Development of Superior Fibre Quality Upland Cotton Cultivar Series 'Ravnaq' Using Marker-Assisted Selection.

Autor: Darmanov MM; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Makamov AK; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Ayubov MS; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Khusenov NN; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Buriev ZT; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Shermatov SE; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Salakhutdinov IB; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Ubaydullaeva KA; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Norbekov JK; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Kholmuradova MM; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Narmatov SE; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Normamatov IS; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan., Abdurakhmonov IY; Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan.
Jazyk: angličtina
Zdroj: Frontiers in plant science [Front Plant Sci] 2022 May 24; Vol. 13, pp. 906472. Date of Electronic Publication: 2022 May 24 (Print Publication: 2022).
DOI: 10.3389/fpls.2022.906472
Abstrakt: Marker-assisted selection (MAS) helps to shorten breeding time as well as reduce breeding resources and efforts. In our MAS program, we have targeted one of previously reported LD-blocks with its simple sequence repeat (SSR) marker(s), putatively associated with, at least, four different fibre quality QTLs such as fibre length, strength, micronaire and uniformity. In order to transfer targeted QTLs from a donor genotype to a cultivar of choice, we selected G. hirsutum donor genotypes L-141 and LN-1, possessing a fibre quality trait-associated LD-block from the chromosome 7/16. We crossed the donor lines with local elite G. hirsutum cultivars 'Andijan-35' and 'Mekhnat' as recipients. As a result, two segregating populations on LD-block of interest containing fibre QTLs were developed through backcrossing (BC) of F 1 hybrids with their relative recipients (used as recurrent parents) up to five generations. In each BC and segregating BC 1 - 5 F 1 populations, a transfer of targeted LD-block/QTLs was monitored using a highly polymorphic SSR marker, BNL1604 genotype. The homozygous cultivar genotypes with superior fibre quality and agronomic traits, bearing a targeted LD-block of interest, were individually selected from self-pollinated BC 5 F 1 (BC 5 F 2-5 ) population plants using the early-season PCR screening analysis of BNL1604 marker locus and the end-of-season fibre quality parameters. Only improved hybrids with superior fibre quality compared to original recipient parent were used for the next cycle of breeding. We successfully developed two novel MAS-derived cotton cultivars (named as 'Ravnaq-1' and 'Ravnaq-2') of BC 5 F 5 generations. Both novel MAS cultivars possessed stronger and longer fibre as well as improved fibre uniformity and micronaire compared to the original recurrent parents, 'Andijan-35' and 'Mekhnat'. Our efforts demonstrated a precise transfer of the same LD-block with, at least, four superior fibre QTLs in the two independent MAS breeding experiments exploiting different parental genotypes. Results exemplify the feasibility of MAS in cotton breeding.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2022 Darmanov, Makamov, Ayubov, Khusenov, Buriev, Shermatov, Salakhutdinov, Ubaydullaeva, Norbekov, Kholmuradova, Narmatov, Normamatov and Abdurakhmonov.)
Databáze: MEDLINE
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