QTL analysis for gossypol and protein contents in upland cottonseeds with two different genetic systems across environments

Liu, He‐Yang; Quampah, Alfred; Chen, J. H.; Li, J. R.; Huang, Zhuangrong; He, Qi-Liang; Shi, Chao; Zhu, Shuijin

doi:10.1007/s10681-012-0733-x

Cited by 18 publications

(13 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Supplementary Table 5 contains a description of each trait used in the study. Table 6a contains a summary of the publications used in the G. hirsutum QTL used in the study Chen et al 2008Chen et al , 2009Fang et al 2014;Kong et al 2011;Jia et al 2011;Gore et al 2014;Guo et al 2008;Gutierrez et al 2010;Ge et al 2008;Jiang et al 2009;Yao et al 2010;Kumar et al 2012;Li et al 2006Li et al , 2008Li et al , 2010Li et al , 2012Liang et al 2013;Liu et al 2010Liu et al , 2012ab, 2013a, b, c;Lopez-Lavalle et al 2012;Mei et al 2014;Ning et al 2014;Nusurat et al 2012;Qin et al 2008Qin et al , 2009Romano et al 2009;Shen et al 2005Shen et al , 2006aSun et al 2012;Ulloa et al 2009;Wang et al 2006;2007a, b, c, 2009Hu et al 2008;Wu et al 2009;Yang et al 2007Yang et al , 2009Xu et al 2010;Yin et al 2002;Wang...…”

Section: Methodsmentioning

confidence: 99%

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

et al. 2014

View full text Add to dashboard Cite

Based on 1075 and 1059 QTL from intraspecific Upland and interspecific Upland × Pima populations, respectively, the identification of QTL clusters and hotspots provides a useful resource for cotton breeding. Mapping of quantitative trait loci (QTL) is a pre-requisite of marker-assisted selection for crop yield and quality. Recent meta-analysis of QTL in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of QTL for various traits called clusters and specific trait QTL called hotspots or meta-QTL (mQTL). However, the meta-analysis included all population types of Gossypium mixing both intraspecific G. hirsutum and interspecific G. hirsutum × G. barbadense populations. This study used 1,075 QTL from 58 publications on intraspecific G. hirsutum and 1,059 QTL from 30 publications on G. hirsutum × G. barbadense populations to perform a comprehensive comparative analysis of QTL clusters and hotspots between the two populations for yield, fiber and seed quality, and biotic and abiotic stress tolerance. QTL hotspots were further analyzed for mQTL within the hotspots using Biomercator V3 software. The ratio of QTL between the two population types was proportional yet differences in hotspot type and placement were observed between the two population types. However, on some chromosomes QTL clusters and hotspots were similar between the two populations. This shows that there are some universal QTL regions in the cultivated tetraploid cotton which remain consistent and some regions which differ between population types. This study for the first time elucidates the similarities and differences in QTL clusters and hotspots between intraspecific and interspecific populations, providing an important resource to cotton breeding programs in marker-assisted selection .

show abstract

Section: Methodsmentioning

confidence: 99%

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Identification of the genes controlling AAC is important to facilitate breeding for improved amino acid composition. There have been several studies on the mapping of quantitative trait locus (QTL) controlling AAC in soybeans (Panthee et al 2006), wheat (Jiang et al 2013), cotton Liu et al 2012;Liu et al 2013), and rapeseed (Wen et al 2014); however, few studies have been performed to identify QTLs for AAC in rice (Wang et al 2008;Zheng et al 2008;Zhao et al 2009;Lu et al 2009). These studies have provided useful genetic information for improving the nutritional quality of rice.…”

Section: Introductionmentioning

confidence: 99%

“…Identification of the genes controlling AAC is important to facilitate breeding for improved amino acid composition. There have been several studies on the mapping of quantitative trait locus (QTL) controlling AAC in soybeans (Panthee et al 2006), wheat (Jiang et al 2013), cotton (Quampah et al 2012Liu et al 2012;Liu et al 2013), and rapeseed (Wen et al 2014); however, few studies have which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. …”

mentioning

confidence: 99%

Quantitative trait loci controlling the amino acid content in rice (Oryza sativa L.)

Yoo

2017

J Plant Biotechnol

View full text Add to dashboard Cite

The amino acid composition of rice is a major concern of rice breeders because amino acids are among the most important nutrient components in rice. In this study, a genetic map was constructed with a population of 134 recombinant inbred lines (RILs) from a cross between Dasanbyeo (Tongil-type indica) and TR22183 (temperate japonica), as a means to detect the main and epistatic effect quantitative trait loci (QTLs) for the amino acid content (AAC). Using a linkage map which covered a total of 1458 cM based on 239 molecular marker loci, a total of six main-effect QTLs (M-QTLs) was identified for the content of six amino acids that were mapped onto chromosome 3. For all the M-QTLs, the TR22183 allele increased the trait values. The QTL cluster (flanked by id3015453 and id3016090) on chromosome 3 was associated with the content of five amino acids. The phenotypic variation, explained by the individual QTLs located in this cluster, ranged from 10.2 to 12.4%. In addition, 26 epistatic QTLs (Ep-QTLs) were detected and the 25 loci involved in this interaction were distributed on all nine chromosomes. Both the M-QTLs and Ep-QTLs detected in this study will be useful in breeding programs which target the development of rice with improved amino acid composition.Keywords Quantitative trait loci, Amino acid content, rice, QTL mapping Introduction Rice (Oryza sativa L.) is one of the most important staple cereal crops for more than 50% of the world's population (Mather et al. 2007). A total of 85% of rice production is consumed by humans, and rice provides 21% of the global human per capita energy and 15% of the per capita protein.Amino acids are the principal building blocks of enzymes and other proteins (Panthee et al. 2006), and protein content and amino acid content (AAC) are key factors in the nutritional quality of rice. Thus, improvement of these factors is a major breeding objective in the effort to meet the food demands of an increasing global population. The 20 amino acids have been classified into two groups, essential and non-essential. Essential amino acids, which cannot be synthesized by animals, need to be taken up from plants or other organisms (D'Mello 2003). Non-essential amino acids are also important because they are required for the synthesis of essential amino acids and other biochemical compounds (Wen et al. 2009). Therefore, genetic knowledge regarding non-essential amino acids will also be beneficial to balancing amino acid composition and improving protein quality. Because rice protein content differs greatly among varieties (Maclean et al. 2002), it is important to utilize rice varieties containing high levels of essential amino acids as genetic resources to breed for improved protein content. The average protein level of the 17 587 cultivars of unmilled (brown) rice in the International Rice Research Institute (IRRI) germplasm collection was 9.5%, and ranged from 4.3 to 18.2%. This phenotypic variation in protein content provides a useful genetic basis for breeding.Protein content and AAC...

show abstract

“…Proses inilah yang menyebabkan konsentrasi gosipol semakin meningkat 29,30 . Liu, et.al 31 menyatakan bahwa kandungan protein dan gosipol merupakan dua ciri yang menjadi hal terpenting yang menentukan kualitas biji kapas. Berdasarkan hasil penelitian Soetan, et.al 32 bahwa proses penghancuran biji kapas dapat merusak ikatan gosipol dan melepas gosipol pada serpihan kernel (bungkil).…”

Section: Tabel 2 Pengaruh Lama Perebusan Terhadap Kandungan Mineral unclassified

Pengaruh Waktu Perebusan Terhadap Kandungan Proksimat, Mineral Dan Kadar Gosipol Tepung Biji Kapas

Diana¹

2017

Jurnal Pasca

View full text Add to dashboard Cite

Biji kapas merupakan salah satu dari jenis biji yang mengandung minyak. Disamping minyak, biji kapas mengandung protein dalam jumlah yang cukup tinggi (20-30%) setara dengan tepung kedelai, mengandung karbohidrat sebesar 57%, namun juga memiliki kandungan toksin berupa gosipol. Penelitian ini bertujuan untuk mengetahui lama perebusan yang optimal dengan mempelajari kandungan proksimat, mineral dan gosipol pada tepung biji kapas. Kegiatan meliputi proses perebusan biji kapas pada suhu 70-80 oC selama 0, ½, 1, 2, 3, 4, dan 5 jam, pengeringan selanjutnya dilakukan proses penepungan biji kapas dan terakhir dilakukan analisis kandungan proksimat, mineral dan kadar gosipol tepung biji kapas. Hasil penelitian menunjukkan bahwa lama perebusan berpengaruh terhadap penurunan kadar serat kasar, protein dan pati, namun tidak berpengaruh terhadap kadar abu dan kadar minyak tepung biji kapas yang diperoleh. Perebusan biji kapas selama 4 jam dapat meningkatkan kadar serat kasar, pati, protein dan minyak pada tepung biji kapas bila dibandingkan jika direbus selama ½ - 3 jam, sedangkan perebusan biji kapas selama 3 hingga 5 jam menghasilkan tepung biji kapas dengan rata-rata kandungan gosipol sebesar 4299 ppm.

show abstract

QTL analysis for gossypol and protein contents in upland cottonseeds with two different genetic systems across environments

Cited by 18 publications

References 20 publications

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

Quantitative trait loci controlling the amino acid content in rice (Oryza sativa L.)

Pengaruh Waktu Perebusan Terhadap Kandungan Proksimat, Mineral Dan Kadar Gosipol Tepung Biji Kapas

Contact Info

Product

Resources

About