar e c
H53 PI 278648 ICARDA-IG-85863 EU England, United Kingdom 1962 Cultivar e b
H59 PI 321702 Nursi EU England, United Kingdom 1967 Cultivar e d
H91 PI 438973 Har’kovskaja 51 EU Kharkiv, Ukraine 1980 Cultivar d 41274 Da
H107 PI 546060 DT367 NA Saskatchewan, Canada 1990 Cultivar e d
H108 PI 546362 DT369 NA Saskatchewan, Canada 1991 Cultivar e d
H11 CItr 17337 Wakooma NA Saskatchewan, Canada 1974 Cultivar e d
H119 PI 583724 8682-D051-NG NA Saskatchewan, Canada 1994 Cultivar e d
H120 PI 583731 G8973-AG1-G NA Saskatchewan, Canada 1994 Cultivar e d
H121 PI 583732 G8973-AG1-NG NA Saskatchewan, Canada 1994 Cultivar e d
H122 PI 583733 G8973-AQ1-G NA Saskatchewan, Canada 1994 Cultivar e d
H98 PI 519751 D 31729-2L-OL NA Federal District, Mexico 1987 Cultivar e 41274 Da
H101 PI 519761 Maghrebi‘S’ NA Federal District, Mexico 1987 Cultivar e 41298 Da
H102 PI 519866 CB 088 NA Federal District, Mexico 1987 Cultivar f d
H103 PI 520053 31814-1L-OC NA Federal District, Mexico 1987 Cultivar e 41287 Da
H104 PI 520173 Tal NA Mexico 1987 Cultivar e 41291 Da
H129 PI 610765 CIGM91.347-6 NA Federal District, Mexico 1999 Cultivar f d
H135 PI 634315 Canelo NA Federal District, Mexico 2001 Cultivar e d
H136 PI 634318 Afuwan NA Federal District, Mexico 2001 Cultivar e d
H30 PI 168708 Barrigon Glabrous Selection NA Mexico 1948 Cultivar b h
H6 CItr 15874 D 19329-28M-11Y NA Mexico 1972 Cultivar a/c d
H86 PI 422289 Maghrebi 72 NA Mexico 1978 Cultivar e 41304 Da
H88 PI 428453 Dommel‘S’ NA Federal District, Mexico 1978 Cultivar f d
H99 PI 519752 D 31648-2L-OL NA Federal District, Mexico 1987 Cultivar d 41304 Da
H110 PI 560335 KS91WGRC14 NA Kansas, United States 1992 Cultivar e d
H118 PI 573005 Imperial NA Arizona, United States 1988 Cultivar f d
H125 PI 600931 D-5003 NA California, United States 1982 Cultivar e d
H126 PI 601250 Westbred Laker NA Arizona, United States 1985 Cultivar e d
H137 PI 656793 NSGC 19376 NA California, United States 2009 Cultivar e 41307 Da
H138 PI 656794 IR51-8 NA California, United States 2009 Cultivar e 41325 Da
H139 PI 656795 IR17-47 NA California, United States 2009 Cultivar e 41317 Da
H150 PI 9872 Galgalos NA Erevan, Armenia 1903 Cultivar f b
H18 CItr 6881 Akrona NA Colorado, United States 1923 Cultivar d 41268 Da
H2 CItr 12068 Kubanka 314 NA North Dakota, United States 1940 Cultivar 40490 Da 41264 Da
H3 CItr 13246 Ramsey NA North Dakota, United States 1955 Cultivar d 41255 Da
H4 CItr 13333 Wells NA North Dakota, United States 1957 Cultivar e 41253 Da
H116 PI 565259 Yurac Mexico SA Cochabamba, Bolivia 1991 Landrace e d
H117 PI 565266 Mexico SA Cochabamba, Bolivia 1991 Landrace e d
H100 PI 519759 D 73121 SA Brazil 1987 Cultivar e 41214 Da
H34 PI 191645 Timor SA Sao Paulo, Brazil 1950 Cultivar e d
H10 CItr 17159 CAR 1234 SA La Araucania, Chile 1972 Cultivar a/c d
H7 CItr 17057 CAR 1131 SA La Araucania, Chile 1972 Cultivar a/c d
H8 CItr 17058 CAR 1132 SA La Araucania, Chile 1972 Cultivar a/c d
H9 CItr 17157 CAR 1232 SA La Araucania, Chile 1972 Cultivar a/c d
H55 PI 286546 Morocho Colorado SA Pichincha, Ecuador 1963 Cultivar e d
H148 PI 91956 Chumpe Negro SA Junin, Peru 1931 Cultivar a/c d
H149 PI 92024 Candeal SA Cajamarca, Peru 1931 Cultivar d d
H29 PI 168692 Muestra 2 Barba Blanca Anquipa SA Peru 1948 Cultivar f d
H22 PI 11715 Marouani AF Mascara, Algeria 1904 Landrace a/c d
H106 PI 532119 2515 AF Minufiya, Egypt 1988 Cultivar f d
H127 PI 60712 Gawi AF Egypt 1924 Landrace f c
H128 PI 60742 Sinai No. 8 AF Sinai, Egypt 1924 Landrace b d
H141 PI 7016 Mishriki AF Alexandria, Egypt 1901 Landrace b c
H145 PI 7422 Girgeh AF Sawhaj, Egypt 1901 Landrace b c
H27 PI 153774 Durum H AF Giza, Egypt 1946 Cultivar f d
H66 PI 352395 T-1303 AF Ethiopia 1969 Cultivar f b
H73 PI 352551 Abyssinicum AF Ethiopia 1969 Landrace d 41252 Da
H87 PI 42425 Zwartbaard AF South Africa 1916 Landrace 40508 Da d
H93 PI 45442 ICARDA-IG-98118 AF Free State, South Africa 1917 Landrace 40546 Da d
H94 PI 45443 ICARDA-IG-98119 AF Cape Province, South Africa 1917 Landrace 40552 Da d
H95 PI 46766 Golden Ball AF Cape Province, South Africa 1918 Cultivar e 41308 Da
H65 PI 352390 T-842 AF Tunisia 1969 Cultivar e d
H96 PI 51210 Mahmoudi AF Tunisia 1920 Landrace e d
H97 PI 519380 BD 1645 AF Tunisia 1987 Cultivar e 41258 Da
H140 PI 67341 Huguenot AU Western Australia, Australia 1926 Cultivar 40514 Da d
H17 CItr 5136 Indian Runner AU Victoria, Australia 1916 Landrace 40497 Da d
H20 PI 107606 Cadia AU Australia 1934 Cultivar b 41259 Da
H31 PI 174645 Huguenot AU Western Australia, Australia 1949 Cultivar a/c d
H46 PI 235159 Giza AU New South Wales, Australia 1956 Cultivar e 41260 Da
H80 PI 377882 Duramba AU Australia 1973 Cultivar e d
H89 PI 428701 AUS 20299 AU Australia 1978 Cultivar e d
a  The accession identifier is adopted from the USDA.ARS National Plant Germplasm System-Germplasm Resources Information Network (https://www.ars-grin.gov/npgs/acc/acc_queries.html).

Protein extraction

Proteins were extracted from 20 mg whole meal based on the sequential procedure of Singh et al. (1991). The samples were extracted with 1.0 ml of 55% propanol-1-ol (v/v) for 5 min vortexing, followed by incubation for 20 min at 65°C, then continued vortexing for 5 min with a centrifugation at 10,000 × g for 5 min. Repeated this step three times to completely remove the gliadins. The glutenin in the pellet was reduced with 55% propanol-1-ol, containing 0.08 M Tris-HCl solution and 1% dithiothreitol (DTT) and incubation for 30 min at 65°C, followed by addition of 1.4% v/v of 4-vinylpyridine, and alkylation and incubation overnight at room temperature. For MALDI-TOF-MS analysis, 80% acetone was used to precipitate the LMW-GS portion.

MALDI-TOF-MS

The dried compounds of LMW-GS samples were dissolved in 60 μl acetonitrile (ACN)/H2O (v/v, 50:50) containing 0.05% v/v trifluoroacetic acid (TFA) for 1 h at room temperature. Referring to the dried droplet method of Kussmann et al. (1997), sample preparation was carried out using sinapinic acid (SA) as matrix. The matrix solution was made by dissolving SA in ACN/H2O (50:50 v/v) containing 0.05% TFA (v/v) at a concentration of 10 mg/ml. Mixing the extracted LMW-GS solution (a total of 60 μl) with SA solution (1:10 v/v) for protein-SA mixture, and 2 μl of this mixture was deposited on to a 96-sample MALDI target probe tip, then dried at room temperature. MALDI-TOF-MS experiments were performed on a Voyager DE-PRO TOF mass spectrometer (Applied Biosystems, Foster City, CA, USA) with UV nitrogen laser (337 nm) at the State Agriculture Biotechnology Center, Murdoch University, Australia. Analyses were performed with the following parameters: acceleration voltage 25 kV and delay time 900 ns, mass range 10,000–50,000 Da. The low mass gate value (10,000 m/z) for analysis was chosen to avoid saturation of the sensor. The new standard established with 16 single Glu-3 allele substitution lines of Aroona, 25 gene deletion lines and 60 wheat lines with known LMW-GS compositions as reference in Wang et al. (2015), was used to analyze the composition of LMW-GS alleles. The established standard in Wang et al. (2015) for specific MALDI-TOF spectrum patterns corresponding to LMW-GS allele were summarized in Supplemental Table 1.

Genetic diversity analysis

The genetic diversity was evaluated based on the allelic variation of LMW-GS in this study and HMW-GS in the study of Elfatih et al. (2013) (see Supplemental Table 2). POWERMARKER Ver. 3.25 (Liu and Muse 2015) was used to analyze the genetic diversity using the genetic parameters Nei’s gene diversity and polymorphism information content (PIC). A phylogenetic NJ tree based on acessions and regions were performed by POWERMARKER Ver. 3.25 with 1000 bootstrap replicates. A consensus tree with bootstrap values was reconstructed by the consensus program of PHYLIP (Plotree and Plotgram 1989) and displayed by FigTree Ver.1.4 (Rambaut 2014).

Results

Allelic variation of LMW-GS at Glu-A3 and Glu-B3

According to the established standard in Wang et al. (2015) for specific MALDI-TOF spectrum patterns corresponding to LMW-GS alleles (Supplemental Table 1), the mass spectra of the LMW glutenin subunits showed well-separated peaks in the spectrum of each material, and the mass spectra of the LMW glutenin subunits for some materials were shown in Fig. 1. The LMW-GS compositions for 149 accessions analyzed by MALDI-TOF-MS are listed in Table 1. A total of 12 alleles (ten previously reported and two unreported alleles) of LMW-GS were found in the MALDITOF-MS profile and their frequencies were presented in Table 2. A total of 23 types of LMW-GS compositions were detected during 149 accessions at Glu-A3 and Glu-B3 loci (Table 3).

Fig. 1

Detection of LMW-GS for some durum accessions by MALDI-TOF-MS. Accessions code: (A) H24, (B) H39, (C) H66, (D) H61. (E) H99, (F) H131.

Table 2 Allele frequencies of LMW-GS revealed by MALDI-TOF-MS
Locus LMW-GS Number Frequency %
GluA3 40500 Da 16 10.7
a/c 24 16.1
b 11 7.4
d 15 10.1
e 64 43.0
f 19 12.8
GluB3 41260 Da 36 24.2
b 9 6.0
c 9 6.0
d 90 60.4
f 1 0.7
h 4 2.7
Table 3 Allele combinations and variants at Glu-A3 and Glu-B3 loci in durum wheat
GluA3 GluB3 Number Frequency %
1 40500 Da 41260 Da 3 2.0
2 40500 Da b 1 0.7
3 40500 Da c 1 0.7
4 40500 Da d 11 7.4
5 a/c 41260 Da 2 1.3
6 a/c b 1 0.7
7 a/c d 19 12.8
8 a/c f 1 0.7
9 a/c h 1 0.7
10 b 41260 Da 2 1.3
11 b c 2 1.3
12 b d 6 4.0
13 b h 1 0.7
14 d 41260 Da 12 8.1
15 d d 1 0.7
16 d h 2 1.3
17 e 41260 Da 17 11.4
18 e b 4 2.7
19 e c 4 2.7
20 e d 39 26.2
21 f b 3 2.0
22 f c 2 1.3
23 f d 14 9.4

At the Glu-A3 locus, five previously reported alleles were identified. Glu-A3e showed the highest frequency that was detected in 43.0% of the 149 accessions, followed by the Glu-A3a/c (16.1%), Glu-A3f (12.8%), Glu-A3d (10.1%) and Glu-A3b (7.4%) (Tables 1, 2). However, alleles Glu-A3a and Glu-A3c have identical molecular masses, and were difficult to be distinguished by MALDI-TOF-MS (Wang et al. 2015). Moreover, one previously unreported allele was detected at Glu-A3 locus in sixteen (10.7%) accessions encoding a novel subunit with a molecular weight of approximately 40,500 Da (ranging from 40,472 Da to 40,580 Da).

At the Glu-B3 locus, five previously reported alleles were identified. Out of 149 accessions, 60.4% (90) of them were identified with Glu-B3d, indicating that Glu-B3d was the most frequent allele at Glu-B3 locus. Glu-B3b and Glu-B3c each accounted for 6.0% of the accessions. Glu-B3h was detected in 4 accessions and Glu-B3f was detected only in one accession. Moreover, a new LMW glutenin subunit was identified with the molecular weight of around 41,260 Da (ranging from 41,214 Da to 41,325 Da) in 36 accessions (24.2% of the accessions examined) (Tables 1, 2).

A total of 23 types of LMW-GS compositions were detected in this study. The most common combination type is Glu-A3e + Glu-B3d (26.2%), followed by Glu-A3a/c + Glu-B3d (12.8%), Glu-A3e + a new subunit with molecular weight of about 41260 Da (11.2%), moreover the combination of a new subunit with a molecular weight of about 40,500 Da and Glu-B3d was detected in 11 accessions (Table 3). Different subunits and different combinations of subunits have different effects on the quality and processing quality of the dough.

Overall, 12 alleles (ten previously reported and two unreported alleles) of LMW-GS were found in the MALDI TOF-MS at the two loci in durum wheat. Two unreported alleles were observed at loci Glu-A3 and Glu-B3, with 10.7% for Glu-A3 and 24.2% for Glu-B3. Furthermore, we also detected, in some materials, the spectrum peaks of approximately 43,267 Da and 41,758 Da, which were reported to be associated with novel subunits in Wang et al. (2015). However, these peaks were not novel in the current study.

Genetic diversity

The genetic diversity is listed in Table 4. For LMW-GS coding loci, a higher genetic diversity was detected at Glu-A3 locus with Nei’s gene diversity, and PIC values of 0.245 and 0.208, respectively, while 0.225 and 0.186 for Glu-B3 locus, respectively. For HMW-GS coding loci, the genetic diversity of Glu-A1 (with Nei’s gene diversity, and PIC values of 0.309 and 0.249, respectively) was higher than Glu-B1 (with Nei’s gene diversity, and PIC values of 0.153 and 0.134, respectively).

Table 4 The genetic diversity of GluA3, GluB3, GluA1 and GluB1 based on LMW-GS and HMW-GS alleles
Locus Genetic Diversity PIC
GluA3 0.245 0.208
GluB3 0.225 0.186
GluA1 0.309 0.249
GluB1 0.153 0.134

The genetic diversity for the 7 geographical regions is shown in Table 5. European accessions showed the highest values of both Nei’s gene diversity (0.216) and PIC (0.181), followed by African (AF: 0.213, 0175), East Asian (EA: 0.206, 0172) and North American accessions (NA: 0.195, 159), while the lowest level of Nei’s gene diversity and PIC were detected in South American accessions (SA: 0.156, 0.128). West Asian (WA) and Australian (AU) accessions had a moderate level of Nei’s gene diversity and PIC (with the values of 0.191, 0.160 and 0.180, 0.145, respectively).

Table 5 The genetic diversity of the accessions from 7 ecogeographic regions based on LMW-GS and HMW-GS alleles
Origin Genetic Diversity PIC
AF 0.213 0.175
AU 0.180 0.145
EA 0.206 0.172
EU 0.216 0.181
NA 0.195 0.159
SA 0.156 0.128
WA 0.191 0.160

The difference of genetic diversity between landrace and cultivar, and the release time is shown in Table 6. The higher genetic diversity was detected in the cultivars with Nei’s gene diversity and PIC values of 0.215 and 0.180, than values in the landrace. Therefore, according to Ren et al. (2013), the cultivars were also further divided into three temporal groups: OC (old cultivars before 1965), EGR (early green revolution, 1966–1980), PGR (post green revolution, 1980–2009), to compare the genetic difference. The genetic diversity parameters of three temporal groups of cultivars are shown in Table 6. Loss of genetic diversity was observed from OC to EGR (Nei’s gene diversity: 0.239 vs. 0.211 and PIC values: 0.200 vs. 0.177). However, the decrease of genetic diversity was observed from EGR to PGR (Nei’s gene diversity: 0.200 vs. 0.177 and PIC values: 0.165 vs. 0.135).

Table 6 Comparison of genetic diversity generated by the allelic variation of LMW-GS and HMW-GS between landraces and cultivars
Group Genetic Diversity PIC
Cultivar 0.215 0.180
Landrace 0.210 0.175
Time group of Cultivar
 Before 1965 0.239 0.200
 1965–1980 0.211 0.177
 1981–2009 0.165 0.135

Cluster analysis

The allelic variation of LMW-GS and HMW-GS loci was used for the cluster analysis. The consensus NJ tree of accessions based on Nei’s genetic distance (Nei 1972) is shown in Fig. 2. The durum wheat accessions were divided into two major groups.

Fig. 2

The NJ tree of 149 durum accessions based on the Nei’s genetic distance calculated from the alleles of LMW-GS and HMW-GS. The allelic variation data of HMW-GS was from the study of Elfatih et al. (2013), L: Landrace, OC: Old cultivars before 1965, EGR: Early green revolution, 1966–1980, PGR: Post green revolution, 1980–2009.

Group I contained the American accessions (North America and South America), this group was dominated by landraces and cultivars released during OC, EGR and PGR. Group II was further divided into 7 subgroups, grouping of some accessions appeared to be associated with the release period of varieties to some extent (Fig. 2, Supplemental Table 3).

The consensus NJ tree was constructed based on geographical regions of accessions (Fig. 3). The result indicated that the accessions of AU was different from the other regions. The accessions from other regions were divided into two group, EA, EU and AF were clustered in one group, WA, SA and NA were in the other group.

Fig. 3

The consensus NJ tree for the accessions from 7 ecogeographic regions based on the Nei’s genetic distance calculated from the alleles of LMW-GS and HMW-GS. The allelic variation data of HMW-GS was from the study of Elfatih et al. (2013).

Discussion

Allelic variation of LMW-GS at Glu-A3 and Glu-B3 and the novel subunits

The allelic variation of glutenin subunits can provide a more direct, reliable and efficient tool for the conservation and management of germplasm. In this study, the compositions and allelic variation of low molecular weight glutenin subunit (LMW-GS) in 149 worldwide-originated durum wheat were analyzed using MALDI-TOF-MS.

For the Glu-A3 locus, the most frequent allele was Glu-A3e accounting for 43.0%, while the frequency of Glu-A3a/c alleles was lower (16.1%). This is different from some previous studies. Bellil et al. (2012), Bradová and Štočková (2010), and Nieto-Taladriz et al. (1997) reported that Glu-A3a/c was the predominant alleles in wheat, while Glu-A3e was relatively low. Glu-A3a and Glu-A3c appeared to be world widely predominant among bread wheat in previous studies, whereas, Glu-A3e was predominant among durum wheat in our collections. However, low frequency of Glu-A3c was found in the Algerian local and old durum wheat cultivars (Cherdouh et al. 2005, Hamdi et al. 2010). Different species (common wheat and durum wheat), different sources and distributions of materials should lead to the differences in allele frequencies of LMW-GS reported by different scientists. It seems that the frequency of Glu-A3a and Glu-A3c were higher in common wheat than in durum wheat, while the frequency of Glu-A3e was relatively low. A previous study discovered that Glu-A3e reduced the maximum resistance and extensibility of dough in relative to other alleles of Glu-A3 (Appelbee 2007). It is worthy of noting that the Glu-A3d is a desirable allele for gluten quality and pan bread quality (He et al. 2005) and presented in 15 landraces. Moreover, a novel allele, encoding a subunit with a molecular weight of approximately 40,500 Da (ranging from 40,472 Da to 40,580 Da) located at Glu-A3, was detected in 20 accessions.

Allelic variation at the Glu-A3 locus did not significantly affect gluten strength, whereas the Glu-B3 locus had a significant influence on gluten strength, as measured by sedimentation volume on durum wheat (Vazquez et al. 1996). For the Glu-B3 locus, five previously reported alleles were identified in our study. The most frequent allele was Glu-B3d (60.4%). The similar result was reported in Saharan bread wheat and Durum wheat from Algerian Oases by Bellil et al. (2012). However, Glu-B3d had medium to weak dough properties, and should be avoided at the early stages of a bread wheat breeding program (Luo et al. 2001). Glu-B3b was rare and only detected in 9 accessions accounting for 6%, which is consistent with the studies of Bellil et al. (2010, 2012). It is worthy of noting that a novel allele, expressing a subunit with a molecular weight of approximately 41,260 Da (ranging from 41,214 Da to 41,325 Da) at Glu-B3, presented in 60 accessions.

Following the standard for LMW-GS of common wheat varieties reported by Wang et al. (2015), we were able to identify the alleles of LMW-GS in most of the durum wheat accessions. Most LMW-GS compositions of durum wheat materials can be detected rapidly and easily according to the characteristic peaks of standard samples in Wang et al. (2015). Several novel alleles were identified in landraces collected from Yangtze-River region of China in our research and in Peng et al. (2016) and Wang et al. (2015) at Glu-A3 and Glu-B3 loci. It should be mentioned that Peng et al. (2016) and Wang et al. (2015) found two novel subunits associated with the spectrum peaks 41,758 Da at Glu-A3 and 40,499 Da at Glu-B3. In our research, we also detected the spectrum peaks with similar masses of approximately 41,758 Da and 40,499 Da. However, compared with the results of Wang et al. (2015), our data tended to indicate the spectrum peak of approximately 41,758 Da present with the characteristic spectrum peak (37,600 Da) of Glu-A3a/c. This might suggest that the spectrum peak 41,758 Da was another characteristic spectrum peak for Glu-A3a/c (Fig. 1B). The spectrum peak 40,499 Da was identified as a characteristic spectrum peak for subunit of a novel allele at Glu-B3 in Peng et al. (2016) and Wang et al. (2015), however, this characteristic peak can be confidently treated as a new allele located at Glu-A3 in our study (Fig. 1D, 1F). Furthermore, another novel allele encoding a subunit with a molecular weight of approximately 41,260 Da at Glu-B3 locus was detected in our study, which was not reported in their studies (Fig. 1E, 1F). A more detailed study is needed to identify the novel alleles in the landraces collected from the Yangtze-River region in China and worldwide-originated durum wheat. Recently, a set of PCR primers have been developed and effectively used to amplify the coding region of the HMW-GS and LMW-GS genes, and numerous LMW-GS genes have been identified in the Glu-A3, Glu-B3 and Glu-D3 coding regions (Lan et al. 2013, Si et al. 2014, Wang et al. 2012). Using the conserved primers, the novel LMW-GS gene sequences may be amplified from genomic DNA of wheat accessions to match the novel alleles to previously reported alleles.

Genetic diversity

The genetic diversity of Glu-A3 was higher than Glu-B3 in this set of durum wheat, similar results were reported in the study of Moragues et al. (2006) for the accessions from North Africa, South Europe and West Asia. However, the genetic diversity of Glu-A1 was higher than Glu-B1 in this study, which was opposite to the result of Moragues et al. (2006). This could be due to different materials. In the study of Moragues et al. (2006), only 63 durum wheat landraces from the Iberian Peninsula and other Mediterranean countries were analyzed, while in our study, more world-wide originated accessions (including landraces and cultivars released in different period) were used.

The genetic diversity of durum wheat from 7 ecogeographic regions revealed by the allelic variation of LMW-GS and HMW-GS indicated the genetic diversity of durum wheat from ecogeographic origins was different. Generally, great genetic variation should exist in the center of origin and domestication. It was reported that “Fertile Crescent” is the centers of origin and diversification of durum wheat (Vavilov 1951). However, in this study, the highest genetic diversity of durum wheat was found in EU accessions, followed by AF and EA accessions, while WA accessions showed moderate levels of genetic diversity. Similar result was reported by Ren et al. (2013) based on SNP markers. One of the reasons should be uneven distribution of landraces or cultivars among countries and different genetic diversity levels between landraces and cultivars used in this study as discussed by Ren et al. (2013). Moreover, the genetic diversity, revealed by the allele variation of LMW-GS and HMW-GS loci, should be different to the genetic diversity evaluated by SNP markers around genome, this should be another reason.

The difference of genetic diversity between landrace and cultivar had been reported by Ren et al. (2013) based on SNP markers. In our study, the difference of genetic diversity based on the allele variation of LMW-GS and HMW-GS loci showed similar results to Ren et al. (2013) on some extent. The higher genetic diversity was detected in cultivar than landrace. Decrease of genetic diversity was observed from OC (before 1965) to EGR (1965–1980), which was consisted to Ren et al. (2013). As discussed in Ren et al. (2013), the low level diversity of varieties released in 1965–1980 (EGR) might be due to the “Early Green Revolution”, which resulted from widely use of the semi-dwarf varieties and the high yield breeding target. While, a continuous loss of genetic diversity was observed from EGR (1965–1980) to PGR (1981–2009), which is opposite to the result of Ren et al. (2013). During PGR, CIMMYT have realized the danger of narrowing down genetic diversity, they changed the breeding strategy for increasing genetic diversity of wheat and durum wheat, which increased genetic diversity (Reeves 1999). However, meanwhile, CIMMYT started to focus on the quality breeding, although, the genetic diversity was generally increased considering the whole genome. While the quality related loci or regions of chromosome were suffered selection pressure in breeding programs, and single germplasms with high-quality subunits was selected by breeder for breeding and promoting, these result in the decreasing of genetic diversity observed from EGR (1965–1980) to PGR (1981–2009) on the allele variation of LMW-GS and HMW-GS loci in this study.

Cluster analysis

Cluster analyses for accessions and their geographical originations were performed based on the allelic variation of LMW-GS and HMW-GS loci (Figs. 2, 3). some of accessions from the same geographic region and release period were clustered together though into different groups corresponding to their geographical regions of collection, release period and accession type (Landrace or Cultivar) (Fig. 2, Supplemental Table 3). For example, Group I contained 11 accessions (Cultivar) from NA (North America), most of which (8/11) were released during PGR (Fig. 2, Supplemental Table 3), and Group II-7 contained 6 landraces, all of which were from AF (Africa) and collection before 1924 (Fig. 2, Supplemental Table 3). These results indicated that many of the accessions were clustered corresponding to their geographical regions, collection time and accession type, which may be due to the similar environmental conditions or the utilization of single elite germplasm in breeding or agronomical practices.

The NJ tree for the origination regions of the durum accessions showed that the accessions from EA, EU and AF were close to each other, and accessions from WA, SA and NA have close relationship (Fig. 3). The accessions of AU were much difference from the others. A close relationship of between EA, EU and AF accessions align well the discussion of Moragues et al. (2006) based on the accepted theory of wheat cultivation spreading across the Mediterranean basin (Feldman and Millet 2001, Zohary et al. 2012), the theory reported T. monococcum spread west from the Fertile Crescent by two ways: North, through the Balcan Peninsula, Greece and Italy, and south through ancient Egypt. This explained the close relationship among the accessions of EA, EU and AF. The close relationship among the accessions of WA, SA and NA indicated that the three geographic regions maybe share some similar origin germplasms with similar allelic variation of LMW-GS and HMW-GS. Moreover, the germplasm exchange through cultural diffusion or historical human dispersal could also play an important role. As we known, between the Old and New World after Columbus’ voyages, not only the European culture, but also many crops (including durum wheat landraces and cultivars) were introduced from Europe to the America (Capparelli et al. 2005). Besides, trade routes and immigration between WA, SA and NA, new varieties of wheat were transported or shared. This maybe also explain the closer relationship among the accessions of WA, SA and NA on some aspect.

In conclusion, the results of allelic variation of LMW-GS provide useful information for wheat breeder to explore germplasm resources for end-use quality improvement. Further studies of the two novel alleles are currently underway to match them with previously reported alleles and to evaluate their potential utility value in improving the bread-making quality. The genetic diversity indicated that despite strict selection pressures on cultivar purity and related breeding practices, there is still a significant level of genetic variation on LMW-GS and HMW-GS alleles in the modern varieties of durum wheat. And there existed abundant genetic variation among loci, released periods of varieties and different geographical origins. The results provide useful information of potential germplasm for the improvement of durum wheat and common wheat.

Acknowledgments

This work is supported by China National Key Project Grant No. 2016YFD0100102 and National Natural Science Foundation of China (No.31701506).

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