- In this study we have analysed a collection of japonica varieties adapted to temperate regions to perform association studies with traits of high agronomical interest such as heading date, plant height, number of panicles, panicle length and number of grains per panicle.. - Results: We have performed a genome wide association study using a panel of 1713 SNPs that, based on previous linkage disequilibrium estimations, provides a full coverage of the whole genome. - We have found a total of 43 SNPs associated with variations in the different traits. - The inspection of the vicinity of these markers also revealed a set of genes associated with physiological functions strongly linked to agronomic traits. - We also detected novel associated sites with heading date, panicle length and number of grain per panicle.. - Some of these markers co-localized with already known genes or QTLs, but the association also provided novel molecular markers that can be of help to elucidate the complicated genetic mechanism controlling important agronomic traits, as flowering regulation in the non-dependent photoperiod pathway. - One of the main challenges for rice breeders is to develop high yielding cultivars. - It is also desirable to increase the in- comes of farmers and the economic profitability of the crop.. - One of the barriers that rice over- came to reach temperate regions was the difference in day length that became one of the main determinants of plant adaptation to new areas [10, 11]. - and contributing to the constriction of the genetic pool of cultivars and the emergence of different subpopulations.. - Full list of author information is available at the end of the article. - 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0. - The characterization of the genetic bases of this di- versity will allow the identification of loci that underlie this phenotypic variation, especially those concerning agronomic traits, with direct application to breeding.. - The number of grains that a plant may pro- duce is also determinant and it can vary according to the number of grains per panicle and the number of panicles, which are quantitative traits [34]. - Panicle num- ber is a difficult trait to study as it relays not only on genetic factors but also on environmental and growth conditions as the density of plants in the fields. - Taking advantage of the diversity of rice, based on his- toric recombination events and linkage disequilibrium across the genome, genome wide association studies (GWAS) have recently become popular to identify QTLs in plant populations. - Studies on panicle architecture, number of spikelets, grain size or heading date have been reported [1, 23]. - Still, the genetic basis of the phenotypic variations among tem- perate cultivars needs further analysis.. - The study of the. - population structure and the genetic relationship among the cultivars evidenced a strong substructure in the tem- perate rice collection, predominantly based on grain type and the origin of the cultivars [24]. - Heading date (DH) of the varieties in the collection ranged from108 to 47 days (Table 1). - Traits presented large phenotypic variation (Table 1) with coefficient of variation ranging from 0.12, in the case of heading time, to 0.41 in the number of panicles. - Table 1 Phenotypic variations of the studied traits. - Panicle length (cm . - Number of panicles . - Estimation of mean, minimum, maximum for days, standard deviation (SD) and coefficient of variation (CV) to heading, height, panicle length, number of grains per panicle, number of panicles and grain weight from all experiments.. - As some of the cultivars displayed dehiscence, the number of grains per panicle (GN) was scored in two batches of plants grown in a greenhouse under natural day conditions before they reached full maturity when data was collected.. - Panicle length was no significantly correlated with number of grains. - The first principal component (PC1), which accounted for 45.9% of the variance, separated cultivars according to panicle length, number of grains per panicle. - (a) heading date, (b) plant height, (c) number of panicles, (d) panicle length and (e) number of grains per panicle. - Histograms show data of all plants used in the assays. - panicle length . - number of panicles − 0.30. - On the other side, PC2, explaining 20.1% of the variance distinguished cultivars according to number of panicles.. - To detect associations between SNP markers and varia- tions in the evaluated traits in the 193 japonica cultivars in the collection, we used the genotypic dataset gener- ated in a previous study consisting in a panel of 1713 SNPs uniformly distributed across the whole genome with a mean distance of 215 Kb between each other [24]. - According to the linkage disequilibrium estimated for this collection, 368 kb in average, [24] and the rice genome size, 321 Mb [13] the number of SNPs in the panel is adequate to detect associations across the whole genome. - It has been suggested that in the case of rice, MLM reduces the number of false positive but in contrast increases the number of false negatives, overcompensating for popula- tion structure and relatedness [43]. - QQ plots for heading date, panicle length and number of grains indicated that the model was well fitted to the data. - We looked for functional genes related to the traits in the. - The proportion of the variance explained by the first (PC1) and second principal (PC2) components is indicated in parenthesis. - PN, number of panicles. - PL, panicle length and GN, number of grains per panicle. - vicinity of the SNP in an extended the interval of 368 Kb according to the estimated LD decay. - Panicle length showed the highest number of associ- ated markers, 14 markers that were distributed across 9 chromosomes (Fig. - Allele A at PL-8 pos- ition was present in 17 cultivars of the corresponding 20 with the shortest panicles. - 3 Genome-wide association mapping of the traits in this study. - Manhattan and quantile-quantile plots for (a) plant height, (b) heading date, (c) panicle length, (d) number of grains per panicle and (e) number of panicles. - was present in 17 of the 20 cultivars with the longest panicles (Additional file 4: Table S2). - In a similar man- ner, allele G at PL-9, in the same locus that PL-8, was found in 17 of the 20 cultivars with the shortest panicles;. - PL-13, asso- ciated with panicle in chromosome 9, co-localised with LAGGING GROWTH AND DEVELOPMENT 1 (LGD1) implicated in growth and in the formation of panicle. - We detected 16 significant markers associated with the number of grains per panicle. - DEP2 is involved in the elongation of rachis and primary. - and secondary branches in the panicles and plants carry- ing mutations in DEP2 exhibited smaller panicles but also reduced height [16]. - High summer temperatures, accompanied by higher number of hours of light with good solar radi- ation, constituted an excellent growth environment allow- ing expansion and originating wide diversity that is reflected in different agronomic traits, as it is shown in this study. - 4 Physical map position of significant associated SNPs detected in the GWAS. - The majority of the analyses that have been previously reported on the identification of variations in genes of agronomic interest have been performed compar- ing japonica and indica cultivars. - The analysis performed in this study has taken into account the structure of the population and relatedness among cultivars, two factors that may led to false associations in GWAS. - The analyses performed considering both Q matrix gave similar results, and most of the detected SNPs were identified using any of the both possibilities in the case of height, panicle length and panicle number (Table 3). - Control of flowering by photoperiod has supposedly been one of the main factors that contributed to the expansion of rice through regions with long day conditions. - It is also a key factor in the adaptation of cultivars to each local condition and it is determined by the latitude where they are grown.. - Winter cold temperatures in temperate cli- mate regions constrain rice cultivation, preventing two harvests per year even in the case of early flowering. - But shortening the growth duration in a few days is still desir- able by farmers as it increases crop security by reducing the risk of pathogen attacks or weather adverse conditions like storms at the end of the growing season, frequent in. - These au- thors suggested the possibility that qDTH6 may be Hd1, a key regulatory gene in the photoperiodic control of flower- ing [37]. - It has been re- ported that the allelic heterogeneity and complex genome structure of the Hd1 causes spurious associations and a shift in the genomic position of the signal corresponding to Hd1 has been observed in some association studies [36].. - We have previously investigated the Hd1 structure in 52 cultivars included in the present collection and found 12 different variants that include non-functional alleles of Hd1 [20]. - However, previous studies have concluded that HD1 is not involved in the regulation of flowering under long day conditions, as many cultivars grown in these conditions carried both functional and non-functional allele of HD1 independently of the geographical origin of the cultivars [20]. - The possibility of the occurrence of another factor in- volved in flowering in the immediacy to Hd1 should not be discarded and it needs further investigation. - No significant associated markers with heading date were found in the im- mediacy of Hd3a or RFT located in chromosome 6.. - In these sense, DH-7 and DH-8, both in the same loci in chromosome 10, appeared to be good candidates as the difference in heading date of cultivars carrying one or the other allele is 7 and 5 days respectively (Additional file 4:. - respectively of the explained variance (Table 3). - We didn’t find any functionally characterized gene in the vicinity of 7 of these loci and we could con- siderer that they represent novel associated sites with panicle length. - Some of the detected SNPs were close to genes that participate in panicle elongation but that also affect other parts of the plant. - OsEBS, at 0.9 Mb of distance from PL-10, produces higher spikelet number in the panicles, leading to an increase in total grain yield although also affects plant height and leaf size [4]. - On the other side, PL-6 localized close to rice panicle 3 (rip-3), coding for a putative α -tubulin protein, which expression was observed in all the repro- ductive organs of rice panicle, but not in other parts of the plant. - Interestingly, rip-3 acts, supposedly, as sup- pressor of panicle elongation in the regions of high growth and in periods of water deficit [27]. - Panicle length is often associated with yield as long panicles may produce higher number of spikelets and, thus, higher number of grains [17]. - But in our collection, no correl- ation could be found between panicle length and the number of grains per panicle (Table 2). - This is in agree- ment with the fact that no significant markers were de- tected in common when analysing both panicle length and number of grain per panicle.. - Height and heading time were measured in the field.. - The number of grains per panicle was measured in three different panicles per plant from plants grown in the greenhouse.. - For grain number regression was performed between plants at different sides of the green house.. - cultivated under long day conditions after removing SNP not present in at least 75% of varieties of the rice core pool, or showing a MAF lower than 5%. - 10 − 3 due to the effectivity of the use of MLM with correction to avoid spurious associations. - in a search for QTLs in the same trait category.. - Mean values of height, days to heading, panicle length, number of panicles and grains per panicle from the different assays in both locations. - Boxplot showing the distribution of data scored for days to heading, height, number of panicles and panicle length in both locations, Copsemar and Malta, during 2015 and 2016.. - Number of alleles carried by the 20 plants with the highest and the lowest value for each trait. - Mean phenotypic values of cultivars carrying different alleles in the significant associated markers. - Proportion of the total and cumulative proportion of each principal component. - GN: Number of grains per panicle. - PL: Panicle length;. - PN: Number of panicles. - This work was supported by the INNPACTO program of the Ministerio de Economía y Competitividad, (grant IPT and by the Insti- tuto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) (grant RTA C03 – 00). - JLR performed GWAS, analysis of the population structure and phenotyping. - The commercial affiliation of one of the authors (L.M.) does not alter our adherence to BMC policies on sharing data and materials.. - Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data.. - Hd3a, a rice ortholog of the Arabidopsis FT gene, promotes transition to flowering downstream of Hd1 under short-day conditions. - Combining image analysis, genome wide association studies and different field trials to reveal stable genetic regions related to panicle architecture and the number of Spikelets per panicle in Rice.. - A new GA-insensitive Semidwarf mutant of Rice (Oryza sativa L.) with a missense mutation in the SDG Gene. - Over-expression of the rice LRK1 gene improves quantitative yield components
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