Comparative pan-genomics reveals pervasive lineage-specific innovations and improves inference of cross-species synteny in cereals.
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Journal Article↗
Biomedical subjects
Emma Mace
Publications and source records attributed to Emma Mace.
Scaling up orphan crop research: genebank genetics highlight geographic structure in cultivated cowpea from 10 617 global accessions.
Vigna unguiculata (L.) Walp. is a dryland legume crop, providing essential food and nutritional security for millions of people across the semi-arid tropics, in Africa, Asia and Latin America. However, as a typical 'orphan crop', cowpea has long remained underrepresented in global genomic research to support crop improvement. Here, we conducted the largest genetic diversity analysis of cowpea to date, comprising 10 617 accessions sourced from seven international collections. Using genotyping-by-sequencing, we characterised the global patterns of genetic diversity, assessed redundancy within and across collections, and examined the geographic structure of the cowpea global allele pool. Our results revealed nine distinct genetic groups with clear geographic associations and fine-scale population differentiation, reflecting dispersal history, regional adaptation and the influence of modern breeding. Duplication across collections was detected, highlighting the need for improved curation and integration of germplasm resources. Landraces from sub-Saharan Africa do not fully capture the genetic diversity present in several other geographic regions, indicating the existence of abundant and untapped genetic resources worldwide. These findings not only provide insights into the genetic structure and evolutionary history of cowpea but also offer a valuable foundation for harnessing global germplasm diversity to enhance breeding potential and accelerate crop improvement.
Vigna↗
Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping.
BACKGROUND: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow. RESULTS: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. CONCLUSION: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/gt-bt/lims/lims.asp.
Algorithms↗