A time series transcriptome analysis of cassava (Manihot esculenta Crantz) varieties challenged with Ugandan cassava brown streak virus

Open Access Journal; Published online: 29 August 2017A time-course transcriptome analysis of two cassava varieties that are either resistant or susceptible to cassava brown streak disease (CBSD) was conducted using RNASeq, after graft inoculation with Ugandan cassava brown streak virus (UCBSV). From approximately 1.92 billion short reads, the largest number of differentially expressed genes (DEGs) was obtained in the resistant (Namikonga) variety at 2 days after grafting (dag) (3887 DEGs) and 5 dag (4911 DEGs). At the same time points, several defense response genes (encoding LRR-containing, NBARC-containing, pathogenesis-related, late embryogenesis abundant, selected transcription factors, chaperones, and heat shock proteins) were highly expressed in Namikonga. Also, defense-related GO terms of ‘translational elongation’, ‘translation factor activity’, ‘ribosomal subunit’ and ‘phosphorelay signal transduction’, were overrepresented in Namikonga at these time points. More reads corresponding to UCBSV sequences were recovered from the susceptible variety (Albert) (733 and 1660 read counts per million (cpm)) at 45 dag and 54 dag compared to Namikonga (10 and 117 cpm respectively). These findings suggest that Namikonga’s resistance involves restriction of multiplication of UCBSV within the host. These findings can be used with other sources of evidence to identify candidate genes and biomarkers that would contribute substantially to knowledge-based resistance breeding

QTL associated with resistance to cassava brown streak and cassava mosaic diseases in a bi-parental cross of two Tanzanian farmer varieties, Namikonga and Albert

Article purchasedCassava production in Africa is compromised by cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). To reduce costs and increase the precision of resistance breeding, a QTL study was conducted to identify molecular markers linked to resistance against these diseases. A bi-parental F1 mapping population was developed from a cross between the Tanzanian farmer varieties, Namikonga and Albert. A one-step genetic linkage map comprising 943 SNP markers and 18 linkage groups spanning 1776.2 cM was generated. Phenotypic data from 240 F1 progeny were obtained from two disease hotspots in Tanzania, over two successive seasons, 2013 and 2014. Two consistent QTLs linked to resistance to CBSD-induced root necrosis were identified in Namikonga on chromosomes II (qCBSDRNFc2Nm) and XI (qCBSDRNc11Nm) and a putative QTL on chromosome XVIII (qCBSDRNc18Nm). qCBSDRNFc2Nm was identified at Naliendele in both seasons. The same QTL was also associated with CBSD foliar resistance. qCBSDRNc11Nm was identified at Chambezi in both seasons, and was characterized by three peaks, spanning a distance of 253 kb. Twenty-seven genes were identified within this region including two LRR proteins and a signal recognition particle. In addition, two highly significant CMD resistance QTL (qCMDc12.1A and qCMDc12.2A) were detected in Albert, on chromosome 12. Both qCMDc12.1A and qCMDc12.2A lay within the range of markers reported earlier, defining the CMD2 locus. This is the first time that two loci have been identified within the CMD2 QTL, and in germplasm of apparent East African origin. Additional QTLs with minor effects on CBSD and CMD resistance were also identified

QTL associated with resistance to cassava brown streak and cassava mosaic diseases in a bi-parental cross of two Tanzanian farmer varieties, Namikonga and Albert

Cassava production in Africa is compromised by cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). To reduce costs and increase the precision of resistance breeding, a QTL study was conducted to identify molecular markers linked to resistance against these diseases. A bi-parental F1 mapping population was developed from a cross between the Tanzanian farmer varieties, Namikonga and Albert. A one-step genetic linkage map comprising 943 SNP markers and 18 linkage groups spanning 1776.2 cM was generated. Phenotypic data from 240 F1 progeny were obtained from two disease hotspots in Tanzania, over two successive seasons, 2013 and 2014. Two consistent QTLs linked to resistance to CBSD-induced root necrosis were identified in Namikonga on chromosomes II (qCBSDRNFc2Nm) and XI (qCBSDRNc11Nm) and a putative QTL on chromosome XVIII (qCBSDRNc18Nm). qCBSDRNFc2Nm was identified at Naliendele in both seasons. The same QTL was also associated with CBSD foliar resistance. qCBSDRNc11Nm was identified at Chambezi in both seasons, and was characterized by three peaks, spanning a distance of 253 kb. Twenty-seven genes were identified within this region including two LRR proteins and a signal recognition particle. In addition, two highly significant CMD resistance QTL (qCMDc12.1A and qCMDc12.2A) were detected in Albert, on chromosome 12. Both qCMDc12.1A and qCMDc12.2A lay within the range of markers reported earlier, defining the CMD2 locus. This is the first time that two loci have been identified within the CMD2 QTL, and in germplasm of apparent East African origin. Additional QTLs with minor effects on CBSD and CMD resistance were also identified.The Bill and Melinda Gates Foundation for funding under Contract ID OPPGD1016.http://www.sherpa.ac.uk/romeo/issn/0040-5752/am2017Forestry and Agricultural Biotechnology Institute (FABI)Genetic

Chromosome-wide distribution of haplotype blocks and the role of recombination hot spots

Recent studies of human populations suggest that the genome consists of chromosome segments that are ancestrally conserved ('haplotype blocks'; refs. 1-3) and have discrete boundaries defined by recombination hot spots(4,5). Using publicly available genetic markers(6), we have constructed a first-generation haplotype map of chromosome 19. As expected for this marker density(7), approximately one-third of the chromosome is encompassed within haplotype blocks. Evolutionary modeling of the data indicates that recombination hot spots are not required to explain most of the observed blocks, providing that marker ascertainment and the observed marker spacing are considered. In contrast, several long blocks are inconsistent with our evolutionary models, and different mechanisms could explain their origins