Evaluation on the germplasm of maize (Zea mays L.) landraces from southwest China.

A Comparative Analysis of B Chromosomes and Genetic Diversity in Maize ( Zea mays L.) Landraces from Southwest China

Genetic Diversity of Maize ( Zea mays L.) Landraces from Southwest China Based on SSR Data

The maize landraces in the North East Himalayan (NEH) region in India, especially in the Sikkim state, are morphologically highly diverse. The present study provides details of phenotypic and molecular characterization of a set of 48 selected maize landrace accessions, including the 'Sikkim Primitives' which have a unique habit of prolificacy (5-9 ears on a single stalk). Multi-location phenotypic evaluation of these 48 accessions revealed significant genetic variability for grain yield and its components, leading to identification of several promising accessions. Cluster analysis and PCA using nine morpho-agronomic characters clearly separated 'Sikkim Primitives' from the rest of the accessions. PCA revealed two principal components describing 90% of the total variation, with hundred kernel weight, ear length, ear diameter, number of kernels per ear and flowering behaviour forming the most discriminatory traits. The accessions were genotyped using 42 microsatellite or simple sequence repeat (SSR) markers using a 'population bulk DNA fingerprinting strategy', with allele resolution using an automated DNA Sequencer. The study revealed a high mean number of alleles per SSR locus (13.0) and high Polymorphism Information Content (PIC) value of 0.60. The analysis also led to identification of 163 private/unique alleles, differentiating 44 out of 48 accessions. Six highly frequent SSR alleles were detected at different loci (phi014, phi062, phi090, umc1266, umc1367 and umc2250) with individual frequencies >/=0.75. Some of these SSR loci were reported to tag specific genes/QTL for some important traits, indicating that chromosomal regions harboring these SSR alleles were not selectively neutral. Cluster analysis using Rogers' genetic distance also revealed distinct genetic identity of the 'Sikkim Primitives' from the rest of the accessions in India, including Sikkim. Mantel's test revealed significant and positive correlation between the phenotypic and molecular genetic dissimilarity matrices. The study was the first to portray the patterns of phenotypic and molecular diversity in the maize landraces from the NEH region in India.

Maize (Zea mays L.) landraces in the northern Guinea savanna and Sudan savanna in West and Central Africa appear to have some drought-adaptive traits. This study was initiated to assess the level of improvement in yield potential and other agronomic traits achieved under drought stress (DS) and in multiple locations (ML) after introgression of alleles from maize landraces into an elite maize variety (AK9443-DMRSR) via backcrossing. Six backcross (BC) populations together with recurrent parent (AK9443-DMRSR), a commercial hybrid (Oba Super-II), and an improved variety (TZLCOMP4C1) were evaluated under controlled DS and full irrigation (FI) during the dry seasons of 1999 and 2000, as well as in seven ML trials. No significant differences were observed among genotypes for grain yield and most of the traits measured under DS and FI. Significant differences were recorded among genotypes for grain yield and other agronomic traits measured in ML and across 11 environments. Drought stress reduced grain yields of the BC1F2 populations by 64% and recurrent parent by 71%. In ML trials, at least half of the populations were better than recurrent parent. The top three BC1F2 populations produced more grains than the recurrent parent (258–360 kg/ha) and Oba Super-II (555–657 kg/ha) with introgression of only 25% genome of the landraces. We concluded that backcross procedure was able to transfer a quantitative trait of grain yield of an elite recurrent parent into maize landraces. Additional backcross generations are needed for improved performance of the BC1F2 populations in drought-prone environments.

Article Details: Received: 2020-06-19 | Accepted: 2020-08-05 | Available online: 2021-03-31 https://doi.org/10.15414/afz.2021.24.01.16-24 The breeding studies targeted to develop high yielding varieties in maize have led to a decrease in genetic variation in secondary biochemical components. Local maize landraces are important genetic sources for these components. The objective of this study was to examine the genetic variation for phytic acid and total phenolic compounds within 192 Turkish maize landraces. The plant material was grown during the summer season of 2017 in Çanakkale, with the inclusion of 7 check hybrids. The field trial used an Augmented Experimental Design, with 6 blocks, each one containing 32 landraces and 7 check hybrids. Phytic acid and total phenolics were detected spectrophotometrically in the seeds of landraces propagated by bulk pollination. The data were subjected to analysis of variance and some genetic estimations (coefficients of variation, heritability, genetic advance) were calculated for the observed traits. Results of data analysis suggest that there is a considerable genetic variation among the investigated genetic materials. The phytic acid content was found between 0.82–4.87 mg g-1 and the total phenolic content was between 0.03–1.99%. For both traits, genetic variation in local maize landraces was observed to be wider than check varieties. The promising materials among landraces may have potential use in the future breeding programs for manipulating the levels of phytic acid and phenolic compounds. According to the calculations made for the inheritance of the traits, it was determined that the heritability in phytic acid content was higher (56.2%) than those for the total phenolics. Genetic gain calculations showed that genetic improvement can be achieved by selection for both investigated traits. Keywords: phytate, antinutrients, phenolic acids, Zea mays , genetic conservation ABBASSIAN, A. (2006). Maize: International market profile. Food and Agriculture Organization of the United Nations, pp. 1–37. ARAVIND, J. et al. (2019). Augmented RCBD: Analysis of Augmented Randomized Complete Block Designs. R package version 0.1.1.9000. BURTON, G.W. (1951). Quantitative inheritance in pearl millet ( Pennisetum glaucum ). Agronomy Journal, 43(9), 409–417. BURTON, G.W. (1952). Qualitative inheritance in grasses. Proceedings of the 6th International Grassland Congress. Pennsylvania State College, pp. 17–23. CARVALHO, I.R. et al. (2018). Heterosis and genetic parameters for yield and nutritional components in half-sibling maize progenies. Genetics and Molecular Research, 17(4), gmr18024. CHANDANA, A.S et al. (2018). Genetic variability and correlation studies of yield and phytic acid in F2 populations of maize ( Zea mays L.). Electronic Journal of Plant Breeding, 9(4), 1469–1475. CHIANGMAI, P.N. et al. (2012). Screening of phytic acid and inorganic phosphorus contents in corn inbred lines and f1 hybrids in tropical environment. Maydica, 56(4), 331–339. CÖMERTPAY, G. et al. (2016). Genetic variation for biofortifying the maize grain. Turkish Journal of Agriculture – Food Science and Technology, 4(8), 684–691. CROMWELL, G.L. and COFFEY, R.D. (1991). Phosphorus-a key essential nutrient, yet a possible major pollutant-its central role in animal nutrition. Biotechnology in the Feed Industry, 1(1), 133–145. DA ROSA, T.C. et al. (2020). Mixed models and multivariate approach applied to maize breeding: a useful tool for biofortification. Australian Journal of Crop Science, 14(2), 213–220. DETURK, E.E. et al. (1933). Chemical transformations of phosphorus in the growing corn plant with results on two first generation crosses. Journal of Agricultural Research, 46(2), 121–141. DRAGIČEVIĆ, V. et al. (2010). The variation of phytic and inorganic phosphorus in leaves and grain in maize populations. Genetika, 42(1), 555–563. EARLEY, E.B. and DE TURK, E.E. (1944). Time and rate of synthesis of phytin in corn grain during the reproductive period. Journal of American Society of Agronomy, 36(1), 803–814. FRANK, M.Y. et al. (2016). A method of estimating broad-sense heritability for quantitative traits in the type 2 modified augmented design. Journal of Plant Breeding and Crop Science, 8(11), 257–272. FEDERER, W.T. (1956). Augmented (or hoonuiaku) designs. The Hawaiian Planters’ Record, LV(2), 191–208. FEDERER, W.T. (1961). Augmented designs with one-way elimination of heterogeneity. Biometrics, 17(2), 447–473. GALICIA, L. et al. (2009). Laboratory protocols 2008. Maize nutrition quality and plant tissue analysis laboratory. CIMMYT, 1–42. GÜLEŞÇİ, N. and AYGÜL, İ. (2016). Located in antioxidant nutrition and phenolic substances containing cookies. Gümüşhane University Journal of Health Sciences, 5(1), 109–129. HEINONEN, I. M. et al. (1998). Antioxidant activity of berry phenolics on human low-density lipoprotein and liposome oxidation. Journal of Agricultural and Food Chemistry, 46(10), 4107–4112. JACELA, J.Y. et al. (2010). Feed additives for swine: fact sheets-prebiotics and probiotics and phytogenics. Kansas Agricultural Experiment Station Research Reports, 18(3), 132–136. JOHNSON, HW, et al. (1955) Estimates of genetic and environmental variability in soybeans. Agronomy Journal, 47(7), 314–318. KAHRIMAN, F. et al. (2020). Analysis of secondary biochemical components in maize flour samples by NIR (near infrared reflectance) spectroscopy. Journal of Food Measurement and Characterization. https://doi.org/10.1007/s11694-020-00479-0 KAHRIMAN, F. et al. (2020). Comparison of colorimetric methods for determination of phytic acid content in raw and oil extracted flour samples of maize. Journal of Food Composition and Analysis, 86(1), 103380. KIZILGEÇİ F. et al. (2018). Evaluation of Turkish maize landraces through observing their yield and agro-morphological traits for genetic improvement of new maize cultivars. Acta fytotechn zootechn, 21(2), 31–43. LOPEZ-MARTINEZ, L.X. et al. (2009). Antioxidant activity, phenolic compounds and anthocyanins content of eighteen strains of mexican maize. LWT-Food Science and Technology, 42(6), 1187–1192. LUGO, D.A.U. et al. (2015). Total phenolics, total anthocyanins and antioxidant capacity of native and elite blue maize hybrids ( Zea mays L.). CyTA – Journal of Food, 13(1), 336–339. LUSH, J.L. (1940). Intra-sire correlations or regressions of offspring on dam as a method of estimating heritability of characteristics. Proceedings of the American Society of Animal Nutrition, pp. 293–301. MAHAN, A.L. et al. (2013). Combining ability for total phenols and secondary traits in a diverse set of colored (red, blue, and purple) maize. Crop Science, 53(4), 1248–1255. NICHENAMETLA, S.N. et al. (2006). A review of the effects and mechanisms of polyphenolics in cancer. Critical Reviews in Food Science and Nutrition, 46(1), 161–183. ÖNER, F. and GÜLÜMSER, A. (2014) Determination of some agronomıcal characteristics of local flint corn ( Zea mays L. indurata) genotypes in the black sea region of Turkey. Türk Tarım ve Doğa Bilimleri, 7(7), 1800–1804. ÖZKAYA, B. et al. (2013). Effects of yeast types on phytic acid content of traditional corn bread. The 2nd International Symposium on Traditional Foods from Adriatic to Caucasus, Macedonia. PURIFICACION, M.V. et al. (2018). Nutritional properties of philippine farmer-bred maize varieties. Philippine Journal of Crop Science (PJCS), 43(3), 35–46. R Core Team. (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/ RABOY, V. et al. (2000). Origin and seed phenotype of maize low phytic acid 1–1 and low phytic acid 2–1. Plant Physiology, 124(1), 355–368. RABOY, V. et al. (2017). Evaluation of simple and inexpensive high-throughput methods for phytic acid determination. Journal of the American Oil Chemists‘ Society, 94(1), 353–362. RECORD, I.R. et al. (2001). Changes in plasma antioxidant status following consumption of diets high or low in fruit and vegetables or following dietary supplementation with an antioxidant mixture. British Journal of Nutrition, 85(4), 459–464. ROBINSON, H.F. (1966) Quantitative genetics in relation to breeding on centennial of Mendelism. Indian Journal of Genetics and Plant Breeding, 26, 171–187. SHI, J. et al. (2003). The maize low-phytic acid mutant lpa2 is caused by mutation in an inositol phosphate kinase gene. Plant Physiology, 131(2), 507–515. SIVASUBRAMANIAM, S. and MADHAVAMENON, P. (1973). Genotypic and phenotypic variability in rice. The Madras Agricultural Journal, 60(9–13), 1093–1096. TERAO, J. (1989). Antioxidant activity of β‐carotene‐related carotenoids in solution. Lipids, 24(7), 659–661. The Maize Program. (1999). Development, maintenance, and seed multiplication of open-pollinated maize varieties (2nd ed.). Mexico, D.F.: CIMMYT. ÜNLÜ, E. et al. (2018). Diversity among Turkish maize landraces based on protein band analyses and kernel biochemical properties. Journal of Crop Improvement, 32(1), 75–187. VELÁSQUEZ-LADINO, Y. et al. (2016). Chemical profiling combined with multivariate analysis of unfractionated kernel-derived extracts of maize ( Zea mays L.) Landraces from Central Colombia. Emirates Journal of Food and Agriculture, 28(1), 713–724. ŽILIĆ, S. et al. (2012). Phenolic compounds, carotenoids, anthocyanins, and antioxidant capacity of colored maize ( Zea mays L.) kernels. Journal of Agricultural and Food Chemistry, 60(1), 1224–1231.

Evolution of maize landraces in southwest China: Evidence from the globulin1 gene

Climate change is one of the most important threats to biodiversity and crop sustainability. The impact of climate change is often evaluated on the basis of expected changes in species' geographical distributions. Genomic diversity, local adaptation, and migration are seldom integrated into future species projections. Here, we examine how climate change will impact populations of two wild relatives of maize, the teosintes Zea mays ssp. mexicana and Z. mays ssp. parviglumis. Despite high levels of genetic diversity within populations and widespread future habitat suitability, we predict that climate change will alter patterns of local adaptation and decrease migration probabilities in more than two-thirds of present-day teosinte populations. These alterations are geographically heterogeneous and suggest that the possible impacts of climate change will vary considerably among populations. The population-specific effects of climate change are also evident in maize landraces, suggesting that climate change may result in maize landraces becoming maladapted to the climates in which they are currently cultivated. The predicted alterations to habitat distribution, migration potential, and patterns of local adaptation in wild and cultivated maize raise a red flag for the future of populations. The heterogeneous nature of predicted populations' responses underscores that the selective impact of climate change may vary among populations and that this is affected by different processes, including past adaptation.

Key messageA replicated experiment on genomic selection in a maize landrace provides valuable insights on the design of rapid cycling recurrent pre-breeding schemes and the factors contributing to their success.The genetic diversity of landraces is currently underutilized for elite germplasm improvement. In this study, we investigated the potential of rapid cycling genomic selection for pre-breeding of a maize (Zea mays L.) landrace population in replicated experiments. We trained the prediction model on a dataset (N = 899) composed of three landrace-derived doubled-haploid (DH) populations characterized for agronomic traits in 11 environments across Europe. All DH lines were genotyped with a 600 k SNP array. In two replications, three cycles of genomic selection and recombination were performed for line per se performance of early plant development, a major sustainability factor in maize production. From each cycle and replication, 100 DH lines were extracted. To evaluate selection response, the DH lines of all cycles and both replications (N = 688) were evaluated for per se performance of selected and unselected traits in seven environments. Selection was highly successful with an increase of about two standard deviations for traits under directional selection. Realized selection response was highest in the first cycle and diminished in following cycles. Selection gains predicted from genomic breeding values were only partially corroborated by realized gains estimated from adjusted means. Prediction accuracies declined sharply across cycles, but only for traits under directional selection. Retraining the prediction model with data from previous cycles improved prediction accuracies in cycles 2 and 3. Replications differed in selection response and particularly in accuracies. The experiment gives valuable insights with respect to the design of rapid cycling genomic selection schemes and the factors contributing to their success.

Drought is the main limiting factor for maize production, and climate change can aggravate this water scarcity. One way to mitigate this problem is to plant drought tolerance maize genotypes. In landrace maize grown under rainfed conditions there are drought-adapted genotypes, which can be used in breeding programs for drought tolerance. The objective of this study was to evaluate the effect of an early water deficit on the seedling growth of 41 maize landraces from Nuevo León, Mexico, plus seven varieties, by means of drought tolerance indices based on biomass accumulation during both stress and post-stress recovery period, for identifying tolerant and susceptible genotypes. This study was performed at 2016 in Texcoco, Mexico (19°27’N, 98°54’W, 2241 masl). In the greenhouse, 96 treatments were compared (48 genotypes × two soil water regimes: without and with drought) under randomized complete blocks experimental design. After the drought stress period, normal irrigation was resumed for 15 days for recovery. In maize landraces there is genetic diversity in drought tolerance. Landraces GalTrini and SITexas outstanded as the most water deficit tolerant, whereas landraces Berrones, Rodeo, Sabanilla, Carmen, AraTrini and the inbred line L65 were the most drought susceptible. The total biomass measured before water stress was not related to drought adaptability. This study demonstrates that the post stress recovery is more important in drought stress adaptability than the drought resistance, regarding root biomass, shoot biomass and total biomass. Thus, to include the post stress recovery in drought tolerance studies can produce a more precise genotypic classification for drought stress resistance and adaptability.

Upland rice (UR) is a unique rice ecotype that can be grown on upland fields without surface water accumulation in cultivation. Although UR has long been recognised as an important genetic resource for breeding of drought‐tolerant rice varieties, it is facing the risk of genetic erosion due to the rapid spread of high‐yielding modern rice strains. In this study, genetic diversity and relationships among 221 UR accessions collected from southwest China were evaluated using microsatellite (i.e. simple sequence repeat, SSR) markers. A total of 269 alleles were detected using 28 pairs of SSR primers, and the number of alleles per locus ranged from 2 to 20, with an average of 9.6. The polymorphism information content value, a measure of gene diversity, was 0.63 with a range of 0.25–0.89. Clustering analysis showed that all 236 accessions fell into two groups corresponding to indica and japonica. More than 75% of UR accessions were identified as japonica. We detected no clear relationship between genetic similarity and geographical distances, which may be partially due to the frequent seed exchange by local farmers. Our study revealed relatively high levels of genetic diversity in the Chinese UR germplasm, which could provide invaluable genetic resources for improving economically important traits in rice, such as tolerance to drought stress.

Constructing a Core Collection for Maize ( Zea mays L.) Landrace from Wuling Mountain Region in China

Societal Impact StatementBhutan is an ancient kingdom in the Himalayan range and one of the most rugged, geodiverse, and mountainous agricultural countries in the world. Historically secluded and geographically isolated, Bhutan is a hotspot for Himalayan agrobiodiversity where small‐scale agriculture supports the livelihoods of a large share of the resident population. Here, Bhutanese maize agrobiodiversity is explored to unlock its adaptation potential using genomics and participatory variety selection in combination with climate research. We show that Bhutanese traditional farmers maintain a wealth of diversity that may support the sustainable intensification of maize cropping in the Himalayas and beyond.Summary Bhutan, an ancient kingdom enshrouded in the Himalayas, hosts largely untapped agrobiodiversity that may harness genetic variation useful for adaptation to local climates and user needs. Here, we genotyped‐by‐sequencing 351 pooled samples of local maize (Zea mays L.) landraces, the entire collection of the Bhutan National Gene Bank, comparing their genomic diversity with maize from other countries in the Himalayan range. We reconstructed the adaptation of Bhutanese maize to historical and projected climates, identifying areas of future maladaptation. We then run a common garden experiment involving local smallholder farmers in a participatory evaluation of landraces' performance, aiming at the identification of quantitative trait nucleotides (QTNs) contributing to adaptation, performance, and farmers' choice. We found that Bhutanese maize agrobiodiversity is unique in the Himalayan range, and a locus on Chromosome 5 supports the differentiation of three distinct genetic clusters. We found that a portion of current genomic diversity can be associated with the Bhutanese landscape and that maize cultivation in the southwest of the country may be negatively impacted by projected climates. We also found that Bhutanese maize agrobiodiversity is large and may contribute to adaptation and improvement. A genome‐wide association study identified 117 QTNs for climatic adaptation, agronomic performance, and farmers' preferences. Our results show that Bhutanese maize landraces are a unique source of genetic agrobiodiversity for local adaptation. We found that the integration of genomics, climate science, and participatory methods can speed up the identification of genetic factors contributing to the sustainable intensification of maize cultivation in the Himalayas and beyond.

Objective: To analyze the race diversity and geographic distribution of the native maize landraces currently cropped at southern Nuevo León, México. Design/Methodology/Approach: Data was obtained from 41 accessions which represent the commercial production in the dry land area, where fertilization and pest control are scarcely used. Landraces were classified according to the CONABIO guidelines for ear traits. Results: The measured accessions correspond to seven maize races and to seven interracial crosses. The two most frequent maize races were Ratón and Cónico Norteño, mostly located in the dry areas with less rain. Study Limitations/Implications: Three races, Celaya, Tablilla de Ocho and Elotes Cónicos, had not been previously reported; while two formerly reported races Tabloncillo and Olotillo, were no longer found. This study did not include the grain-colored accessions. Findings/Conclusions: Three collections stood out for producing large ears with large kernels, thus showing a high yield potential. The maize landraces harvested in dryland areas might offer advantages to be grown under harsh environments or be used as gene donors for drought tolerance.

The intelligent exploitation of maize landraces for maize breeding requires a detailed knowledge of genetic and historical relationships among these populations and an understanding of the partitioning of genetic diversity among populations. In this study, the diversity of 102 maize landraces from Hubei Province was evaluated on the basis of phenotype data (collected over two years) and simple sequence repeat (SSR) data. The results showed that significant differences in important traits were present among the landraces, especially in kernel weight and ear height. The comparison of the yield components of two elite populations, BSSSC9 and Suwan2, with those of landraces indicated that the ear length of 28 landraces, the kernel weight of 35 landraces, the row number per ear of 11 landraces, and the kernel number of 3 landraces were better than those of the two elite populations, implicating that abundant genetic diversity and favorable genes were accumulated within these landraces. Thirty-six SSR markers revealed a total of 179 alleles in 102 landraces, with an average of 4.97 alleles per loci, and 0.4362 polymorphism information content (ranging from 0.3141 to 0.5601). Cluster analysis based on the phenotypic data and SSR data divided the 102 landraces into two or three major groups. Integrating the phenotypic data and SSR diversity, we suggested that abundant genetic variability and specific alleles were contained within the set of landraces. A few landraces (including Batangbai, Bairihui, Dongjingbai, and Huangyumi) with large genetic diversity and specific favorable characteristics could be selected for further research and utilization.

In this study, morphological characteristics as well as ten of Simple Sequence Repeat (SSRs) loci were used to analyze the genetic diversity and relationships among 12 natural populations of Persian walnut (Juglans regia L.) in northern and western regions of Iran. The results showed that there was a high level of genetic diversity among the walnuts, both in terms of their SSRs loci as well as morphological traits. The nut weight ranged from 11.5 to 17.2 g, kernel weight from 3.2 to 6.3 g, and kernel percentage from 28 to 46.7%. In SSRs analysis, the number of alleles per locus ranged from 6 to 11, with a total of 83 alleles and average of 8.3 alleles and 4.9 effective alleles per locus. The expected heterozygosity (He) varied between 0.70 and 0.87, with an average of 0.79 per locus. The proportion of genetic differences among the walnut populations accounted for 19% of the total variation. The overall gene flow among populations equaled 1.10. The 12 walnut populations were separated into four main groups via the unweighted pair group method (UWPGM) with arithmetic mean cluster analyses based on Nei’s unbiased genetic distances.