The present study applies a bootstrapped data envelopment analysis (DEA) procedure to compute bias-corrected measures of agricultural total factor productivity (TFP) change and its components (technical change and technical efficiency change) using a panel data of 19 regions of Bangladesh covering a 23-year period (1987–2009), thereby overcoming the limitation of the lack of statistical inference of the conventional non-parametric DEA. Results revealed that overall productivity grew at a modest rate of 0.03%, mainly powered by technological progress at 0.03% and a negligible decline in technical efficiency at 0.004% with large disparities amongst regions. Six regions in the middle order shifted ranks with regard to TFP change following bias correction. The estimated confidence intervals demonstrated that many regions underwent either progress or regress in productivity performance over time. Investments in research and development (R&D), agricultural extension, and crop diversification are suggested to improve regional inequality and declining technical efficiency.

Lilies (Lilium sp.) are commercially important horticultural crops widely cultivated for their flowers and bulbs. Here, we conducted large-scale data mining of the lily transcriptome to develop transcription factor (TF)-associated microsatellite markers (TFSSRs). Among 216,768 unigenes extracted from our sequence data, 6966 unigenes harbored simple sequence repeats (SSRs). Seventy-one SSRs were associated with TF genes, and these were used to design primers and validate their potential as markers. These 71 SSRs were accomplished with 31 transcription factor families; including bHLH, MYB, C2H2, ERF, C3H, NAC, bZIP, and so on. Fourteen highly polymorphic SSRs were selected based on Polymorphic Information Content (PIC) values and used to study genetic diversity and population structure in lily accessions. Higher genetic diversity was observed in Longiflorum compared to Oriental and Asiatic populations. Lily accessions were divided into three sub-populations based in our structure analysis, and an un-rooted neighbor-joining tree effectively separated the accessions according to Asiatic, Oriental, and Longiflorum subgroups. Finally, we showed that 46 of the SSR-associated genes were differentially expressed in response to Botrytis elliptica infection. Thus, our newly developed TFSSR markers represent a powerful tool for large-scale genotyping, high-density and comparative mapping, marker-aided backcrossing, and molecular diversity analysis of Lilium sp.

Trait tagging through molecular markers is an important molecular breeding tool for crop improvement. SSR markers encoded by functionally relevant parts of a genome are well suited for this task because they may be directly related to traits. However, a limited number of these markers are known for Musa spp. Here, we report 35136 novel functionally relevant SSR markers (FRSMs). Among these, 17,561, 15,373 and 16,286 FRSMs were mapped in-silico to the genomes of Musa acuminata, M. balbisiana and M. schizocarpa, respectively. A set of 273 markers was validated using eight accessions of Musa spp., from which 259 markers (95%) produced a PCR product of the expected size and 203 (74%) were polymorphic. In-silico comparative mapping of FRSMs onto Musa and related species indicated sequence-based orthology and synteny relationships among the chromosomes of Musa and other plant species. Fifteen FRSMs were used to estimate the phylogenetic relationships among 50 banana accessions, and the results revealed that all banana accessions group into two major clusters according to their genomic background. Here, we report the first large-scale development and characterization of functionally relevant Musa SSR markers. We demonstrate their utility for germplasm characterization, genetic diversity studies, and comparative mapping in Musa spp. and other monocot species. The sequences for these novel markers are freely available via a searchable web interface called Musa Marker Database.

Microsatellites, or simple sequences repeat (SSRs), are distributed in genes, intergenic regions and transposable elements in the genome. SSRs were identified for developing markers from draft genome assemblies, transcriptome sequences and genome survey sequences in plant and animals. The identification, distribution, and density of microsatellites in pre-microRNAs (miRNAs) are not well documented in plants. In this study, SSRs were identified in 16,892 pre-miRNA sequences from 292 plant species in six taxonomic groups (algae to dicots). Fifty-one percent of pre-miRNA sequences contained SSRs. Mononucleotide repeats were the most abundant, followed by di- and trinucleotide repeats. Tetra-, penta-, and hexarepeats were rare. A total of 9,498 (57.46%) microsatellite loci had potential as pre-miRNA SSR markers. Of the markers, 3,573 (37.62%) were non-redundant, and 2,341 (65.51%) primer pairs could be transferred to at least one of the plant taxonomic groups. All data and primer pairs were deposited in a user-friendly, freely accessible plant miRNA SSR marker database. The data presented in this study, accelerate the understanding of pre-miRNA evolution and serve as valuable genomic treasure for genetic improvements in a wide range of crops, including legumes, cereals, and cruciferous crops.