Tropentag 2021, hybrid conference September 15-17, 2021 Conference on International Research on Food Security, Natural Resource Management and Rural Development organised by the University of Hohenheim, Germany Fodder quality comparison in two sorghum populations under drought Vinutha K Somegowda1, 3, Prasad KVSV2, Jalaja Naravula3, Anilkumar Vemula1, Sivasubramani S1, Abhishek Rathore1, Chris S Jones2, Rajeev Gupta1 and Santosh P Deshpande1* 1 International Crops Research Institute for the Semi-arid Tropics (ICRISAT)-HQ, Patancheru-502324, TS, India, 2 International Livestock Research Institute (ILRI), ICRISAT Campus, Patancheru-502324, TS, India, 3 VFSTR, Guntur, India *Corresponding author Email: s.deshpande@cgiar.org Abstract Digestibility and lignin content are important in determining feed quality and plant fitness, with higher lignin content reducing digestibility and vice versa. Reports suggest that a variation of 5% in fodder digestibility between poor and premium fodder result in a 20% price variation. Sorghum is gaining importance as a food, feed, and fuel crop; it has similar feed quality to maize, which demands high nutrient and water availability. Additionally, drought in the semi- arid tropics is also affecting feed quality, and sorghum is known to encounter drought mainly in the post rainy season. Therefore, two sorghum populations, a recombinant inbred line (RIL) population (n=320) and reference set (n=130) were evaluated under drought for fodder qualities. In this study, irrigation was withheld at the booting stage for the stress plots, whereas the control plots were fully irrigated, all other crop management practices were performed equally. The dry weight (DW) was recorded at maturity, and the fodder was subjected to near-infrared spectroscopy (NIRS) scanning to record: nitrogen content on a dry matter basis (NDM); neutral and acid detergent fibre (NDF and ADF); acid detergent lignin (ADL); metabolizable energy (ME) and; in vitro organic matter digestibility (IVOMD). Significant variation was recorded across treatments and for all traits in the RIL population. Significant genotypic variation and genotype by treatment variation were recorded for the reference set in 2016 only. Pearson’s correlation was pooled across years and treatments for both populations. DW and IVOMD showed negative correlations with NDF and ADL, while positive correlations were observed between DW, ME, and IVOMD in the RIL population. However, in the reference set, there was no strong positive or negative correlation between DW, ME, and IVOMD. Genotyping by sequencing (GBS) analysis was used to perform quantitative trait loci (QTL) estimation for the RIL population, while a genome-wide association study (GWAS) was performed for the reference set. A total of 98 and 47 associated genes were extracted from Phytozome v12.1.6 for the RIL and reference populations, respectively. Several genes belong to pathways that may help explain a causal functionality with the associated traits. These results will help select these traits in plant breeding programs and help achieve greater genetic gains at a faster pace. Key word: Sorghum, drought, fodder, digestibility Background Sorghum is a failsafe crop in semi-arid and tropical regions as it has innate drought tolerance coupled with high water use efficiency and photosynthetic efficiency (Sunoj et al., 2020). The grain is used as food and feed, and the crop residue is used as feed for livestock. Fodder digestibility and lignin content determine the feed quality and plant fitness, respectively. However these traits show a high trade-off. A 5% variation in fodder digestibility is reported to result in a 20% price variation for sorghum fodder (Fig. 1). Thus, this trait has a high economic impact and affects the cost and productivity of livestock (Blummel et al., 2013). Methods Two sorghum populations (RIL and Reference set) were evaluated under terminal drought stress by withholding irrigation at the boot leaf stage. Fodder dry weight (DW) was recorded at maturity and the fodder was subjected to near-infrared spectroscopy (NIRS) to record nitrogen content on a dry matter basis (NDM); neutral and acid detergent fibre (NDF and ADF); acid detergent lignin (ADL); metabolizable energy (ME) and; in vitro organic matter digestibility (IVOMD). ICIM software for QTL mapping and rMVP (R package) for GWAS were used to identify genomic regions for the traits under study. Genes were blasted against the reference genome, and Zea mays in Phytozome and plotted in Circos (Krzywinski et al., 2009). Fig 1: Relation between stover price and in vitro digestibility in sorghum fodder Results Significant genotypic variation was observed for both years; genotype by treatment significance was observed in the Reference set alone in year 2016. The second-year showed no significant variation across genotypes or treatments. The control treatment across years had no significant variation for fodder quality in the current study, but stress in the RIL population had a significant effect on all of the traits under study (Table 1). Table 1: ANOVA for fodder quality traits across years and treatments for the RIL population and Reference set Across years Across Treatments Year 2016 2017 Control Stress Traits σg2 σgxt2 σg2 σgxt2 σg2 σg2 RIL population DW 13035** 5471** 3395** 2057** 0.3* 2202* NDM 0.0007* 0.003934 0 0.001951 0.01 0.01* NDF 0.784 0.979 0.03 0.388 -0.01 0.69** ADF 0.309 1.074 0.06 0.125 -0.07 0.49** ADL 0.007* 0.02635 0.0018 0.0049 0.01 0.01* ME 0.007* 0.02703 0 0.00329 -0.01 0.02** IVOMD 0.253* 0.965 0.159 0.148* -0.11 0.38** Reference set DW 12115 12231 700.81 2640.15* 23.86 451 NDM 0.000469 0.001** 0.00048 0.004** -0.00056 -0.00014 NDF 1.56* 2.40** -0.83 0.64 -0.03 -1.35 ADF 1.502* 1.32* -0.35 0.06 -0.39 -0.62 ADL 0.038** 0.019* 0.0003 -0.0019 0.0088 -0.0083 ME 0.045** 0.038** 0.0154 -0.0234 -0.0138 -0.0146 IVOMD 1.57** 1.48** 0.15 0.08 -0.482 -0.555 σg2 = genotypic variance; σgxt2 genotypicx treatment variance= * Significant at P < 0.05, ** Significant at P < 0.01 Pearson’s correlation across years and treatments for DW and IVOMD showed negative correlations with NDF and ADL (Table 2). Six genes were mapped for IVOMD, on chromosomes 1, 2, 5, 7, 8, and 9, Sobic.001G530300 and Sobic.008G054500 mapped under drought stress, and three genes each were identified under drought stress on chromosome 1 and 2 for IVOMD. Sobic.001G354800, which is associated with seed-dry grain maturity was mapped against ADL, IVOMD, and ME under drought stress (Table 3). Table 2: Correlation between fodder quality traits for both populations under study. Pop Trait NDF ADL ME IVOMD DW 0.00 0.04 0.07 0.07 NDF 0.60** -0.71** -0.78** REF ADL -0.75** -0.75** ME 0.97** DW -0.07 -0.14* 0.28** 0.19** NDF 0.60** -0.70** -0.75** RIL ADL -0.79** -0.79** ME 0.97** Table 3: Genes identified for DW and IVOMD using significant positions from QTL mapping and GWAS Pop Trait Chr Gene ID Pop Trait Chr Gene ID REF IVOMD_C_17.FarmCPU Chr01 Sobic.001G180700 REF DW_S_17.FarmCPU Chr01 Sobic.001G279000 REF IVOMD_S.FarmCPU Chr01 Sobic.001G530300 REF DW_S_17.FarmCPU Chr02 Sobic.002G249600 REF IVOMD_C_17.FarmCPU Chr02 Sobic.002G231800 REF DW_S_17.FarmCPU Chr04 Sobic.004G046900 REF IVOMD_C_17.FarmCPU Chr07 Sobic.007G023400 REF DW_S_17.FarmCPU Chr04 Sobic.004G046900 REF IVOMD_S_16.FarmCPU Chr08 Sobic.008G054500 REF DW_S_17.FarmCPU Chr05 Sobic.005G196500 REF IVOMD_S.FarmCPU Chr09 Sobic.009G217500 REF DW_S_17.FarmCPU Chr05 Sobic.005G196500 RIL q_IVOMD_16_S_1_1 Chr01 Sobic.001G354800 REF DW_S_17.FarmCPU Chr08 Sobic.008G116300 RIL q_IVOMD_17_S_1_2 Chr01 Sobic.001G463900 REF DW_C_17.FarmCPU Chr09 Sobic.009G206700 RIL q_IVOMD_17_S_1_3 Chr01 Sobic.001G463900 RIL q_DW_17_S_2_1 Chr02 Sobic.002G073700 RIL q_IVOMD_17_S_1_1 Chr01 Sobic.001G472301 RIL q_DW_17_C_3_1 Chr03 Sobic.003G280500 RIL q_IVOMD_S_2_1 Chr02 Sobic.002G222500 RIL q_DW_17_S_3_1 Chr03 Sobic.003G280500 RIL q_IVOMD_16_S_2_1 Chr02 Sobic.002G335900 RIL q_DW_C_3_1 Chr03 Sobic.003G291700 RIL q_IVOMD_S_2_2 Chr02 Sobic.002G350600 RIL q_DW_C_3_2 Chr03 Sobic.003G407800 RIL q_IVOMD_16_S_4_1 Chr04 Sobic.004G180200 RIL q_DW_17_S_5_1 Chr05 Sobic.005G010900 RIL q_IVOMD_16_C_5_1 Chr05 Sobic.005G153033 RIL q_DW_16_C_7_1 Chr07 Sobic.007G099700 RIL q_IVOMD_C_5_1 Chr05 Sobic.005G172400 RIL q_DW_S_7_1 Chr07 Sobic.007G099700 RIL q_IVOMD_17_C_6_1 Chr06 Sobic.006G014700 RIL q_DW_17_C_7_1 Chr07 Sobic.007G103600 RIL q_IVOMD_16_C_7_1 Chr07 Sobic.007G098800 RIL q_DW_C_7_2 Chr07 Sobic.007G136300 RIL q_IVOMD_S_8_1 Chr08 Sobic.008G026400 RIL q_DW_17_S_7_1 Chr07 Sobic.007G145600 RIL q_IVOMD_16_C_10_1 Chr10 Sobic.010G107100 RIL q_DW_16_C_7_2 Chr07 Sobic.007G146200 RIL q_IVOMD_C_10_1 Chr10 Sobic.010G139600 RIL q_DW_16_C_7_3 Chr07 Sobic.007G153900 RIL q_IVOMD_16_S_10_1 Chr10 Sobic.010G229000 RIL q_DW_17_C_10_1 Chr10 Sobic.010G229000 The gene Sobic.007G023400, mapped to IVOMD under control conditions in the Reference set, is linked to the super pathway of cytosolic glycolysis (plants), pyruvate dehydrogenase and TCA cycle, glyoxylate cycle and fatty acid degradation and aerobic respiration I, II and III. ME for the Reference set under stress was associated with Sobic.003G282600, a gene linked to homogalacturonan biosynthesis which contributes to plant growth and development and cell wall structure. Dry weight in the RIL population was associated with Sobic.007G145600 and Sobic.007G146200, which are involved in multiple pathways associated with cell wall-bound phenolic acids that play a major role in plant defense against pathogens, mapped on chromosome 7. ADL under stress in the RIL population was linked to Sobic.009G148200 on chromosome 9, associated with the pyrimidine and purine deoxyribonucleoside salvage pathway which is notably triggered under stress. These results will help in trait manipulation during plant breeding practices and to achieve genetic gains at a faster pace. In Fig. 2, genes in the genomic regions associated with DW, IVOMD, and combined are indicated, while the unmarked regions contain genes associated with DW. The genes Sobic.010G229000 and Sobic.002G335900 were associated with both key traits in the RIL population, while no such gene associations were identified in the Reference set. Dry weight in the RIL population was associated with Sobic.007G145600 and Sobic.007G146200, involved in the production of cell wall-bound phenolic acids that play a major role in defense against pathogens, all on chromosome 7. ME in the Reference set under stress was associated with Sobic.003G282600, a gene linked to homogalacturonan biosynthesis that contributes to plant growth and development and cell wall structure. The syntenic relation between sorghum and maize showed that Sobic.007G023400, a gene associated the IVOMD, shared 97.2 % similarity with the maize gene GRMZM2G134134_T02, while Sobic.009G206700, associated with DW, shared 98.6% similarity with maize gene GRMZM2G319747_T02. Fig 2: Synteny between sorghum RIL population (left) and Reference Set (right) with Zea mays Conclusion The concurrent improvement of fodder dry weight and IVOMD in sorghum crop improvement is possible. A gene, Sobic.001G356000, was linked to lignin and metabolizable energy traits under stress conditions; this can be key to understanding their behavior and for the use of genetic tools to reduce the negative impacts observed. While the gene Sobic.001G463900 was mapped to in vitro organic matter digestibility, further fine mapping for IVOMD on chromosomes 1 and 2 will improve the opportunity for trait dissection. Reference Blummel, M., Homann-Kee Tui, S., Valbuena, D., Duncan, A. and Herrero, M., 2013. Biomass in crop-livestock systems in the context of the livestock revolution. Secheresse, 24, pp.330-339. Fracasso, A., Trindade, L.M. and Amaducci, S., 2016. Drought stress tolerance strategies revealed by RNA-Seq in two sorghum genotypes with contrasting WUE. 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