Cassava (Manihot esculenta Crantz) is a perennial shrub but a root crop in Euphorbiaceae. This crop serves as a staple food for millions of people in tropical and subtropical regions because the dry matter in its storage roots contains more than 80% starch (Alves, 2002; El-Sharkawy, 2004). In addition, cassava can grow on barren and drought land where other crops fail due to its stronger tolerance to stressful environments (Alves, 2002). Beyond its role in human nutrition, cassava starch is also a versatile material with a wide range of applications in food processing and industrial sectors (Tappiban et al., 2019) due to its unique physicochemical properties of swelling and solubility, gelatinization, retrogradation, pasting, and viscoelasticity (Chisenga et al., 2019) . On these ground, the roles of cassava starch in economic and nutritional value cannot be overstated. Therefore, understanding starch biosynthesis of cassava is very necessary for tailoring it to specific needs.

Up to now, a large number of in-depth reviews at different layers and aspects have been conducted on the starch biosynthesis in plants (Martin and Smith, 1995; Orzechowski, 2008; Hannah and James, 2008; Jeon et al., 2010; Kötting et al., 2010; Stitt and Zeeman, 2012; Bahaji et al., 2014; Saripalli and Gupta, 2015; Tappiban et al., 2019; Tetlow and Bertoft, 2020; Huang et al., 2021; Li et al., 2021). But, integrative understanding of cassava starch biosynthesis is relatively limited. Fortunately, the completion of cassava genome sequencing (Wang et al., 2014) provides an excellent opportunity and foundation for doing this.

Based on our understanding, this brief review is to focus on the biochemical pathways of starch synthesis in and implications for breeding programs of cassava, only making a start.

1 Outline of Starch Biosynthesis in Plants

Starch biosynthesis in plants usually occurs in the chloroplast of leaves during the day (Martin and Smith, 1995; Orzechowski, 2008; Stitt and Zeeman, 2012). However, this process is involving multi-step catalytic processes by multiple enzymes and further complicated due to the transient synthesis that is also present in other organs such as meristems and root cap cells (Martin and Smith, 1995). No matter how, the key enzymes for starch biosynthesis are, but not limited to, adenosine 5’-diphosphate glucose pyrophosphorylase (AGPase) responsible for the synthesis of ADP glucose, comprising two large (ApL) and two small (ApS) catalytic subunits; starch branching enzyme (SBE) to produce branches connected by a-1,6-glycoside bonds, including SBEI (SBE1), SBEII, and SBEIII; starch debranching enzyme (DBE) hydrolyzing a-(1,6)-linkages, with three isoforms of isoamylase-type DBE and one pullulanase-type DBE; soluble starch synthase (SS) catalyzing the transfer of glucose from ADP-glucose to an acceptor glucan chain and involving solely in amylopectin synthesis, with 4 classes of SSI to SSIV; granule bound starch synthase (GBSS) involving amylose biosynthesis, with GBSSI and GBSSII; phosphoglucoisomerase converting fructose 6-phosphate to glucose 6-phosphate; phosphoglucomutase converting glucose 6-phosphate to glucose 1-phosphate; and starch phosphorylase responsible for glucan-elongation reactions (Orzechowski, 2008; Keeling and Myers, 2010; Tetlow and Emes, 2014; Li and Gilbert, 2016; Huang et al., 2021). In these enzymes, AGPase is considered as a rate-limiting enzyme responsible for the synthesis of ADP-glucose in the first and key step of starch biosynthesis (Ihemere et al., 2006).

2 Complexity of Cassava Starch Biosynthesis

According to current research in other plants, each enzyme has multiple isoforms (Tappiban et al., 2019), and the enzyme activity and function of the isormors are not entirely the same (Ohdan et al., 2005; Keeling and Myers, 2010; Kötting et al., 2010; Li and Gilbert, 2016; Huang et al., 2021). The expression of some starch biosynthesis genes such as AGPases have been found in both source (leaves) and sink (seeds) organs of rice, and the gene expression modes are tissue and developmental stage-specific (Ohdan et al., 2005). The enzymes’ function depends on the formation of protein complexes (Keeling and Myers, 2010; Cho and Kang, 2020), showing protein–protein interactions.

Cassava is considered one of orphan crops that are also known as underutilized crops, lost crops, neglected crops, or crops for the future (Tadele, 2019; Zambrano et al., 2022). The research on genetic background and molecular mechanisms controlling many traits in cassava is still insufficient. The investigation of the mechanism of cassava starch synthesis is currently only in the age of enlightenment. The 98 known wild species of the New World genus Manihot have been found, which are extremely heterogeneous for any particular genotype. Cassava is an outbreeding species (2n=36 chromosomes) and considered to be an amphidiploid or sequential allopolyploids, and asexually propagated by mature woody stem cuttings (El-Sharkawy, 2004). Recently, a total of 45 genes participating in starch biosynthesis in cassava (Tappiban et al., 2019), including AGPase, GBSS, SS, SBE, DBE, and glucan, water dikinase (GWD). The starch synthesis of cassava may be much more complex than expected and may also have its unique characteristics. With 6 field-grown cultivars and 1 wild species, we have found that starch synthesis-related enzymes have multiple active isoforms in cassava. The types of the active isoforms varied depending on the cultivars. The same active isoforms varied greatly with the roots, stems, and leaves of the same and different cultivars with the growth stage. What is even more confusing was that it was hard to associate these corresponding changes with the starch accumulation (unpublished). These factors together will undoubtedly make cassava starch biosynthesis processes more complex than existing paradigms/frameworks proposed in other plant species.

3 Cases of Engineering Cassava Starch

Efforts have been made to improve cassava starch yield and alter starch properties by regulating the expression of starch biosynthesis-related genes through gene engineering, with several cases. Expressing AGPase genes usually enhances starch production of plants including cassava in most cases but were found to have no impacts on starch production in rare cases, and even generated unexpected results with respect to yield components including starch content (Tuncel and Okita, 2013). For example, transgenic cassava expressing AGPase-encoding glgC gene of bacterial Escherichia coli showed slight decrease in root starch contents (mg per gram fresh weight) (Ihemere et al., 2006), 151 for wild type cassava and 143 (149 and 138) for transgenic cassava. Overexpressing AGPase gene in cereals increased starch yield, and meantime, resulted in increases in seed number and plant biomass (Tuncel and Okita, 2013). Suppression of GBSSI gene expression caused the reduced amylose content but increased values for clarity, peak viscosity, gel breakdown, and swelling index (Zhao et al., 2011). CRISPR-Cas9-mediated targeted mutagenesis of PROTEIN TARGETING TO STARCH or GBSS gene reduced or eliminated amylose content in root starch of cassava (Bull et al., 2018). Silencing expression of SBE1 and SBE2 by short short interfering RNAs-mediated RNAi produced starch containing up to 50% amylose (Zhou et al., 2020). Three mutants with long fragment deletions in the second exon of SBE2 showed higher amylose (up to 56% in apparent amylose content) and resistant starch (up to 35%), and also resulted in starch viscosity with a higher pasting temperature and peak time (Luo et al., 2022). Simultaneous suppression of both SBE1 and SBE2 endowed cassava with a reduced degree of polymerization of 6–13 chains in amylopectin (Utsumi et al., 2022b). GWD1-RNAi cassava plants not only showed both retarded plant and storage root growth, had excess starch accumulation in leaves, and also led to changes in physico-chemical properties of transient and storage starch (Zhou et al., 2017). MeSSII-RNAi cassava had an increase in amylose content and presented alterations in starch physicochemical properties in the storage roots (He et al., 2022). In fact, engineering cassava as well as testing in the field are still in its infancy (Koehorst-van Putten et al., 2012; Zambrano et al., 2022).

4 Quantitative Trait Loci (QTL) Controlling Starch Yield and Properties

Starch yield and properties are very close but different traits, which are associated with QTLs. The QTLs could be used for identification of key target genes of interest and for selection of cassava germplasms of desirable traits for breeding. So far, research on QTL controlling starch yield and properties has not been as extensive as one might think. Fifteen QTLs associated with starch pasting viscosity were identified by using 100 lines of an F1 mapping population from a cross between two cassava cultivars Huay Bong 60 and Hanatee (Thanyasiriwat et al., 2014). Total 115 QTLs controlling starch yield and properties on starch content, amylose content, pasting temperature, thermal and retrogradation, and textural property were reported from 2005-2018 (Tappiban et al., 2019), with candidate genes. Five QTLs for starch content were identified with 2 cassava cultivars of CI-732 (high dry matter content and starch content) and MNga-1 (low dry matter content and starch content) by simple interval mapping (Prasannakumari et al., 2021). With a panel of 276 cassava genotypes by using the genome-wide association study (GWAS), 21 starch pasting property-related QTLs were recently found (Phumichai et al., 2022).

5 Challenges in Engineering Cassava Starch Yield and Starch Properties

Cassava improvement either through conventional cross-breeding or by engineering biotechnologies faces more rigorous challenges (Otun et al., 2023). After entering the era of omics, many new and powerful genetic engineering technologies have emerged and are constantly being improved, such as CRISPR/Cas9 for gene editing, and RNAi and virus-induced gene silencing (VIGS) for suppressing gene expression. Each technology has its own pros and cons. For all these technologies, the basic principle and requirement is high specificity and precision (Senthil-Kumar and Mysore, 2011; Ma et al., 2014; Rössner et al., 2022). However, although not all, unexpected off-target phenomena and non-specific events are also commonly reported. The engineering strategies based on Agrobacterium-mediated overexpression (Utsumi et al., 2022a), CRISPR/Cas9, RNAi, and VIGS have been used for cassava improvement and gene function identification research. The challenges are, but not limited to, as follows.

It is currently not very clear about the chromosomal ploidy and heterozygosity for the vast majority of cassava cultivars. Cassava materials resulting from natural outcrosses are preferentially retained in the long-term production and breeding process because larger and much more vigorous cassava materials from outcrosses are more favored by farmers. Therefore, it can be speculated that most of the cultivars/elite variety should be heterozygous polyploids. However, such heterozygosity results in wide and unpredictable diversity of phenotypes that breeders are interested in but farmers dislike in propagation (Ceballos et al., 2004).

The heterozygosity makes it very likely that some key starch biosynthesis genes are in a heterozygous state. For MeSSI gene, there are 5 heterozygous loci in coding regions in 44 cassava accessions, and 1 heterozygous locus is in non-coding region in 44 cassava accessions (Vasconcelos et al., 2016). With regard to MeGBSS1 gene, only one copy is in cassava genome (Tappiban et al., 2019), however, there existed 1 heterozygous locus in coding regions in 87 cassava accessions, and 5 heterozygous loci were present in non-coding regions in 84 cassava accessions (Vasconcelos et al., 2016). The MeSBE gene had 1 heterozygous locus in non-coding regions in 280 cassava accessions (Vasconcelos et al., 2016). In addition, expression of genes encoding starch biosynthesis enzymes, such as AGPases, shows changes with tissues and growth stages of cassava (Tappiban et al., 2019). All these factors will be bound to bring great difficulties to selection in hybrid breeding, and also cause instability of traits of cassava which is engineered but vegetatively propagated.

In some cases of improving cassava starch yield and properties by key starch synthesis gene, in addition to expected changes, additional unexpected traits or characteristic changes have also emerged as mentioned above, indicating that precision and targeting are still problematic. Even though engineered cassava that has been obtained, it is unclear whether the traits have genetic stability in propagation and production through stem cutting in the field. Additionally, there seem to be very few cases of cassava germplasm selection/screening with the help of the currently obtained QTLs. The core functional genes in the QTLs have not been identified yet, expression regulation mechanisms of which are still unknown.

6 Opportunities and Future Prospects

(1) With regard to cassava materials for engineering cassava and conventional crossing breeding, it is much more important to develop homozygous, heterozygous, and possibly chimeric lines containing a spectrum of different starch contents and properties. In this regard, Bull and his colleagues have done an excellent job through targeted mutagenesis of GBSS or PROTEIN TARGETING TO STARCH1 genes (Bull et al., 2018).

(2) As for enzymes, it is very necessary to conduct identifications of isoforms, active enzyme species and their activity profiles with tissues and growth stages due to the lack of holographic information in these aspects.

(3) Developing new starch-related QTLs, and integrating QTLs and GWAS data to address expression regulation of the key genes in QTLs and further understand the functional role of both genotype and phenotype-associated variations in cassava. These include splicing QTL which is a genetic variant regulating alternative splicing as one of the major causal mechanisms in GWAS loci (Yamaguchi et al., 2022), and expression quantitative trait loci which are namely the discovery of genetic variants that explain variation in gene expression levels (Nica and Dermitzakis, 2013; Joehanes et al., 2017).

(4) Utilizing informative and accurate access maps for engineering cassava. A remarkable research is that the genome-based reconstruction of starch biosynthesis pathway has been established in the form of an informative map with all important information of the pathway to investigate the dynamic regulation of starch biosynthesis in cassava roots, which is available at the Systems Biology and Bioinformatics Research Group’s website (http://sbi.pdti.kmutt.ac.th/?page_id=33) (Saithong et al., 2013).

Acknowledgments

I would like to express my gratitude to the two anonymous peer reviewers for their comments and suggestions on the manuscript.

Conflict of Interest Disclosure

The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Alves A.A.C., 2002, Cassava botany and physiology, In: Hillocks R.J., Thresh J.M., Bellotti A.C. (eds.), Cassava: biology, production and utilization, CAB Publishing, Wallingford, pp.67-89.

https://doi.org/10.1079/9780851995243.0067

Bahaji A., Li J., Sánchez-López Á.M., Baroja-Fernández E., Muñoz F.J., Ovecka M., Almagro G., Montero M., Ezquer I., Etxeberria E., and Pozueta-Romero J., 2014, Starch biosynthesis, its regulation and biotechnological approaches to improve crop yields, Biotechnol Adv., 32(1): 87-106.

https://doi.org/10.1016/j.biotechadv.2013.06.006

PMid:23827783

Bull S.E., Seung D., Chanez C., Mehta D., Kuon J.E., Truernit E., Hochmuth A., Zurkirchen I., Zeeman S.C., Gruissem W., and Vanderschuren H., 2018, Accelerated ex situ breeding of GBSS- and PTST1-edited cassava for modified starch, Sci. Adv., 4(9): eaat6086.

https://doi.org/10.1126/sciadv.aat6086

Ceballos H., Iglesias C.A., Pérez J.C., and Dixon A.G., 2004, Cassava breeding: opportunities and challenges, Plant Mol. Biol., 56(4): 503-516.

https://doi.org/10.1007/s11103-004-5010-5

PMid:15630615

Chisenga S.M., Workneh T.S., Bultosa G., and Alimi B.A., 2019, Progress in research and applications of cassava flour and starch: a review, J. Food Sci. Technol., 56(6): 2799-2813.

https://doi.org/10.1007/s13197-019-03814-6

PMid:31205336 PMCid:PMC6542882

Cho Y.G., and Kang K.K., 2020, Functional analysis of starch metabolism in plants, Plants (Basel), 9(9): 1152.

https://doi.org/10.3390/plants9091152

PMid:32899939 PMCid:PMC7569781

El-Sharkawy M.A., 2004, Cassava biology and physiology, Plant Mol. Biol., 56(4): 481-501.

https://doi.org/10.1007/s11103-005-2270-7

PMid:15669146

Hannah L.C., and James M., 2008, The complexities of starch biosynthesis in cereal endosperms, Curr. Opin. Biotechnol., 19: 160-165.

https://doi.org/10.1016/j.copbio.2008.02.013

PMid:18400487

He S., Hao X., Wang S., Zhou W., Ma Q., Lu X., Chen L., and Zhang P., 2022, Starch synthase II plays a crucial role in starch biosynthesis and the formation of multienzyme complexes in cassava storage roots, J. Exp. Bot., 73(8): 2540-2557.

https://doi.org/10.1093/jxb/erac022

PMid:35134892

Huang L., Tan H., Zhang C., Li Q., and Liu Q., 2021, Starch biosynthesis in cereal endosperms: an updated review over the last decade, Plant Commun., 2: 100237.

https://doi.org/10.1016/j.xplc.2021.100237

PMid:34746765 PMCid:PMC8554040

Ihemere U., Arias-Garzon D., Lawrence S., and Sayre R., 2006, Genetic modification of cassava for enhanced starch production, Plant Biotechnology Journal, 4(4): 453-465.

https://doi.org/10.1111/j.1467-7652.2006.00195.x

PMid:17177810

Jeon J.S., Ryoo N., Hahn T.R., Walia H., and Nakamura Y., 2010, Starch biosynthesis in cereal endosperm, Plant Physiol. Biochem., 48(6): 383-392.

https://doi.org/10.1016/j.plaphy.2010.03.006

PMid:20400324

Joehanes R., Zhang X., Huan T., Yao C., Ying S.X., Nguyen Q.T., Demirkale C.Y., Feolo M.L., Sharopova N.R., Sturcke A., Schäffer A.A., Heard-Costa N., Chen H., Liu P.C., Wang R., Woodhouse K.A., Tanriverdi K., Freedman J.E., Raghavachari N., Dupuis J., Johnson A.D., O'Donnell C.J., Levy D., and Munson P.J., 2017, Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies, Genome Biol., 18(1): 16.

https://doi.org/10.1186/s13059-016-1142-6

PMid:28122634 PMCid:PMC5264466

Keeling P.L., and Myers A.M., 2010, Biochemistry and genetics of starch synthesis, Annu. Rev. Food Sci. Technol., 1: 271-303.

https://doi.org/10.1146/annurev.food.102308.124214

PMid:22129338

Koehorst-van Putten H.J., Sudarmonowati E., Herman M., Pereira-Bertram I.J., Wolters A.M., Meima H., de Vetten N., Raemakers C.J., and Visser R.G., 2012, Field testing and exploitation of genetically modified cassava with low-amylose or amylose-free starch in Indonesia, Transgenic Res., 21(1): 39-50.

https://doi.org/10.1007/s11248-011-9507-9

PMid:21465166 PMCid:PMC3264866

Kötting O., Kossmann J., Zeeman S.C., and Lloyd J.R., 2010, Regulation of starch metabolism: the age of enlightenment? Curr. Opin. Plant Biol., 13(3): 321-329.

https://doi.org/10.1016/j.pbi.2010.01.003

PMid:20171927

Li C., and Gilbert R.G., 2016, Progress in controlling starch structure by modifying starch-branching enzymes, Planta, 243(1): 13-22.

https://doi.org/10.1007/s00425-015-2421-2

PMid:26486516

Li R., Tan Y., and Zhang H., 2021, Regulators of starch biosynthesis in cereal crops, Molecules, 26(23): 7092.

https://doi.org/10.3390/molecules26237092

Luo S., Ma Q., Zhong Y., Jing J., Wei Z., Zhou W., Lu X., Tian Y., and Zhang P., 2022, Editing of the starch branching enzyme gene SBE2 generates high-amylose storage roots in cassava, Plant Mol. Biol., 108(4-5): 429-442.

https://doi.org/10.1007/s11103-021-01215-y

PMid:34792751

Ma Y., Zhang L., and Huang X., 2014, Genome modification by CRISPR/Cas9, FEBS J, 281(23): 5186-5193.

https://doi.org/10.1111/febs.13110

PMid:25315507

Martin C., and Smith A.M., 1995, Starch biosynthesis, Plant Cell, 7(7): 971-985.

https://doi.org/10.1105/tpc.7.7.971

PMid:7640529 PMCid:PMC160895

Ohdan T., Francisco Jr P.B., Sawada T., Hirose T., Terao T., Satoh H., and Nakamura Y., 2005, Expression profiling of genes involved in starch synthesis in sink and source organs of rice, J. Exp. Bot., 56(422): 3229-3244.

https://doi.org/10.1093/jxb/eri292

PMid:16275672

Nica A.C., and Dermitzakis E.T., 2013, Expression quantitative trait loci: present and future, Philos. Trans. R Soc Lond B Biol. Sci., 368(1620): 20120362.

https://doi.org/10.1098/rstb.2012.0362

PMid:23650636 PMCid:PMC3682727

Orzechowski S., 2008, Starch metabolism in leaves, Acta Biochim. Pol., 55: 435-445.

https://doi.org/10.18388/abp.2008_3049

PMid:18787712

Otun S., Escrich A., Achilonu I., Rauwane M., Lerma-Escalera J.A., Morones-Ramírez J.R., and Rios-Solis L., 2023, The future of cassava in the era of biotechnology in Southern Africa, Crit. Rev. Biotechnol., 43(4): 594-612.

https://doi.org/10.1080/07388551.2022.2048791

PMid:35369831

Phumichai C., Aiemnaka P., Nathaisong P., Hunsawattanakul S., Fungfoo P., Rojanaridpiched C., Vichukit V., Kongsil P., Kittipadakul P., Wannarat W., Chunwongse J., Tongyoo P., Kijkhunasatian C., Chotineeranat S., Piyachomkwan K., Wolfe M.D., Jannink J.L., and Sorrells M.E., 2022, Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava, Theor. Appl. Genet., 135(1): 145-171.

https://doi.org/10.1007/s00122-021-03956-2

Prasannakumari V., Nair A.G.H., and Mohan C., 2021, Identification of quantitative trait loci (QTLs) conferring dry matter content and starch content in cassava (Manihot esculenta Crantz), Am. J. BioSci, 9(1): 1-9.

https://doi.org/10.11648/j.ajbio.20210901.11

Rössner C., Lotz D., and Becker A., 2022, VIGS goes viral: How VIGS transforms our understanding of plant science, Annu. Rev. Plant Biol., 73: 703-728.

https://doi.org/10.1146/annurev-arplant-102820-020542

PMid:35138878

Saithong T., Rongsirikul O., Kalapanulak S., Chiewchankaset P., Siriwat W., Netrphan S., Suksangpanomrung M., Meechai A., and Cheevadhanarak S., 2013, Starch biosynthesis in cassava: a genome-based pathway reconstruction and its exploitation in data integration, BMC Syst. Biol., 7: 75.

https://doi.org/10.1186/1752-0509-7-75

PMid:23938102 PMCid:PMC3847483

Saripalli G., and Gupta P.K., 2015, AGPase: its role in crop productivity with emphasis on heat tolerance in cereals, Theor. Appl. Genet., 128: 1893-1916.

https://doi.org/10.1007/s00122-015-2565-2

PMid:26152573

Senthil-Kumar M., and Mysore K.S., 2011, Caveat of RNAi in plants: the off-target effect, Methods Mol. Biol., 2744: 13-25.

https://doi.org/10.1007/978-1-61779-123-9_2

Stitt M., and Zeeman S.C., 2012, Starch turnover: pathways, regulation and role in growth, Curr. Opin. Plant Biol., 15: 282-292.

https://doi.org/10.1016/j.pbi.2012.03.016

PMid:22541711

Tadele Z., 2019, Orphan crops: their importance and the urgency of improvement, Planta, 250(3): 677-694.

https://doi.org/10.1007/s00425-019-03210-6

PMid:31190115

Tappiban P., Smith D., Triwitayakorn K., and Bao J., 2019, Recent understanding of starch biosynthesis in cassava for quality improvement: A review, Trends in Food Science & Technology, 83: 167-180.

https://doi.org/10.1016/j.tifs.2018.11.019

Tetlow I.J., and Bertoft E., 2020, A review of starch biosynthesis in relation to the building block-backbone model, Int. J. Mol. Sci., 21(19): 7011.

https://doi.org/10.3390/ijms21197011

PMid:32977627 PMCid:PMC7582286

Tetlow I.J., and Emes M.J., 2014, A review of starch-branching enzymes and their role in amylopectin biosynthesis, IUBMB Life, 66(8): 546-558.

https://doi.org/10.1002/iub.1297

PMid:25196474

Thanyasiriwa T., Sraphet S., Whankaew S., Boonseng O., Bao J., Lightfoot D.A., Tangphatsornruang S., and Triwitayakorn K., 2014, Quantitative trait loci and candidate genes associated with starch pasting viscosity characteristics in cassava (Manihot esculenta Crantz), Plant Biol. (Stuttg), 16(1): 197-207.

https://doi.org/10.1111/plb.12022

Tuncel A., and Okita T.W., 2013, Improving starch yield in cereals by over-expression of ADPglucose pyrophosphorylase: expectations and unanticipated outcomes, Plant Sci., 211: 52-60.

https://doi.org/10.1016/j.plantsci.2013.06.009

Utsumi Y., Utsumi C., Tanaka M., Okamoto Y., Takahashi S., Huong T.T., Nguyen A.V., Van Dong N., Tokunaga H., Taylor N., and Seki M., 2022a, Agrobacterium-mediated cassava transformation for the Asian elite variety KU50, Plant Mol. Biol., 109(3): 271-282.

https://doi.org/10.1007/s11103-021-01212-1

PMid:34825349

Utsumi Y., Utsumi C., Tanaka M., Takahashi S., Okamoto Y., Ono M., Nakamura Y., and Seki M., 2022b, Suppressed expression of starch branching enzyme 1 and 2 increases resistant starch and amylose content and modifies amylopectin structure in cassava, Plant Mol. Biol., 108(4-5): 413-427.

https://doi.org/10.1007/s11103-021-01209-w

PMid:34767147

Vasconcelos L.M., Brito A.C., Carmo C.D., and Oliveira E.J., 2016, Polymorphism of starch pathway genes in cassava, Genet. Mol. Res., 15(4): gmr15049082.

https://doi.org/10.4238/gmr15049082

Wang W., Feng B., Xiao J., Xia Z., Zhou X., Li P., Zhang W., Wang Y., Møller B., Zhang P., Luo M., Xiao G., Liu J., Yang J., Chen S., Rabinowicz P., Chen X., Zhang H., Ceballos H., Lou Q., Zou M., Carvalho L., Zeng C., Xia J., Sun S., Fu Y., Wang H., Lu C., Ruan M., Zhou S., Wu Z., Liu H., Kannangara R., Jørgensen K., Neale R., Bonde M., Heinz N., Zhu W., Wang S., Zhang Y., Pan K., Wen M., Ma P., Li Z., Hu M., Liao W., Hu W., Zhang S., Pei J., Guo A., Guo J., Zhang J., Zhang Z., Ye J., Ou W., Ma Y., Liu X., Tallon L., Galens K., Ott S., Huang J., Xue J., An F., Yao Q., Lu X., Fregene M., Lopez-Lavalle L., Wu J., You F., Chen M., Hu S., Wu G., Zhong S., Ling P., Chen Y., Wang Q., Liu G., Liu B., Li K., and Peng M., 2014, Cassava genome from a wild ancestor to cultivated varieties, Nat. Commun., 5: 5110.

https://doi.org/10.1038/ncomms6110

Yamaguchi K., Ishigaki K., Suzuki A., Tsuchida Y., Tsuchiya H., Sumitomo S., Nagafuchi Y., Miya F., Tsunoda T., Shoda H., Fujio K., Yamamoto K., and Kochi Y., 2022, Splicing QTL analysis focusing on coding sequences reveals mechanisms for disease susceptibility loci, Nat. Commun., 13(1): 4659.

https://doi.org/10.1038/s41467-022-32358-1

PMid:36002455 PMCid:PMC9402578

Zambrano P., Wood-Sichra U., Ruhinduka R.D., Phillip D., Pratt A.N., Komen J., Kikulwe E.M., Zepeda J.F., Dzanku F.M., and Chambers J.A., 2022, Opportunities for orphan crops: Expected economic benefits from biotechnology, Front. Plant Sci., 13: 825930.

https://doi.org/10.3389/fpls.2022.825930

PMid:35873974 PMCid:PMC9297366

Zhao S.S., Dufour D., Sánchez T., Ceballos H., and Zhang P., 2011, Development of waxy cassava with different biological and physico-chemical characteristics of starches for industrial applications, Biotechnol Bioeng, 108(8): 1925-1935.

https://doi.org/10.1002/bit.23120

PMid:21370230

Zhou W., He S., Naconsie M., Ma Q., Zeeman S.C., Gruissem W., and Zhang P., 2017, Alpha-glucan, water dkinase 1 affects starch metabolism and storage root growth in cassava (Manihot esculenta Crantz), Sci. Rep., 7(1): 9863.

https://doi.org/10.1038/s41598-017-10594-6

PMid:28852191 PMCid:PMC5575247

Zhou W., Zhao S., He S., Ma Q., Lu X., Hao X., Wang H., Yang J., and Zhang P., 2020, Production of very-high-amylose cassava by post-transcriptional silencing of branching enzyme genes, J. Integr. Plant Biol., 62(6): 832-846.

https://doi.org/10.1111/jipb.12848

PMid:31180179