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  • Research article
  • Open Access

Interactive effects of multiple vernalization (Vrn-1)- and photoperiod (Ppd-1)-related genes on the growth habit of bread wheat and their association with heading and flowering time

  • 1,
  • 1,
  • 2,
  • 3,
  • 1,
  • 1 and
  • 1Email author
BMC Plant Biology201818:374

https://doi.org/10.1186/s12870-018-1587-8

  • Received: 19 June 2018
  • Accepted: 3 December 2018
  • Published:

Abstract

Background

The precise identification of Winterness/Springness (growth habit) for bread wheat, which is determined by genes involved in vernalization and photoperiod, will contribute to the effective utilization of bread wheat varieties. Here, 198 varieties from the Yellow and Huai wheat production region (YHW) in China were collected to identify their vernalization (Vrn-1) and photoperiod (Ppd-1) gene composition via a series of functional markers and their association with vernalization and photoperiod requirements at three locations during two years of experiments. The growth habits were measured during the spring sowing season.

Results

The results showed that the semi-winter varieties (grades1–4) were most prevalent in the population. The relative effects of single Vrn alleles on the growth period, such as heading date (HD) and/or flowering date (FD), were as follows: Vrn-B1b > Vrn-B1a > Vrn-D1b > Vrn-D1a > vrn-D1 = vrn-B1. The interactive effects of Vrn-B1 and Vrn-D1 on HD and FD were identical to those of Vrn-B1b. Approximately 35.3% of the cultivars carried Ppd-B1a (photoperiod-insensitive) and exhibited the earliest HD and FD. The Ppd-D1a-insensitive allele (Hapl II) was carried by just 0.5% of the varieties; however, the other two sensitive alleles were present at a higher frequency, and their effects were slightly weaker than those of Ppd-B1a. In addition, strong interactive effects between Ppd-B1 and Ppd-D1 were detected. In terms of mean values among various genotypes, the effects followed the order of Vrn-1 > Ppd-1.

Conclusions

According to the results of ANOVA and least significant range (LSR) tests, we can conclude that Vrn-1 rather than Ppd-1 played a major role in controlling vernalization and photoperiod responses in this region. This research will be helpful for precisely characterizing and evaluating the HD, FD and even growth habit of varieties in the YHW at molecular levels.

Keywords

  • Winter wheat
  • The yellow and Huai wheat production region (YHW)
  • Growth habit
  • Growth period
  • Vernalization
  • Photoperiod

Background

Because of the ease of determining its optimum time for flowering and maturation, bread wheat (Triticum aestivum L., AABBDD, 2n = 42) is cultivated worldwide. Day length and low temperature act as environmental cues affecting the time to heading and flowering. The ability to perceive and respond to these signals is controlled by molecular pathways that regulate early growth habits in response to abiotic stress (Vrn alleles) and photoperiod (Ppd alleles) [1, 2].

In the past, the characterization of the growth habits of winter wheat in China, especially in the Yellow and Huai wheat production region, which is the largest winter wheat production region, relied on field evaluations or in-house artificial identification [3, 4]. However, these identification procedures are tedious and costly, and thus, the practicality of field evaluation and in-house artificial identification methods is limited. Furthermore, inconsistencies between breeders’ descriptions and government registrations sometimes occur due to inexact phenotypic identification methods. In contrast, molecular identification methods are relatively credible, but more novel types of vernalization alleles must be surveyed, and their interactive effects among each other remain unclear.

Indeed, the molecular basis for flowering time regulation has been extensively studied in wheat and other crops [5]. In hexaploid wheat, vernalization requirements are controlled by three major orthologous Vrnalleles—Vrn-A1, Vrn-B1, and Vrn-D1—which have been mapped onto the long arm of chromosomes 5A, 5B, and 5D, respectively [68]. Each of these loci encodes a MADS-box transcription factor orthologous to AP1 in Arabidopsis, which is reported to be involved in floral meristem development during the transition from the vegetative phase to the reproductive phase [8]. The VRN-1 gene is dominant for the spring growth habit, and it is upregulated by vernalization in winter lines [9, 10]. A homologue of the Arabidopsis FT gene, the Vrn-3 gene, has been mapped to the short arm of chromosome 7 in wheat; this gene upregulated the Vrn-1 genes and thus accelerated heading and flowering indirectly [11].

The emergence of dominant alleles at the Vrn-A1 locus is a result of insertions and deletions within the promoter or a deletion within intron 1, which have been designated Vrn-A1a, Vrn-A1b, and Vrn-A1c, respectively [9, 10, 12, 13]. Spring growth habits can also be attributed to deletions at the Vrn-B1 and Vrn-D1 loci, which have been classified as insensitive vernalization types, and have been designated Vrn-B1a [10, 14, 15], Vrn-D1a, and Vrn-D1b [16]. The Vrn-B1c (novel) allele, which is due to the deletion of 0.8 kb and the duplication of 0.4 kb within intron 1, differs from Vrn-B1a [17, 18]. Another spring allele, Vrn-B1b, has also been described; this allele contains two deletions in the promoter region and is present in spring variety ‘Alpowa’ [14]. The various vernalization requirements of the Vrn-1 alleles or combinations can result in variations in flowering time and spring growth habit [19]. In wheat and other temperate grasses, VRN1 is also expressed in the leaves, where it acts as a repressor of VRN2 [20, 21]. The detailed pathway of the vernalization genes involved in controlling wheat flowering was reviewed by Chen and Dubcovsky (2012) [20].

Photoperiod response is another vital factor affecting flowering time under long-day conditions. For wheat, photoperiod insensitivity (Ppd-1a) is widespread and especially prevalent in regions where crops grow during short days or when the crops mature before the onset of high summer temperatures [22]. Three semi-dominant orthologous Ppd-1 loci—Ppd-A1, Ppd-B1, and Ppd-D1—have been mapped onto the short arm of chromosomes 2A, 2B, and 2D, respectively [23, 24]; these loci are all members of the Pseudo-Response Regulator (PRR) gene family, which is orthologous to the Ppd-H1 gene family in barley [25]. A series of diagnostic markers have been used to efficiently screen for several variants [10, 13, 16, 24, 26].

The Yellow and Huai valley wheat production region (YHW) covers 45% of China’s total cultivation area but contributes 60–70% of the country’s wheat production. Varieties that flower and mature early are helpful in sustaining China’s double-harvest cropping system. In this study, we collected and identified a total of 198 popular varieties, elite lines, and landraces from China to (i) accurately identify the growth habits of the varieties via the field spring sowing method and evaluate their association with heading date (HD; growth period) and flowering date (FD; growth period) at three locations within the YHW during a two-year period (Zhengzhou, Zhumadian and Shangqiu in 2014 and 2015); (ii) use diagnostic molecular markers to determine the main allelic frequencies of Vrn-1 and Ppd-1; and (iii) specifically determine the interactive effects between Vrn-1 and Ppd-1 allelic combinations on heading and flowering times. This study contributes knowledge concerning the effective selection of various types of growth habits of varieties and will be of service to the selection of early-maturation cultivars at the molecular level.

Results

Semi-winter varieties were predominant in the YHW according to the field spring sowing method.

The results of the two-year growth habits were very similar, and the order ranks recorded in 2015 strongly correlated with those recorded in 2016 (Pearson coefficient = 0.96). In general, the ranks of two accessions (Xinong979 and Yumai47) were inconsistent between years, but the discrepancies were only 1–2 grades. Our method separated 10 accessions (Yannong19, Beijing841, etc.) into winterness (grade 0) in 2015 and 2016, which accounted for 5.05%. One hundred and forty-seven accessions (74.24%) were identified as semi-winter types in 2015, and 145 (73.23%) were identified in 2016. In contrast, 41 (20.71%) and 43 (21.72%) grade 5 accessions belonged to the spring type in 2015 and 2016. Overall, the semi-winter varieties (grades1–4) were predominant in the YHW (Table 1; Fig. 1).
Table 1

The phenotypic variants in winter/spring growth habits and allelic variants on Vrn-1 alleles

ID

Taxa

Registered

Origination

W/S_2016

W/S_2015

Vrn-A1

Vrn-B1

Vrn-D1

Vrn-B3

QZ01

Shanyou 225

winter

Shaanxi

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ02

Aikang 58

semi-winter

Henan

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ03

Zhoumai 24

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ04

Zaoxiang 158

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ05

Zhengmai 366

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ06

Bainong 418

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ07

Taihemai 1

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ08

Anmai 8

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ09

Huaimai 05159

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ10

Zhoumai 16

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ11

Xinmai 18

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ12

Xianmai 13

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ13

Yandian 9433

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ14

Zhongchuang 805

weak spring

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ15

Zhengyumai 9987

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ16

Luomai 31

semi-winter

Henan

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ17

Yimai 6

semi-winter

Henan

2

2

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ18

Zhengzhong 17

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ19

Fanmai 803

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ20

Zhoumai 27

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ21

Luomai 28

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ22

Yunong 982

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ23

Zhengmai 1023

semi-winter

Henan

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ24

BN 160

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ25

04 zhong 36

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ26

Lankao198

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ27

Fengdecunmai 5

semi-winter

Henan

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ28

Guoyu 101

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ29

Wen 0418

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ30

Yunong 202

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ31

Zhongyu 9307

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ32

Ruzhou 0319

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ33

Yumai 41

semi-winter

Henan

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ34

Yumai 55

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ35

Yunong 186

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ36

Junda 106

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ37

Yumai 49

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ38

Zhengmai 7698

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ39

Lunxuan 1298

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ40

Mengmai 023

weak spring

Henan

5

5

vrn-A1

Vrn-B1a

vrn-D1

vrn-B3

QZ41

Luomai 23

semi-winter

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ42

Jiyanmai 7

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ43

Fengdecunmai 8

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ44

Zhoumai 9

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ45

Zhengyumai 0519

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ46

Xuke 316

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ47

Luomai 18

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ48

Xinong 979

semi-winter

Henan

5

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ49

Cunmai 11

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ50

Fengdecunmai 12

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ51

Huaichuan 919

semi-winter

Henan

2

2

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ52

Zou 8425B

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ53

Yunong 211

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ54

LS 6109

semi-winter

Shandong

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ55

Lankao 182

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ56

Xumai 1242

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ57

Zhoumai 26

semi-winter

Henan

5

5

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ58

Yamai 1

weak spring

Henan

5

5

vrn-A1

Vrn-B1a

vrn-D1

vrn-B3

QZ59

Yujiao 5

semi-winter

Henan

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ60

Fanmai 11

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ61

Zhengmai 103

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ62

Pumai 053

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ63

Tunfeng 802

semi-winter

Henan

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ64

Fengdecunmai 1

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ65

Pu2056

semi-winter

Henan

5

5

vrn-A1

Vrn-B1b

vrn-D1

vrn-B3

QZ66

Xinmai 19

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ67

Wenliang 1

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ68

Zhongyu 9302

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ69

Zhengmai 583

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ70

Hengguan 35

semi-winter

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ71

Luomai 24

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ72

Yunong 416

semi-winter

Henan

5

5

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ73

Zhoumai 22

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ74

Yumai 52

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ75

FS 059

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ76

Pingan 11

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ77

Bonong 6

weak spring

Henan

5

5

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ78

Zhoumai 18

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ79

Xuke 168

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ80

Pumai 10

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ81

Xumai 0054

semi-winter

Jiangsu

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ82

Zhengyou 6

semi-winter

Henan

5

5

vrn-A1

Vrn-B1a

vrn-D1

vrn-B3

QZ83

Yunong 9901

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ84

Zhengmai 0856

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ85

Luomai 8

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ86

Zhoumai 13

semi-winter

Henan

2

2

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ87

Luo 10 T07

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ88

Yuanyu 3

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ89

Fengdecunmai 10

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ90

Hongmai 118

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ91

Yumai 14 You

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ92

Zhoumai 19

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ93

Guomai 301

semi-winter

Henan

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ94

Zhengmai 113

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ95

Pumai 9

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ96

Pingan 8

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ97

Xinmai 20

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ98

Zhongmai 875

semi-winter

Beijing

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ99

Zhongyanmai 0708

weak spring

Jiangsu

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ100

Zhongmai 1

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ101

Nongda 1108

semi-winter

Beijing

1

1

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ102

Yumai 47

weak spring

Henan

5

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ103

Zhengmai 98

semi-winter

Henan

2

2

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ104

Xinong 889

semi-winter

Shaanxi

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ105

Neixiang 188

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ106

Jimai 22

semi-winter

Shandong

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ107

Fanmai 5

semi-winter

Henan

2

2

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ108

Huayu 198

semi-winter

Henan

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ109

Huangming 116

weak spring

Henan

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ110

Zhengmai 9694

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ111

Yunong 949

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ112

Shan 160

semi-winter

Shaanxi

3

3

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ113

Luomai 4

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ114

Luoxin 998

semi-winter

Henan

1

1

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ115

Yunong 201

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ116

Kaimai 21

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ117

Yubao 1

semi-winter

Henan

1

1

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ118

Bainong 207

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ119

Luomai 21

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ120

Zhengmai 101

weak spring

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ121

Xinmai 9

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ122

Xinmai 208

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ123

Yumai 34

weak spring

Henan

5

5

vrn-A1

Vrn-B1b

vrn-D1

vrn-B3

QZ124

Kaimai 18

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ125

Xuke 793

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ126

Fanmai 7030

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ127

Shi 4185

semi-winter

Hebei

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ128

Xin 0208

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ129

Zhengmai 379

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ130

Jimai 20

semi-winter

Shandong

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ131

Qiule 2122

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ132

Zhoumai 23

weak spring

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ133

Zhengyumai 043

semi-winter

Henan

1

1

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ134

Zhengmai 004

semi-winter

Henan

3

3

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ135

Wennong 14

semi-winter

Shandong

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ136

Xinhan 1

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ137

Yumai 18

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ138

Xuke 415

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ139

Pingan 9

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ140

Shangmai 156

semi-winter

Henan

1

1

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ141

Xinong 9871

semi-winter

Shaanxi

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ142

Pingan 3

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ143

Zhongyu 12

semi-winter

Henan

2

2

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ144

Yumai 58

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ145

Xun 9917

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ146

Ping’an 6

weak spring

Henan

5

5

vrn-A1

Vrn-B1b

Vrn-D1a

vrn-B3

QZ147

Xinmai 26

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ148

Lankaoaizao 8

weak spring

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ149

Fengyou 6

weak spring

Henan

5

5

vrn-A1

Vrn-B1a

vrn-D1

vrn-B3

QZ150

Huaimai 0882

semi-winter

Jiangsu

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ151

Taikong 6

weak spring

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ152

Xinong 529

weak spring

Shaanxi

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ153

Yumai 51

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ154

Luo 6073

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ155

Bainong 64

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ156

Jinan 17

winter

Shandong

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ157

Yanzhan 4110

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ158

Weilai 0818

semi-winter

Anhui

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ159

Yanke 028

weak spring

Henan

5

5

vrn-A1

Vrn-B1a

vrn-D1

vrn-B3

QZ160

86(79)-128

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ161

Yanmai864

weak spring

Henan

5

5

vrn-A1

Vrn-B1b

vrn-D1

vrn-B3

QZ162

Xiaoyan 81

semi-winter

Beijing

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ163

Liangxing 99

semi-winter

Shandong

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ164

Tainong 8968

semi-winter

Shandong

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ165

Huayumai 118

semi-winter

Henan

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ166

Yanshi 16

weak spring

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ167

Xuke 1

semi-winter

Henan

1

1

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ168

Zhoumai 30

semi-winter

Henan

1

1

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ169

Yunong 4023

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ170

Zhengpinmai 8

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ171

Zhengmai 9023

weak spring

Henan

5

5

vrn-A1

Vrn-B1b

vrn-D1

vrn-B3

QZ172

Shiluan 02–1

semi-winter

Hebei

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ173

Aifeng 3

winter

Shaanxi

1

1

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ174

Han 6172

winter

Hebei

2

2

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ175

Luohan 3

semi-winter

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ176

Yannong 19

winter

Shandong

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ177

Huaimai 19

weak spring

Jiangsu

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ178

Yanmai 8911

semi-winter

Shaanxi

1

1

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ179

Bainong 3217

weak winter

Henan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ180

Yumai 68

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ181

Yumai 2

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ182

Gaocheng 8901

semi-winter

Hebei

1

1

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ183

Huarui 00712

semi-winter

Jiangsu

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ184

Shannong 7859

semi-winter

Shaanxi

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ185

Xiaoyan 22

weak spring

Shaanxi

1

1

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ186

Ruiquanmai 168

semi-winter

Henan

4

4

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ187

Hemai 26

semi-winter

Henan

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ188

Yan 99,102

semi-winter

Shandong

2

2

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ189

Jihan 2

semi-winter

Shandong

5

5

vrn-A1

vrn-B1

Vrn-D1b

vrn-B3

QZ190

Yumai 4

weak spring

Henan

4

4

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ191

Luohan 6

semi-winter

Henan

5

5

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ192

Zhenghan 1

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ193

Jinmai 47

semi-winter

Shanxi

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ194

Yumai 8

semi-winter

Henan

1

1

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ195

Beijing 841

winter

Beijing

0

0

vrn-A1

vrn-B1

vrn-D1

vrn-B3

QZ196

Sumai 3

weak spring

Jiangsu

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ197

Nanda 2419

weak spring

Jiangsu

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

QZ198

Chinese Spring

spring

Sichuan

5

5

vrn-A1

vrn-B1

Vrn-D1a

vrn-B3

W/S means winter/spring growth habits in 2015 or 2016

Fig. 1
Fig. 1

Distribution rate in each grade of winter/spring growth habits among 198 wheat materials in 2015 and 2016

In comparison with the data on regional trials (registered, Table 1), our data showed that the consistency was 89.39% when the accessions were divided into winter and spring groups, although 21 varieties need to be re-examined. In detail, of the varieties identified in the winter group, 10 varieties, including Huangming116, Lankaoaizao8, Yumai4, Taikong6, Zhengmai101, Zhongchuang805, Zhoumai23, Zhongyanmai 0708, Huaimai 19 and Xiaoyan 22, qualified as week spring (spring) type according to the registered results. The 11 spring growth habit accessions, which included Jihan2, Hengguan35, Zhengyou6, Luohan6, Luomai23, Pu2056, Shanyou225, Xinong9871, Yunong416, Zhoumai26 and Huarui 00712, were misclassified as accessions having winter (or semi-winter) growth habits. The reason is that these varieties were registered ten years ago, and winter-spring identification was not evaluated during registration tests at that time.

Growth habits were highly associated with growth periods in six environments

The results of the joint ANOVA analysis revealed that significant differences in the mean values of the HD or FD grouped by grades 0–5 in all six environments (Table 2). Briefly, grade 5 exhibited the shortest length of the growth period, while grade 0 exhibited the greatest length. In detail, significant differences in the average values of growth period data were also found between different levels of each trait. The trend was similar to that revealed by the joint ANOVA results. Generally, the smaller the value of the HD or FD is, the greater the value of the grade (Fig. 2).
Table 2

The joint ANOVA analysis in HD and FD grouped by growth habit in six environments

Traits

0

1

2

3

4

5

r

HD_14_SQ

183.3 ± 2.0(a)

182.3 ± 2.2(ab)

181.9 ± 2.2(ab)

181.3 ± 1.9(b)

181.7 ± 2.9(ab)

178.5 ± 2.9(c)

−0.871*

HD_15_SQ

189.3 ± 2.4(a)

187.9 ± 2.0(b)

186.9 ± 2.0(b)

187.1 ± 2.0(b)

186.5 ± 2.1(b)

183.7 ± 2.2(c)

−0.922**

HD_14_ZMD

172.0 ± 1.8(a)

171.3 ± 1.4(a)

171.3 ± 1.2(a)

171.3 ± 1.7(a)

171.0 ± 1.7(a)

169.9 ± 1.1(b)

−0.884**

HD_15_ZMD

159.1 ± 1.5(a)

158.3 ± 1.1(b)

157.9 ± 1.5(bc)

157.9 ± 1.1(bc)

158.1 ± 1.2(b)

157.2 ± 1.5(c)

−0.869*

HD_14_ZZ

181.7 ± 1.9(a)

180.9 ± 1.1(ab)

180.8 ± 1.3(ab)

180.1 ± 1.3(b)

180.1 ± 1.5(b)

177.6 ± 1.6(c)

−0.897**

HD_15_ZZ

190.2 ± 3.5(a)

187.9 ± 2.3(b)

187.6 ± 1.8(bc)

186.8 ± 1.8(bc)

186.4 ± 1.9(c)

183.1 ± 2.2(d)

−0.938**

HD_average

180.3 ± 11.4(a)

179.1 ± 10.7(a)

178.8 ± 10.7(a)

178.4 ± 10.4(ab)

178.3 ± 10.3(ab)

176.0 ± 9.5(b)

−0.915**

FD_14_SQ

193.7 ± 1.8(a)

192.2 ± 1.8(b)

191.4 ± 2.0(b)

191.5 ± 1.5(b)

191.9 ± 2.6(b)

188.3 ± 2.5(c)

−0.838*

FD_15_SQ

198.4 ± 1.0(a)

197.5 ± 1.0(b)

197.1 ± 0.8(b)

197.4 ± 0.7(b)

196.9 ± 1.0(b)

194.8 ± 1.4(c)

−0.867*

FD_14_ZMD

181.3 ± 1.0(a)

179.5 ± 1.8(b)

179.2 ± 1.8(b)

179.5 ± 1.8(b)

178.7 ± 1.9(b)

177.0 ± 1.8(c)

−0.907**

FD_15_ZMD

167.4 ± 2.1(a)

166.5 ± 1.5(ab)

166.1 ± 1.4(b)

165.9 ± 1.4(b)

166.4 ± 1.6(ab)

165.6 ± 1.6(b)

−0.813*

FD_14_ZZ

190.6 ± 1.6(a)

189.5 ± 1.4(ab)

189.0 ± 1.5(b)

188.8 ± 1.3(b)

188.6 ± 1.3(b)

185.4 ± 1.9(c)

−0.885**

FD_15_ZZ

199.3 ± 1.7(a)

198.2 ± 1.6(ab)

197.9 ± 1.6(bc)

197.3 ± 1.6(bc)

196.8 ± 1.6(c)

192.9 ± 2.6(d)

−0.889**

FD_average

189.1 ± 11.4(a)

188.1 ± 11.2(a)

187.6 ± 11.3(ab)

187.6 ± 11.1(ab)

187.4 ± 11.0(ab)

184.9 ± 10.2(b)

−0.886**

Lowercase letters indicate significant differences at the 0.05 level; * and ** indicates significant differences at the 0.05 and 0.01 level, respectively. The correlation coefficients (r) were calculated between the mean values of each grade and corresponding rank (r0.05,5 = 0.754 and r0.01,5 = 0.875); the ranks of the growth habit were calculated via the arithmetic means obtained during a two-year period, and all the data of all discrepant individuals were omitted

Fig. 2
Fig. 2

Correlations between growth habits and heading and flowering date (HD and FD) in six environments

Significant negative correlations were detected between growth habit and growth period in six environments (Table 2, p < 0.01). According to the results of joint variance analysis, the mean values of HD and FD were also correlated with growth habit; the Pearson correlation coefficients were − 0.915 and − 0.886, respectively. Generally, these results also indicated that HD were more tightly, though negatively, related with growth habits. Furthermore, the range of correlation coefficients in six environments were from −0.813 (FD_15_ZMD) to −0.938 (HD_15_ZZ). Thus, we could conclude that the duration of the heading and flowering time of cultivars was tightly associated with growth habits (Additional file 1: Table S2).

Distribution frequency of Vrn-1 alleles in varieties

Because no polymorphisms were found in the Vrn-A1 and Vrn-B3 alleles, we focused on Vrn-B1 and Vrn-D1. The distribution frequency order of the dominant alleles was Vrn-D1a (23.70%) > Vrn-D1b (8.10%) > Vrn-B1a (2.50%) > Vrn-B1b (2.00%) (Table 3). Only one accession was found to carry Vrn-B1b + Vrn-D1a, and 125 accessions presented no dominant alleles. We also used the “consistency index” to evaluate the reliability between the allelic detection and speculated results as described by Stelmakh [19]. According to Stelmakh’s report, the accessions that contained at least one dominant allele were classified as spring types, whereas they were classified as winter types if they had three recessive alleles. Then, we found that nine accessions harbouring dominant Vrn-B1a or Vrn-B1b alleles as well as one accession harbouring Vrn-B1b + Vrn-D1a exhibited the highest rate of consistency (100%). Therefore, these accessions were classified as spring types, which were identical to the results of identification of growth habit in this research. The genotype rate of vrn-B1 + vrn-D1 (63.1%) dominated in all tested panels, and its consistency (96.8% or 95.2%) was also higher than that of Vrn-D1a (48.9%) and Vrn-D1b (25.0%). Therefore, Vrn-D1, especially Vrn-D1b, could not accurately estimate the growth habit.
Table 3

Distribution rates of Vrn-1 and their consistency with results of identification of W/S growth habit

Genotype

Material number (only)

Frequency (%)

Speculation of winter/spring habit

Winter

Spring

Consistency (%)

Vrn-B1a (only)

5

2.5

Spring

0

5

100.0

Vrn-B1b (only)

4

2.0

Spring

0

4

100.0

Vrn-D1a (only)

47

23.7

Spring

24

23

48.9

Vrn-D1b (only)

16

8.1

Spring

12

4

25.0

Vrn-B1b + Vrn-D1a

1

0.5

Spring

0

1

100.0

vrn-B1 + vrn-D1

125

63.1

Winter

119/117

4/6

96.8/95.2

Total

198

100.0

 

155/153

41/43

79.8/78.2

The values in parentheses represent the percentage in each group; “only” in parentheses indicates that the value is specific to the single genotype

Effects of Vrn-1 combinations on HD and FD

The effects of Vrn-B1 + Vrn-D1 combinations concerning HD and FD were examined. In total, there were 6 different types of genotypes grouped by combinations. Among them, 125 accessions had double-recessive vrn-B1 + vrn-D1 alleles. However, Vrn-B1a + vrn-D1, Vrn-B1b + vrn-D1, vrn-B1 + Vrn-D1a, vrn-B1 + Vrn-D1b alleles were carried by 5, 4, 47 and 16 varieties, respectively. Only 1 accession harboured double-dominant Vrn-B1b + Vrn-D1a alleles. Least significant range (LSR, a method of multiple comparison) tests revealed significant differences among the six groups with respect to the mean values of HD and FD in almost all environments (P < 0.05), with the exception that LSR tests for FD_15_ZMD were not significant (highlightedwith yellow). However, no significant differences in the mean values of each group across environments were revealed by the joint ANOVA results (highlighted with green) (Table 4).
Table 4

LSR method of multiple comparison for the effects of Vrn-B1 combined with Vrn-D1

Types

N

HD_14_SQ

HD_15_SQ

HD_14_ZMD

HD_15_ZMD

HD_14_ZZ

HD_15_ZZ

HD_average

vrn-B1 + vrn-D1

125

183.1 ± 2.3(a)

188.5 ± 2.2(a)

172.2 ± 1.6(a)

159.1 ± 1.3(a)

181.8 ± 1.3(a)

188.7 ± 2.5(a)

178.9 ± 10.7(a)

Vrn-B1a + vrn-D1

5

179.1 ± 0.8(bc)

184.6 ± 0.8(bc)

171.2 ± 0.4(ab)

157.8 ± 0.5(ab)

178.6 ± 0.8(bc)

184.4 ± 1.6(bc)

175.9 ± 9.5(a)

Vrn-B1b + vrn-D1

4

177.5 ± 1.9(c)

182.5 ± 0.7(c)

170.0 ± 1.1(b)

156.7 ± 2.0(b)

177.3 ± 1.1(c)

181.7 ± 1.6(c)

174.3 ± 9.1(a)

vrn-B1 + Vrn-D1a

47

181.2 ± 3.2(ab)

186.5 ± 2.6(ab)

171.5 ± 1.3(ab)

158.8 ± 1.4(a)

179.8 ± 1.8(ab)

186.1 ± 2.6(ab)

177.4 ± 10.0(a)

Vrn-B1b + Vrn-D1a

1

180.5 ± NA(abc)

184.0 ± NA(bc)

171.0 ± NA(ab)

159.0 ± NA(a)

178.5 ± NA(bc)

184.5 ± NA(bc)

176.3 ± 9.8(a)

vrn-B1 + Vrn-D1b

16

180.8 ± 2.5(abc)

186.5 ± 2.7(ab)

171.5 ± 1.4(ab)

158.7 ± 1.1(ab)

179.7 ± 1.9(abc)

186.75 ± 2.9(ab)

177.4 ± 10.8(a)

Types

N

FD_14_SQ

FD_15_SQ

FD_14_ZMD

FD_15_ZMD

FD_14_ZZ

FD_15_ZZ

FD_average

vrn-B1 + vrn-D1

125

192.9 ± 1.9(a)

197.4 ± 1.0(a)

180.4 ± 1.9(a)

167.4 ± 1.7(a)

190.4 ± 1.5(a)

198.9 ± 1.8(a)

187.9 ± 11.1(a)

Vrn-B1a + vrn-D1

5

190.4 ± 0.8(ab)

195.0 ± 0.6(bc)

181.2 ± 1.1(a)

165.8 ± 1.0(a)

187.0 ± 0.9(bc)

195.0 ± 1.5(bc)

185.7 ± 10.3(a)

Vrn-B1b + vrn-D1

4

187.1 ± 0.9(b)

193.5 ± 0.7(c)

177.1 ± 1.2(b)

165.3 ± 1.3(a)

184.7 ± 1.5(c)

191.3 ± 2.2(d)

183.2 ± 9.8(a)

vrn-B1 + Vrn-D1a

47

191.0 ± 3.23(a)

195.9 ± 1.6(ab)

178.7 ± 1.9(ab)

167.2 ± 1.5(a)

187.9 ± 2.1(ab)

196.2 ± 3.0(abc)

186.2 ± 10.7(a)

Vrn-B1b + Vrn-D1a

1

190.0 ± NA(ab)

195.0 ± NA(bc)

181.0 ± NA(a)

167.5 ± NA(a)

187.0 ± NA(bc)

193.0 ± NA(cd)

185.6 ± 10.1(a)

vrn-B1 + Vrn-D1b

16

191.6 ± 3.3(a)

196.1 ± 1.6(ab)

178.6 ± 2.1(ab)

167 ± 1.1(a)

187.7 ± 2.5(ab)

196.7 ± 2.9(ab)

186.4 ± 11.5(a)

Letters in parentheses indicate a significant difference at the 0.05 level; decimal values preceded by “±” indicate standard deviation

Because the low frequency of the Vrn-B1b + Vrn-D1a type (0.5%) made it difficult to exactly compare this allelic combination with other genotypes, we focused on the other five combinations. With respect to their effects, we found that accessions with the vrn-B1 + vrn-D1 genotype presented the latest HD and FD (178.9 d), while varieties that harboured the Vrn-B1b + vrn-D1 allelic combination presented the earliest HD and FD (174.3 d) as well as the shortest growth habit. This method could be useful for precisely identifying the differences in growth habits in each group individually. Then, analyses of Vrn-1 combinations revealed that the effects of the dominant Vrn-B1 genotype on HD and FD were stronger than those of the dominant Vrn-D1 genotype. Finally, we concluded that the rank order of the effects on the growth period was as follows: Vrn-B1b > Vrn-B1a > Vrn-D1b > Vrn-D1a > vrn-D1 = vrn-B1 (Table 4).

Allelic variations of Ppd-1 alleles

No polymorphisms were found in the promoter of Ppd-A1 or Ppd-B1; thus, we focused on their internal variants. Here, variations in the junction sequences of Ppd-B1 were investigated to analyse their allelic variations and effects, which were considered copy number variations (CNVs) [28]. For Ppd-B1, the Ppd-B1a gene has three types in terms of CNV, accounting for 33.8% (Truncated CS type), 8.6% (Intact CS type) and 35.3% (Sonora 64 type) (Table 5). According to a previous report, the first two genotypes were named Ppd-B1c and the Sonora 64 type was named Ppd-B1a [30]. For variations within Ppd-B1, 6 types of genotypic combinations were all detected because of their different types of combination. As to percentage, the “S: N: N” type constituted the largest proportion (34.34%, “Sonora 64 type” only), while the percentages of “N: I: N” (1.01%, “Intact CS type” only) and “S: N: T” (1.01%, “Sonora 64 type + Truncated CS type” for short) were the lowest (Additional file 1: Table S2; Table 5).
Table 5

Allelic variants of Ppd-B1

Genotype

Sonora 64 type

Intact CS type

Truncated CS type

N

Proportion (%)

Ppd-B1

No

No

No

61

30.81

Yes

No

No

68

34.34

No

Yes

No

2

1.01

No

No

Yes

50

25.25

Yes

No

Yes

2

1.01

No

Yes

Yes

15

7.58

Total

35.3%

8.6%

33.8%

198

100

For Ppd-D1, the haplotypes identified among the materials were divided into three types in accordance with the reports of Guo et al. (2010) [31] and Chen et al. (2013) [13]: Hapl I (34.85%, sensitive), Hapl II (0.5%, Chinese Spring, insensitive), and Hapl VII (64.6%, sensitive). Only one variety (Chinese Spring) had a 2.0-kb deletion in the promoter region and thus should be designated Ppd-D1a (insensitive, theoretical relatively short HD and FD). Thus, Hapl I and Hapl VII could be considered recessive alleles in this study (Table 6).
Table 6

Allelic variants of Ppd-D1

Genotype

2-kb deletion

Transposable element (TE)insertion

5-bp deletion

16-bp insertion

Number

Proportion (%)

Ppd-D1

Hapl I

69

34.85

Hapl II

1

0.51

Hapl VII

128

64.65

Total

 

198

100

The method for dissecting the haplotypes of Ppd-D1was described by Guo et al. (2010)

Effects of single Ppd-1 alleles on HD and FD

One hundred and twenty-five materials that had double-recessive Vrn alleles (vrn-B1 + vrn-D1) were selected to evaluate the influence of Ppd-B1 or Ppd-D1 on plant traits. There were four genotypes, but no significant differences were found among groups according to ANOVA results. Because inconsistencies between the ANOVA and LSR test results were sometimes detected, multiple comparisons were subsequently performed. The average values for phenotypes among the four groups differed significantly for only five traits (three traits in Zhumadian). Furthermore, varieties that harboured “Sonora 64 type” (“N: N: S”) showed the shortest HD and FD. This result was consistent with those reported by Díaz et al. (2012) [28] (Table 7).
Table 7

The effects of single Ppd-B1 and Ppd-D1alleles on HD and FD

Type

N

HD_14_SQ

HD_15_SQ

HD_14_ZMD

HD_15_ZMD

HD_14_ZZ

HD_15_ZZ

HD_average

N:N:N

39

183.2 ± 2.7(ab)

188.7 ± 2.6(a)

172.1 ± 1.5(b)

159.2 ± 1.4(b)

181.8 ± 1.5(ab)

189.2 ± 2.6(a)

179.1 ± 10.9(a)

T:N:N

30

183.3 ± 2.1(ab)

188.6 ± 1.9(a)

172.7 ± 1.7(ab)

159.2 ± 1.2(b)

181.9 ± 1.4(ab)

188.4 ± 2.6(a)

179.0 ± 10.6(a)

T:I:N

10

184.1 ± 2.1(a)

189.3 ± 1.9(a)

173.6 ± 1.3(a)

160.2 ± 0.8(a)

182.7 ± 0.7(a)

189.7 ± 1.3(a)

179.9 ± 10.5(a)

N:N:S

44

182.6 ± 2.1(b)

188.2 ± 2.1(a)

171.8 ± 1.4(b)

158.8 ± 1.3(b)

181.7 ± 1.3(b)

188.2 ± 2.5(a)

178.6 ± 10.6(a)

Type

N

FD_14_SQ

FD_15_SQ

FD_14_ZMD

FD_15_ZMD

FD_14_ZZ

FD_15_ZZ

FD_average

N:N:N

39

193.3 ± 2.5(a)

197.3 ± 1.3(a)

180.4 ± 2.1(a)

167.5 ± 1.9(ab)

190.5 ± 1.8(a)

199.2 ± 2.1(a)

188.1 ± 11.3(a)

T:N:N

30

192.7 ± 1.6(a)

197.5 ± 0.9(a)

180.5 ± 1.9(a)

167.5 ± 1.4(b)

190.2 ± 1.4(a)

198.7 ± 2.2(a)

187.9 ± 11.1(a)

T:I:N

10

193.1 ± 0.9(a)

197.7 ± 0.8(a)

181.0 ± 1.4(a)

168.5 ± 1.4(a)

190.9 ± 0.8(a)

199.4 ± 0.8(a)

188.5 ± 10.8(a)

N:N:S

44

192.7 ± 1.5(a)

197.3 ± 0.8(a)

180.3 ± 1.8(a)

166.9 ± 1.6(b)

190.3 ± 1.4(a)

198.7 ± 1.5(a)

187.7 ± 11.2(a)

Type

N

HD_14_SQ

HD_15_SQ

HD_14_ZMD

HD_15_ZMD

HD_14_ZZ

HD_15_ZZ

HD_average

Hapl I

45

183.1 ± 2.2(a)

188.5 ± 2.0(a)

172.3 ± 1.5(a)

159.1 ± 1.1(a)

181.9 ± 1.3(a)

188.8 ± 2.2(a)

179.0 ± 10.6(a)

Hapl VII

77

183.1 ± 2.4(a)

188.5 ± 2.3(a)

172.2 ± 1.6(a)

159.1 ± 1.4(a)

181.8 ± 1.4(a)

188.6 ± 2.6(a)

178.9 ± 10.7(a)

Type

N

FD_14_SQ

FD_15_SQ

FD_14_ZMD

FD_15_ZMD

FD_14_ZZ

FD_15_ZZ

FD_average

Hapl I

45

192.7 ± 1.5(a)

197.3 ± 1.0(a)

180.7 ± 1.7(a)

167.2 ± 1.4(a)

190.4 ± 1.4(a)

199.1 ± 1.7(a)

187.9 ± 11.1(a)

Hapl VII

77

193.1 ± 2.1(a)

197.4 ± 1.1(a)

180.3 ± 2.0(a)

167.4 ± 1.8(a)

190.4 ± 1.5(a)

198.8 ± 1.9(a)

187.9 ± 11.2(a)

N” in the “Type” column indicates that no target bands were amplified in the “Truncated CS type (425 bp)”, “Intact CS type (994 bp)"or”Sonora64 (223 bp)"CNVs at the Ppd-B1 locus

Regarding Ppd-D1, two genotypes were found, and no significant differences were detected via the LSR method between groups. We predicted that two recessive types of alleles did not contribute to the advancement of heading and flowering time. With respect to the comparisons of the mean values of Ppd-B1 and Ppd-D1 on HD and FD, the effects of Ppd-B1 were somewhat stronger than those of Ppd-D1 (Table 7).

Interactive effects of Ppd-1 combinations on HD and FD

We also examined and assessed the interactive effects of Ppd-B1 and Ppd-D1 combinations. Similarly, no significant differences were found according to the ANOVA results. A total of eight genotypes that contained two Ppd alleles were surveyed, in which the type “N: N: S + Hapl VII” constituted the largest proportion (29, 23.6%), while the percentages of “T: I: N + Hapl I or Hapl VII” were the lowest (Table 8). With respect to their effects, the LSR method revealed significant differences in the mean values among groups for four traits (three in Zhumadian and one in Zhengzhou). We suspected that Ppd-1, especially Ppd-B1, functioned only in specific environments. Generally, the mean values of HD and FD were advanced by the Ppd-1 combinations by only 0.2–0.5 d. Therefore, the effects of Ppd-1 combinations were stronger than those of single Ppd-B1 or Ppd-D1 alleles but were far weaker than those of Vrn alleles (5–7 d earlier heading or flowering in Zhengzhou and Zhumadian). With respect to the individual genotypes, the rank order of their effects on growth period was as follows: Ppd-1 > Ppd-B1 > Ppd-D1.
Table 8

Interactive effects of Ppd-1 combinations on growth period and growth habit

Truncated CS type

Intact CS type

Sonara64 type

Ppd-D1

N

HD_14_SQ

HD_15_SQ

HD_14_ZMD

HD_15_ZMD

HD_14_ZZ

HD_15_ZZ

HD_average

 No

No

No

Hapl-I

13

182.9 ± 2.4(a)

188.3 ± 2.6(a)

172.1 ± 1.3(bc)

159.0 ± 1.1(b)

181.5 ± 1.2(b)

188.4 ± 1.9(a)

178.7 ± 10.6(a)

 Yes

No

No

Hapl-I

11

183.2 ± 2.2(a)

188.2 ± 1.6(a)

172.8 ± 1.9(abc)

159.1 ± 1.2(b)

181.8 ± 1.4(b)

188.8 ± 2.3(a)

179.0 ± 10.6(a)

 Yes

Yes

No

Hapl-I

5

184.1 ± 1.7(a)

189.2 ± 2.2(a)

173.6 ± 1.3(a)

159.9 ± 0.4(ab)

183.1 ± 0.2(a)

190.1 ± 0.6(a)

180.0 ± 10.7(a)

 No

No

Yes

Hapl-I

15

182.7 ± 2.2(a)

188.8 ± 1.8(a)

171.9 ± 1.1(c)

159.0 ± 1.2(b)

182.1 ± 1.3(ab)

188.7 ± 2.8(a)

178.9 ± 10.8(a)

 No

No

No

Hapl-VII

26

183.5 ± 2.9(a)

188.9 ± 2.6(a)

172.1 ± 1.6(abc)

159.3 ± 1.6(ab)

182.1 ± 1.6(ab)

189.6 ± 2.8(a)

179.3 ± 11.0(a)

 Yes

No

No

Hapl-VII

19

183.4 ± 2.0(a)

188.8 ± 2.1(a)

172.6 ± 1.6(abc)

159.2 ± 1.1(b)

181.9 ± 1.3(ab)

188.2 ± 2.8(a)

179.1 ± 10.7(a)

 Yes

Yes

No

Hapl-VII

5

184.0 ± 2.7(a)

189.5 ± 1.8(a)

173.6 ± 1.5(ab)

160.5 ± 1.1(a)

182.3 ± 0.9(ab)

189.4 ± 1.8(a)

179.9 ± 10.5(a)

 No

No

Yes

Hapl-VII

29

182.5 ± 2.1(a)

187.8 ± 2.2(a)

171.8 ± 1.6(c)

158.7 ± 1.4(b)

181.5 ± 1.3(b)

187.9 ± 2.3(a)

178.4 ± 10.5(a)

Truncated

Intact

Sonara64

Ppd-D1

N

FD_14_SQ

FD_15_SQ

FD_14_ZMD

FD_15_ZMD

FD_14_ZZ

FD_15_ZZ

FD_average

CS type

CS type

type

 No

No

No

Hapl-I

13

192.8 ± 1.8(a)

197.1 ± 1.3(a)

180.6 ± 1.7(a)

167.3 ± 1.2(b)

190.41 ± 1.3(a)

198.9 ± 2.0(a)

187.9 ± 11.1(a)

 Yes

No

No

Hapl-I

11

192.4 ± 1.1(a)

197.3 ± 0.8(a)

181.1 ± 2.1(a)

167.3 ± 1.4(b)

190.0 ± 1.2(a)

199.0 ± 1.8(a)

187.9 ± 11.0(a)

 Yes

Yes

No

Hapl-I

5

193.4 ± 0.5(a)

197.9 ± 1.1(a)

181.2 ± 1.4(a)

167.8 ± 1.3(ab)

191.1 ± 0.7(a)

199.8 ± 0.4(a)

188.5 ± 11.2(a)

 No

No

Yes

Hapl-I

15

192.6 ± 1.8(a)

197.5 ± 0.8(a)

180.4 ± 1.9(a)

167.0 ± 1.7(b)

190.6 ± 1.7(a)

198.8 ± 1.7(a)

187.8 ± 11.3(a)

 No

No

No

Hapl-VII

26

193.6 ± 2.9(a)

197.5 ± 1.4(a)

180.3 ± 2.4(a)

167.7 ± 2.2(b)

190.5 ± 2.0(a)

199.3 ± 2.1(a)

188.2 ± 11.4(a)

 Yes

No

No

Hapl-VII

19

192.9 ± 1.9(a)

197.6 ± 0.9(a)

180.1 ± 1.8(a)

167.6 ± 1.5(b)

190.4 ± 1.5(a)

198.6 ± 2.4(a)

187.9 ± 11.2(a)

 Yes

Yes

No

Hapl-VII

5

192.8 ± 1.3(a)

197.5 ± 0.5(a)

180.8 ± 1.4(a)

169.3 ± 1.1(a)

190.8 ± 1.1(a)

199.1 ± 1.1(a)

188.4 ± 10.6(a)

 No

No

Yes

Hapl-VII

29

192.8 ± 1.4(a)

197.2 ± 0.8(a)

180.2 ± 1.8(a)

166.8 ± 1.6(b)

190.2 ± 1.2(a)

198.6 ± 1.4(a)

187.7 ± 11.2(a)

Letters in parentheses indicate a significant difference at the 0.05 level; decimal values preceded by “±” indicate standard deviation; ‘N’ indicates no target bands were amplified in ‘Truncated CS type’, ‘Intact CS type’ and ‘Sonara64’ of CNVs at Ppd-B1 locus

Discussion

Consistency of marker analysis and growth habit identification

Wheat is the major crop in the YHW in terms of yield and area in China. This region is located in the transition zone of winter and spring wheat cultivation, where semi-winter varieties and weak spring cultivars are also planted. However, inconsistencies sometimes occur between registered and empirical results. Hence, the precise identification of winter/spring growth habits for newly registered varieties is necessary and helpful not only for the rational use of varieties but also for the provision of vital information for breeders in the YHW. Here, growth habits were examined during a two-year period via a novel field spring sowing identification method and materials along with marker-assisted selection (MAS).

We believe that our identification method in the field is more practical than that conducted in greenhouses, where the materials are grown under conditions closely related to those in the field. Furthermore, correlation analysis revealed that the phenotypic data during two years were also consistent between years. In comparison with registered information, 10 of 155 (6.45%, 2016) winter wheat varieties were inconsistent (Zhongchuang805, Taikong6, Xiaoyan22, etc.), and similar situations were observed in other groups—in particular, 43 spring wheat varieties containing 13 (25.6%, 2016) inconsistent samples (Bainong3217, Luohan6, Xinong979, etc.). We doubted that the reason for this situation was due to their early registration before the materials were rigorously identified. In total, the consistency was approximately 90%, although some varieties presented discrepancies, and our method was more convenient than the report of Gardener and Barnett [32].

More vital clues that we wanted to examine included the consistency between vernalization alleles and growth habit. The results indicated that all ten Vrn-B1 genotypes of spring wheat varieties presented a value of 100%, whereas Vrn-D1 exhibited lower results. Among the 43 cultivars ranked as grade 5 (data from2016, Xinzheng), 37 (86.04%) carried at least one of the tested dominant vernalization alleles and were classified as spring varieties; the other 6 varieties carried the recessive alleles at the three vernalization loci. For winter types, 131 of 155 (84.51%) accessions presented similar consistency. We predicted that there are two main factors that could be responsible for this phenomenon. First, a single individual is genotyped, whereas the phenotype is assessed on a plot scale of multiple individuals, and there may be some variation among individual seeds. Second, two other major pathways also control heading and flowering dates in plants, i.e., the phytohormone gibberellic acid (GA) and the autonomous pathways, in addition to the vernalization and photoperiod pathways [33, 34].

Allelic distributions of Vrn-1 revealed trends and orientations in the YHW.

As no dominant allele of Vrn-A1 or Vrn-B3 was detected, which are probably the two genes that have the strongest effects of those examined, the allelic distributions of the dominant Vrn-B1 and Vrn-D1 alleles are likely responsible for the spring genotypes of wheat varieties. Indeed, the scarcity and decreasing frequency of the Vrn-A1 and Vrn-B3 loci in the YHW have been previously discussed by Zhang et al. (2008) and Chen et al. (2013) [4, 13]. We suspected that the frequencies of recessive vrn-B1 and vrn-D1 likely increased via direct selection due to their contributions to yield traits because of the long maturation period. This inference was in agreement with that reported in the literature [14, 35]. Furthermore, the frequency of dominant Vrn-D1 was higher than that of Vrn-B1 in our tested materials. These results were also consistent with the previous report of Zhang et al. (2015) [36].

Although only 10 dominant Vrn-B1 alleles (5.0%) were discovered in the spring genotypes, the consistency of the marker-growth habit (100%) was better than that of Vrn-D1. Additionally, we found that accessions with single Vrn-B1b alleles exhibited the earliest HD and FD in the six environments; these effects were stronger than those forVrn-B1a, Vrn-D1b and Vrn-D1a. These results were consistent with those of previous studies in which the rank order was Vrn-A1 > Vrn-B1 > Vrn-D1 [37]. Santra et al. (2009) reported that a novel Vrn-B1b allele that resulted from a 36-bp deletion within intron 1, which is referred to as ‘Alpowa’ and carries the winter growth habit alleles vrn-A1 and vrn-B1, was likely to cause a spring growth habit; however, the authors did not provide sufficient evidence [14].

The dominant Vrn-D1 locus occurs in the most popular types and is distributed throughout nearly the entire wheat production region [4, 13]. The previous data also established that carriers of Vrn-A1 or Vrn-D1 tend to produce longer spikes than do carriers ofVrn-B1. As a result, the Vrn-D1 genotypes were prevalent in China [38, 39]. In the present study, in terms of Vrn-D1, the allelic frequency reached 31.8%, which represented the most dominant allele distribution in the population. Thus, the proportion was similar to previous reports; however, poor consistency in the growth habit of Zhengzhou was observed. Thus, it would be interesting to test whether Vrn-D1 and other alleles interact to influence growth habits and period (HD and FD).

The results of the Vrn-1 combination analysis revealed that only one accession carried Vrn-B1b + Vrn-D1a alleles; thus, the samples were so limited that phenotypic data were not statistically representative. For genotypic analysis, in combination with growth habit identification, 63.1% of the materials that had three recessive alleles all belonged to winter or semi-winter wheat (grade 0–4). This tendency was in accordance with that reported by Sun et al. (2009, 61.1%). Moreover, the ANOVA and LSR tests revealed that the mean values of the HD, FD and growth habit among six genotypes differed significantly, which also indicated that the Vrn-1 combinations were tightly associated with phenotypes. Although the effects of these combinations on HD and FD were not definitively stronger than those of single Vrn-B1 alleles, the growth habit level was divided in greater detail. This division will enable a more precise identification of vernalization requirements for accessions at molecular levels.

Interactive effects detected between the Ppd-B1 and Ppd-D1 alleles

Photoperiod responses are controlled by members of the pseudo-response regulator (PRR) gene family in plants. In general, the potential of Ppd-1 alleles to affect insensitivity has been ranked as Ppd-D1 > Ppd-B1 > Ppd-A1 [17, 38]. However, in the present study, only one accession (Chinese spring) was found to carry a 415-bp band that indicated a genotype of Ppd-D1a. Thus, it was difficult to precisely evaluate its effect on phenotype statistically. According to the criterion of previous research, two sensitive haplotypes (Hapl I and Hapl II) of Ppd-D1 were used for the evaluation for their distribution and effects [13, 31].

For Ppd-B1, we only examined the polymorphisms of CNVs of the Ppd-B1 locus because of its tight association with heading and flowering time. Indeed, Zhang et al. (2015) designated eight haplotypes according to the combinations of CNVs of Ppd-B1 and found that the cultivar with Ppd-B1_hapl-VI demonstrated the earliest heading and flowering times [36]. However, the results were not consistent with those of Díaz et al. (2012) [28]. In the present study, 125 accessions carrying recessive vrn-B1 and vrn-D1 alleles were selected. With respect to Ppd-B1, we found that wheat cultivars with “Sonora 64” Ppd-B1a alleles flower earlier than those with “Chinese Spring” alleles, which was in accordance with Díaz et al. (2010). Furthermore, we found that six types of combinations emerged, and the “Truncated CS type” and “Intact CS type” did not simultaneously emerge for Ppd-B1. These results were also not the same as those reported by Chen et al. (2013). We suspected that the complex genetic background (genotypes mixed with Vrn-1 genes) would hinder us from providing definitive results. Thus, we believed that our method was possibly more reliable than previous methods because of the uniform background [30]. With respect to Ppd-D1a, the rare diversity of the Ppd-D1 allele could not be used to exactly evaluate the effects of the variants, and no significant differences were observed between the two haplotypes (Hapl I and Hapl II).

Comparison of effects on growth period (HD and FD) between the Vrn-1 and Ppd-1 alleles

Moreover, from a comprehensive perspective, we concluded that, compared with Ppd-1, Vrn-1 played a major role in regulating heading and flowering traits as well as growth habit. At the Vrn-1 locus, cultivars with the Vrn-B1b + vrn-D1 (174.3 d for HD, 183.2 d for FD) allele both headed and flowered earlier by approximately 4 days than did cultivars with the vrn-B1 + vrn-D1 (178.9 d for HD, 187.9 d for FD) allele (Table 4). Whereas at the Ppd-1 locus, cultivars with the “N: N: S” allele combination (178.6 d for HD, 187.7 d for FD) both headed and flowered approximately 1 day earlier than did cultivars with the “T: I: N” allele combination (179.9 d for HD, 188.5 d for FD) (Table 7). Indeed, the interactive effects of Vrn-1 and Ppd-1 gene combinations were also detected in our research. However, the results of ANOVA and LSR tests revealed weak interactions between Vrn-B1 and Ppd-B1, Vrn-D1 and Ppd-D1, Vrn-B1and Ppd-D1, Vrn-D1and Ppd-B1 (data not shown). We suspected that the complex genetic background in natural populations would make it difficult to reveal this interaction. In a previous study, Shcherban et al. (2014) also found that the haplotypes Ppd-D1a/Vrn-B1a or Ppd-D1a/Vrn-B1a did not differ significantly in heading time from the respective Vrn-1haplotypesharbouring the sensitive allele Ppd-D1b [40]. This finding suggests that it is better for us to examine the interaction between Ppd-1 and Vrn-1 in biparental populations.

Conclusion

In the present study, we dissected the Vrn-1 and Ppd-1 gene composition and found that Vrn-1, rather than Ppd-1, played a major role in controlling vernalization and photoperiod responses in this region. The work will be helpful for guiding the breeding of wheat in the Yellow and Huai wheat production region.

Methods

We tested 198 cultivars (lines) including historic varieties, commercial varieties, and newly bred varieties originating from the YHW. Among them, 159 accessions were from Henan, 10 accessions were from Shandong, 10 accessions were from Shaanxi, 8 accessions were from Jiangsu,4 accessions were from Hebei, 4 accessions were from Beijing, 1 accession was from Shanxi, 1 accession was from Anhui, and 1 accession (Chinese Spring) was from Sichuan (Table 1). The entire original source of the plant materials used in our study was kindly provided by other labs. We complied with the Convention on the Trade in Endangered Species of Wild Fauna and Flora: https://www.cites.org.

Characterization of winter/spring growth habits

Although the growth habit for assessing vernalization is already well established, identification of the exact materials involved is necessary because of differences in environmental conditions. The tested materials were planted at the Zhengzhou Scientific Research and Education Center of Henan Agriculture University (113.7°E, 34.7°N) on 12 March 2015 and at another test site [ZhengHan Seed Technology Co. Ltd., XinZheng (113.7°E, 34.4°N)] on 12 March 2016. Seeds were sown in 1.0-m rows, and individual seeds were spaced 6.67 cm apart; 15 seedlings were reserved per row after wheat seedling emergence. Two replications were planted for reliable data collection. The stage of maturity and percentage of headed spikes were recorded on 25 June in the same year; we repeated these measurements one week later. The growth habit of the materials was divided into grades numbered 0 to 5. The criteria were as follows: 0, no jointing and booting; 1, partial main stem headed; 2, main stem and a few tillers headed; 3, normal heading but abnormal grain filling and immature; 4, normal heading and grain filling but premature; 5, normal maturity.

Identification of HD and FD

The varieties used to assess agronomic traits were planted on 9 October 2013 and 2014 in Zhengzhou (113.7°E, 34.7°N), on 15 October 2013 and 17 October 2014 in Shangqiu (115.7°E, 34.5°N), and on 19 October 2013 and 5 November 2014 in Zhumadian (114.0°E, 32.9°N). All of these locations differed significantly in day length and climatic factors in Henan Province. Each material was planted in two 1.5-m rows; there were 110 seeds per row, and the rows were spaced 23 cm apart. Two replications were planted at each location. Field management practices during our experiments were in accordance with agronomic practices commonly used in the area. The HD and FD were assessed on a plot scale of multiple individuals when more than half of the individual seedlings exhibited classic morphological traits for these events.

DNA extraction and diagnostic markers for Vrn-1 and Ppd-1

DNA was extracted from the seedlings in accordance with a modified SDS-phenol-chloroform method [27]. The primers used were based on those described in many previous reports and were synthesized by Sangon Biotech Co., Ltd. (Shanghai) (Additional file 2: Table S1). To recognize the segments amplified from Ppd-B1, accessions harbouring 994 bp, 425 bp, and 223 bp were designated intact Chinese Spring type (I), truncated Chinese Spring type (T), and Sonora 64 type (S), respectively. If no bands were amplified in the materials, the genotypes were referred to as null (N) [28].

PCR amplification and electrophoresis

PCR amplification reactions were conducted in a 12-μL reaction flask containing 40 ng of genomic DNA, each primer at 2.5 μM, each dNTP at 200 μM, 1× buffer containing1.5 μM MgCl2, and 0.5 units of Taq polymerase. We used a Bio-Rad thermocycler with the following PCR conditions: 94 °C for 3 min; 34 cycles of 94 °C for 30 s, 50 °C to 65 °C for 30 s (annealing temperatures for each primer pair are listed in Additional file 2: Table S1), and 72 °C for 1 min; and a final 10-min extension at 72 °C for preservation. The PCR products were separated by electrophoresis either on a 0.8–1.2% agarose gel stained with ethidium bromide (EB) or an 8% nondenaturing polyacrylamide gel and visualized with silver staining [29].

Statistical analysis

A consistency index (%) was used; this index indicated the number of accessions that originated from the consistent results of both genotype and field identifications divided by the total number of materials. The phenotypic data were imported into R software (R 3.4.1) for analysis via ANOVA, Student’s t-tests and correlation; we used the “reshape” and “agricolae” packages to perform these analyses and the “ggplot2” package for graphical construction.

Abbreviations

YHW: 

Yellow and Huai wheat production region.

HD: 

Heading date.

FD: 

Flowering date.

ZZ: 

Zhengzhou.

ZMD: 

Zhumadian.

SQ: 

Shangqiu.

ANOVA: 

Analysis of variance.

LSR: 

Least significant range method of multiple comparison.

CNVs: 

Copy number variations.

MAS: 

Marker-assisted selection.

PRR: 

Pseudo-response regulator.

WS: 

Winter/Spring growth habit.

Declarations

Acknowledgements

The authors would like to thank Aimin Zhang for his support, advice and revisions regarding this manuscript as well as the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences.

Funding

The design of the study and collection, analysis, and interpretation of data were supported by the National Basic Research Program of China (2014CB138105); the molecular experiments were supported by the Youth Science and Technology Innovation Fund (30601440).

Availability of data and materials

All data are available in the additional files.

Authors’ contributions

KZ conceived the project and prepared the trials. JW, GD and LC performed the experiments. SC analysed the data and was a major contributor in writing the manuscript. XC and HX performed statistical analysis and edited the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
College of Agronomy, Henan Agricultural University/Collaborative Innovation Center of Henan Grain Crops, Zhengzhou, 450002, China
(2)
HuaGuan Seed Technology Co. Ltd., Zhoukou, Henan, China
(3)
YuLong Crops Research Institute, Xinzheng, Henan, China

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© The Author(s). 2018

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