• Ешқандай Нәтиже Табылған Жоқ

Раздел 1

БОТАНИКА

© 2021 Al-Farabi Kazakh National University ISSN 1563-0218; eISSN 2617-7498 Experimental Biology. №2 (87). 2021 https://bb.kaznu.kz

36

IRSTI 68.35.29; 34.15.23 https://doi.org/10.26577/eb.2021.v87.i2.04 Y.A.Genievskaya1,2 , S.S. Almerekova1 ,

A.I. Abugalieva2 , S.I. Abugalieva1*

1Institute of Plant Biology and Biotechnology, Kazakhstan, Almaty

2Kazakh Research Institute of Agriculture and Plant Industry, Kazakhstan, Almalybak, Almaty region *e-mail: absaule@yahoo.com

GENOME-WIDE ASSOCIATION STUDY OF GRAIN QUALITY TRAITS IN SPRING BARLEY COLLECTION GROWN IN KYZYLORDA REGION

Barley, among many other crops, has better resistance to harsh environmental conditions. Still, high temperature, drought, and soil salinity prevent the formation of high-quality grain, especially for the malting and brewing industry. In this study, spring barley accessions were tested in conditions of high- salinity soil of Kyzylorda region and analyzed for major grain quality traits, including protein, β-glucan, and starch contents, plumpness, grain hardness, and extractivity. Based on the results, the list of ac- cessions optimal in the region for malting and the list for livestock feeding was made using the above- mentioned traits. Genome-wide association study revealed 20 marker-trait(s) associations combined into 7 quantitative trait loci (QTLs). Three QTLs demonstrated pleiotropic effect affecting grain protein, β-glucan, and starch content and extractivity, two QTLs were identified for grain protein and starch content and extractivity, one QTL was for grain hardness index, and one QTL for plumpness. Identified pleiotropic QTLs were genetically mapped in the vicinity of known barley flowering genes. QTLs identi- fied in the study, as well as promising accessions, can be integrated into the barley breeding process in stressed conditions of Kyzylorda region.

Key words: Hordeum vulgare L., malting, livestock feed, genotype × environment, molecular mark- ers, single nucleotide polymorphism.

Ю.А. Гениевская1,2, Ш.С. Альмерекова1, А.И. Абугалиева2, С.И. Абугалиева1*

1Өсімдіктер биологиясы және биотехнологиясы институты, Қазақстан, Алматы қ.

2Қазақ егіншілік және өсімдік шаруашылығы ғылыми-зерттеу институты, Қазақстан, Алмалыбақ, Алматы облысы

*e-mail: absaule@yahoo.com

Қызылорда облысы жағдайында өсірілген жаздық арпа коллекциясының дән сапасы белгілерінің ассоциацияларын толық геномдық талдау

Арпа – бұл басқа мәдени өсімдіктермен салыстырғанда қоршаған ортаның қолайсыз жағдайларына төзімділігі жоғары дақыл. Алайда, жоғары температура, құрғақшылық және тұзды топырақ жоғары сапалы дәннің қалыптасуына жол бермейді, әсіресе сыра қайнату өнеркәсібі үшін. Бұл зерттеуде жаздық арпа үлгілері Қызылорда облысының жоғары тұздануы жағдайында өсіріліп, дән сапасының негізгі ерекшеліктеріне, оның ішінде, ақуыз құрамына, крахмал, β-глюкан, сығындалғыштығы, дән натурасы және оның қаттылығы бойынша талданды. Алынған нәтижелер негізінде сыра қайнату өнеркәсібі үшін оңтайлы көрсеткіштерге ие үлгілер тізімі, сонымен қатар жем өндірісі үшін де тізбе құрылды. Толық геномдық талдау 7 сандық белгілер локусына (СБЛ) топтастырылған 20 маркер-белгі ассоциацияларын анықтады. Үш СБЛ дәннің құрамындағы ақуызға, крахмалға, β-глюканға және сығындыға плеотропты әсерін көрсетті, екі СБЛ ақуыз, крахмал мен сығынды үшін анықталды. Дәннің қаттылығы мен натурасы үшін, әрқайсысына 1 СБЛ анықталды. Табылған плейотропты СБЛ арпаның белгілі гүлдеу гендеріне жақын орналасты.

Осы жұмыс барысында табылған барлық СБЛ, сондай-ақ перспективалы арпа үлгілері Қызылорда облысының стресстік жағдайында арпа селекциясы процесіне интеграциялануы мүмкін.

Түйін сөздер: Hordeum vulgare L., сыра қайнату, жем өндірісі, генотип × орта, молекулалық  маркерлер, бір нуклеотидтік полиморфизм.

37 Y.A.Genievskaya et al.

Ю.А. Гениевская1,2, Ш.С. Альмерекова1, А.И. Абугалиева2, С.И. Абугалиева1

1Институт биологии и биотехнологии растений, Казахстан, г. Алматы

2Казахский научно-исследовательский институт земледелия и растениеводства, Казахстан, Алмалыбак, Алматинская область

*e-mail: absaule@yahoo.com

Полногеномный анализ ассоциаций признаков качества зерна коллекции ярового ячменя, выращенного в Кызылординской области

Ячмень – это культура, которая в сравнении с другими культурными растениями обладает лучшей устойчивостью к неблагоприятным условиям среды. Тем не менее, высокая температура, засуха и засоленная почва не позволяют формироваться высококачественному зерну, особенно для пивоваренной промышленности. В данной работе образцы ярового ячменя были выращены в условиях высокой засоленности Кызылординской области и проанализированы по основным признакам качества зерна, в т. ч. содержание белка, кархмала, β-глюкана, экстрактивности, натуры зерна и его твердости. На основе полученных результатов был сформирован список образцов с оптимальными показателями для пивоваренной промышленности, а также список для кормопроизводства. Полногеномный анализ выявил 20 ассоциаций маркер-признак сгруппированных в 7 локусов количественных признаков (ЛКП). Три ЛКП показали плейотропный эффект в отношении содержания в зерне белка, крахмала, β-глюкана и экстрактивности, два ЛКП были обнаружены для содержания белка, крахмала и экстрактивности. Для твердозерности и натуры зерна было идентифицировано по 1 ЛКП. Найденные плейотропные ЛКП находились в непосредственной близости к известным генам цветения ячменя. Все ЛКП, обнаруженные в ходе данной работы, а также перспективные образцы ячменя могут быть потенциально интегрированы в процесс селекции ячменя в стрессовых условиях Кызылординской области.

Ключевые слова: Hordeum vulgare L., пивоварение, кормопроизводство, генотип × среда, молекулярные маркеры, однонуклеотидный полиморфизм.

Abbreviations

GPC – grain protein content, GBGC – grain β-glucan content, GSC – grain starch content, GPL – grain plumpness, GH – grain hardness index, GEX – grain extractivity.

Introduction

Barley (Hordeum vulgare L.) is one of the wide- ly produced cereal crops in the world (156.41 mil- lion metric tons in 2019 / 2020) [1]. In Kazakhstan, it is the third mostly-cultivated cereal after wheat and rice (18.25 % in 2020) [2]. Barley production in Kazakhstan has three basic directions: for the live- stock feeding (43.3 % from total barley production), for the food industry (36.5 %), and for grain deposi- tory or export (20.1 %) [2]. Barley plays an impor- tant role in Kazakhstan’s economics. The country was the 7th largest barley exporter in 2019 / 2020 [1].

In Kazakhstan, barley is annually cultivated in all grain sowing regions. There is a list of highly productive cultivars developed for each particular region and approved by the State register of breed- ing achievements of the Republic of Kazakhstan [3]. Many regional breeding programs are focused on the development of highly productive cultivars with good grain quality. Although barley grain qual- ity indicators may vary depending on the direction

of use, the content of protein, starch, and extractivity are very important. For example, barley grain used for malting require low protein content (less than 12

% according to the GOST 5060-86 [4]) and high ex- tractivity, while grain for livestock feeding, on the contrary, have to be enriched with protein (more than 13 % according to the GOST 53900-2010 [5]).

Most barley quality traits are complex quantitative traits with polygenic control [6]. In addition, there is a great influence of both genotype and environment on barley grain quality, as well as productivity. In this regard, the agricultural industry needs a large assortment of modern barley cultivars oriented on different usage directions for all grain-sowing re- gions of Kazakhstan.

Akmola and North Kazakhstan regions tradi- tionally are leaders in spring barley production in Kazakhstan [2]. Together these two regions pro- duced 46.6 % of the total barley yield in 2020 [2]. It is explained by high fertility of the soil and optimal climatic conditions in the northern Kazakhstan. At the same time, high ecological and genetic plastic- ity of barley allows developing cultivars adapted to drought and hot climate of the southern Kazakhstan too. One of the southern regions – Kyzylorda region – produced less than 1 % of the total spring barley in the country in 2020 [2]. The climate of Kyzy- lorda region is sharply continental; summers are hot and dry; winters are cold with unstable snow cover.

38

Genome-wide association study of grain quality traits in spring barley collection grown in Kyzylorda region

The average annual air temperature is 9.8 ° С. The soil in the region is meadow-boggy, typical for rice growing (the region is a leader in rice production in Kazakhstan), with less than 1 % humus content and chloride and sulfate salinity [7]. High soil salinity in combination with arid land results in poor protein synthesis and inhibited growth processes [8]. Thus, arid climate and barren soil have a great negative influence on both productivity and grain quality of barley in the region.

Previously, due to the collaborative projects be- tween Institute of Plant Biology and Biotechnology and breeding organizations from the Ministry of Ag- riculture, barley accessions from Kazakhstan were studied for morphological traits and yield compo- nents in 7 different regions of Kazakhstan [9]. It was shown that some cultivars initially developed for the northern regions, for example, for the Kostanay re- gion, in Kyzylorda region had a higher yield than the cultivars traditionally cultivated here [10]. Part of those local lines and cultivars were additionally studied in Kazakh Research Institute of Rice-grow- ing (KRIRG) for morphological and productivity parameters in order to identify cultivars resistant to abiotic stresses [7], and for protein and starch con- tent [8]. Promising lines from the world barley col- lection were also selected and recommended for the cultivation in Kazakhstan’s Aral region, including Kyzylorda region [11]. Due to a collaborative study between IPBB and KRIRG (2009-2014) a new cul- tivar Shakhristan was developed and approved for cultivation in 2017 [3]. Nowadays, several barley cultivars with the yield of 2.5-3.5 t/ha, such as Ro- sava winter, Baishek, Saule, Zhuldyz, Asem, Arna, Shakhristan, and Syr Aruy, are officially approved for mass cultivation in Kyzylorda region [3, 12].

Still, it is possible to increase the yield and grain quality of spring barley in the harsh environment of Kyzylorda region by introducing new early ripening genotypes with good grain quality potential.

Modern crop breeding is an effective combina- tion of traditional breeding and genomic technolo- gies, such as marker-assisted selection (MAS) and genetic modifications (GMO) [13]. One of these technologies, called genome-wide association study (GWAS), has been successfully applied to identify the causative loci used in the breeding of crops for adaptation, productivity, and quality improvement by molecular breeding gene modifications [14-16].

This method is based on the searching of associa- tions between genotypic and phenotypic variability resulting in the identification of molecular markers for the trait(s) [17]. Previously, in Kazakhstan, this approach was effectively used for a wide range of

crop studies: productivity of barley [19-20], wheat [20], and soybean [21], as well as diseases resistance in wheat [22], barley [23], and soybean [24]. Barley collection used in this study was already involved in GWAS analysis for productivity and adaptation [19-20]. However, this study is the first attempt to identify loci in barley genome associated with bar- ley grain quality traits.

Materials and methods

Barley collection used for the study. The bar- ley collection used in this study was composed of two-rowed and six-rowed spring barley cultivars and breeding lines from the USA and Kazakhstan.

USA’s part of the collection included 557 acces- sions. Kazakhstan’s part included 103 accessions originated from 6 agricultural institutions: 17 ac- cessions from Aktobe Agricultural Experimental Station (AES) (Aktobe region), 15 accessions from Karabalyk AES (Kostanay region), 20 accessions from Karaganda AES (Karaganda region), 16 acces- sions from Kazakh Research Institute of Agriculture and Plant Industry (Almaty region), 20 accessions from Kazakh Research Institute of Rice-growing (Kyzylorda region), and 15 accessions from Kras- novodopad AES (Turkestan region) [9]. In to- tal, 660 accessions were used for genotyping and phenotyping.

Phenotyping and genotyping of barley col- lection. Cultivation of 660 barley accessions was performed in the field of Kazakh Research Institute of Rice-growing (Kyzylorda region) [9]. Each line was grown in tripled one meter plots at each site.

Grains of each accession were analyzed on the con- tent of raw protein (GPC, %), β-glucan (GBGC, %), and starch (GSC, %), plumpness (GPL, g/L), grain hardness (GH, SKCS units), and extractivity (GEX,

%) in the laboratory of grain quality (Kazakh Re- search Institute of Agriculture and Plant Industry).

The GPC was determined by near-infrared spectros- copy using calibration equations based on Kjeldahl method [25] using FOSS 1241 and FOSS 2500. The GBGC was determined by the spectrofluorimetric method [26]. The GSC was analyzed using polari- metric method [27]. Also the collection was tested for indicators of plumpness, grain hardness index, and extractivity. GPL levels were determined us- ing methods described in GOST 1084064 [28]; the hardness index (HI) measured by Single Kernel Characterization System 4100 (SKCS 4100; Perten Instruments, Huddinge, Sweden) according to the manufacturer’s mannual: GEX was calculated us- ing method described in GOST 12136-77 [29]. The

39 Y.A.Genievskaya et al.

correlations between quality traits and productiv- ity components, such as thousand kernels weight (TKW, g) and yield per m2 (YM2, g/m2) were also analyzed.

Accessions from Kazakhstan were genotyped using the 9K SNP chip by GoldenGate Illumina at the TraitGenetics company (TraitGenetics GmbH, Gatersleben, Germany). The SNP genotyping data of BOPA1 and BOPA2 (Barley Oligo Pool Assay) sets from Illumina assays [30] for USA’s accessions were obtained from Triticeae toolbox (www.triti- ceaetoolbox.org). In total, 2344 polymorphic SNPs with MAF (minor allele frequency) > 0.05 and with SNP’s call rate > 0.90 were selected for GWAS analysis.

GWAS analysis and statistics. The genetic structure of 660 studied barley accessions was de- termined in order to obtain Q-matrix for GWAS analysis. Based on the ΔK method [31], the K was set at 3. The Kinship matrix (K-matrix) was ob- tained using TASSEL 5 software [32]. The Mixed Linear Model (MLM) with K- and Q-matrices was

used for GWAS analysis. The significant associa- tions were selected after the application of a thresh- old at P<1E-3.

Pearson correlation and PCA analysis were per- formed using R statistical platform [33]. A genetic map with significant SNPs was constructed based on physical positions in barely genome [34] using MapChart 2.32 software [35].

Results and Discussion

Grain quality and productivity of barley grown in Kyzylorda. Analysis of basic barley grain quality traits had showed a wide range of GH and GPL, while GPC, GSC, and GBGC had demonstrat- ed a moderate level of variability (Table 1). Barley productivity measured as yield per m2 varied greatly from 63.0 g/m2 (USA’s line FEG148-16) and up to 1336.0 g/m2 (USA’s line FEG142-16). Among Ka- zakhstan’s accessions, the best yield was observed for the cultivar Nurinskiy 1 (655.0 g/m2) originated from Karaganda AES.

Table 1 – Grain quality traits of USA’s and Kazakhstan’s barley grown in Kyzylorda 2010

Quality trait Minimum Maximum Mean ± SD

Grain protein content (GPC) 10.2 15.5 12.6 ± 0.9

Grain starch content (GSC) 50.6 57.0 54.0 ± 1.1

Grain β-Glucan content (GBGC) 2.9 4.9 4.1 ± 0.2

Grain hardness (GH) 67.0 132.0 92.8 ± 8.6

Grain plumpness (GPL) 300.0 704.0 585.4 ± 38.8

Grain extractivity (GEX) 70.2 76.2 73.4 ± 1.0

Yield per m2 (YM2) 63.0 1336.0 599.5 ± 234.7

Notes: SD – standard deviation.

The correlational analysis had demonstrated strong positive relations between GEX and GSC.

The concentration of β-Glucan was moderately pos- itively associated with GPC and weakly associated with GH. GH was also positively associated with GPC. GSC and GEX were negatively correlated with GBGC, GH, and GPC. As for the GPL, a weak negative correlation was observed for GH only. Bar- ley productivity (YM2) had positive associations with GBGC and GPC and negative correlations with GEX, GSC, and GPL.

Promising barley accessions for Kyzylorda region. The lists of promising lines and cultivars for

livestock feeding (Table 2) and for malting (Table 3) were made using the indicators of grain quality and productivity in Kyzylorda region 2010.

The list of accessions that had demonstrated promising levels of grain quality and yield for live- stock feeding included 6 cultivars and breeding lines from Kazakhstan and 6 breeding lines from the USA (Table 2). All selected accessions had showed a high GPC level and good productivity;

however, GPL close to the GOST was observed for USA’s accessions only. Accessions from Ka- zakhstan exceeded GOST’s requirement for GPL by 10% on average.

40

Genome-wide association study of grain quality traits in spring barley collection grown in Kyzylorda region

Figure 1 – Pearson correlation among grain quality traits and productivity.

Red color denotes negative correlation, blue color – positive.

Color intensity increases with the increasing of significance (P<0.05).

Table 2 – Promising accessions for livestock feeding according to grain quality traits and productivity of barley in Kyzylorda region

# Barley accessions GPC (%) GPL (g/L) YM2 (g/m2)

Livestock feeding (GOST R 53900-2010, first class) > 13 590 -

1 Accession-1 (USA) 15.1 592 546

2 Accession-2 (USA) 15.0 598 314

3 Accession-3 (KAZ, Kazakh Research Institute of Rice-growing) 15.4 661 566

4 Accession-4 (USA) 14.5 597 770

5 Accession-5 (KAZ, Kazakh Research Institute of Rice-growing) 14.5 669 555

6 Accession-6 (KAZ, Krasnovodopad AES) 14.5 665 449

7 Accession-7 (USA) 14.5 592 392

8 Accession-8 (USA) 15.5 512 528

9 Accession-9 (USA) 15.5 590 369

10 Accession-10 (KAZ, Aktobe AES) 14.6 658 396

11 Accession-11 (KAZ, Krasnovodopad AES) 14.8 627 418

12 Accession-12 (KAZ, Krasnovodopad AES) 14.8 655 347

The list of barley accessions that are promising for malting according to their grain quality and yield performance included 13 breeding lines from the USA only (Table 3). All of them had protein con- centration less than 12% as required by GOST, but their average GEX was 3.3 % lower than the recom- mended level.

Results of Kazakhstan’s and USA’s barley phe- notyping in Kyzylorda region had demonstrated a wide range for studied grain quality traits. One of the crucial barley quality traits for both malting and livestock feeding is protein. Generally, barley lines from the USA used in this study expectedly show lower GPC (Table 3), since the majority of them are

41 Y.A.Genievskaya et al.

malting-oriented. As for Kazakhstan’s accessions, promising lines were observed only for livestock feeding with relatively high GPC (Table 2). It is ex- plained by the specialization of these accessions for the livestock. At the same time, the combination of accessions from Kazakhstan and the USA provided a good range for the GWAS.

For malting and brewing, low GPC has to be combined with low GBGC [36] and high level of GSC providing high GEX. Accessions grown in Kyzylorda region had demonstrated a strong posi- tive correlation between GPC and GBGC, as well as the strong negative correlation between GPC and GSC / GEX (Figure 1). GH is another important trait for malting quality. Usually, GH declines with the increasing GSC and decreasing GPC [37]. Usu- ally, the good grain quality of barley is associated with low productivity and low grain yield [38]. The same correlation was observed in the current study,

where high YM2 was associated with increased GPC, while high levels of GSC / GEX were nega- tive correlated with the yield (Figure 1). Still, bar- ley cultivars with high GPC and YM2 are a great raw material for livestock feeding [39]. GPL levels had showed absence of correlation with other qual- ity traits except for weak negative correlation with GH (Figure 1), which confirms the small impact of GPL on other grain and malting qualities [40].

Generally, 6 grain quality traits of barley grown in Kyzylorda region had demonstrated good variabil- ity for GWAS analysis. In the studied collection, the majority of accessions from the USA had good grain quality levels for malting and brewing, while accessions from Kazakhstan fitted requirements for livestock feeding. The list of USA’s accessions from table 3 is good candidates for the introduc- tion into potential malting barley breeding in Ky- zylorda region.

Table 3 – Promising accessions for malting according to grain quality traits and productivity of barley in Kyzylorda region

# Barley accessions GPC (%) GEX (%) YM2 (g/m2)

Barley for malting (GOST 5060-86) < 12 > 78 -

1 Accession-13 (USA) 10.9 75.8 493

2 Accession-14 (USA) 10.9 73.8 439

3 Accession-15 (USA) 10.8 75.6 669

4 Accession-16 (USA) 10.8 75.4 420

5 Accession-17 (USA) 10.7 75.9 383

6 Accession-18 (USA) 10.7 75.1 490

7 Accession-19 (USA) 10.7 75.5 758

8 Accession-20 (USA) 10.6 75.5 840

9 Accession-21 (USA) 10.2 76.2 421

10 Accession-22 (USA) 11.0 75.7 342

11 Accession-23 (USA) 11.0 75.5 408

12 Accession-24 (USA) 11.0 75.0 515

13 Accession-25 (USA) 11.0 75.4 482

Marker-trait associations (MTAs) identified for barley grain quality traits. In total, 20 MTAs for studied grain quality traits were identified on 6 out of 7 barley chromosomes (Table 4). Their posi- tions on the barley physical map are demonstrated in Figure 2.

Seven SNPs associated with the different num- ber of traits were positioned on all barley chromo- somes, except chromosome 4H. Chromosome 6H contained 2 trait-associated SNPs. Several markers had demonstrated multiple associations. Markers

11_20971 (1H), 11_21505 (3H), and 12_31509 (6H) were associated with 4 quality traits: GPC, GSC, GBGC, and GEX. Markers 11_21414 (2H) and 11_21103 (7H) were associated with 3 traits:

GPC, GSC, and GEX. Marker 12_10408 on chro- mosome 5H was associated with GPL only, and marker 12_10199 on chromosome 6H only with GH. All 20 MTAs had demonstrated significant associations at P < 0.001 (Table 4). The total phe- notypic variation explained by MTA (R2) varied from 1.9 to 3.4% (Table 4).

42

Genome-wide association study of grain quality traits in spring barley collection grown in Kyzylorda region

Table 4 – Marker-trait associations for barley grain quality traits identified in Kyzylorda in 2010

# Trait SNP Chr.1 Pos. (cM)1 Pos. (bp)2 P-value R2 (%) All. Effect

1 GEX 11_20971 U (1H2) U 496,660,040 1.04E-04 2.9 A -1.035

2 GEX 11_21414 2H 158.15 761,624,420 4.73E-04 2.3 A -0.733

3 GEX 11_21505 3H 87.24 580,635,994 2.17E-04 2.3 A -0.869

4 GEX 12_31509 6H 55 203,509,034 1.29E-05 3.2 A 1.021

5 GEX 11_21103 U (7H2) U 582,767,743 7.59E-04 1.9 A -0.718

6 GBGC 11_20971 U (1H2) U 496,660,040 4.17E-04 3.0 A 0.202

7 GBGC 11_21505 3H 87.24 580,635,994 5.48E-04 2.3 A 0.168

8 GBGC 12_31509 6H 55 203,509,034 1.44E-04 2.8 A -0.184

9 GH 12_10199 6H 45.44 66,485,252 1.28E-04 2.5 A 8.655

10 GPC 11_20971 U (1H2) U 496,660,040 1.29E-04 2.8 A 0.932

11 GPC 11_21414 2H 158.15 761,624,420 2.62E-04 2.4 A 0.685

12 GPC 11_21505 3H 87.24 580,635,994 3.94E-04 2.1 A 0.764

13 GPC 12_31509 6H 55 203,509,034 2.10E-05 3.1 A -0.915

14 GPC 11_21103 U (7H2) U 582,767,743 4.78E-04 2.1 A 0.677

15 GSC 11_20971 U (1H2) U 496,660,040 4.20E-05 3.2 A -1.208

16 GSC 11_21414 2H 158.15 761,624,420 3.24E-04 2.4 A -0.822

17 GSC 11_21505 3H 87.24 580,635,994 1.21E-04 2.5 A -1.002

18 GSC 12_31509 6H 55 203,509,034 7.34E-06 3.4 A 1.165

19 GSC 11_21103 U (7H2) U 582,767,743 3.32E-04 2.2 A -0.843

20 GPL 12_10408 5H 102.06 547,771,176 4.74E-05 3.0 A -51.508

Notes: 1 – Position according to 9K GoldenGate Illumina; 2 – Physical position according to Morex 2016 map. Chr. – chromosome;

Pos. – position; R2 –phenotypic variation explained by MTA; All. – effective allele.

Twenty MTAs identified in this study were com- bined into 7 QTLs (Figure 2). Five out of those 7 QTLs had demonstrated pleiotropic effect since they were associated with several traits. It may indicate the presence of strong pleiotropic genes in these loci or in close regions. Grain quality traits are highly influenced by major heading and flowering genes.

For example, SNP 11_20971 (GPS, GSC, GBGC, GEX) on the chromosome 1H was previously iden- tified as associated with adaptability traits (time of heading and grain maturity, plant height) and with thousand kernels weight [18], which is also qual- ity trait. Heading time genes HvCMF6a [41], HvC- MF6b [41] and Esp1L / HvELF3 / eam8 [42] are lo- cated in the region close to SNP 11_20971 and may be linked. The SNP 11_21414 (GPS, GSC, GEX) on the chromosome 2H was also previously mentioned as associated with the time of heading and grain ma- turity, plant height, and peduncle length [18]. Head- ing time gene HvAP2 located on 126.7 cM [43] may be linked with this SNP; however, the distance be- tween them is relatively large (about 31 cM) [44].

The SNP 11_21505 (GPS, GSC, GBGC, GEX) on

the chromosome 3H was also earlier described as highly pleiotropic associated with both yield and adaptability traits [18]. This SNP is probably linked with the heading time gene HvCMF1 [41]. The next pleiotropic SNP is 12_31509 (GPS, GSC, GBGC, GEX) on the chromosome 6H reported as associated with yield and adaptability traits [18] is more likely linked with the group of heading and flowering genes densely located in this region of the chromosome [44]. The last pleiotropic SNP 11_21103 (GPS, GSC, GEX) on the chromosome 7H previously associated with yield and adaptability traits [18] may be connect- ed with flowering gene HvCO6 [44] located in this chromosome region. Thus, SNPs with the pleiotropic effects described above and associated with highly correlated grain quality traits GPS, GSC, GBGC, and GEX are most likely linked with known heading / flowering genes of barley. The mixed effect (nega- tive and positive) on different traits may be used for more effective breeding of barley for either livestock feeding or malting. For example, SNP 12_31509 may help to increase GSC and GEX, but decrease GPC and GBGC, which is good for malting barley.