Mapping QTLs and association of differentially expressed gene transcripts for multiple agronomic traits under different nitrogen levels in sorghum

Gelli, Malleswari; Mitchell, Sharon E.; Liu, Kan; Clemente, Thomas E.; Weeks, Donald P.; Zhang, Chi; Holding, David R.; Dweikat, İsmail

doi:10.1186/s12870-015-0696-x

Cited by 60 publications

(54 citation statements)

References 81 publications

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“…Overlying of the DEG transcripts between parents and RIL bulks on to this co-localized region found candidate DEG transcripts associated with QTL, qBY-7 (Tables 5, 6). Of these, Gibberellin receptor GID1L2 and rotamase transcripts were abundant in CK60 and phospholipase A and ribosomal proteins L1p/L10e were abundant in San Chi San similar to China17 from earlier study [46]. On chromosome 8, a major QTL for biomass yield was detected under LN similar to earlier studies.…”

Section: Discussionsupporting

confidence: 81%

“…Transcripts encoding TFIIIC and seed storage 2S albumin were expressed higher in CK60 and senescence-related gene 1 was expressed higher in CK60 and in RIL bulk with low NUE. However, HSP70 had a higher expression in San Chi San similar to China17 [46]. In addition, a DW 2 transcript encoding multidrug resistance-associated protein-9 homolog showed higher transcript abundance in CK60, similar finding was observed in earlier study [46] and indicates this common DEG transcript may be involved in regulating plant height under N-stress in the seedlings (Table 5).…”

Section: Discussionsupporting

confidence: 78%

“…However, HSP70 had a higher expression in San Chi San similar to China17 [46]. In addition, a DW 2 transcript encoding multidrug resistance-associated protein-9 homolog showed higher transcript abundance in CK60, similar finding was observed in earlier study [46] and indicates this common DEG transcript may be involved in regulating plant height under N-stress in the seedlings (Table 5). Another candidate DEG transcript encoding mediator subunit 8 associated with qPH-6 , was abundant in sensitive genotype CK60 under N-stress.…”

Section: Discussionsupporting

confidence: 78%

“…In the corresponding region, a QTL cluster containing QTLs for chlorophyll content measured at flowering and maturity, days to anthesis detected under both N regimes, plant height, total biomass and grain yield were detected under normal N regime in our earlier study (Additional file 2) [46]. In this co-localized region, QTL for flowering time [90, 100], total seed weight [91], stay green [110, 111] and plant height [93] were detected earlier.…”

Section: Discussionmentioning

confidence: 98%

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Validation of QTL mapping and transcriptome profiling for identification of candidate genes associated with nitrogen stress tolerance in sorghum

et al. 2017

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BackgroundQuantitative trait loci (QTLs) detected in one mapping population may not be detected in other mapping populations at all the time. Therefore, before being used for marker assisted breeding, QTLs need to be validated in different environments and/or genetic backgrounds to rule out statistical anomalies. In this regard, we mapped the QTLs controlling various agronomic traits in a recombinant inbred line (RIL) population in response to Nitrogen (N) stress and validated these with the reported QTLs in our earlier study to find the stable and consistent QTLs across populations. Also, with Illumina RNA-sequencing we checked the differential expression of gene (DEG) transcripts between parents and pools of RILs with high and low nitrogen use efficiency (NUE) and overlaid these DEGs on to the common validated QTLs to find candidate genes associated with N-stress tolerance in sorghum.ResultsAn F7 RIL population derived from a cross between CK60 (N-stress sensitive) and San Chi San (N-stress tolerant) inbred sorghum lines was used to map QTLs for 11 agronomic traits tested under different N-levels. Composite interval mapping analysis detected a total of 32 QTLs for 11 agronomic traits. Validation of these QTLs revealed that of the detected, nine QTLs from this population were consistent with the reported QTLs in earlier study using CK60/China17 RIL population. The validated QTLs were located on chromosomes 1, 6, 7, 8, and 9. In addition, root transcriptomic profiling detected 55 and 20 differentially expressed gene (DEG) transcripts between parents and pools of RILs with high and low NUE respectively. Also, overlay of these DEG transcripts on to the validated QTLs found candidate genes transcripts for NUE and also showed the expected differential expression. For example, DEG transcripts encoding Lysine histidine transporter 1 (LHT1) had abundant expression in San Chi San and the tolerant RIL pool, whereas DEG transcripts encoding seed storage albumin, transcription factor IIIC (TFIIIC) and dwarfing gene (DW2) encoding multidrug resistance-associated protein-9 homolog showed abundant expression in CK60 parent, similar to earlier study.ConclusionsThe validated QTLs among different mapping populations would be the most reliable and stable QTLs across germplasm. The DEG transcripts found in the validated QTL regions will serve as future candidate genes for enhancing NUE in sorghum using molecular approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-017-1064-9) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 81%

Section: Discussionsupporting

confidence: 78%

Section: Discussionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 98%

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Validation of QTL mapping and transcriptome profiling for identification of candidate genes associated with nitrogen stress tolerance in sorghum

et al. 2017

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“…For sorghum, only the forward genetic approach using QTLs has been used to identify genes involved in NUE. Gelli et al (2014Gelli et al ( , 2016) used a combination of QTLs and transcriptional profiling to search for genes involved in NUE traits in 2 RIL populations (CK60 "low-NUE US line" x China17 "higher NUE Chinese line" and Ck60 x San Chi San "low-N tolerant Chinese line") evaluated under low (0 kg N.ha -1 ) and normal N (100 kg N. ha -1 ) conditions. The RNA-seq data showed that one QTL for NUE contained differentially expressed gene transcripts encoding ferredoxin-nitrite reductase (FNR), chloroplast localized serine/threonine-protein kinase (SNT7), and a SufE/NifU family protein.…”

Section: Genes Associated With Nuementioning

confidence: 99%

Genome wide analysis and allele mining of diverse sorghum genes involved in nitrogen use efficiency

Diatloff¹

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Nitrogen (N) is the most important plant nutrient and is the most commonly applied element to agricultural crops. In many cases nitrogen fertiliser is the main input cost for farmers, and in addition, is a major pollutant from agricultural activity. Most plants only take up 50% or less of the applied N, and most of the remainder is lost to leaching into ground water and waterways, or volatilised into the atmosphere. Hence, improving the nitrogen responsiveness of crops is crucial for food security and environmental sustainability, and breeding N use efficient (NUE) crops has to exploit genetic variation for this complex trait.In this thesis, reverse genetics was used to examine allelic variation in two key N metabolism genes. In silico analysis of the genomes of 44 genetically diverse sorghum genotypes identified a nitrate reductase and a glutamate synthase gene (NADH-GOGAT) that were under balancing selection in improved sorghum cultivars. It was hypothesised that these genes are a potential source of differences in NUE, and parents and progenies of nested association mapping populations were selected with different allelic combinations for these genes. Allelic variation was sourced from African (Macia) and Indian (ICSV754) genotypes that had been backcrossed into the Australian elite parent R931945-2-2. Nine genotypes with different allelic combinations were grown for 30 days in a glasshouse and supplied with continuous limiting (1 mM nitrate) or replete N (10 mM nitrate), or replete N for 27 days followed by three days N starvation prior to harvest. Biomass, N and nitrate contents were quantified together with gene expressions in leaves, stems and roots.Limiting N supply universally resulted in less shoot and root growth, increased root weight ratio, reduced tissue nitrate and N concentrations, and reduced NADH-GOGAT expression. None of the tested genotypes exceeded growth or NUE of elite parent R931945-2-2. This may indicate that the allelic combinations did not confer an advantage during early vegetative growth, or that selection in a modern plant breeding program has already optimised the allelic combinations for these loci. It is also noteworthy that plants were grown under controlled environment conditions, and field responses may have been somewhat different. It is also possible that any selective advantage of other allelic combinations may only have been apparent in plants grown to anthesis and/or grain maturity. Thus, the next steps for ascertaining potential effects on NUE include growing plants to maturity. It is concluded that reverse genetics that take advantage of rapidly expanding genomic databases contributes towards a systematic approach for developing N efficient crops.ii

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Genome‐wide association mapping of agronomic traits and grain characteristics in spring wheat under conventional and organic management systems

et al. 2022

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Previous genome‐wide association studies in Canadian spring wheat (Triticum aestivum L.) cultivars were based on consensus linkage maps of small population sizes. Here, we used a panel of 192 spring wheat cultivars widely used in western Canada to (a) explore the allelic variation and effects of six known genes and (b) identify genomic regions associated with eight agronomic traits and grain characteristics using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 map. The panel was evaluated for heading, maturity, plant height, lodging, grain yield, grain protein content, test weight, and kernel weight under four conventionally (high N) and three organically (low N) managed environments and genotyped with the wheat 90K single‐nucleotide polymorphism (SNP) array of which 23,342 SNPs were polymorphic. Using gene‐specific functional markers, the proportion of homozygous genotypes with favorable alleles was low for Fhb1 (7–8%), Rht‐D1 (14%), and Rht‐B1 (18%); moderate for Lr34/Yr18 (28–39%); and high for Glu‐A1 (78%) and Glu‐D1 (85%). We identified a total of 172 SNPs located at 94 genomic regions across 19 chromosomes of which 82 regions were associated with a single trait and 12 regions coincided with two to three traits. Twenty‐seven of the 94 regions (28%) were common between the conventional and organic managements systems; the remaining were management specific. Two of the identified regions on chromosome 5A (586.5–588.6 Mb) and 5B (575.8 Mb) coincided with the vernalization response Vrn‐A1 and Vrn‐B1 genes, respectively. The IWGSC RefSeq v2.0 physical positions presented here would serve as the basis for easily comparing independent discovery studies in the future.

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Mapping QTLs and association of differentially expressed gene transcripts for multiple agronomic traits under different nitrogen levels in sorghum

Cited by 60 publications

References 81 publications

Validation of QTL mapping and transcriptome profiling for identification of candidate genes associated with nitrogen stress tolerance in sorghum

Validation of QTL mapping and transcriptome profiling for identification of candidate genes associated with nitrogen stress tolerance in sorghum

Genome wide analysis and allele mining of diverse sorghum genes involved in nitrogen use efficiency

Genome‐wide association mapping of agronomic traits and grain characteristics in spring wheat under conventional and organic management systems

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