Physical mapping for quantitative trait loci underlying protein content in cassava leaves

Cassava breeding for higher leaf protein content (LPC) is one of the major goals of breeders to improve the diet in developing countries. Towards this goal, a physical map of an F 1 cassava population derived from a cross between ‘Huay Bong 60’ (HB60) and ‘Hanatee’ (HN) was constructed by assigning linkage groups (LGs) to chromosome numbers based on the Phytozome database. A total of 23 LGs were assigned to 18 cassava chromosomes. The map composed of 500 loci covering 553.93 Mbp or approximately 72% of the cassava genome, with a mean distance between two loci of 1.36 Mbp. A total of four QTL controlling leaf protein content with 10.1–22.4% of the phenotypic variation explained (PVE), were detected. Two major QTL, LPC08_2 and LPC09_1 on chromosome 12 were detected across two years with positive correlations between the phenotypes. Many candidate genes were annotated from the 2-LOD interval of QTLs for leaf protein content in cassava. Candidate proteins included ATPases Associated with diverse cellular Activities (AAA ATPase) proteins which are related to protein metabolism, pentatricopeptide repeat (PPR) genes involved in chloroplast function, Galactolipase DONGLE proteins which regulates chloroplast lipid metabolism. Ubiquitin-related proteins and leucine-rich repeat (LRR) proteins that are related to protein turnover and plant defense response, respectively, were also found. These QTL and trait-linked markers will be useful for improving protein content in leaves of cassava through marker-assisted selection programs (MAS).

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Publication Details

Journal
Scientific Reports
Published
2026-09-11
DOI
https://doi.org/10.1038/s41598-026-69400-x
Primary Topic
Cassava research and cyanide
Type
article
Field-Weighted Citation Impact
0.00

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article

Physical mapping for quantitative trait loci underlying protein content in cassava leaves

Nattaya Srisawad, Piengtawan Tappiban, Kanokporn Triwitayakorn, Supajit Sraphet et al.
Scientific Reports
Cassava research and cyanide
article

Physical mapping for quantitative trait loci underlying protein content in cassava leaves

Nattaya Srisawad, Piengtawan Tappiban, Kanokporn Triwitayakorn, Supajit Sraphet, Duncan R. Smith
article en

Abstract

Cassava breeding for higher leaf protein content (LPC) is one of the major goals of breeders to improve the diet in developing countries. Towards this goal, a physical map of an F 1 cassava population derived from a cross between ‘Huay Bong 60’ (HB60) and ‘Hanatee’ (HN) was constructed by assigning linkage groups (LGs) to chromosome numbers based on the Phytozome database. A total of 23 LGs were assigned to 18 cassava chromosomes. The map composed of 500 loci covering 553.93 Mbp or approximately 72% of the cassava genome, with a mean distance between two loci of 1.36 Mbp. A total of four QTL controlling leaf protein content with 10.1–22.4% of the phenotypic variation explained (PVE), were detected. Two major QTL, LPC08_2 and LPC09_1 on chromosome 12 were detected across two years with positive correlations between the phenotypes. Many candidate genes were annotated from the 2-LOD interval of QTLs for leaf protein content in cassava. Candidate proteins included ATPases Associated with diverse cellular Activities (AAA ATPase) proteins which are related to protein metabolism, pentatricopeptide repeat (PPR) genes involved in chloroplast function, Galactolipase DONGLE proteins which regulates chloroplast lipid metabolism. Ubiquitin-related proteins and leucine-rich repeat (LRR) proteins that are related to protein turnover and plant defense response, respectively, were also found. These QTL and trait-linked markers will be useful for improving protein content in leaves of cassava through marker-assisted selection programs (MAS).

Scientific Reports
Mahidol University (TH)
Mahidol University
Zero hunger
Openalex Percentile: Top 13%
Cassava research and cyanide
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Physical mapping for quantitative trait loci underlying protein content in cassava leaves — Nattaya Srisawad, Piengtawan Tappiban, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS