bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 QTL Mapping and integration as well as candidate gene prediction for branch 2 number in soybean 3 Yuhua Yang1,2, Yang Lei3, Zhiyuan Bai2, Yichao Wei4, Ruijun Zhang2* 4 1 School of Life Science, Shanxi University, Taiyuan 030006, China 5 2 Institute of Crop Germplasm Resources，Shanxi Academy of Agricultural Sciences, 6 Taiyuan 030031, China 7 3 Vegetables research institute, Shanxi Academy of Agricultural Sciences, Taiyuan 8 030031, China 9 4 Institute of Agricultural Resources & Economics，Shanxi Academy of Agricultural 10 Sciences，Taiyuan 030006, China 11 These authors contributed equally to this work 12 *Correspondence author: [email protected] 13 1 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 2 Running title: QTL Mapping of branch number in Soybean 3 Key Words: Soybean; Branch number; QTL Integration; Candidate Gene 4 Correspondence author: Zhang Ruijun 5 Longcheng 161 Road, Taiyuan 6 Shanxi, 030031 7 Phone: 0351-7967045 8 Email: [email protected] 2 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 2 Abstract 3 Branch number is an important factor that affects crop plant architecture and yield in 4 soybean. With the aim of elucidating the genetic basis of branch number, we 5 identified 10 consensus quantitative trait loci (QTLs) through preliminary mapping, 6 which were on chromosome A1, B2, C1, C2, D1a, D1b, F, L and N, explained 7 0.3-33.3% of the phenotypic variance. Of these, three QTLs were identical to 8 previously identified ones, whereas the other seven were novel. In addition, one major 9 QTL-qBN.C2 (R2=33.3%) was detected in all three environments and another new 10 major QTL-qBN.N (R2=19.6%) was detected in two environments (Taiyuan 2017 and 11 Taiyuan 2018), but only in Taiyuan. Thus, the QTL × environment interaction 12 analysis confirmed that QTL-qBN.N was strongly affected by the environment. We 13 compared the physical positions of the QTL intervals of the candidate genes 14 potentially involved in branching development, and five orthologous genes were 15 ultimately selected and related to the establishment of axillae meristem organization 16 and lateral organs, qBN.A1 (SoyZH13_05G177000.m1), qBN.C2 17 (SoyZH13_06G176500.m1, SoyZH13_06G185600.m1), and qBN.D1b-1 18 (SoyZH13_02G035400.m1, SoyZH13_02G070000.m3). The results of our study 19 reveal a complex and relatively complete genetic architecture and can serve as a basis 20 for the positional gene cloning of branch number in soybean. 21 3 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Introduction 2 Plant architecture is an extremely important role in plant yield, which can affect 3 light distribution in the canopy and photosynthesis. Modification of crop plant 4 architecture has been used to improve plant fitness and agricultural performance, and 5 these modifications are achieved through genetics and breeding [1-3]. Branching is a 6 major factor that affects plant architecture, together with plant height, main stem, leaf, 7 pod and others [2]. The number and distribution of branches determine the canopy 8 architecture, which influences light interception as well as lodging resistance and 9 ultimately seed yield [4]. Branch number is strongly dependent on aspects related to 10 the cultural practices and growth environment [5]. 11 Branch number is also the most complex trait and is very sensitive to the 12 environmental conditions. Because the environmental effects on branch number are so 13 prominent, there have been few studies on the genetics of this trait, although varietal 14 differences in branch number have been observed in the adaptation to row spacing in 15 accordance with its modest heritability observed in most studies [6, 7]. Two dominant 16 alleles at independent loci were found to be associated with a high-branch number 17 phenotype [8] but the loci and other genetic factors that determine branch number in 18 soybean remain unknown. However, branch number is difficult to improve efficiently 19 by traditional breeding methods and the genetic and especially the molecular 20 mechanism involved in branch number in soybean are poorly understood. 21 Previous studies have shown that branch number is controlled by multiple 4 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 quantitative trait loci (QTLs), and almost 93 branch number QTLs have been 2 identified from nearly 18 linkage mapping populations [9-20]. Interestingly, a few 3 QTLs on the C2 chromosome were found to be concentrated in a region (103-121cM) 4 derived from different parents and environments [4, 21-25]. It is indicated that this 5 region on the C2 chromosome is a hotspot for branch number in soybean. However, 6 only a few of these QTLs have been repeatedly detected, in accordance with the 7 modest heritability of branch number. In addition, almost all these branch number 8 QTLs were found to have a moderate effect. Therefore, these data suggest that the 9 existence of varietal differences in branch number among soybean cultivars and it is 10 difficult to narrow down these QTLs and identify the underlying candidate genes. 11 The objectives of the present study were to (a) identify the genetic mechanism 12 that controls branch number in soybean by performing quantitative trait locus (QTL) 13 analysis using F2 population derived from two soybean lines, C025 and JD18, that 14 have showed consistent significant differences in branch number in different 15 environments, to (b) dissect the relationship between major QTLs and the 16 environment, to (c) integrate QTLs associated with branch number in soybean using 17 meta-analysis and to (d) predict the potential candidate genes for further fine-mapping 18 and mechanism studies. 19 Materials and methods 20 Plant materials, field experiments and trait investigation 21 The F2 population included 109 individuals, and was derived from two soybean lines, 5 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 C025 (high branch number) and JD18 (low branch number). The F2 individuals were 2 planted in Hainan from Nov. 2016 to Feb. 2017 (code Hainan 2016), the F2:3 and F2:4 3 lines were planted in Taiyuan from May 2017 to Oct. 2017 (code Taiyuan 2017) and 4 May 2018 to Oct. 2018 (code Taiyuan 2018). The F2, F2:3 and F2:4 populations and 5 two parents were arranged in a randomized complete block design with two 6 replications. Each block contained two rows with a space of 50 cm between rows and 7 13.5 cm between individual plants. The seeds were sown by hand, and the field 8 management followed standard agriculture practices. In each block, 10 representative 9 individuals from the two rows were harvested by hand at maturity. The branch 10 number was measured based on a previously described method [4]. 11 SSR molecular marker analysis and linkage map construction 12 The SSR markers from the SoyBase database (https://soybase.org/) were used for 13 polymorphism screening between the two parents and used to genotype the F2 14 individuals. Leaf tissue was collected from seedlings of the parents and F2 populations. 15 Genomic DNA was extracted according to the CTAB method [26]. The PCR, 16 electrophoresis, and silver staining procedures were performed as described 17 previously [27]. 18 The genetic linkage map was constructed using the software JoinMap 4.1 19 (https://www.kyazma.nl/index.php/JoinMap/) with a threshold for goodness-of-fit ≤ 20 5, recombination frequency of < 0.4 and minimum logarithm of odds (LOD) score of 21 2.0. The genetic distances were measured based on the Kosambi function. To avoid 6 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.27.889287; this version posted December 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.