Sequencing of bulks of segregants allows dissection of genetic control of amylose content in rice

Abstract

SummaryAmylose content (AC) is a key quality trait in rice. A cross between Oryza glaberrima (African rice) and Oryza sativa (Asian rice) segregating for AC was analysed by sequencing bulks of individuals with high and low AC. SNP associated with the granule bound starch synthase (GBSS1) locus on chromosome 6 were polymorphic between the bulks. In particular, a G/A SNP that would result in an Asp to Asn mutation was identified. This amino acid substitution may be responsible for differences in GBSS activity as it is adjacent to a disulphide linkage conserved in all grass GBSS proteins. Other polymorphisms in genomic regions closely surrounding this variation may be the result of linkage drag. In addition to the variant in the starch biosynthesis gene, SNP on chromosomes 1 and 11 linked to AC was also identified. SNP was found in the genes encoding the NAC and CCAAT‐HAP5 transcription factors that have previously been linked to starch biosynthesis. This study has demonstrated that the approach of sequencing bulks was able to identify genes on different chromosomes associated with this complex trait.

Discovery of genomic regions and candidate genes controlling shelling percentage using QTL‐seq approach in cultivated peanut (Arachis hypogaea L.)

“…According to the QTL‐seq approach, only one parent was sequenced and used as reference to compare the two extreme bulks (Takagi et al ., ), and recent reports in cucumber (Lu et al ., ), tomato (Illa‐Berenguer et al ., ), rapeseed (Hua et al ., ), chickpea (Singh et al ., ), pigeonpea (Singh et al ., ), peanut (Pandey et al ., ), soybean (Zhong et al ., ) and rice (Wambugu et al ., ) used one parent as reference. Whether the choice of different parent would affect the results were not reported.…”

“…This approach is cost‐effective as sample number is less for sequencing and facilitates development of cost‐effective markers in less time for deployment in GAB. This approach has been deployed in several crops including rice (Wambugu et al ., ), cucumber (Lu et al ., ), tomato (Illa‐Berenguer et al ., ), rapeseed (Hua et al ., ), chickpea (Singh et al ., ), pigeonpea (Singh et al ., ), peanut (Pandey et al ., ) and soybean (Zhong et al ., ), and proved to be very successful in RIL populations with phenotyping data generated in multiple environments. Since the reference genome sequence of cultivated peanut is still unpublished, the available reference genome sequences of its two diploid ancestors, A. duranensis (AA, 2 n = 2 x = 20) and A. ipaensis (BB, 2 n = 2 x = 20) (Bertioli et al ., ) provided a foundation to find candidate genes and SNPs present in QTL regions.…”

The Genetic Basis and Nutritional Benefits of Pigmented Rice Grain

“…A more integrated approach, focusing on identifying linkages between regulatory networks is needed (Figure 2). Combining diverse datasets facilitates the reconstruction of regulatory networks and the identification of key modulators Wambugu et al, 2018). As an example, an exploration of the key genetic influences affecting grain amylose-amylopectin composition has implicated two genomic regions, one on chromosome 6 and the other on chromosome 7 .…”

A Partially Phase-Separated Genome Sequence Assembly of the Vitis Rootstock ‘Börner’ (Vitis riparia × Vitis cinerea) and Its Exploitation for Marker Development and Targeted Mapping

“…A recent review on BSA (Zou et al, 2016) mentioned an optimal bulk size for monogenic traits of 10 to 20% of the segregating population for each pool or "tail" of the trait value distribution. However, a BSA study in rice (Wambugu et al, 2018) was successful with 10 or fewer individuals per pool. In addition, equal size of the contrasting pools is considered to be important.…”