Summary Background Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden. Methods We updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics. Findings We present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000–17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8–277·7) to 193·9 million (156·6–240·2) and deaths declined from 925 800 (596 900–1 341 100) to 618 700 (368 600–952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017. Interpretation High-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period. Funding Bill & Melinda Gates Foundation. ...

Context. The alpaca roan pattern is characterised by white and coloured fibre interspersed together, with a distinctive lighter body and darker extremities, and commonly is believed to be inherited in an autosomal dominant manner. It is of interest to the alpaca fibre industry as it causes 'contamination' of coloured fibre with white fibres, but cannot be detected in white or light fawn animals. Other livestock species, such as horses, cattle, goats, and pigs, exhibit comparable phenotypes, which are associated with candidate variant(s) in either KIT or KITLG. Aims. To identify a region or regions of the genome that is/are causative of the roan pattern in alpacas. Methods. We conducted a genome-wide association study (GWAS) by using 13 roan and 14 non-roan alpacas sampled from the USA, Australia, and New Zealand. Regions of genome-wide significance were examined for variants that correlated with the roan phenotype. Key results. A novel candidate single-nucleotype polymorphism (SNP; Super-Scaffold_15:39 742 851T > A), located 272 kb upstream of KITLG, was identified in 1 of 12 regions with genome-wide significant association (P ≤ 5 × 10 −8 ). We identified the candidate SNP-containing region (Super-Scaffold_15:39 742 096-39 887 419) to be a 145 kb copy number variant (CNV) that is likely to be a tandem duplication. All 13 roan alpacas had one or two copies of the roan-associated T allele and all except three non-roans had zero copies. Furthermore, we determined the Mendelian inheritance of copy number haplotypes and their allelic composition in a roan and a non-roan family. Conclusions. Our data support the hypothesised autosomal incomplete dominant mode of inheritance of the roan pattern in alpacas and suggests that the effect of the T allele CNV version is likely to be suppressed when in cis with the A allele CNV version. However, additional verification is required to validate the finding and determine the functional effect. Implications. Identification of the cause, or a marker for roan pattern will allow alpaca breeders to select for or against the roan pattern, even when the phenotype is hidden, and therefore increase production output and profitability.

Context Currently, there is a growing consumer demand for more ecologically sustainable practices in the textile industry. Fabric dyeing is highly pollutive, and one way to avoid dyeing is to use naturally coloured fibres. Alpacas exhibit a wide range of fleece colours, thereby making them a good source of fibre for sustainable textile production. Our understanding of the colour genetics of alpacas is improving, but there is still no explanation for all the variation seen in alpaca coat colours. Aims To identify a region or regions in the alpaca genome that contribute to differences in pigment intensity. Methods Colorimetric analysis using L*a*b* colourspace of fibre from white and black alpacas, that had been genotyped using the Neogen Australasia alpaca coat colour test, was used to classify the samples into intense and dilute groups for each colour. Illumina short-read genotyping by sequencing of the DNA from these alpacas was used to identify single nucleotide polymorphisms that were subsequently used in a case–control genome-wide association study (GWAS) comparing the extreme dilute and intensely pigmented animals. Key results Intense eumelanic fibre is darker (P = 0.0003), less red (P = 0.004), and more blue (P = 0.001) than is dilute eumelanic fibre. Intense pheomelanic fibre is darker (P = 1 × 10−7), more red (P = 3 × 10−20), and more yellow (P = 2 × 10−6) than is dilute pheomelanic fibre. The GWAS showed six regions of genome-wide significance. After manual inspection of these six regions, the best candidate region was upstream of KITLG, a gene previously associated with pigment intensity in dogs. Conclusions In combination with ASIP genotype, a regulatory mutation in a region upstream of KITLG in alpacas potentially has a major effect on pigment intensity in the species. Implications Successful identification of a marker for pigment intensity will allow breeders to select more precisely for breeding and production animals that will assist them in supplying the desired fibre colours to the textile industry.